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Communities Need Safe Drinking Water: A Rural Environmental Justice Case Study

April 3, 2024  • Community Strategies Group

Vision: Community Solutions for Safe Drinking Water

Everyone deserves to have clean drinking water. But for much of our history, rural communities and Native nations — especially historically marginalized communities — have lacked access to this basic foundation of life and health. While unsafe drinking water is an environmental justice and public health issue for both urban and rural places, rural communities face barriers related to scale and remoteness that require specialized solutions, including prioritization and support from non-rural agencies, organizations, and leaders. Across the country, rural communities and Native nations are working to build systems that work for their specific needs.

“It was a community effort, what we did. It took all of us organizing for what the community needed. We had churches organizing buses, and elderly people going up to the county commission meeting every month. It opened up the eyes of a lot of people here. Now they’re talking about air and water quality—landfill, pollution, hog waste. Our success with the water opened up the door for that.”

Edward Gillim, community leader, Sampson County, North Carolina

Voices: Communities Creating Clean Water Systems

Access to safe drinking water is a question of environmental justice because structural racial, economic, and geographic inequities have contributed to the causes of water contamination and hindered efforts to create needed systems for affected communities. Structural discrimination based on place, race, and class has contributed to the location of pollution sources near underinvested communities and communities of color like Ivanhoe, NC, as well as to challenges in accessing funding and other support for solutions.

The communities and organizations profiled in this case study are all working hard to design, build, and maintain effective rural clean water systems. They are envisioning and building thriving futures of equitable rural prosperity. They generously shared their thoughts, focusing on two key questions: What structural challenges keep rural communities from accessing clean water solutions? and What will it take for rural communities to drive their own clean water solutions?

“In my traditional Indigenous head, they’re not actually natural disasters, they’re human disasters. Mama, she’s just doing what she needs to do, she’s being insulted and abused. What are we going to do with those water systems [damaged by disasters]—are we going to rebuild them as is? How do we think outside the box on reconstructions? How are we going to construct water systems that are more resilient and can withstand more? How are we going to protect our source water? How are we going to lessen depletion?”

Jacqueline Shirley, RCAC

Place Matters

“Why don’t they just move?” This all-too-common urban response to rural challenges — even from well-intentioned leaders with a stated focus on equity — is to question whether struggling rural communities should exist at all. There is a common and persistent sentiment that people should simply leave these places rather than receive investment and support. As shocking as this response may be, given its prevalence, it is essential to address it directly.

First, people are not pieces on a game board — they have deep relationships with family, friends, community, and land that sustain them as key parts of their history and identity. Rural place-based networks are essential to the health of rural people and communities, and they support people when formal systems fail them — and formal systems are failing rural people, especially in historically marginalized communities.

Second, for communities of color and Native communities, the land they occupy is a vital part of their history, resilience, and perseverance. These communities were often forced to their current locations because the land was less desirable, and they should not be asked to abandon these places without the investment and opportunity they have historically been denied.

Finally, rural and urban communities are also deeply interdependent — rural communities provide food, energy, manufacturing, and other resources that the country depends on, though this relationship has historically been inequitable and extractive. At the most basic level, rural communities are valuable in and of themselves and deserve to achieve equitable prosperity and thrive on their own terms.

“Rural economic justice is so different from what everybody understands — we have to do so much education. My fear is by the time people I work with get to explain what it’s like, the funds will have evaporated and folks who really need it won’t get it. I feel like we’ve missed some grants because the funders didn’t quite get the difference between rural and urban projects.”

Sherri White-Williamson, EJCAN

Aspen CSG’s consultant Rebecca Huenink led the writing process for our  What’s Working in Rural  series. We are grateful for her contributions.

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Challenges to Sustainable Safe Drinking Water: A Case Study of Water Quality and Use across Seasons in Rural Communities in Limpopo Province, South Africa

Joshua n. edokpayi.

1 Department of Hydrology and Water Resources, University of Venda, Thohoyandou 0950, South Africa; [email protected]

2 Department of Civil and Environmental Engineering, University of Virginia, Charlottesville, VA 22904, USA; ude.qud@drelhak (D.M.K.); moc.liamg@320hlc (C.L.H.); ude.ainigriv@sm4rfc (C.R.); ude.ainigriv@e9saj (J.A.S.)

Elizabeth T. Rogawski

3 Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA; ude.ainigriv@m5rte

4 Division of Infectious Diseases & International Health, University of Virginia, Charlottesville, VA 22908, USA; ude.ainigriv.ccm.liamcsh@v8dr

David M. Kahler

5 Center for Environmental Research and Education, Duquesne University, Pittsburgh, PA 15282, USA

Courtney L. Hill

Catherine reynolds.

6 School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA

Emanuel Nyathi

7 Department of Animal Science, University of Venda, Thohoyandou 0950, South Africa; [email protected]

James A. Smith

John o. odiyo, amidou samie.

8 Department of Microbiology, University of Venda, Thohoyandou 0950, South Africa; [email protected] (A.S.); [email protected] (P.B.)

Pascal Bessong

Rebecca dillingham.

Author Contributions: Conceived and designed the experiments: J.N.E., E.T.R., D.M.K., C.L.H. Performed the experiments: J.N.E., E.T.R., D.M.K., C.L.H., C.R., E.N. Contributed reagents/materials/analysis tools: P.B., E.N., A.S., R.D., J.A.S., J.O.O. Analyzed the data: J.N.E., E.T.R., D.M.K., C.L.H. Wrote the paper: J.N.E., E.T.R., D.M.K., C.L.H. Participated in the editing of the manuscript: J.N.E., E.T.R., D.M.K., C.L.H., P.B., A.S., R.D., J.A.S., J.O.O., E.N., C.R.

Associated Data

Table S2: Membrane-filtration results for E. Coli and total coliforms of water sources,

Table S3: Anion concentrations (mg/L) of water sources,

Table S4: Major metal concentrations (mg/L) of water sources,

Table S5: Trace metal concentrations μg/L) of water sources.

Consumption of microbial-contaminated water can result in diarrheal illnesses and enteropathy with the heaviest impact upon children below the age of five. We aimed to provide a comprehensive analysis of water quality in a low-resource setting in Limpopo province, South Africa. Surveys were conducted in 405 households in rural communities of Limpopo province to determine their water-use practices, perceptions of water quality, and household water-treatment methods. Drinking water samples were tested from households for microbiological contamination. Water from potential natural sources were tested for physicochemical and microbiological quality in the dry and wet seasons. Most households had their primary water source piped into their yard or used an intermittent public tap. Approximately one third of caregivers perceived that they could get sick from drinking water. All natural water sources tested positive for fecal contamination at some point during each season. The treated municipal supply never tested positive for fecal contamination; however, the treated system does not reach all residents in the valley; furthermore, frequent shutdowns of the treatment systems and intermittent distribution make the treated water unreliable. The increased water quantity in the wet season correlates with increased treated water from municipal taps and a decrease in the average contaminant levels in household water. This research suggests that wet season increases in water quantity result in more treated water in the region and that is reflected in residents’ water-use practices.

1. Introduction

Clean and safe drinking water is vital for human health and can reduce the burden of common illnesses, such as diarrheal disease, especially in young children. Unfortunately, in 2010, it was estimated that 1.8 billion people globally drank water that was not safe [ 1 ]. This scenario is most common in developing countries, and the problem is exacerbated in rural areas [ 1 ]. Significant amounts of time are spent by adults and school children upon water abstraction from various sources [ 2 , 3 ]. It is estimated that, in developing countries, women (64%) and girls (8%) spend billions of hours a year collecting water [ 1 ]. The erratic supply of safe drinking and domestic water often affects good hygiene practices. In most developing countries of the world, inadequate supplies of drinking water can contribute to the underage death of children in the region [ 4 – 10 ].

Storage of collected water from rivers, springs, community stand-pipes, and boreholes is a common practice in communities that lack potable water supplies piped into their homes. Even when water is piped into the home, it is often not available on a continuous basis, and water storage is still necessary. Water is stored in various containers which include jerry cans, buckets, drums, basins and local pots [ 11 – 13 ]. It has been reported that when collection of water from sources of high quality is possible, contamination during transport, handling and storage and poor hygienic practices often results and can cause poor health outcomes [ 11 , 13 – 15 ].

South Africa is a semi-arid country that has limited water resources, and the provision of adequate water-supply systems remains a great challenge. In some of the major cities, access to clean and safe drinking water is comparable to what is found in other developed cities, but this is not the case in some cities, towns and most villages where there is constant erratic supply of potable water, and in some cases, there is no water supply system [ 16 ]. Although access to clean and safe drinking water is stipulated as a constitutional right for all South Africans in the country’s constitution [ 17 , 18 ], sustainable access to a potable water supply by millions of South Africans is lacking.

Residents of communities with inadequate water supply are left with no alternative other than to find local sources of drinking water for themselves. Rural areas are the most affected, and residents resort to the collection of water from wells, ponds, springs, lakes, rivers and rainwater harvesting to meet their domestic water needs [ 19 – 24 ]. Water from such sources is often consumed without any form of treatment [ 12 , 19 , 21 ]. However, these alternative sources of drinking water are often vulnerable to point and non-point sources of pollution and are contaminated frequently by fecal matter [ 5 , 19 , 25 ]. A report by the South African Council for Scientific and Industrial Research clearly showed that almost 2.11 million people in South Africa lack access to any safe water infrastructure. The consumption of water from such unimproved sources without treatment constitutes a major public health risk [ 26 ].

Consumption of contaminated drinking water is a cause of diarrheal disease, a leading cause of child mortality in developing countries with about 700,000 deaths of children under the age of 5 reported in 2011 [ 10 , 27 ]. In South Africa, diarrhea is one of the leading causes of death among young children, and this problem is worst in children infected with HIV (Human Immunodeficiency Virus).

The health risks associated with the consumption of unsafe drinking water are not only related to infectious diseases but also to other environmental components such as fluoride, arsenic, lead, cadmium, nitrates and mercury. Excessive consumption of these substances from contaminated drinking water can lead to cancer, dental and skeletal fluorosis, acute nausea, memory lapses, renal failure, anemia, stunted growth, fetal abnormalities and skin rashes [ 16 , 28 ]. Groundwater contamination with high arsenic concentrations have been reported in Bangladesh, and high fluoride concentrations have been reported in the drinking water from various provinces in South Africa [ 28 – 34 ].

Temporary seasonal variations have been reported to influence the levels of contaminants in various water sources differently. The key environmental drivers across the wet and dry seasons include: volume of water, flow, frequency of rainfall events, storm run-off, evaporation and point sources of pollution [ 35 , 36 ]. An increase in storm-water run-off within a river catchment may increase the level of contaminants due to land-use activities. Increased water volume could lead to a decrease in the concentration of contaminants due to the dilution effect. A low incidence of rainfall and high evaporation can cause a contaminant to concentrate in water. Very few water-quality parameters such as turbidity are expected to be higher in the wet season. Other parameters can vary depending on the key environmental drivers. There is paucity of data on the effect of change across seasons on water-use practices among household in rural areas of developing countries.

The geographic area for this study is located 35 km north of Thohoyandou, in Limpopo Province, South Africa. The area is primarily agricultural, such that water contamination by nitrates is a potential concern. In addition, mining operations in the area may contaminate water sources with heavy metals.

The significance of this study lies in the broad characterization of water-quality parameters that could affect human health, which is not restricted to microbiological analysis. In a rural community, the primary concern of drinking water is the microbiological quality of the water and chemical constituents are often considered not as problematic. This study was designed to evaluate a broad spectrum of water-quality constituents of natural water sources and household drinking water used by residents of rural communities in Limpopo Province. We also aimed to determine how water sources and collection practices change between dry and wet seasons within a one-year sampling period.

2. Materials and Methods

2.1. study design.

A baseline census of 10 villages in the Thulamela Municipality of Limpopo Province was completed to identify all households in which there was at least one healthy child under 3 years of age in the household, the child’s caregiver was at least 16 years of age, and the household did not have a permanent, engineered water-treatment system. 415 households that met these eligibility criteria were enrolled for the purposes of a water-treatment intervention trial. The baseline assessment of water-quality and use practices is reported here. Caregivers of the child under 3 years of age were given a questionnaire concerning demographics, socioeconomic status, water-use practices, sanitation and hygiene practices, and perceptions of water quality and health. In addition, a sample of drinking water was taken from a random selection of 25% of the total enrolled households in the dry (June–August 2016) and wet seasons (January–February 2017). The participant population was sorted by community, as a surrogate for water supply, and one-third from each community was randomly selected by a random number generated within Microsoft Excel (Seattle, WA, USA), which was sampled. The protocol used was approved by the Research Ethics Committee at the University of Venda (SMNS/15/MBY/27/0502) and the Institutional Review Board for Health Sciences Research at the University of Virginia (IRB-HSR #18662). Written informed consent was obtained from all participants and consent documentation was made available in English and Tshivenda. The majority of the baseline surveys were conducted in the dry season (approximately April to October). Six-months later, follow-on surveys were conducted at the height of the wet season (approximately November to March; however, the height of the season in 2016–17 was January to March).

2.2. Regional Description of the Study Area

The communities are located in a valley in the Vhembe District of Limpopo Province, South Africa ( Figure 1 ). The valley surrounds the Mutale River in the Soutpansberg Mountains and is located around 22°47′34′′ S and 30°27′01′′ E, in a tropical environment that exhibits a unimodal dry/wet seasonality ( Figure 2 ). In recent years, the area has received annual precipitation between 400 mm and 1100 mm; more importantly, the timing of the precipitation is highly variable ( Figure 2 ). Specifically, in 2010, the annual precipitation was about 750 mm; however, the majority of the precipitation came in March while, traditionally, the wet season begins earlier, in September or October. The year 2011 had the highest precipitation in the six-year period and had the majority of the rainfall in November. The years 2012 and 2015 began with a typical precipitation pattern; however, the rainfall did not continue as it did in 2013 and 2014. Annual temperature of the area also varies, with the highest temperature always recorded in the wet season ( Figure 3 ). There has been much variability of temperature in past years; however, this is beyond the scope of this study. The abbreviations used in Figure 1 and other figures, including the supplementary data and the type of the various water sources used in this study, are shown in Table 1 .

Map of the study area. The communities are all located within the Mutale River watershed. The rivers are indicated in blue, villages outlined in purple, environmental samples in blue squares, tributaries in green circles (which have intermittent flow), watershed boundary in orange. This heavily agricultural area has cultivated areas along both sides of thee Mutale River for the vast majority of the region; the area is shown with green outlines. There are two identified brick-processing areas shown in brown rectangles. Unfortunately, some sites are so close that the markers overlap (as with CR and IR). The location of the community supplies (CA, CB, and CC) are not shown to protect the privacy of those villages. See supplemental information for Google Earth files.

Precipitation trends in the study area. ( a ) Annual precipitation by hydrologic year. Data quality are presented on a scale of zero to unity where the quantity shown represents the proportion of missing or unreliable data in a year; ( b ) Cumulative precipitation for the last five complete years; ( c ) Average monthly precipitation calculated for years with greater than 90% reliable data (bottom right). All data are presented by the standard Southern hemisphere hydrologic year from July to June numbered with the ending year. Data are from the Nwanedzi Natural Reserve at the Luphephe Dam (17 km from the study area) and fire available through the Republic of South Africa, Department of Water and Sanitation, Hydrologic Services ( http://www.dwa.gov.za/Hydrology/ ).

The mean monthly temperature in the region recorded at Punda Milia. ( a ) Mean monthly temperature based on the means from 1962–1984; ( b ) Mean monthly temperature record. Data are available from the National Oceanic and Aviation Administration (U.S.), National Climatic Data Center, Climate Data Online service ( https://www.ncdc.noaa.gov/cdo-web/ ).

Abbreviations, water sources and type.

Agriculture occupies tine greatest land cover in the valley. Mogt households are engaged in some level of farming. Crops cultivated include maize and vegetables, and tree fruits include mangos and citrus fruits. Livestock is prevalent in the area with chickens, goats, and cattle. Smaller animals typically remain closer to households and larger animals graze throughout the region without boundaries. There are several brick-making facilities in the valley that include excavation, brick-forming and drying.

2.3. Water Sources

Drinking water in the study communities is available from a number of municipal and natural sources. The primary source of drinking water for seven of the villages is treated, municipal water. Two of the villages have community-level boreholes, storage tanks, and distribution tanks. An additional village has a borehole as well; however, residents report that, since its installation, the system has never supplied water.

The water for the treatment facility is drawn from behind a weir in the Mutale River and pumped to a retention basin. The water then undergoes standard treatment that includes pH adjustment, flocculation, settling, filtration, and chlorine disinfection. Water is then pumped to two elevated tanks that supply several adjacent regions, including the study area. Specifically, Branch 1 supplies Tshandama, Pile, Mutodani, Tshapasha and Tshibvumo; Branch 2 supplies an intermediary tank that in turn serves Matshavhawe, Muledane and Thongwe. Households can pay for a metered yard connection for the water used; these yard connections can be connected to household plumbing at the household’s discretion. The treated municipal water service is intermittent. Service in Tshandama and Pile was observed to be constant during the wet season and for only about two to three days per week during the dry season. Service in the remaining communities is two to four days per week during the wet season and about two days per week during the dry season. Furthermore, for the past two years, major repairs in the dry season caused the treated municipal water to cease completely. Households typically stored water for the periods when the treated municipal water was off; however, when the municipal water was unavailable for longer periods or not on the anticipated schedule, households obtained water from natural sources. The community-level boreholes provided water almost constantly but were subject to failure and delays in repairs.

Aside from the municipal sources, many residents of three villages have access to a community installed and operated distribution system that delivers water from the adjacent ephemeral rivers throughout the community (CA, CB, and CC). These systems are constructed with 50 mm to 70 mm (5 to 7 × 10 −2 m) high-density polyethylene pipes. Even these community-level schemes provide water on a schedule and sometimes require repair. Another common source of water for the community is springs. These shallow groundwater sources are common in the valley; however, there are communities that do not have a nearby spring. Some springs have had a pipe placed at the outlet to keep the spring open and facilitate filling containers. Researchers did not observe any constructions around the springs to properly isolate them from further contamination, and they are, therefore, not improved water sources. Pit latrines are common in every household throughout the region. Source (TS) is located near these communities while other springs (OS, LS) are located in agricultural areas. Boreholes provide deep groundwater supplies but require a pump. Such systems provide water as long as there is power for the pump and the well is deep enough to withstand seasonal variations. The two clinics in the study area surveyed each relied on a borehole for their water supply. Some residents also collected water directly from the river. The Mutale River is a perennial river; however, the ephemeral rivers, the Tshiombedi, Madade, Pfaleni, and Tshala Rivers, do not flow in the dry season all the way to the floor of the valley. The Tshala River has a diversion to a lined irrigation canal that always carries water, but there is very little flow that remains in the natural channel.

2.4. Water Sampling

The team of community health workers (CHW) that had previously conducted the MAL-ED (Malnutrition and Enteric Diseases) study in the same region [ 37 ] were recruited to assist with the data collection for this study; specifically, the regional description and water sources. These CHWs have an intimate knowledge of the communities as they are residents and have conducted health research in the area. The CHWs provided information on the location and condition of the various water sources in the study communities.

Water sources were tested during two intensive study periods: one in the dry season (June–August, 2016) and the other in the wet season (January–February, 2017). Water sources for investigation were selected based on identification from resident community health workers. Single samples were taken from all 28 identified drinking water sources in the 10 villages and three days of repeated samples were taken from six sources, which represented a range of sources (e.g., surface, borehole, shallow ground, pond, and municipal treated) in the dry season. Single samples of 17 of the original sources and three days of repeated samples were taken from five sources in the wet season, six months later. Some sources were not resampled because the routes to the sources were flooded, and these sources were likely infrequently used during the wet season due to blocked pathways. The wet and dry season measurements gave two different scenarios for water-use behaviors and allowed the researchers to measure representative water-quality parameters.

2.5. Measurement of Physicochemical Parameters

Physicochemical parameters of source water samples were measured in the field by a YSI Professional Plus meter (YSI Inc., Yellow Springs, OH, USA) for pH, dissolved oxygen and conductivity. The probes and meter was calibrated according to the manufacturer’s instructions. Turbidity was measured in the field with an Orbeco-Hellige portable turbidimeter (Orbeco Hellige, Sarasota, FL, USA) (U.S. Environmental Protection Agency method 180.1) [ 38 ]. The turbidimeter was calibrated according to the manufacturer’s instructions. Measured levels were compared to the South African water-quality standards in the regulations [ 39 ], pursuant to the Water Services Act of 1997.

2.6. Microbiological Water-Quality Analysis

Escherichia coli ( E. coli ) and total coliform bacteria were measured in both source and household water samples by membrane filtration according to U.S. Environmental Protection Agency method 10,029 [ 40 ]. Sample cups of the manifold were immersed in a hot-water bath at 100 °C for 15 min. Reverse osmosis water was flushed through the apparatus to cool the sample cups. Paper filter disks of 47 mm (4.7 × 10 −2 m) diameter and 0.45 μm (4.5 × 10 −7 m) pore size (EMD Millipore, Billerica, MA, USA) were removed from their sterile, individual packages and transferred to the surface of the manifold with forceps with an aseptic technique. Blank tests were run with reverse osmosis dilution water. Two dilutions were tested: full-strength (100 mL sample) and 10 −2 (1 mL sample with 99 mL of sterile dilution water) were passed through the filters; this provides a range of zero to 30,000 CFU/100 mL (colony forming units) for both E. coli and total coliforms. The filter paper was placed in a sterile petri dish with absorbent pad with 2 mL (2 × 10 −6 m 3 ) of selective growth media solution (m-ColiBlue24, EMD Millipore, Billerica, MA, USA). The samples were incubated at 35 °C (308.15 K) for 23–25 h. Colonies were counted on the full-strength sample. If colonies exceeded 300 (the maximum valid count), the dilution count was used. In all tests, the dilution value was expected to be within 10 −2 of the full-strength value and the sample was discarded otherwise.

The distribution of the household bacteria levels was evaluated by the (chi square) χ 2 goodness-of-fit test for various subsets of the data. Subsets of the data were then compared by an unpaired Student’s t-test for statistical significance; specifically, wet versus dry season levels as well as any other subsets that could demonstrate differences within the data.

2.7. Major Metals Analysis

A Thermo ICap 6200 Inductively Coupled Plasma Atomic Emission Spectrometer (ICP-AES, Chemetix Pty Ltd., Johannesburg, South Africa) was used to analyze the major metals in the various samples. The National Institute of Standards and Technology traceable standards (NIST, Gaithersburg, MD, USA) purchased from Inorganic Ventures (INORGANIC VENTURES 300 Technology Drive Christiansburg, Christiansburg, VA, USA) were used to calibrate the instrument for the quantification of selected metals. A NIST-traceable quality control standard from De Bruyn Spectroscopic Solutions, Bryanston, South Africa, were analyzed to verify the accuracy of the calibration before sample analysis, as well as throughout the analysis to monitor drift.

2.8. Trace Metals Analysis

Trace elements were analyzed in source water samples using an Agilent 7900 Quadrupole inductively coupled plasma mass spectrometer (ICP-MS) (Chemetix Pty Ltd., Johannesburg, South Africa). Samples were introduced via a 0.4 mL/min (7 × 10 −9 m 3 s −1 ) micro-mist nebulizer into a Peltier-cooled spray chamber at a temperature of 2 °C (275.15 K), with a carrier gas flow of 1.05 L/min (1.75 × 10 −5 m 3 s −1 ). The elements V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se were analyzed under He-collision mode to remove polyatomic interferences. NIST-traceable standards was used to calibrate the instrument. A NIST-traceable quality control standard of a separate supplier to the main calibration standards was analyzed to verify the accuracy of the calibration before sample analysis.

2.9. Anion Analysis

The anions were analyzed in source-water samples as stated in Edokpayi et al. [ 41 ]. Briefly, an Ion Chromatograph (Metrohm, Johannesburg, South Africa) was used to analyze the concentrations of fluoride, bromide, nitrates, chloride and sulfate. Calibration standards in the range of 1–20 mg/L were prepared from 100 mg/L stock solution containing all the test elements. Prior to analysis, the samples were filtered with a 0.45 μm (4.5 × 10 −7 m) syringe filter. Eluent for the sample run was prepared from sodium bicarbonate and sodium carbonate. A 50 mmol/L sulphuric acid with a flow rate of 0.5 mL/min (8 × 10 −9 m 3 s −1 ) was used as suppressant.

3.1. Socio-Demographic Characteristics of Enrolled Households

We included 405 enrolled households who completed the baseline questionnaire. The majority of caregivers were the mothers (n = 342, 84.4%, median age = 27 years) or grandmothers (n = 51, 12.6%, median age = 50 years) of a young child in the household. Almost all the caregivers had completed at least secondary school education (n = 371, 91.6%). Median monthly income for the entire household was USD$106 (interquartile range (IQR): 71–156). Access to improved sanitation was high. 373 (n = 92.1%) households used an improved pit latrine, and only 19 (n = 4.7%) reported open defecation. However, few households (n = 35,8.6%) reported having a designated place to wash hands near their toilet, and only 29% (n = 119) reported always using soap when washing hands.

Most households had their primary water source ( Table 2 ) piped into their or their neighbor’s yard (dry: n = 226, 62.3%; wet: n = 241, 67.5%) or used a public tap (dry: n = 69, 19.0%; wet: n = 74, 20.7%). A minority (dry: n = 40, 11.0%; wet: n = 19, 5.3%) collected their water directly from rivers, lined canals, or springs. Water was collected by adult women in most households, and it was reported to take a median of 10 min (IQR, both seasons: 5–30) to go to their water source, collect water, and come back in one trip. Three quarters (n = 270, 74.4%) reported that their water source was not continually available in the dry season and two-thirds (n = 234, 65.5%) in the wet season. Almost half (48.9%) reported interruptions in availability that lasted at least 7 days in the dry season and 32.8% in the wet season. Households stored water during interruptions and/or collected water from alternative sources (dry: n = 133, 36.6%; wet: n = 115, 32.2%), which were surface water or shallow groundwater sources (e.g., rivers, lined canals, or springs).

Primary drinking-water sources reported among 363 and 357 households in the study area in the dry and wet seasons, respectively.

Household water was most frequently stored in jerry cans or plastic buckets (n = 363, 89.7%), while 25 households stored water in large drums or plastic tanks (6.2%). Most households reported that their drinking water containers were covered (n = 329, 81.2%), but most used a cup with a handle (n = 281, 69.4%) or their hands (n = 93, 23.0%) for water collection ( Table 3 ). Only 13.3% (n = 54) households reported treating their water, mainly by boiling (n = 22), chlorine (n = 15), or letting the water stand and settle (n = 11).

Mode of water collection from storage containers.

Approximately one-third of caregivers (n = 114, 28.2%) perceived that one can get sick from drinking water (n = 114, 28.2%), and cited diarrhea, schistosomiasis, cholera, fever, vomiting, ear infections, malnutrition, rash, flu and malaria as specific illnesses associated with water. Despite these perceptions, the majority were satisfied with their current water source (n = 297, 73.3%). Those who were unsatisfied cited reasons of insufficient quantity (n = 75), shared water supply (n = 65), uncleanliness (n = 73), cloudiness (n = 47), and bad odor or taste (n = 38).

3.2. Physicochemical and Microbiological Characteristics of the Water Sources

pH and conductivity values ranged between 5.5–7.3 and 24–405 μS/cm in the wet season and 5.8–8.7 and 8–402 μS/cm in the dry season ( Table S1 ). Both pH and conductivity levels were within the recommended limits of the World Health Organization (WHO) for drinking water. The microbiological results and turbidity of the sources tested are presented in Figures ​ Figures4 4 and ​ and5, 5 , and Table S2 , respectively. Microbiological data show contamination with E. coli , a fecal coliform that is potentially pathogenic, and other coliform bacteria.

Membrane filtration results for ( a ) E. coli and ( b ) other coliforms. Data are presented for wet and dry seasons. The four ephemeral rivers (*) have no dry season data because they had no flow; all other sources have the results reported, some of which are zero or near-zero. South African National Standard (SANS 241:1-2015) set the limit of 0 CFU/100 mL for E. coli and 10 CFU/100 mL for total coliforms (CFU/10 −4 m 3 ). Ephemeral rivers that do not flow all the way into the valley are indicated (*) in the dry season.

Turbidity of the water sources in the study area. Two to three measurements were taken during an intensive study period from 13 January 2017 to 4 February 2017 in the wet season and three to four measurements from 5 June 2016 to 15 July 2016 in the dry season. The median measurement of the values is reported here. Ephemeral rivers that do not flow all the way into the valley are indicated (*) in the dry season.

Municipal treated water never showed any detectable colony-forming units (CFU) in a 100 mL sample for E. coli , which is within the Soufh African regulation [ 39 ]. In the wet season, other coliform bacteriaweae detected in the treated wtter (a median valueof 10 CFU/100 mL wac recorded).

Household sample of stored water ( Figure 6 ) show that bacterial contamination levels ranged from no detectable colonies lo the maximum detection level of our protocol of 30,000 CFU/100 mL. There is a trend that total colitorm levels ere lower (during the wet season than the dry season. In the wet season, some communities within the sturdy area had access to constant municipal treated water as monitored by researcher verification of public tap-watcr availebJlity. Othet communities had intermittent access to municipal treated water. Of these honseholds, those that had constant access to treated water at or near their household did have less total coliform in their stored water than those with intermittent services ( Figure 7 ). This neglects the communities that are outside of the municipal treated-water servic e area.

Box-and-whisker plot of total coliform measurements of stored, untreated water in study households in the wet (n = 95) and dry (n = 103) seasons. The box-and-whisker plot indicates the mean (diamond), first, second, and third quartiles (box), and minimum and maximum (whiskers).

Box-and-whisker plot of total coliform measurements of stored water in the wet season in study households in communities that had verified continuous access to municipal treated water versus verified intermittent access.

The total coliform from households in communities with verified continuous treated water had a log-normal distribution (verified by 99%, α = 1 significance level, χ 2 goodness-of-fit test) and were statistically significantly lower (α =1 significance level) than those from households in communities with verified intermittent treated water. Unfortunately, due to the low number of samples from intermittent households, a χ 2 goodness-of-fit test was not meaningful.

3.3. Anion Concentrations

Major anions investigated in the various water sources fell within the recommended guideline values from the WHO [ 42 ]. Fluoride concentrations ranged from below the detection limit (bdl) to 0.82 mg/L in the dry season and to 1.48 mg/L ( Table S3 ) in the wet season. Fluoride levels fell below the threshold limit for fluoride in drinking water from the WHO (1.5 mg/L). Nitrates were also observed within the limit of drinking water, between bdl–17.48 mg/L and bdl–9.72 mg/L in the dry and wet seasons, respectively. Chloride, sulfate and phosphate levels were also present in moderate levels in the various water sources; however, a relatively high concentration of chloride of 462.9 mg/L was determined in the Mutale River in the wet season.

3.4. Trace and Major Elements Composition

Major metals in the various water sources in both seasons complied with the recommended limits of SANS and WHO in drinking water [ 39 , 42 ]. Sodium concentrations in the range of 3.14–41.03 mg/L and 3.02–15.34 mg/L were measured in the wet and the dry seasons, respectively ( Table S4 ). Low values of potassium were measured. Calcium levels ranged between 0.66–33.91 mg/L and 0.53–27.39 mg/L, in the wet and dry seasons, respectively. Low levels of magnesium were also found. Most of the water sources can be classified as soft water owing to the low levels of calcium and magnesium. Aluminium (Al) concentration ranged between 39.18–438 μg/L ( Figure 8 ). Two of the water sources which are community-based water supply systems recorded high levels of Al which exceeded the aesthetic permissible levels of drinking water; others fell within this limit. Similarly, the levels of iron (Fe) varied between 37.30–1354 mg/L and 35.21–1262 mg/L in the wet and the dry seasons, respectively ( Figure 9 ). Some of the sources showed high Fe concentration which exceeded the aesthetic permissible limit of WHO in drinking water [ 42 ]. Two community-based water systems had higher levels of Fe in the wet season as well as the major river in the region (Mutale River) for which high Fe levels were observed in both seasons. One of the clinic boreholes also recorded high levels of Fe above the permissible aesthetic value of (300 mg/L) in both seasons. Temporary seasonal variation was significant only in the levels of Fe and Al. In the wet season, their levels were generally higher than in the dry season. Some other trace metals of concern like Pb, Hg, As, Cd, Cr, Ni, Cu, Mn, Sr were all present at low levels that were below their recommended limits in drinking water for both seasons ( Table S5 ).

Aluminum, measured by an inductively coupled plasma mass spectrometer (ICP-MS), concentration for natural sources in the study area in the wet and dry seasons. The SANS 241 standard is shown (an operational standard is intended for treated water). Sources marked with * are intermittent sources and had no dry-season sample. Other sources have measured concentrations; although they may be too low to plot.

Iron, measured by an ICP-MS, concentration for natural sources in the study area in the wet and dry seasons. The SANS 241 standard is shown. Sources marked with * are intermittent sources and had no dry-season sample. Other sources have measured concentrations; although they may be too low to plot.

4. Discussion

This study provides a comprehensive description of water quality and drinking-water use across seasons in a low-resource community in rural South Africa, including a variety of water sources, ranging from the municipal tap to natural sources and a combination of both when the municipal tap was intermittently available.

Water sources in the study area, aside from the municipal tap, were highly contaminated with E. coli in both the wet and dry seasons; that is, E. coli was above the South African standard (acute health) of 0 CFU/100 mL. It is particularly important to note that E. coli was detected in the boreholes used for water at the local clinics, implying inadequate access to potable water for potentially immunocompromised patients. While the municipal treated water met the E. coli detection limit, the municipal tap did not always fall within the standards of turbidity (≤1 NTU operational and ≤5 NTU aesthetic) and total coliform (≤10 CFU/100 mL) [ 39 ]. These are not direct health risks; however, both measurements can be used to judge the efficacy of the treatment process and suggest that treatment may not have removed other pathogens that were not directly tested, such as protozoan parasites.

While the microbiological contamination of the drinking-water sources was not acceptable, the chemical constituents fell within the South African guidelines [ 39 ]. Calcium, sodium, magnesium and potassium were present in low levels and their concentrations complied with regulatory standards of SANS [ 39 ] and WHO [ 42 ]. Some metals (cadmium, mercury, arsenic and lead) known to be carcinogenic, mutagenic and teratogenic, causing various acute and chronic diseases to humans even at trace levels in drinking water, were investigated and found to be present in very low concentrations that could be of no health risk to the consumers of the various water resources in the region. However, some other metals, such as Al and Fe, were higher in some of the water sources; yet these were still well below the health guidelines for the respective constituent (recommended health levels from SANS and WHO are given as Al < 0.9 mg/L, Fe < 2 mg/L). At these levels, they do not present a health risk but could impart color and significant taste to the water thereby affecting its aesthetic value. Water sources from the community water-supply systems and one of the clinic boreholes recorded higher levels of Al and Fe. The other metals evaluated (copper, zinc, nickel, chromium, Se and Mn) were present in low levels that complied with their recommended limits in drinking water [ 39 , 42 ].

Fluoridation of drinking water is a common practice for oral health in many countries [ 43 ]. The required level of fluoride to reduce incidences of dental caries is in the range of 0.6–0.8 mg/L; however, levels above 1.5 mg/L are associated with dental and skeletal fluorosis [ 43 – 45 ]. The likelihood of fluorosis as a result of high concentration of fluoride is low in these communities, but there could be a high incidence of dental caries since fluoride levels below 0.6 mg/L were measured and some of the water sources did not have fluoride concentrations detectable by the instrument. The National Children’s Health Survey conducted in South Africa showed that 60.3% of children in the age group of 6 years have dental caries. Approximately a third (31.3%) of children aged 4–5 years in Limpopo province have reported cases of dental caries [ 44 , 45 ].

Chloride levels in the water sources do not cause any significant risk to the users except imparting taste to the water for some of the sources that recorded chloride levels above 300 mg/L. Although the study area is characterized by farming activities, the nitrate concentrations measured do not present any health risks. Therefore, the occurrence of methemoglobinemia or blue-baby syndrome as a result of high nitrate levels is unlikely. Other anions were present in moderate levels that would also not constitute any health risks. The levels of all the anions determined in the various sources were lower than the recommended guidelines of WHO [ 42 ].

The microbiological analysis of environmental water sources revealed several trends. Without exception in these samples, bacterial levels in the wet season were higher than in the dry season. This may be caused by greater runoff or infiltration, which carries bacteria from contaminated sources to these water bodies. The upward trend in bacteria in the municipal treated water is not explained by an increase in runoff, but may be due to higher turbidity of the intake for the municipal treated water in the wet season. The treatment facility workers reported to the researchers that they were unable to monitor the quality of the treated water due to instrument failure during the wet season surveillance period.

Water stored in the household showed that the mean total coliform in the wet season was lower than that in the dry season. This trend is opposite to what was observed in the source, or environmental samples. This difference may be explained by the greater availability of treated water in the wet season versus the dry season for approximately 40% of the sampled households ( Figure 7 ). In addition, it is possible that families try to save water during the dry season and do not reject residual water, while the rainy season allows easier washing of the container and for it to be filled with fresh water more regularly.

In the wet season, two communities had consistently treated water available from household connections (usually a tap somewhere in a fence-in yard) or public taps. While the municipal treated water was of lower quality in the wet season than the dry season, the quality was significantly better than most environmental sources.

Another potential explanation is that residents stored their water within their households for a shorter time, which is supported by the use data that showed interruptions in supply were more common and for longer duration in the dry season. The quality of the water stored in households with continuous supply versus intermittent supply also suggests that water availability may play a role in household water quality. This is consistent with research that demonstrates that intermittent water supply introduces contamination into the distribution system in comparison with continuous supply [ 46 ]. Intermittent supply of water may also result in greater quantity and duration of storage at household level, which could increase the likelihood of contamination.

While it has been shown that the quality of water used for drinking in these villages does not meet South African standards, this problem is confounded by evidence from surveys indicating that residents believe they have high-quality water and, therefore, do not use any form of treatment. In the rare case that they do, it is by letting the water stand and settle or by boiling. In addition, even if treated water is collected, there is a risk of recontamination during storage and again when using a cup held by a hand to retrieve water from storage devices, which was common in surveyed homes. In addition, there was little to no detectable residual chlorine in the municipal tap water to prevent recontamination. A previous study performed in an adjacent community showed higher household treatment levels; however, this may have been due to intervention studies in that community (the community in question was excluded from this study because of previous interventions) [ 47 ]. The study also concurred that boiling was the most common method employed.

Given that most of the water from the various sources in this community is contaminated and not treated, there is a high risk of enteric disease in the community. Lack of access to adequate water and sanitation cause exposure to pathogens through water, excreta, toxins, and water-collection and storage pathways, resulting in immense health impacts on communities [ 48 ]. A large burden of death and disability due to lack of access to clean water and sanitation is specifically associated with diarrheal diseases, intestinal helminths, schistosomiasis and trachoma [ 49 ]. While it was found in this study that the study area has a high prevalence of improved sanitation, the likelihood of poor water quality due to intermittent supply and lack of treatment poses a risk of the adverse health effects described. In a previous longitudinal cohort study of children in these villages, most children were exclusively breastfed for only a month or less, and 50% of children had at least one enteropathogen detected in a non-diarrheal stool by three months of age [ 50 ]. Furthermore, the burden of diarrhea was 0.66 episodes per child-year in the first 2 years of life, and stunting prevalence (length-for-age z-score less than −2) in the cohort increased from 12.4% at birth to 35.7% at 24 months [ 50 ]. It is likely that contaminated water contributed to the observed pathogen burden and stunting prevalence in these communities. In summary, microbiological contamination of the drinking water is high in the study area, and risk from other chemical constituents is low. Therefore, engineered solutions should focus more on improving the microbiological quality of the drinking water.

The intermittent supply in municipal tap water, inadequate water quality from alternative sources, and the risk of recontamination during storage suggest a need for a low-cost, point-of-use water-treatment solution to be used at the household level in these communities. Access to clean drinking water will contribute to improving the health of young children who are at highest risk of the morbidity and mortality associated with waterborne diseases. Such an intervention may go beyond the prevention of diarrhea by impacting long-term outcomes such as environmental enteropathy, poor growth and cognitive impairment, which have been associated with long-term exposure to enteropathogens [ 51 ]. This is supported by a recent finding that access to improved water and sanitation was associated with improvements on a receptive vocabulary test at 1, 5 and 8 years of age among Peruvian, Ethiopian, Vietnamese and Indian children [ 52 ]. The implementation of point-of-use water treatment devices would ensure that water is safe to drink before consumption in the homes of these villages, improving child health and development.

5. Conclusions

This study was comprehensive in the assessment of all aspects of water quality and corresponding water-use practices in rural areas of Limpopo Province. The results obtained indicate that microbiological water quality is more likely to have adverse effect on the consumers of natural water without adequate treatment, as E. coli was determined in all the natural water sources. Local needs assessments are critical to understanding local variability in water quality and developing appropriate interventions. Interventions to ensure clean and safe drinking water in rural areas of Limpopo province should, first and foremost, consider microbiological contamination as a priority. Risk-assessment studies of the impact of water quality on human health is, therefore, recommended.

Supplementary Material

Tables s1 through s5.

Table S1: Physical characteristics of water sources. Two to three measurements were taken during an intensive study period from 13 January 2017 to 4 February 2017 in the wet season, and three to four measurements from 5 June 2016 to 15 July 2016 in the dry season. The median measurement of the values is reported here. Sites with missing samples, such as ephemeral rivers that do not flow all the way into the valley in the dry season, are indicated (*). Sites with missing data due to instrument failure are indicated (#). Values that were below the detection limit are indicated (bdl). South African regulation (SANS 241:1-2015) and the World Health Organization Recommended Guidelines for Drinking Water Quality (Fourth Edition) are listed; parameters not listed are indicated (nl),

Acknowledgments:

This project was funded by the Fogarty International Center (FIC) of the National Institutes of Health (NIH) (Award Number D43 TW009359), National Science Foundation (NSF) (Award Number CBET-1438619), the Center for Global Health at the University of Virginia (CGH), and the University of Virginia’s Jefferson Public Fellows (JPC) program. The content is solely the responsibility of the authors and does not represent the official views of the funders. The authors also acknowledge the tireless work of the community field workers who undertook interventions and collected all of the survey data. The authors also acknowledge A. Gaylord, N. Khuliso, S. Mammburu, K. McCain and E. Stinger, who performed much of the water-quality analysis and T. Singh, who supported the laboratory analysis for inorganic materials.

Supplementary Materials: The following are available online at www.mdpi.com/s1 ,

Conflicts of Interest: The authors declare no conflict of interest.

Global Nitrate Water Pollution: Lessons from Nebraska's Platte River Valley and Beyond

Water pollution caused by agricultural practices is an increasingly alarming problem around the world. As the global demand for food continues to rise, more farmers are turning to pesticides and fertilizers to sustain and maximize output. The upshot of these practices, however, is the contamination of groundwater and surface water that negatively impacts lives and ecosystems.

Pesticides and Fertilizer: Friends or Foes?

The practice of using pesticides and fertilizers comes with a particular challenge that largely contributes to agricultural water pollution. As it is hard to gauge the ideal amount of pesticide and fertilizer for a given plant, farmers spray their crops liberally because they believe spraying more is preferable to spraying less. This causes excess chemicals from pesticides and fertilizers to either seep deep into the ground and into groundwater or be carried off by rain into other surface water—streams, rivers, lakes, and oceans.

Groundwater is especially important as a source of drinking water internationally. According to a report done by the United Nations Educational, Scientific, and Cultural Organization (UNESCO), roughly 2.5 billion people around the world rely on groundwater as their source of drinking water. In the U.S. alone, 40 percent of people rely on groundwater for drinking water, especially in rural areas where it is often the only source of drinking water for entire communities.

In addition to the health risks posed by groundwater, surface water contamination has similarly pernicious effects. As chemical contaminants from pesticides and fertilizers find their way into surface water, land and aquatic plants and animals are becoming ill or dying off . The threat of surface water contamination is especially well understood through the process of biomagnification . As people eat contaminated plants and animals, they too consume and ingest the chemicals; consequently, water contamination upsets entire ecosystems and the food chain.

With the effects water pollution has on people and ecosystems, water pollution caused by agricultural practices calls for urgent measures. In order to effectively apply a solution, it is essential to recognize where efforts would best be targeted. In the case of water pollution caused by agricultural practices, there is evidence to suggest that it is most effective to simultaneously clean up contaminated water and prevent chemical contamination in the first place. Part of this stems from the unfortunate reality that it is tremendously difficult to clean up contaminated water, given how quickly contaminants disperse when in the substance. For this reason, according to the Natural Resources Defense Council (NRDC), polluted groundwater aquifers alone, can be “unusable for decades, or even thousands of years.”

In addition to acknowledging the difficulty of cleaning up polluted water, it is important to recognize which particular contaminants have especially negative global effects. The Food and Agriculture Organization of the United Nations (FAO) argues that nitrate is among the worst. Nitrate comes from nitrogen, the main ingredient in fertilizers, implying that fertilizers, more so than pesticides, are one of the world’s greatest sources of water pollution. Although nitrates are vital for proper plant growth, they can be “ dangerous for humans in large amounts.”

Despite high amounts of nitrate dangerously affecting people’s health, the FAO claims that use of global nitrogen fertilizer is expected to grow in coming years with the rising demand for food, particularly in Sub-Saharan Africa, East and South Asia, and North America. Now, more than ever, it is pertinent to look for solutions that allow farmers to use fertilizers in more environmentally friendly ways.

Farmers and scientists in Nebraska’s Platte River Valley appear to have found an answer. Looking at their example might provide a better sense of what farmers around the world can do to prevent nitrate water pollution.

Case Study: Water Pollution in Nebraska’s Platte River Valley

Nebraska’s Platte River Valley is well-known for contributing to the state’s booming agricultural business. Right behind California, Texas, and Iowa, Nebraska ranks fourth in overall agricultural output in the United States. This success can partly be attributed to the valley’s nutrient rich-soil. As the Platte River runs its course, minerals are deposited into the surrounding ground. Farmers in Nebraska’s Platte River Valley take advantage of this natural fertilizer to sustain their agricultural practices.

However, the global demand for food is pressuring Nebraskan farmers to increase their crop yield, and consequently, to change their strategies. As such, from the later half of the 20th century and into the modern era, they have begun to couple the river’s natural fertilizer with chemical fertilizers. The effects of chemical fertilizer use have been similar to the effects seen around the world: nitrate water pollution.

While the Platte River aids Nebraska’s farmers, it also restricts the type of crops they can grow. Given the high amount of groundwater in the valley, deep-root plants are best suited to survive and thrive in the area. Thus, corn and soybeans are Nebraska’s main crops. These deep-rooted plants can withstand being swept by the unstable soil underneath them. Chemical fertilizers, on the other hand, lack the structural capacity to do the same. Instead, excess fertilizer seeps into the groundwater and drains into local streams and rivers. Hence, Nebraskan farmers are facing more nitrate in their drinking water.

The legal limit for nitrate in public water systems is 10 parts per million (ppm); in Nebraska, the levels are two to three times higher than that. Feeling personally responsible for Nebraska’s problem with nitrate water pollution, farmer Ken Seim and others are turning to precision technology to help prevent nitrate run-off.

The name of this precision technology is “Project Sense.” It was created by researchers from the University of Nebraska and relies on sensors to measure just the right amount of fertilizer a plant needs. According to the website Flatland , “Farmers would apply fertilizer evenly and generously across their fields. Some farmers figured that if some nitrogen fertilizer was good for their plants, more was better. That meant that some plants would get more than they could use, which left nitrates [leaching] into groundwater.” Project Sense prevents excess nitrate runoff. As the machine rolls through fields, its sensors measure the size and color of the plants. Based on this data, the machine is able to gauge how much fertilizer a plant needs, and then delivers the correct dosage.

Farmers like Seim have noticed less nitrate runoff from their farms; however, there is no existing research that investigates the potential long-term effect of using precision technology to solve nitrate water pollution on a larger scale. Part of this stems from how expensive the technology is, which makes it infeasible for enough farmers to use this technology in order to be able to do a proper study.

For farmers who cannot afford Project Sense, other options exist. Researchers from the University of Nebraska recommend cover crops as another method of mitigating nitrate water pollution. Cover crops are off-season crops, planted after main crops have already been harvested. They help fight soil erosion and maintain soil fertility, with the added benefit of retaining moisture and nitrate runoff.

Current Policies and Potential Solutions

Governments and international organizations around the world can also step up to the plate and fund research that helps tackle the global problem of nitrate water pollution. As of now, government farm subsidies around the world are used to control the cost and supply of crops, not agricultural practices. They are rarely used as investments in new research and technology that can help make agricultural practices more environmentally friendly. This makes it difficult for farmers to afford stopping environmentally damaging practices. Furthermore, lack of global legislation mandating farmers to institute environmentally friendly practices makes it even less likely that problems like nitrate water pollution will be sufficiently dealt with any time soon. As of now, such initiatives remain largely voluntary.

In the United States, for example, no laws mandate farmers to incorporate precision technology nor cover crops. Thus, as a 2010 report by the U.S. Department of Agriculture shows, areas particularly likely to be responsible for significant nitrate water pollution (Corn Belt) are also just as likely to not be applying methods to mitigate this problem.

In the developing countries of Africa and Asia, there are few, if any, policies mandating environmentally friendly agricultural practices; furthermore, poverty makes it difficult for farmers in developing countries to implement environmentally friendly agricultural practices. Such circumstances only exacerbate the problem of global nitrate water pollution.

Overall, evidence shows that the best way to mitigate the problem of global nitrate water pollution is to prevent it from happening in the first place. In order for that to happen, however, a balance between precision technology, government subsidies for research and farm technology, and laws mandating the implementation of environmentally friendly agricultural practices must exist. Otherwise, nitrate water pollution will continue to poison water systems, thereby disrupting people’s lives and ecosystems. As global fertilizer use is projected to grow, it is crucial that people around the world unite in collective action to help prevent further nitrate water pollution.

Jelena Dragicevic

Jelena studies history and literature with a secondary in economics and a citation in Russian. She specializes in Eastern European politics and military intelligence.

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Water Pollution: “Dal Lake a Case Study”

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• Shabina Masoodi 4 ,
• Lone Jaseem Saleem 4 ,
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• Aflak Rashid Wani 4 ,
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Dal lake is one of the famous freshwater lakes of Jammu & Kashmir and is rightly called as “Liquid jewel “in the heart of capital city Srinagar.

Over the years the lake is under serious anthropogenic activities which has resulted in pollution of the lake threatening its health and ecology. Despite many consultancies were engaged for the conservation of this lake yet the trophic condition of the lake has not shown any significant progress nor the water quality has improved.

In this paper an attempt has been made to assess the measures taken for its conservation, study the current Ecological status of the lake and reasons for the failure of the Conservation of the lake coupled with suggestive measures.

• Settling basin
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• Seasonal variation
• Suggestive measures

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MRD Kundangar, SabhaulSalim and Adnan Abubakr. Deweeding practices in Dal lake and their impact assessment Studies National Environment and Pollution Technology. vol.2, no.1. Pp 95–103, 2003.

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Qazi Tanveer, Houseboat sanitation and its impact on Dal lake Ecology. M tech. Dissertation. Punjab Technical University, 2017)

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Acknowledgement

Words at our command are not adequate in spirit and form to meet the ends of justice in matter of expression of profound sense of gratitude and indebtedness to Er Shabeena Masoodi and especially Dr MRD Kundangar, Former Director, Lakes & Waterways Development Authority, J&K for encouraging, material guidance, valuable suggestions and objective approach towards work which enables us to accomplish this paper.

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Masoodi, S., Saleem, L.J., Majeed, S., Wani, A.R., Furqan, M., Banday, R.J. (2022). Water Pollution: “Dal Lake a Case Study”. In: Kanwar, V.S., Sharma, S.K., Prakasam, C. (eds) Proceedings of International Conference on Innovative Technologies for Clean and Sustainable Development (ICITCSD – 2021). Springer, Cham. https://doi.org/10.1007/978-3-030-93936-6_54

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Ground Water Vulnerability Assessment: Predicting Relative Contamination Potential Under Conditions of Uncertainty (1993)

Chapter: 5 case studies, 5 case studies, introduction.

This chapter presents six case studies of uses of different methods to assess ground water vulnerability to contamination. These case examples demonstrate the wide range of applications for which ground water vulnerability assessments are being conducted in the United States. While each application presented here is directed toward the broad goal of protecting ground water, each is unique in its particular management requirements. The intended use of the assessment, the types of data available, the scale of the assessments, the required resolution, the physical setting, and institutional factors all led to very different vulnerability assessment approaches. In only one of the cases presented here, Hawaii, are attempts made to quantify the uncertainty associated with the assessment results.

Introduction

Ground water contamination became an important political and environmental issue in Iowa in the mid-1980s. Research reports, news headlines, and public debates noted the increasing incidence of contaminants in rural and urban well waters. The Iowa Ground water Protection Strategy (Hoyer et al. 1987) indicated that levels of nitrate in both private and municipal

wells were increasing. More than 25 percent of the state's population was served by water with concentrations of nitrate above 22 milligrams per liter (as NO 3 ). Similar increases were noted in detections of pesticides in public water supplies; about 27 percent of the population was periodically consuming low concentrations of pesticides in their drinking water. The situation in private wells which tend to be shallower than public wells may have been even worse.

Defining the Question

Most prominent among the sources of ground water contamination were fertilizers and pesticides used in agriculture. Other sources included urban use of lawn chemicals, industrial discharges, and landfills. The pathways of ground water contamination were disputed. Some interests argued that contamination occurs only when a natural or human generated condition, such as sinkholes or agricultural drainage wells, provides preferential flow to underground aquifers, resulting in local contamination. Others suggested that chemicals applied routinely to large areas infiltrate through the vadose zone, leading to widespread aquifer contamination.

Mandate, Selection, and Implementation

In response to growing public concern, the state legislature passed the Iowa Ground water Protection Act in 1987. This landmark statute established the policy that further contamination should be prevented to the "maximum extent practical" and directed state agencies to launch multiyear programs of research and education to characterize the problem and identify potential solutions.

The act mandated that the Iowa Department of Natural Resources (DNR) assess the vulnerability of the state's ground water resources to contamination. In 1991, DNR released Ground water Vulnerability Regions of Iowa , a map developed specifically to depict the intrinsic susceptibility of ground water resources to contamination by surface or near-surface activities. This assessment had three very limited purposes: (1) to describe the physical setting of ground water resources in the state, (2) to educate policy makers and the public about the potential for ground water contamination, and (3) to provide guidance for planning and assigning priorities to ground water protection efforts in the state.

Unlike other vulnerability assessments, the one in Iowa took account of factors that affect both ground water recharge and well development. Ground water recharge involves issues related to aquifer contamination; well development involves issues related to contamination of water supplies in areas where sources other than bedrock aquifers are used for drinking water. This

approach considers jointly the potential impacts of contamination on the water resource in aquifers and on the users of ground water sources.

The basic principle of the Iowa vulnerability assessment involves the travel time of water from the land surface to a well or an aquifer. When the time is relatively short (days to decades), vulnerability is considered high. If recharge occurs over relatively long periods (centuries to millennia), vulnerability is low. Travel times were determined by evaluating existing contaminants and using various radiometric dating techniques. The large reliance on travel time in the Iowa assessment likely results in underestimation of the potential for eventual contamination of the aquifer over time.

The most important factor used in the assessment was thickness of overlying materials which provide natural protection to a well or an aquifer. Other factors considered included type of aquifer, natural water quality in an aquifer, patterns of well location and construction, and documented occurrences of well contamination. The resulting vulnerability map ( Plate 1 ) delineates regions having similar combinations of physical characteristics that affect ground water recharge and well development. Qualitative ratings are assigned to the contamination potential for aquifers and wells for various types and locations of water sources. For example, the contamination potential for wells in alluvial aquifers is considered high, while the potential for contamination of a variable bedrock aquifer protected by moderate drift or shale is considered low.

Although more sophisticated approaches were investigated for use in the assessment, ultimately no complex process models of contaminant transport were used and no distinction was made among Iowa's different soil types. The DNR staff suggested that since the soil cover in most of the state is such a small part of the overall aquifer or well cover, processes that take place in those first few inches are relatively similar and, therefore, insignificant in terms of relative susceptibilities to ground water contamination. The results of the vulnerability assessment followed directly from the method's assumptions and underlying principles. In general, the thicker the overlay of clayey glacial drift or shale, the less susceptible are wells or aquifers to contamination. Where overlying materials are thin or sandy, aquifer and well susceptibilities increase. Vulnerability is also greater in areas where sinkholes or agricultural drainage wells allow surface and tile water to bypass natural protective layers of soil and rapidly recharge bedrock aquifers.

Basic data on geologic patterns in the state were extrapolated to determine the potential for contamination. These data were supplemented by databases on water contamination (including the Statewide Rural Well-Water Survey conducted in 1989-1990) and by research insights into the transport, distribution, and fate of contaminants in ground water. Some of the simplest data needed for the assessment were unavailable. Depth-to-bedrock information had never been developed, so surface and bedrock topographic

maps were revised and integrated to create a new statewide depth-to-bedrock map. In addition, information from throughout the state was compiled to produce the first statewide alluvial aquifer map. All new maps were checked against available well-log data, topographic maps, outcrop records, and soil survey reports to assure the greatest confidence in this information.

While the DNR was working on the assessment, it was also asked to integrate various types of natural resource data into a new computerized geographic information system (GIS). This coincident activity became a significant contributor to the assessment project. The GIS permitted easier construction of the vulnerability map and clearer display of spatial information. Further, counties or regions in the state can use the DNR geographic data and the GIS to explore additional vulnerability parameters and examine particular areas more closely to the extent that the resolution of the data permits.

The Iowa vulnerability map was designed to provide general guidance in planning and ranking activities for preventing contamination of aquifers and wells. It is not intended to answer site-specific questions, cannot predict contaminant concentrations, and does not even rank the different areas of the state by risk of contamination. Each of these additional uses would require specific assessments of vulnerability to different activities, contaminants, and risk. The map is simply a way to communicate qualitative susceptibility to contamination from the surface, based on the depth and type of cover, natural quality of the aquifer, well location and construction, and presence of special features that may alter the transport of contaminants.

Iowa's vulnerability map is viewed as an intermediate product in an ongoing process of learning more about the natural ground water system and the effects of surface and near-surface activities on that system. New maps will contain some of the basic data generated by the vulnerability study. New research and data collection will aim to identify ground water sources not included in the analysis (e.g., buried channel aquifers and the "salt and pepper sands" of western Iowa). Further analyses of existing and new well water quality data will be used to clarify relationships between aquifer depth and ground water contamination. As new information is obtained, databases and the GIS will be updated. Over time, new vulnerability maps may be produced to reflect new data or improved knowledge of environmental processes.

The Cape Cod sand and gravel aquifer is the U.S. Environmental Protection Agency (EPA) designated sole source of drinking water for Barnstable County, Massachusetts (ca. 400 square miles, winter population 186,605 in 1990, summer population ca. 500,000) as well as the source of fresh water for numerous kettle hole ponds and marine embayments. During the past 20 years, a period of intense development of open land accompanied by well-reported ground water contamination incidents, Cape Cod has been the site of intensive efforts in ground water management and analysis by many organizations, including the Association for the Preservation of Cape Cod, the U.S. Geological Survey, the Massachusetts Department of Environmental Protection (formerly the Department of Environmental Quality Engineering), EPA, and the Cape Cod Commission (formerly the Cape Cod Planning and Economic Development Commission). An earlier NRC publication, Ground Water Quality Protection: State and Local Strategies (1986) summarizes the Cape Cod ground water protection program.

The Area Wide Water Quality Management Plan for Cape Cod (CCPEDC 1978a, b), prepared in response to section 208 of the federal Clean Water Act, established a management strategy for the Cape Cod aquifer. The plan emphasized wellhead protection of public water supplies, limited use of public sewage collection systems and treatment facilities, and continued general reliance on on-site septic systems, and relied on density controls for regulation of nitrate concentrations in public drinking water supplies. The water quality management planning program began an effort to delineate the zones of contribution (often called contributing areas) for public wells on Cape Cod that has become increasingly sophisticated over the years. The effort has grown to address a range of ground water resources and ground water dependent resources beyond the wellhead protection area, including fresh and marine surface waters, impaired areas, and water quality improvement areas (CCC 1991). Plate 2 depicts the water resources classifications for Cape Cod.

Selection and Implementation of Approaches

The first effort to delineate the contributing area to a public water supply well on Cape Cod came in 1976 as part of the initial background studies for the Draft Area Wide Water Quality Management Plan for Cape

Cod (CCPEDC 1978a). This effort used a simple mass balance ratio of a well's pumping volume to an equal volume average annual recharge evenly spread over a circular area. This approach, which neglects any hydrogeologic characteristics of the aquifer, results in a number of circles of varying radii that are centered at the wells.

The most significant milestone in advancing aquifer protection was the completion of a regional, 10 foot contour interval, water table map of the county by the USGS (LeBlanc and Guswa 1977). By the time that the Draft and Final Area Wide Water Quality Management Plans were published (CCPEDC 1978a, b), an updated method for delineating zones of contribution, using the regional water table map, had been developed. This method used the same mass balance approach to characterize a circle, but also extended the zone area by 150 percent of the circle's radius in the upgradient direction. In addition, a water quality watch area extending upgradient from the zone to the ground water divide was recommended. Although this approach used the regional water table map for information on ground water flow direction, it still neglected the aquifer's hydrogeologic parameters.

In 1981, the USGS published a digital model of the aquifer that included regional estimates of transmissivity (Guswa and LeBlanc 1981). In 1982, the CCPEDC used a simple analytical hydraulic model to describe downgradient and lateral capture limits of a well in a uniform flow field (Horsley 1983). The input parameters required for this model included hydraulic gradient data from the regional water table map and transmissivity data from the USGS digital model. The downgradient and lateral control points were determined using this method, but the area of the zone was again determined by the mass balance method. Use of the combined hydraulic and mass balance method resulted in elliptical zones of contribution that did not extend upgradient to the ground water divide. This combined approach attempted to address three-dimensional ground water flow beneath a partially penetrating pumping well in a simple manner.

At about the same time, the Massachusetts Department of Environmental Protection started the Aquifer Lands Acquisition (ALA) Program to protect land within zones of contribution that would be delineated by detailed site-specific studies. Because simple models could not address three-dimensional flow and for several other reasons, the ALA program adopted a policy that wellhead protection areas or Zone IIs (DEP-WS 1991) should be extended upgradient all the way to a ground water divide. Under this program, wells would be pump tested for site-specific aquifer parameters and more detailed water table mapping would often be required. In many cases, the capture area has been delineated by the same simple hydraulic analytical model but the zone has been extended to the divide. This method has resulted in some 1989 zones that are 3,000 feet wide and extend 4.5

miles upgradient, still without a satisfactory representation of three-dimensional flow to the well.

Most recently the USGS (Barlow 1993) has completed a detailed subregional, particle-tracking three-dimensional ground water flow model that shows the complex nature of ground water flow to wells. This approach has shown that earlier methods, in general, overestimate the area of zones of contribution (see Figure 5.1 ).

In 1988, the public agencies named above completed the Cape Cod Aquifer Management Project (CCAMP), a resource-based ground water protection study that used two towns, Barnstable and Eastham, to represent the more and less urbanized parts of Cape Cod. Among the CCAMP products were a GIS-based assessment of potential for contamination as a result of permissible land use changes in the Barnstable zones of contribution (Olimpio et al. 1991) and a ground water vulnerability assessment by Heath (1988) using DRASTIC for the same area. Olimpio et al. characterized land uses by ranking potential contaminant sources without regard to differences in vulnerability within the zones. Heath's DRASTIC analysis of the same area, shown in Figure 5.2 , delineated two distinct zones of vulnerability based on hydrogeologic setting. The Sandwich Moraine setting, with deposits of silt, sand and gravel, and depths to ground water ranging from 0 to more than 125 feet, had DRASTIC values of 140 to 185; the Barnstable Outwash Plain, with permeable sand and fine gravel deposits with beds of silt and clay and depths to ground water of less than 50 feet, yielded values of 185 to 210. The DRASTIC scores and relative contributions of the factors are shown in Tables 5.1 and 5.2 . Heath concluded that similar areas of Cape Cod would produce similar moderate to high vulnerability DRASTIC scores. The CCAMP project also addressed the potential for contamination of public water supply wells from new land uses allowable under existing zoning for the same area. The results of that effort are shown in Plate 4 .

In summary, circle zones were used initially when the hydrogeologic nature of the aquifer or of hydraulic flow to wells was little understood. The zones improved with an understanding of ground water flow and aquifer characteristics, but in recognition of the limitations of regional data, grossly conservative assumptions came into use. Currently, a truer delineation of a zone of contribution can be prepared for a given scenario using sophisticated models and highly detailed aquifer characterization. However, the area of a given zone still is highly dependent on the initial assumptions that dictate how much and in what circumstances a well is pumped. In the absence of ability to specify such conditions, conservative assumptions,

FIGURE 5.1 Contributing areas of wells and ponds in the complex flow system determined by using the three-dimensional model with 1987 average daily pumping rates. (Barlow 1993)

such as maximum prolonged pumping, prevail, and, therefore, conservatively large zones of contribution continue to be used for wellhead protection.

The ground water management experience of Cape Cod has resulted in a better understanding of the resource and the complexity of the aquifer

FIGURE 5.2 DRASTIC contours for Zone 1, Barnstable-Yarmouth, Massachusetts.

system, as well as the development of a more ambitious agenda for resource protection. Beginning with goals of protection of existing public water supplies, management interests have grown to include the protection of private wells, potential public supplies, fresh water ponds, and marine embayments. Public concerns over ground water quality have remained high and were a major factor in the creation of the Cape Cod Commission by the Massachusetts legislature. The commission is a land use planning and regulatory agency with broad authority over development projects and the ability to create special resource management areas. The net result of 20 years of effort by many individuals and agencies is the application of

TABLE 5.1 Ranges, Rating, and Weights for DRASTIC Study of Barnstable Outwash Plain Setting (NOTE: gpd/ft 2 = gallons per day per square foot) (Heath 1988)

TABLE 5.2 Ranges, Rating, and Weights for DRASTIC Study of Sandwich Moraine Setting (NOTE: gpd/ft 2 = gallons per day per square foot) (Heath 1988)

higher protection standards to broader areas of the Cape Cod aquifer. With some exceptions for already impaired areas, a differentiated resource protection approach in the vulnerable aquifer setting of Cape Cod has resulted in a program that approaches universal ground water protection.

Florida has 13 million residents and is the fourth most populous state (U.S. Bureau of the Census 1991). Like several other sunbelt states, Florida's population is growing steadily, at about 1,000 persons per day, and is estimated to reach 17 million by the year 2000. Tourism is the biggest industry in Florida, attracting nearly 40 million visitors each year. Ground water is the source of drinking water for about 95 percent of Florida's population; total withdrawals amount to about 1.5 billion gallons per day. An additional 3 billion gallons of ground water per day are pumped to meet the needs of agriculture—a $5 billion per year industry, second only to tourism in the state. Of the 50 states, Florida ranks eighth in withdrawal of fresh ground water for all purposes, second for public supply, first for rural domestic and livestock use, third for industrial/commercial use, and ninth for irrigation withdrawals.

Most areas in Florida have abundant ground water of good quality, but the major aquifers are vulnerable to contamination from a variety of land use activities. Overpumping of ground water to meet the growing demands of the urban centers, which accounts for about 80 percent of the state's population, contributes to salt water intrusion in coastal areas. This overpumping is considered the most significant problem for degradation of ground water quality in the state. Other major sources of ground water contaminants include: (1) pesticides and fertilizers (about 2 million tons/year) used in agriculture, (2) about 2 million on-site septic tanks, (3) more than 20,000 recharge wells used for disposing of stormwater, treated domestic wastewater, and cooling water, (4) nearly 6,000 surface impoundments, averaging one per 30 square kilometers, and (5) phosphate mining activities that are estimated to disturb about 3,000 hectares each year.

The Hydrogeologic Setting

The entire state is in the Coastal Plain physiographic province, which has generally low relief. Much of the state is underlain by the Floridan aquifer system, largely a limestone and dolomite aquifer that is found in both confined and unconfined conditions. The Floridan is overlain through most of the state by an intermediate aquifer system, consisting of predominantly clays and sands, and a surficial aquifer system, consisting of predominantly sands, limestone, and dolomite. The Floridan is one of the most productive aquifers in the world and is the most important source of drinking water for Florida residents. The Biscayne, an unconfined, shallow, limestone aquifer located in southeast Florida, is the most intensively used

aquifer and the sole source of drinking water for nearly 3 million residents in the Miami-Palm Beach coastal area. Other surficial aquifers in southern Florida and in the western panhandle region also serve as sources of ground water.

Aquifers in Florida are overlain by layers of sand, clay, marl, and limestone whose thickness may vary considerably. For example, the thickness of layers above the Floridan aquifer range from a few meters in parts of west-central and northern Florida to several hundred meters in south-central Florida and in the extreme western panhandle of the state. Four major groups of soils (designated as soil orders under the U.S. Soil Taxonomy) occur extensively in Florida. Soils in the western highlands are dominated by well-drained sandy and loamy soils and by sandy soils with loamy subsoils; these are classified as Ultisols and Entisols. In the central ridge of the Florida peninsula, are found deep, well-drained, sandy soils (Entisols) as well as sandy soils underlain by loamy subsoils or phosphatic limestone (Alfisols and Ultisols). Poorly drained sandy soils with organic-rich and clay-rich subsoils, classified as Spodosols, occur in the Florida flatwoods. Organic-rich muck soils (Histosols) underlain by muck or limestone are found primarily in an area extending south of Lake Okeechobee.

Rainfall is the primary source of ground water in Florida. Annual rainfall in the state ranges from 100 to 160 cm/year, averaging 125 cm/year, with considerable spatial (both local and regional) and seasonal variations in rainfall amounts and patterns. Evapotranspiration (ET) represents the largest loss of water; ET ranges from about 70 to 130 cm/year, accounting for between 50 and 100 percent of the average annual rainfall. Surface runoff and ground water discharge to streams averages about 30 cm/year. Annual recharge to surficial aquifers ranges from near zero in perennially wet, lowland areas to as much as 50 cm/year in well-drained areas; however, only a fraction of this water recharges the underlying Floridan aquifer. Estimates of recharge to the Floridan aquifer vary from less than 3 cm/year to more than 25 cm/year, depending on such factors as weather patterns (e.g., rainfall-ET balance), depth to water table, soil permeability, land use, and local hydrogeology.

Permeable soils, high net recharge rates, intensively managed irrigated agriculture, and growing demands from urban population centers all pose considerable threat of ground water contamination. Thus, protection of this valuable natural resource while not placing unreasonable constraints on agricultural production and urban development is the central focus of environmental regulation and growth management in Florida.

Along with California, Florida has played a leading role in the United

States in development and enforcement of state regulations for environmental protection. Detection in 1983 of aldicarb and ethylene dibromide, two nematocides used widely in Florida's citrus groves, crystallized the growing concerns over ground water contamination and the need to protect this vital natural resource. In 1983, the Florida legislature passed the Water Quality Assurance Act, and in 1984 adopted the State and Regional Planning Act. These and subsequent legislative actions provide the legal basis and guidance for the Ground Water Strategy developed by the Florida Department of Environmental Regulation (DER).

Ground water protection programs in Florida are implemented at federal, state, regional, and local levels and involve both regulatory and nonregulatory approaches. The most significant nonregulatory effort involves more than 30 ground water studies being conducted in collaboration with the Water Resources Division of the U.S. Geological Survey. At the state level, Florida statutes and administrative codes form the basis for regulatory actions. Although DER is the primary agency responsible for rules and statutes designed to protect ground water, the following state agencies participate to varying degrees in their implementation: five water management districts, the Florida Geological Survey, the Department of Health and Rehabilitative Services (HRS), the Department of Natural Resources, and the Florida Department of Agriculture and Consumer Services (DACS). In addition, certain interagency committees help coordinate the development and implementation of environmental codes in the state. A prominent example is the Pesticide Review Council which offers guidance to the DACS in developing pesticide use regulation. A method for screening pesticides in terms of their chronic toxicity and environmental behavior has been developed through collaborative efforts of the DACS, the DER, and the HRS (Britt et al. 1992). This method will be used to grant registration for pesticide use in Florida or to seek additional site-specific field data.

Selecting an Approach

The emphasis of the DER ground water program has shifted in recent years from primarily enforcement activity to a technically based, quantifiable, planned approach for resource protection.

The administrative philosophy for ground water protection programs in Florida is guided by the following principles:

Ground water is a renewable resource, necessitating a balance between withdrawals and natural or artificial recharge.

Ground water contamination should be prevented to the maximum degree possible because cleanup of contaminated aquifers is technically or economically infeasible.

It is impractical, perhaps unnecessary, to require nondegradation standards for all ground water in all locations and at all times.

The principle of ''most beneficial use" is to be used in classifying ground water into four classes on the basis of present quality, with the goal of attaining the highest level protection of potable water supplies (Class I aquifers).

Part of the 1983 Water Quality Assurance Act requires Florida DER to "establish a ground water quality monitoring network designed to detect and predict contamination of the State's ground water resources" via collaborative efforts with other state and federal agencies. The three basic goals of the ground water quality monitoring program are to:

Establish the baseline water quality of major aquifer systems in the state,

Detect and predict changes in ground water quality resulting from the effects of various land use activities and potential sources of contamination, and

Disseminate to local governments and the public, water quality data generated by the network.

The ground water monitoring network established by DER to meet the goals stated above consists of two major subnetworks and one survey (Maddox and Spicola 1991). Approximately 1,700 wells that tap all major potable aquifers in the state form the Background Network, which was designed to help define the background water quality. The Very Intensively Studied Area (VISA) network was established to monitor specific areas of the state considered highly vulnerable to contamination; predominant land use and hydrogeology were the primary attributes used to evaluate vulnerability. The DRASTIC index, developed by EPA, served as the basis for statewide maps depicting ground water vulnerability. Data from the VISA wells will be compared to like parameters sampled from Background Network wells in the same aquifer segment. The final element of the monitoring network is the Private Well Survey, in which up to 70 private wells per county will be sampled. The sampling frequency and chemical parameters to be monitored at each site are based on several factors, including network well classification, land use activities, hydrogeologic sensitivity, and funding. In Figure 5.3 , the principal aquifers in Florida are shown along with the distribution of the locations of the monitoring wells in the Florida DER network.

The Preservation 2000 Act, enacted in 1990, mandated that the Land Acquisition Advisory Council (LAAC) "provide for assessing the importance

FIGURE 5.3 Principal aquifers in Florida and the network of sample wells as of March 1990 (1642 wells sampled). (Adapted from Maddox and Spicola 1991, and Maddox et al. 1993.)

of acquiring lands which can serve to protect or recharge ground water, and the degree to which state land acquisition programs should focus on purchasing such land." The Ground Water Resources Committee, a subcommittee of the LAAC, produced a map depicting areas of ground water significance at regional scale (1:500,000) (see Figure 5.4 ) to give decision makers the basis for considering ground water as a factor in land acquisition under the Preservation 2000 Act (LAAC 1991). In developing maps for their districts, each of the five water management districts (WMDs) used the following criteria: ground water recharge, ground water quality, aquifer vulnerability, ground water availability, influence of existing uses on the resource, and ground water supply. The specific approaches used by

FIGURE 5.4 General areas of ground water significance in Florida. (Map provided by Florida Department of Environmental Regulation, Bureau of Drinking Water and Ground Water Resources.)

the WMDs varied, however. For example, the St. Johns River WMD used a GIS-based map overlay and DRASTIC-like numerical index approach that rated the following attributes: recharge, transmissivity, water quality, thickness of potable water, potential water expansion areas, and spring flow capture zones. The Southwest Florida WMD also used a map overlay and index approach which considered four criteria, and GIS tools for mapping. Existing databases were considered inadequate to generate a DRASTIC map for the Suwannee River WMD, but the map produced using an overlay approach was considered to be similar to DRASTIC maps in providing a general depiction of aquifer vulnerability.

In the November 1988, Florida voters approved an amendment to the Florida Constitution allowing land producing high recharge to Florida's aquifers to be classified and assessed for ad valorem tax purposes based on character or use. Such recharge areas are expected to be located primarily in the upland, sandy ridge areas. The Bluebelt Commission appointed by the 1989 Florida Legislature, studied the complex issues involved and recommended that the tax incentive be offered to owners of such high recharge areas if their land is left undeveloped (SFWMD 1991). The land eligible

for classification as "high water recharge land" must meet the following criteria established by the commission:

The parcel must be located in the high recharge areas designated on maps supplied by each of the five WMDs.

The high recharge area of the parcel must be at least 10 acres.

The land use must be vacant or single-family residential.

The parcel must not be receiving any other special assessment, such as Greenbelt classification for agricultural lands.

Two bills related to the implementation of the Bluebelt program are being considered by the 1993 Florida legislation.

THE SAN JOAQUIN VALLEY

Pesticide contamination of ground water resources is a serious concern in California's San Joaquin Valley (SJV). Contamination of the area's aquifer system has resulted from a combination of natural geologic conditions and human intervention in exploiting the SJV's natural resources. The SJV is now the principal target of extensive ground water monitoring activities in the state.

Agriculture has imposed major environmental stresses on the SJV. Natural wetlands have been drained and the land reclaimed for agricultural purposes. Canal systems convey water from the northern, wetter parts of the state to the south, where it is used for irrigation and reclamation projects. Tens of thousands of wells tap the sole source aquifer system to supply water for domestic consumption and crop irrigation. Cities and towns have sprouted throughout the region and supply the human resources necessary to support the agriculture and petroleum industries.

Agriculture is the principal industry in California. With 1989 cash receipts of more than $17.6 billion, the state's agricultural industry produced more than 50 percent of the nation's fruits, nuts, and vegetables on 3 percent of the nation's farmland. California agriculture is a diversified industry that produces more than 250 crop and livestock commodities, most of which can be found in the SJV.

Fresno County, the largest agricultural county in the state, is situated in the heart of the SJV, between the San Joaquin River to the north and the Kings River on the south. Grapes, stone fruits, and citrus are important commodities in the region. These and many other commodities important to the region are susceptible to nematodes which thrive in the county's coarse-textured soils.

While agricultural diversity is a sound economic practice, it stimulates the growth of a broad range of pest complexes, which in turn dictates greater reliance on agricultural chemicals to minimize crop losses to pests, and maintain productivity and profit. Domestic and foreign markets demand high-quality and cosmetically appealing produce, which require pesticide use strategies that rely on pest exclusion and eradication rather than pest management.

Hydrogeologic Setting

The San Joaquin Valley (SJV) is at the southern end of California's Central Valley. With its northern boundary just south of Sacramento, the Valley extends in a southeasterly direction about 400 kilometers (250 miles) into Kern County. The SJV averages 100 kilometers (60 miles) in width and drains the area between the Sierra Nevada on the east and the California Coastal Range on the west. The rain shadow caused by the Coastal Range results in the predominantly xeric habitat covering the greater part of the valley floor where the annual rainfall is about 25 centimeters (10 inches). The San Joaquin River is the principal waterway that drains the SJV northward into the Sacramento Delta region.

The soils of the SJV vary significantly. On the west side of the valley, soils are composed largely of sedimentary materials derived from the Coastal Range; they are generally fine-textured and slow to drain. The arable soils of the east side developed on relatively unweathered, granitic sediments. Many of these soils are wind-deposited sands underlain by deep coarse-textured alluvial materials.

From the mid-1950s until 1977, dibromochloropropane (DBCP) was the primary chemical used to control nematodes. DBCP has desirable characteristics for a nematocide. It is less volatile than many other soil fumigants, such as methylbromide; remains active in the soil for a long time, and is effective in killing nematodes. However, it also causes sterility in human males, is relatively mobile in soil, and is persistent. Because of the health risks associated with consumption of DBCP treated foods, the nematocide was banned from use in the United States in 1979. After the ban, several well water studies were conducted in the SJV by state, county and local authorities. Thirteen years after DBCP was banned, contamination of well waters by the chemical persists as a problem in Fresno County.

Public concern over pesticides in ground water resulted in passage of the California Pesticide Contamination Prevention Act (PCPA) of 1985. It is a broad law that establishes the California Department of Pesticide Regulation

as the lead agency in dealing with issues of ground water contamination by pesticides. The PCPA specifically requires:

pesticide registrants to collect and submit specific chemical and environmental fate data (e.g., water solubility, vapor pressure, octanol-water partition coefficient, soil sorption coefficient, degradation half-lives for aerobic and anaerobic metabolism, Henry's Law constant, hydrolysis rate constant) as part of the terms for registration and continued use of their products in California.

establishment of numerical criteria or standards for physical-chemical characteristics and environmental fate data to determine whether a pesticide can be registered in the state that are at least as stringent as those standards set by the EPA,

soil and water monitoring investigations be conducted on:

pesticides with properties that are in violation of the physical-chemical standards set in 2 above, and

pesticides, toxic degradation products or other ingredients that are:

contaminants of the state's ground waters, or

found at the deepest of the following soil depths:

2.7 meters (8 feet) below the soil surface,

below the crop root zone, or

below the microbial zone, and

creation of a database of wells sampled for pesticides with a provision requiring all agencies to submit data to the California Department of Pesticide Regulation (CDPR).

Difficulties associated with identifying the maximum depths of root zone and microbial zone have led to the establishment of 8 feet as a somewhat arbitrary but enforceable criterion for pesticide leaching in soils.

Selection and Implementation of an Approach

Assessment of ground water vulnerability to pesticides in California is a mechanical rather than a scientific process. Its primary goal is compliance with the mandates established in the PCPA. One of these mandates requires that monitoring studies be conducted in areas of the state where the contaminant pesticide is used, in other areas exhibiting high risk portraits (e.g., low organic carbon, slow soil hydrolysis, metabolism, or dissipation), and in areas where pesticide use practices present a risk to the state's ground water resources.

The numerical value for assessments was predetermined by the Pesticide Use Report (PUR) system employed in the state. Since the early

1970s, California has required pesticide applicators to give local authorities information on the use of restricted pesticides. This requirement was extended to all pesticides beginning in 1990. Application information reported includes names of the pesticide(s) and commodities, the amount applied, the formulation used, and the location of the commodity to the nearest section (approximately 1 square mile) as defined by the U.S. Rectangular Coordinate System. In contrast to most other states that rely on county pesticide sales in estimating pesticide use, California can track pesticide use based on quantities applied to each section. Thus, the section, already established as a political management unit, became the basic assessment unit.

The primary criteria that subject a pesticide to investigation as a ground water pollutant are:

detection of the pesticide or its metabolites in well samples, or

its failure to conform to the physical-chemical standards set in accordance with the PCPA, hence securing its position on the PCPA's Ground Water Protection List of pesticides having a potential to pollute ground water.

In either case, relatively large areas surrounding the original detection site or, in the latter case, high use regions are monitored via well surveys. Positive findings automatically increase the scope of the surveys, and since no tolerance levels are specified in the PCPA, any detectable and confirmed result establishes a pesticide as a contaminant.

When a pesticide or its degradation products is detected in a well water sample and the pesticide is judged to have contaminated the water source as a result of a legal agricultural use, the section the well is in is declared a Pesticide Management Zone (PMZ). Further application of the detected pesticide within PMZ boundaries may be prohibited or restricted, depending on the degree of contamination and subject to the availability of tried and tested modifications in management practices addressing environmental safety in use of the pesticide. PMZs are pesticide-specific—each contaminant pesticide has its own set of PMZs which may or may not overlap PMZs assigned another pesticide. Currently, consideration is being given to the extension of PMZs established for one chemical to other potential pesticide pollutants. In addition to monitoring activities in PMZs, protocols have been written to monitor ground water in sections adjacent to a PMZ. Monitoring of adjacent sections has resulted in many new PMZs. Currently, California has 182 PMZs involving five registered pesticides.

California has pursued this mechanical approach to assessing ground water vulnerability to pesticides for reasons that cover a spectrum of political, economic, and practical concerns. As noted earlier, the scale of the assessment unit was set at the section level because it is a well-defined

geopolitical unit used in the PUR system. Section boundaries frequently are marked by roads and highways, which allows the section to be located readily and makes enforcement of laws and regulations more practical. California law also requires that well logs be recorded by drillers for all wells in the state. Well-site information conforms to the U.S. Rectangular Coordinate System's township, range, and section system.

The suitability and reliability of databases available for producing vulnerability assessments was a great concern before passage of the PCPA in 1985. Soil survey information holds distinct advantages for producing assessments and developing best management practices strategies, but it was not available in a format that could work in harmony with PUR sections. To date, several areas of the SJV are not covered by a modern soil survey; they include the western part of Tulare County, which contains 34 PMZs. Other vadose zone data were sparse, it available at all.

The use of models was not considered appropriate, given the available data and because no single model could cope with the circumstances in which contaminated ground water sources were being discovered in the state. While most cases of well contamination were associated with the coarse-textured soils of the SJV and the Los Angeles Basin, several cases were noted in areas of the Central Valley north of the SJV, where very dense fine-textured soils (vertisols and other cracking clays) were dominant.

The potential vagaries and uncertainties associated with more scientific approaches to vulnerability assessment, given the tools available when the PCPA was enacted, presented too large a risk for managers to consider endorsing their use. In contrast, the basic definition of the PMZ is difficult to challenge (pesticide contamination has been detected or not detected) in the legal sense. And the logic of investing economic resources in areas immediately surrounding areas of acknowledged contamination are relatively undisputable. The eastern part of the SJV contains more than 50 percent of the PMZs in the state. Coarse-textured soils of low carbon content are ubiquitous in this area and are represented in more than 3,000 sections. The obvious contamination scenario is the normal scenario in the eastern SJV, and because of its size it creates a huge management problem. While more sophisticated methods for assessing ground water vulnerability have been developed, a question that begs to be asked is "How would conversion to the use of enhanced techniques for evaluating ground water vulnerability improve ground water protection policy and management in the SJV?"

More than 90 percent of the population of Hawaii depends on ground water (nearly 200 billion gallons per day) for their domestic supply (Au 1991). Ground water contamination is of special concern in Hawaii, as in other insular systems, where alternative fresh water resources are not readily available or economically practical. Salt water encroachment, caused by pumping, is by far the biggest source of ground water contamination in Hawaii; however, nonpoint source contamination from agricultural chemicals is increasingly a major concern. On Oahu, where approximately 80 percent of Hawaii's million-plus population resides, renewable ground water resources are almost totally exploited; therefore, management action to prevent contamination is essential.

Each of the major islands in the Hawaiian chain is formed from one or more shield volcanoes composed primarily of extremely permeable thin basaltic lava flows. On most of the Hawaiian islands the margins of the volcanic mountains are overlapped by coastal plain sediments of alluvial and marine origin that were deposited during periods of volcanic quiescence. In general, the occurrence of ground water in Hawaii, shown in Figure 5.5 , falls into three categories: (1) basal water bodies floating on and displacing salt water, (2) high-level water bodies impounded within compartments formed by impermeable dikes that intrude the lava flows, and (3) high-level water bodies perched on ash beds or soils interbedded with

FIGURE 5.5 Cross section of a typical volcanic dome showing the occurrence of ground water in Hawaii (After Peterson 1972. Reprinted, by permission, from Water Well Journal Publishing Company, 1972.)

thin lava flows on unconformities or on other relatively impervious lava flows (Peterson 1972).

A foundation of the tourist industry in Hawaii is the pristine environment. The excellent quality of Hawaii's water is well known. The public has demanded, and regulatory agencies have adopted, a very conservative, zero-tolerance policy on ground water contamination. The reality, however, is that past, present, and future agricultural, industrial, and military activities present potentially significant ground water contamination problems in Hawaii.

Since 1977 when 1,874 liters of ethylene dibromide (EDB) where spilled within 18 meters of a well near Kunia on the island of Oahu, the occurrence and distribution of contaminants in Hawaii's ground water has been carefully documented by Oki and Giambelluca (1985, 1987) and Lau and Mink (1987). Before 1981, when the nematocide dibromochloropropane (DBCP) was found in wells in central Oahu, the detection limit for most chemicals was too high to reveal the low level of contamination that probably had existed for many years.

Concern about the fate of agriculture chemicals led the Hawaii State Department of Agriculture to initiate a large sampling program to characterize the sources of nonpoint ground water contamination. In July 1983, 10 wells in central Oahu were closed because of DBCP and EDB contamination. The public has been kept well informed of possible problems through the publication of maps of chemicals detected in ground water in the local newspaper. Updated versions of these maps are shown in Figures 5.6a , b , c , and d .

In Hawaii, interagency committees, with representation from the Departments of Health and Agriculture, have been formed to address the complex technical and social questions associated with ground water contamination from agricultural chemicals. The Hawaii legislature has provided substantial funding to groups at the University of Hawaii to develop the first GIS-based regional scale chemical leaching assessment approach to aid in pesticide regulation. This effort, described below, has worked to identify geographic areas of concern, but the role the vulnerability maps generated by this system will play in the overall regulatory process is still unclear.

Agrichemicals are essential to agriculture in Hawaii. It is not possible to maintain a large pineapple monoculture in Hawaii without nematode control using pesticides. Pineapple and sugar growers in Hawaii have generally employed well controlled management practices in their use of fertilizers, herbicides, and insecticides. In the early 1950s, it was thought that organic chemicals such as DBCP and EDB would not leach to ground water

FIGURE 5.6a The occurrence and distribution of ground water contamination on the Island of Oahu. (Map provided by Hawaii State Department of Health.)

FIGURE 5.6b The occurrence and distribution of ground water contamination on the Island of Hawaii. (Map provided by Hawaii State Department of Health.)

FIGURE 5.6c The occurrence and distribution of ground water contamination on the Island of Maui. (Map provided by Hawaii State Department of Health.)

FIGURE 5.6d The occurrence and distribution of ground water contamination on the Island of Kauai. (Map provided by Hawaii State Department of Health.)

because (1) the chemicals are highly sorbed in soils with high organic carbon contents, (2) the chemicals are highly volatile, and (3) the water table is several hundred meters below the surface. Measured concentrations of DBCP and EDB down to 30 meters at several locations have shown the original assessment to be wrong. They have resulted in an urgent need to understand processes such as preferential flow better and to predict if the replacement chemicals used today, such as Telon II, will also leach to significant depths.

Leaching of pesticides to ground water in Hawaii could take decades. This time lag could lead to a temporary false sense of security, as happened in the past and potentially result in staggering costs for remedial action. For this reason, mathematical models that permit the user to ask ''what if" questions have been developed to help understand what the future may hold under certain management options. One needs to know what the fate of chemicals applied in the past will be and how to regulate the chemicals considered for use in the future; models are now being developed and used to help make these vulnerability assessments.

Researchers have embarked on several parallel approaches to quantitatively assess the vulnerability of Hawaii's ground water resources, including: (1) sampling, (2) physically-based numerical modeling, and (3) vulnerability mapping based on a simple chemical leaching index. Taken together these approaches have provided insight and guidance for work on a complex, spatially and temporally variable problem.

The sampling programs (Wong 1983 and 1987, Peterson et al. 1985) have shown that the chemicals applied in the past do, in fact, leach below the root zone, contrary to the original predictions, and can eventually reach the ground water. Experiments designed to characterize the nuances of various processes, such as volatilization, sorption, and degradation, have been conducted recently and will improve the conceptualization of mathematical models in the future.

The EPA's Pesticide Root Zone Model (PRZM), a deterministic-empirical/conceptual fluid flow/solute transport model, has been tested by Loague and co-workers (Loague et al. 1989a, b; Loague 1992) against measured concentration profiles for DBCP and EDB in central Oahu. These simulations illustrate that the chemicals used in the past can indeed move to considerable depths. Models of this kind, once properly validated, can be used to simulate the predicted fate of future pesticide applications. One must always remember, however, that numerical simulations must be interpreted in terms of the limiting assumptions associated with model and data errors.

Ground water vulnerability maps and assessments of their uncertainty were pioneered at the University of Hawaii in the Department of Agriculture Engineering (Khan and Liang 1989, Loague and Green 1990a). These pesticide leaching assessments were made by coupling a simple mobility index to a geographic information system. Loague and coworkers have investigated the uncertainty in these maps owing to data and model errors (Loague and Green 1988; Loague et al. 1989c, 1990; Loague and Green 1990b, 1990c; Loague 1991; Kleveno et al. 1992; Yost et al. 1993). The Hawaiian database on soils, climate, and chemicals is neither perfect nor poor for modeling applications; it is typical of what exists in most states—major extrapolations are required to estimate the input parameters required for almost any chemical fate model.

Sampling from wells in Hawaii has shown the concentrations of various chemicals, both from agriculture and industrial sources, which have leached to ground water in Hawaii. These concentrations, in general, are low compared to the levels detected in other states and for the most part are below health advisory levels established by EPA. In some instances contamination has not resulted from agriculture, but rather from point sources such as chemical loading and mixing areas and possibly from ruptured fuel lines. The widespread presence of trichloropropane (TCP) in Hawaii's ground water and deep soil cores at concentrations higher than DBCP was totally unexpected. TCP was never applied as a pesticide, but results from the manufacture of the fumigant DD, which was used until 1977 in pineapple culture. The occurrence of TCP illustrates that one must be aware of the chemicals applied as well as their components and transformation products.

Wells have been closed in Hawaii even though the measured contaminant concentrations have been below those considered to pose a significant health risk. At municipal well locations in central Oahu, where DBCP, EDB, and/or TCP have been detected, the water is now passed through carbon filters before it is put into the distribution system. The cost of this treatment is passed on to the water users, rather than to those who applied the chemicals.

The pesticide leaching assessment maps developed by Khan and Liang (1989) are intended for incorporation into the regulatory process. Decisions are not made on the basis of the red and green shaded areas for different chemicals (see Plate 3 ), but this information is considered. The uncertainty analysis by Loague and coworkers has shown some of the limitations of deterministic assessments in the form of vulnerability maps and provided initial guidance on data shortfalls.

APPLICATION OF A VULNERABILITY INDEX FOR DECISION-MAKING AT THE NATIONAL LEVEL

Need for a vulnerability index.

A vulnerability index for ground water contamination by pesticides has been developed and used by USDA as a decision aid to help attain the objectives of the President's Water Quality Initiative (see Box 1.1 ). A vulnerability index was needed for use in program management and to provide insight for policy development. Motivation for the development of the vulnerability index was provided by two specific questions:

Given limited resources and the geographic diversity of the water quality problems associated with agricultural production, what areas of the country have the highest priority for study and program implementation?

What policy implications emerge from the spatial patterns of the potential for conamination from a national perspective, given information currently available about farming practices and chemical use in agriculture?

Description of the Vulnerability Index

A vulnerability index was derived to evaluate the likelihood of shallow ground water contamination by pesticides used in agriculture in one area compared to another area. Because of the orientation of Initiative policies to farm management practices, it was necessary that the vulnerability measure incorporate field level information on climate, soils, and chemical use. It also needed to be general enough to include all areas of the country and all types of crops grown.

A Ground Water Vulnerability Index for Pesticides (GWVIP) was developed by applying the Soil-Pesticide Interaction Screening Procedure (SPISP) developed by the Soil Conservation Service to the National Resource Inventory (NRI) land use database for 1982 and the state level pesticide use database created by Resources for the Future (Gianessi and Puffer 1991). Details of the computational scheme and databases used are described by Kellogg et al. (1992). The 1982 NRI and the associated SOIL-5 database provide information on soil properties and land use at about 800,000 sample points throughout the continental United States. This information is sufficient to apply the SPISP to each point and thus obtain a relative measure of the soil leaching potential throughout the country. The RFF pesticide use database was used to infer chemical use at each point on the basis of the crop type recorded in the NRI database. By taking advantage of the statistical properties of the NRI database, which is based on a statistical survey

sampling design, the GWVIP score at each of the sample points can be statistically aggregated for making comparisons among regions.

Since the GWVIP is an extension of a screening procedure, it is designed to minimize the likelihood of incorrectly identifying an area as having a low potential for contamination—that is, false negatives are minimized and false positives are tolerated. The GWVIP is designed to classify an area as having a potential problem even if the likelihood is small.

GWVIP scores were graphically displayed after embedding them in a national cartographic database consisting of 13,172 polygons created by overlaying the boundaries of 3,041 counties, 189 Major Land Resource Areas (MLRAs), 2,111 hydrologic units, and federal lands.

Three caveats are especially important in using the GWVIP and its aggregates as a decision aid:

Land use data are for 1982 and do not represent current cropping patterns in some parts of the country. Although total cropland acreage has remained fairly stable over the past 10 years, there has been a pronounced shift from harvested cropland to cropland idled in government programs.

The approach uses a simulation model that predicts the amount of chemical that leaches past the root zone. In areas where the water table is near the surface, these predictions relate directly to shallow ground water contamination. In other areas a time lag is involved. No adjustment was made for areas with deep water tables.

No adjustment in chemical use is made to account for farm management factors, such as chemical application rates and crop rotations. The approach assumes that chemical use is the same for a crop grown as part of a rotation cropping system as for continuous cropping. Since the chemical use variable in the GWVIP calculation is based on acres of land treated with pesticides, application rates are also not factored into the analysis.

Application to Program Management

By identifying areas of the country that have the highest potential for leaching of agrichemicals, the GWVIP can serve as a basis for selecting sites for implementation of government programs and for more in-depth research on the environmental impact of agrichemical use. These sites cannot be selected exclusively on the basis of the GWVIP score, however, because other factors, such as surface water impacts and economic and demographic factors, are also important.

For example, the GWVIP has been used as a decision aid in selecting sites for USDA's Area Study Program, which is designed to provide chemical use and farming practice information to aid in understanding the relationships among farming activities, soil properties, and ground water quality.

The National Agricultural Statistics Service interviews farm operators in 12 major watersheds where the U.S. Geological Survey is working to measure the quality of surface and ground water resources under its National Water Quality Assessment Program. At the conclusion of the project, survey information will be combined with what is learned in other elements of the President's Water Quality Initiative to assess the magnitude of the agriculture-related water quality problem for the nation as a whole and used to evaluate the potential economic and environmental effects of Initiative policies of education, technical assistance, and financial assistance if implemented nationwide.

To meet these objectives, each Area Study site must have a high potential for ground water contamination relative to other areas of the country. A map showing the average GWVIP for each of the 13,172 polygons comprising the continental United States, shown in Plate 3 , was used to help select the sites. As this map shows, areas more likely to have leaching problems with agrichemicals than other areas of the country occur principally along the coastal plains stretching from Alabama and Georgia north to the Chesapeake Bay area, the corn belt states, the Mississippi River Valley, and the irrigated areas in the West. Sites selected for study in 1991 and 1992 include four from the eastern coastal plain (Delmarva Peninsula, southeastern Pennsylvania, Virginia and North Carolina, and southern Georgia), four from the corn belt states (Nebraska, Iowa, Illinois, and Indiana), and two from the irrigated areas in the West (eastern Washington and southeastern Idaho). Four additional sites will be selected for study in 1993.

Application to Policy Analysis and Development

The GWVIP has also been used by USDA to provide a national perspective on agricultural use of pesticides and the potential for ground water contamination to aid in policy analysis and development.

The geographic distribution of GWVIP scores has shown that the potential for ground water contamination is diverse both nationally and regionally. Factors that determine intrinsic vulnerability differ in virtually every major agricultural region of the country. Whether an impact is realized in these intrinsically vulnerable areas depends on the activities of producers—such as the type of crop planted, chemical use, and irrigation practices—which also vary both nationally and regionally. High vulnerability areas are those where a confluence of these factors is present. But not all cropland is vulnerable to leaching. About one-fourth of all cropland has GWVIP scores that indicate very low potential for ground water contamination from the use of agrichemicals. Nearly all agricultural states have significant acreage that meets this low vulnerability criterion. Areas of the country identified as being in a high vulnerability group relative to potential

for agrichemical leaching also have significant acreages that appear to have low vulnerability.

This mix of relative vulnerabilities both nationally and regionally has important policy implications. With the potential problem so diverse, it is not likely that simple, across-the-board solutions will work. Simple policies—such as selective banning of chemicals—may reduce the potential for ground water contamination in problem areas while imposing unnecessary costs on farming in nonproblem areas. The geographic diversity of the GWVIP suggests that the best solutions will come from involvement of both local governments and scientists with their state and national counter-parts to derive policies that are tailored to the unique features of each problem area.

In the future, USDA plans to use vulnerability indexes, like the GWVIP, in conjunction with economic models to evaluate the potential for solving agriculture-related water quality problems with a nationwide program to provide farmers with the knowledge and technical means to respond voluntarily to water quality concerns.

These six case studies illustrate how different approaches to vulnerability assessment have evolved under diverse sets of management requirements, data constraints, and other technical considerations. In addition, each of these examples shows that vulnerability assessment is an ongoing process through which information about a region's ground water resources and its quality can be organized and examined methodically.

In Iowa, the Iowa DNR staff elected to keep their vulnerability characterization efforts as simple as possible, and to use only properties for which data already existed or could be easily checked. They assumed that surficial features such as the soil are too thin and too disrupted by human activities (e.g., tillage, abandoned wells) to provide effective ground water protection at any particular location and sought to identify a surrogate measure for average travel time from the land surface to the aquifer. Thus, a ground water vulnerability map was produced which represents vulnerability primarily on the basis of depth to ground water and extent of overlying materials. Wells and sinkholes are also shown. The results are to be used for informing resource managers and the public of the vulnerability of the resource and to determine the type of information most needed to develop an even better understanding of the vulnerability of Iowa's ground water.

The Cape Cod approach to ground water vulnerability assessment is perhaps one of the oldest and most sophisticated in the United States. Driven by the need to protect the sole source drinking water aquifer underlying this sandy peninsula, the vulnerability assessment effort has focused on the identification

and delineation of the primary recharge areas for the major aquifers. This effort began with a simple mass balance approach which assumed even recharge within a circular area around each drinking water well. It has since evolved to the development of a complex, particle-tracking three-dimensional model that uses site-specific data to delineate zones of contribution. Bolstered by strong public concern, Cape Cod has been able to pursue an ambitious and sophisticated agenda for resource protection, and now boasts a sophisticated differential management ground water protection program.

In Florida, ground water resource managers rely on a combination of monitoring and vulnerability assessment techniques to identify high recharge areas the develop the state ground water protection program. Overlay and index methods, including several modified DRASTIC maps were produced to identify areas of ground water significance in support of decision making in state land acquisition programs aimed at ground water protection. In addition, several monitoring networks have been established to assess background water quality and monitor actual effects in areas identified as highly vulnerable. The coupling of ground water vulnerability assessments with monitoring and research efforts, provides the basis of an incremental and evolving ground water protection program in Florida.

The programs to protect ground water in California's intensely agricultural San Joaquin Valley are driven largely by compliance with the state Pesticide Contamination Prevention Act. The California Department of Pesticide Regulation determined that no model would be sufficient to cover their specific regulatory needs and that the available data bases were neither suitable nor reliable for regulatory purposes. Thus, a ground water protection program was built on the extensive existing pesticide use reporting system and the significant ground water monitoring requirements of the act. Using farm sections as management units, the state declares any section in which a pesticide or its degradation product is detected as a pesticide management zone and establishes further restrictions and monitoring requirements. Thus, the need to devise a defensible regulatory approach led California to pursue a mechanistic monitoring based approach rather than a modeling approach that would have inherent and difficult to quantify uncertainties.

In contrast, the approach taken in Hawaii involves an extensive effort to understand the uncertainty associated with the assessment models used. The purpose of this is to provide guidance to, but not the sole basis for, the pesticide regulation program. The combined use of sampling, physically-based numerical modeling, and a chemical leaching index has led to extensive improvements in the understanding of the fate of pesticides in the subsurface environment. Uncertainty analyses are used to determine where additional information would be most useful.

Finally, USDA's Ground Water Vulnerability Index for Pesticides illustrates a national scale vulnerability assessment developed for use as a decision aid and analytical tool for national policies regarding farm management and water quality. This approach combines nationally available statistical information on pesticide usage and soil properties with a simulation model to predict the relative likelihood of contamination in cropland areas. USDA has used this approach to target sites for its Area Study Program which is designed to provide information to farmers about the relationships between farm management practices and water quality. The results of the GWVIP have also indicated that, even at the regional level, there is often an mix of high and low vulnerability areas. This result suggests that effective ground water policies should be tailored to local conditions.

Au, L.K.L. 1991. The Relative Safety of Hawaii's Drinking Water. Hawaii Medical Journal 50(3): 71-80.

Barlow, P.M. 1993. Particle-Tracking Analysis of Contributing Areas of Public-Supply Wells in Simple and Complex Flow Systems, Cape Cod, Massachusetts. USGS Open File Report 93-159. Marlborough, Massachusetts: U.S. Geological Survey.

Britt, J.K., S.E. Dwinell, and T.C. McDowell. 1992. Matrix decision procedure to assess new pesticides based on relative ground water leaching potential and chronic toxicity. Environ. Toxicol. Chem. 11: 721-728.

Cape Cod Commission (CCC). 1991. Regional Policy Plan. Barnstable, Massachusetts: Cape Cod Commission.

Cape Cod Planning and Economic Development Commission (CCPEDC). March 1978a. Draft Area Wide Water Quality Management Plan for Cape Cod. Barnstable, Massachusetts: Cape Cod Commission.

Cape Cod Planning and Economic Development Commission (CCPEDC). September 1978b. Final Area Wide Water Quality Management Plan for Cape Cod. Barnstable, Massachusetts: Cape Cod Commission.

Department of Environmental Protection, Division of Water Supply (DEP-WS). 1991. Guidelines and Policies for Public Water Supply Systems. Massachusetts Department of Environmental Protection.

Gianessi, L.P., and C.A. Puffer. 1991. Herbicide Use in the United States: National Summary Report. Washington, D.C.: Resources for the Future.

Guswa, J.H., and D.R. LeBlanc. 1981. Digital Models of Ground water Flow in the Cape Cod Aquifer System, MA. USGS Water Supply Paper 2209. U.S. Geological Survey.

Heath, D.L. 1988. DRASTIC mapping of aquifer vulnerability in eastern Barnstable and western Yarmouth, Cape Cod, Massachusetts. In Appendix D, Cape Cod Aquifer Management Project, Final Report, G.A. Zoto and T. Gallagher, eds. Boston: Massachusetts Department of Environmental Quality Engineering.

Horsely, S.W. 1983. Delineating zones of contribution of public supply wells to protect ground water . In Proceedings of the National Water Well Association Eastern Regional Conference, Ground-Water Management, Orlando, Florida.

Hoyer, B.E. 1991. Ground water vulnerability map of Iowa. Pp. 13-15 in Iowa Geology, no. 16. Iowa City, Iowa: Iowa Department of Natural Resources.

Hoyer, B.E., J.E. Combs, R.D. Kelley, C. Cousins-Leatherman, and J.H. Seyb. 1987. Iowa Ground water Protection Strategy. Des Moines: Iowa Department of Natural Resources.

Kellogg, R.L., M.S. Maizel, and D.W. Goss. 1992. Agricultural Chemical Use and Ground Water Quality: Where Are the Potential Problems? Washington, D.C.: U.S. Department of Agriculture, Soil Conservation Service.

Khan, M.A., and T. Liang. 1989. Mapping pesticide contamination potential. Environmental Management 13(2):233-242.

Kleveno, J.J., K. Loague, and R.E. Green. 1992. An evaluation of a pesticide mobility index: Impact of recharge variation and soil profile heterogeneity. Journal of Contaminant Hydrology 11(1-2):83-99.

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Loague, K. 1992. Simulation of organic chemical movement in Hawaii soils with PRZM: 3. Calibration. Pacific Science 46(3):353-373.

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Wong, L. 1987. Analysis of ethylene dibromide distribution in the soil profile following shank injection for nematode control in pineapple culture. Pp. 28-40 in Toxic Organic Chemicals in Hawaii's Water Resources, P.S.C. Rao and R.E. Green, eds. Ser. 086. Honolulu: Hawaii Inst. Trop Agric. Hum. Resources Res. Exten. University of Hawaii.

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Since the need to protect ground water from pollution was recognized, researchers have made progress in understanding the vulnerability of ground water to contamination. Yet, there are substantial uncertainties in the vulnerability assessment methods now available.

With a wealth of detailed information and practical advice, this volume will help decision-makers derive the most benefit from available assessment techniques. It offers:

• Three laws of ground water vulnerability.
• Six case studies of vulnerability assessment.
• Guidance for selecting vulnerability assessments and using the results.
• Reviews of the strengths and limitations of assessment methods.
• Information on available data bases, primarily at the federal level.

This book will be indispensable to policymakers and resource managers, environmental professionals, researchers, faculty, and students involved in ground water issues, as well as investigators developing new assessment methods.

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Evidence for the effectiveness of nature-based solutions to water issues in Africa

M Acreman 1,2 , A Smith 3 , L Charters 4 , D Tickner 4 , J Opperman 5 , S Acreman 6 , F Edwards 1 , P Sayers 7 and F Chivava 8

Published 7 June 2021 • © 2021 The Author(s). Published by IOP Publishing Ltd Environmental Research Letters , Volume 16 , Number 6 Citation M Acreman et al 2021 Environ. Res. Lett. 16 063007 DOI 10.1088/1748-9326/ac0210

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1 UK Centre for Ecology & Hydrology, Wallingford, United Kingdom

2 Hydro-Ecology Consulting Ltd, Wallingford, United Kingdom

3 University of Oxford, Oxford, United Kingdom

4 WWF-UK, Woking, United Kingdom

5 WWF-US, Washington, DC, United States of America

6 University of Gothenburg, Gothenburg, Sweden

7 Sayers and Partners, Watlington, United Kingdom

8 WWF—Zambia, Lusaka, Zambia

S Acreman https://orcid.org/0000-0001-5117-4447

• Received 24 February 2021
• Accepted 17 May 2021
• Published 7 June 2021

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Method : Double-anonymous Revisions: 1 Screened for originality? Yes

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There is increasing global interest in employing nature-based solutions, such as reforestation and wetland restoration, to help reduce water risks to economies and society, including water pollution, floods, droughts and water scarcity, that are likely to become worse under future climates. Africa is exposed to many such water risks. Nature-based solutions for adaptation should be designed to benefit biodiversity and can also provide multiple co-benefits, such as carbon sequestration. A systematic review of over 10 000 publications revealed 150 containing 492 quantitative case studies related to the effectiveness of nature-based solutions for downstream water quantity and water quality (including sediment load) in Africa. The solutions assessed included landscape-scale interventions and patterns (forests and natural wetlands) and site-specific interventions (constructed wetlands and urban interventions e.g. soakaways). Consistent evidence was found that nature-based solutions can improve water quality. In contrast, evidence of their effectiveness for improving downstream water resource quantity was inconsistent, with most case studies showing a decline in water yield where forests (particularly plantations of non-native species) and wetlands are present. The evidence further suggests that restoration of forests and floodplain wetlands can reduce flood risk, and their conservation can prevent future increases in risk; in contrast, this is not the case for headwater wetlands. Potential trade-offs identified include nature-based solutions reducing flood risk and pollution, whilst decreasing downstream water resource quantity. The evidence provides a scientific underpinning for policy and planning for nature-based solutions to water-related risks in Africa, though implementation will require local knowledge.

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Corrections were made to this article on 1 July 2021. The author affiliations were amended.

1. Introduction

Globally, for the period between 2001 and 2018 floods and droughts affected over three billion people and caused total economic damage of almost US$700 billion. (UNESCO 2020 ). For the period between 1995 and 2015, droughts accounted for 5% of natural disasters, affecting 1.1 billion people, killing 22 000, and causing US$100 billion in damage (UNISDR 2015 , Wallemacq and Below 2015 ). Africa is experiencing many serious water issues including floods (Di Baldassarre et al 2010 , Ekwezuo and Ezeh 2020 , Lumbroso 2020 ), droughts (Haile et al 2019 ) and river pollution (Fayiga et al 2018 ), presenting major risks to economies and societies. Furthermore, these issues may worsen in the future as the climate changes (De Wit and Stankiewicz 2006 , Douglas et al 2008 ). Seven African countries are in the recent top ten rank of countries with the highest risk of drought for combined agricultural systems of rainfed and irrigated crops (Meza et al 2020 ). Floods are associated with a 35% decrease in total and food per-capita consumption and 17 percentage point increase in extreme poverty (Azzarri and Signorelli 2020 ). Consequences will continue to impair economic development and poverty alleviation, increasing risks linked to conflict and migration (Scholes et al 2018 ).

There is increasing interest in Africa, as well as globally, in employing nature-based solutions to help address water issues (Boelee et al 2017 , Kalantari et al 2018 , Frantzeskaki et al 2019 , Seddon et al 2020 ). These can include protection and/or restoration of naturally occurring systems, such as regrowth of natural forests, removal of non-native vegetation, reconnecting floodplains with their rivers and constructed interventions, including installing green roofs and creating artificial wetlands. Past studies have shown how landscape elements, such as natural wetlands (Bullock and Acreman 2003 ) and forests (Dadson et al 2017 , Filoso et al 2017 ), can alter the hydrological cycle, and how site-based interventions, such as constructed wetlands (Kivaisi 2001 ) can be effective for wastewater treatment in developing countries.

A widely acknowledged definition of nature-based solutions, used by IUCN, is 'Actions to protect, sustainably manage, and restore natural or modified ecosystems, that address societal challenges effectively and adaptively, simultaneously providing human well-being and biodiversity benefits' (Cohen-Shacham et al 2019). In contrast, other solutions, such as dams, embankments or pipelines to transfer water between catchments often disrupt natural processes and lack biodiversity benefits. Nature-based solutions for adaptation can also produce multiple additional benefits, such as carbon sequestration (Reid et al 2006 ), thus addressing the Triple Challenge of simultaneously minimising climate change, restoring biodiversity and addressing food security and other development priorities (Baldwin-Cantello et al 2020 ). Nature-based solutions are increasingly attracting the attention of governments and non-state actors in climate, conservation and natural resource management arenas. For instance, they feature in national climate change adaptation policies in African countries (Seddon et al 2021 ). Yet, there is a lack of scientific evidence on nature-based solutions and their effectiveness, particularly in Africa (FAO 2015 ) and limited meta-analysis of available evidence; this has led to the emergence of 'popular narratives', such as in forest hydrology, that are not consistent with the best available scientific evidence (Gilmour 2014 ).

This paper presents the results of a systematic review of the available evidence for nature-based solutions to water-related risks in Africa. Systematic reviews were designed specifically to find, classify and analyse all available scientific evidence in a comprehensive, objective, transparent and repeatable manner. We focus on blue water issues of floods and water resources in rivers and aquifers (Falkenmark and Rockström 2006 ); we do not cover green water in soils and solutions such as conservation agriculture. We considered solutions at the landscape scale, (forests and natural wetlands) and site-specific scale (constructed wetlands and urban interventions). This evidence provides the basis for identifying the potential for nature-based solutions to current and future water risks in Africa and can guide policy development, strategic planning and investments.

Whilst most studies start with an assessment of past literature, reviews can vary enormously in methods employed and quality. In some cases, specific evidence may be selected to justify a pre-determined viewpoint at the exclusion of contrary evidence (Goldacre 2009 ) or interpreted in a manner to create fake science (Hopf et al 2019 ). Systematic evidence reviews provide a means of collating in a comprehensive and unbiased manner all available science to produce conclusions and summary statements supported by an audit trail back to original studies. They originated in medical research (Cook et al 1997 ), have been widely accepted as best practice to develop health policies and are now applied to environmental issues, including effectiveness of protected areas for freshwater biodiversity conservation (Acreman et al 2019 ) and impacts of riverine aggregate mining on freshwater ecosystems (Koehnken et al 2020 ).

We undertook a systematic evidence review to answer focused questions (table 1 ), by applying the preferred reporting items of systematic reviews and meta-analyses (Moher et al 2009 ) and guidance produced by the UK Government's Department of Environment, Food and Rural Affairs (Collins et al 2015 ). Our review included search and selection protocols based on the population, intervention, comparator and outcome framework (table 1 ). The search strategy, search terms and inclusion/exclusion criteria were peer-reviewed and amended before searching.

Table 1.  PICO elements.

We searched the Web of Science database (including SciELO) and Google Scholar, made requests to experts and institutions and scanned reference lists of review papers and books (termed 'snow-balling') to obtain publications containing evidence of the effectiveness of nature-based solutions in Africa. Throughout the rest of this paper, the term 'searches' refers to this activity. These searches returned a range of information including published papers and unpublished reports and brochures from conservation organisations, UN agencies and development banks. Some documents referred to more than one study area or water metric (e.g. nitrate concentration or flood peak magnitude); these were each recorded as separate case studies. Only those containing primary quantitative evidence related to the effectiveness of nature-based solutions to downstream water issues (floods, water quality, water resource quantity) were retained. This meant rejecting other documents that reported the same study results. We also rejected publications that reported confounding factors, which precluded unambiguous, firm conclusions; for example where recorded hydrological changes could have resulted either from deforestation or from concurrent urban development. Documents that reported other hydrological metrics, such as evaporation or infiltration rates, from which floods or water resource quantity had to be inferred, were also discarded. Furthermore, we rejected documents recording metrics downstream of wetlands or forests that lacked comparative data for reference sites (without wetlands or forests) or before interventions. The exception to this was for process studies that clearly demonstrated the link between interventions and hydrological metrics, particularly related to groundwaters. Modelling studies not supported by data were excluded from the review. However, studies were included where pre-intervention reference conditions were simulated using a model, but where post-intervention data were employed. Because we were primarily interested in local and landscape-scale effects of nature-based solutions, the review excluded studies of regional or continental processes, such as deforestation in the tropics altering the hydrology of higher latitudes. Key information was recorded for each case study (table 2 ).

Table 2.  Meta-data collected for each case study.

Water resource quantity metrics were of three types: 'annual flow volume', 'dry season flow volume', 'wet season flow volume'. The flood metrics are predominantly peak flow during flood events. Water quality metrics were primarily percentage removal of pollutants (e.g. nutrients, biological oxygen demand (BOD), chemical oxygen demand (COD), cadmium, zinc, pharmaceuticals, coliforms, petroleum products and sediment).

In this paper we use the term afforestation to refer to planting of trees where the species would not have occurred naturally, such as use of non-native species or planting any species on land that would have been grassland in the past. We use reforestation to refer to planting of native trees where they would have existed or allowing natural regrowth of native trees.

3. Overall results

The searches returned 10 633 publications. After applying inclusion/exclusion criteria, we were left with 150 publications containing 492 case studies from across Africa (table 3 ), all meta-data for which are provided in the supplementary file (available online at stacks.iop.org/ERL/16/063007/mmedia ). Only 13 case studies were explicitly referred to by the authors as 'nature-based solutions', five were urban and eight rural. They covered a range of intervention types, such sustainable urban drainage.

Table 3.  Numbers of case studies in African countries.

Of the 133 forest case studies, 50 were of native forests, 45 related to non-native forests, whilst 14 were mixed native and non-native. In 24 forest case studies the forest type was not specified. These 133 case studies reported mainly downstream water resource quantity metrics, though a small number reported impacts on floods and sediment loads.

Afforestation case studies totalled 35, with 31 explicitly planting non-native trees, two planting a mix of native and non-native and in two cases the tree species were not specified. Only two studies involved reforestation. Deforestation case studies totalled 92 studies, with 50 involving removal of native trees, 10 removal of non-native trees, 12 removal of mixed tree species, whilst in 20 case studies the tree species were unspecified.

The 144 natural wetland case studies reported a range of water resource quantity and quality parameters and groundwater interactions. The 202 constructed wetland case studies only reported water quality parameters comparing input concentrations of pollutants with outputs from the wetland to calculate effectiveness of removal.

In the following sections we present the numbers of case studies grouped according to different associations between land cover and hydrological metrics; we also provide graphs of the associations. The cases studies of various species, at different scales and employing a range of analysis techniques and method of inference. Furthermore, the majority were single observational studies rather than experimentally designed with replicates, and few provided statistical significance of their results. Therefore, we avoid making definitive conclusions but indicate tendencies in the evidence found.

4. Hydrological response to forest

4.1. forests and water resource quantity.

Of the 133 case studies involving forests, 97 reported effects on downstream surface water resource quantity. Most (32 of the 35) afforestation case studies showed decreased downstream surface water quantity, with 30 non-native species examples and two mixed forest types (figure 1 ). Most studies were for a single time period, and only a few reported flow changes at different stages of tree growth. For example, after replanting of pine trees (following clear-felling and flow increases) in Jonkershoek, South Africa, flows reduced to preclearing levels within 12 years, with the peak decrease after 20 years; thereafter the reduction was less (Scott et al 2000 ). The two reforestation case studies in Ethiopia were of exclosures that allowed natural tree regrowth, without replanting; they reported a significant decrease in runoff generation, which continued for 20 years (Descheemaeker et al 2006 ).

Figure 1.  Numbers of case studies reporting changes in downstream surface water resource quantity (increase, neutral or decrease) under deforestation (left) and afforestation (centre) and reforestation (right). Case studies of native forest studies are shown as triangles, non-native forest studies as circles, mixed forest studies as diamonds and unspecified forest studies as squares. 'annual' indicates mean annual flow was measured, whereas 'dry' and 'wet' refer to the season that flows were recorded.

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Deforestation was reported to increase downstream surface water resource quantity, in almost 60% (35 of 59) of case studies. Most studies considered only one time period, so changes in hydrological impact over time were not present, but studies directly after deforestation showed effects were immediate. Of these 35, 15 case studies concerned native species, 11 non-native, three mixed species and six unspecified. Almost one third (19 of 59) of deforestation case studies reported decreased surface water quantity. Of the 19, eight were native species studies, one non-native, five mixed and five unspecified. Of the case studies reporting dry season flows, just of over half (8 of 15) recorded a decrease following deforestation, whilst 40% (6 of 15) recorded an increase. Considering only studies of native or mixed forests, twice as many (8) showed a decrease in dry season flows in response to deforestation as those that showed an increase (4).

A subset of case studies reported the percentage changes in water resources. Of these, more than 70% (17 of 24) of the case studies of afforestation show decreases in surface water resource quantity of greater than 60%. Changes were less consistent for deforestation. Most (7 of 8) case studies of native tree deforestation reported increased water quantity of greater than 80%, with one reporting a decrease of over 80%. Almost half (13 of 28) of the case studies of non-native deforestation (e.g. Scott et al 2000 ) showed increases in water quantity of greater than 40%, whereas one third (9 of 28) show decreases.

A few studies showed maps of forest cover change, which were distributed across the catchment, but most simply reported the percentage change within the catchment. Therefore, it was not possible to assess the differing impacts of forest change in different locations, such as in headwaters or along the main channel. All case studies reported at a single measuring point at the outlet of the catchment under study, so it was not possible to determine how changes in water resources might propagate downstream.

Figure 2 shows the percentage change in surface water resource quantity for a given change in percentage of the catchment forested for the subset of the case studies that reported both values. The maximum decrease in surface water quantity from deforestation was 50% from clear-felling native trees in Tanzania (Lundgren 1980 ), though this was from a micro-plot study of 12 m 2 . In contrast, several studies reported 100% decrease (drying of the river) from afforestation. The general trend was for increasing water resource quantity as the percentage of the catchment covered by forests decreases and decreasing water resource quantity as the percentage of the catchment forested area increased. Changes in water resource quantity were generally greater for non-native than for native species. Case studies covered a range of ecoregions and forest types found in Africa, but two types found on the continent and not represented in the literature were tropical rainforests and cloud forests. There was no clear pattern of the direction of change in water resource quantity with native forest type or ecoregion (table 4 ).

Figure 2.  Relationship between change in forest cover (% of catchment area) and change in downstream surface water resource quantity (%). The vertical axis is truncated at 250% to aid visualisation of lower values, which excludes the four most extreme increases in resource quantity due to deforestation (maximum 3450%).

Table 4.  Type of native forests (ecoregion from Olson et al 2001 ) in case studies of deforestation impacts on water resource quantity Reproduced with permission from Olson et al ( 2001 ). CC BY-NC 3.0 .

4.2. Forests and floods

The 20 case studies of flood response to changes in forest cover were from a range of catchment sizes from >17000 km 2 to <1 km 2 and show a diverse pattern of responses. Three quarters (12 of 16) of deforestation case studies reported an increase in downstream flood peak flow (e.g. Mumeka 1986 ), whilst three showed no effect (e.g. Mwendera 1994 ). The afforestation case studies reported increases (1 of 4), decreases (1 of 4) and no effect (2 of 4) on flood magnitude. Sub-dividing the case studies into native and non-native did not reveal strong trends, partly due to the small numbers of studies.

The ten case studies providing numerical values for percentage change in flood magnitude and percentage in catchment area forested are shown in figure 3 ; there were no studies providing quantitative results of afforestation effects on floods. Although data were limited, they suggested that greater deforestation was associated with a greater increase in flood magnitude.

Figure 3.  Relationship between change in forest cover (%) and change in flood magnitude (%). The horizontal axis shows negative value for deforestation.

Most case studies reported flood metrics at a single time period after deforestation. One exception was in Kapchorwa, Kenya, where the conversion from forest to agricultural land in the first 5 years caused half of the total increases in flood discharge (Recha et al 2012 ).

4.3. Forests and sediment yield

There were 11 case studies of change in sediment yield in response to alterations in forest cover. Most (9 of 11) case studies indicated that deforestation was associated with increases in sediment yield downstream and one showed decreasing sediment yield with afforestation. One study reported higher sediment loads in naturally forested catchment than a savannah catchment in the Congo (Coynel et al 2005 ), but sediment concentrations from both catchments were very low, so the difference may not be significant.

Only 5 of the 11 case studies reported the percentage change in sediment yield and percentage in catchment area forested (figure 4 ). Their data suggested sediment yield increases with decreasing forest cover, with up to a four-fold increase in sediment following clear-felling.

Figure 4.  Relationship between change in forest cover (%) and sediment yield (%). The horizontal axis shows negative value for deforestation and positive for afforestation Reproduced with permission from Olson et al ( 2001 ). CC BY-NC 3.0 .

5. Hydrological response to natural wetlands

5.1. classification of natural wetlands.

The searches returned 144 case studies reporting changes to water metrics associated with the presence of natural wetlands within catchments ranging in size from >300 000 km 2 to <1 km 2 . Although a range of wetland types was represented (characterised by different vegetation and soils), the vast majority were referred to by the authors as one of two types: (a) headwater wetlands including dambos and headwater peat swamps and (b) floodplains including lowland papyrus wetlands, inland deltas and lowland valley swamps. Catchment location is a long-standing simple method of classifying wetlands for functional assessment (Novitski 1978 ). Three case studies involved a statistical analysis of many wetlands of various types, but the remaining 141 studies were divided into the two broad categories: headwater wetlands and floodplains.

Most case studies recorded metrics immediately downstream of the wetland, compared to immediately upstream or on a similar catchment without a wetland. A few studies used chemical tracers to define hydrological processes. All case studies reported at a single measuring point, none reported changes in metrics at different distances downstream, so it was not possible to determine how an effect might propagate downstream. No case studies reported how metrics varied over time or with different types of wetland management, such as grazing or drainage.

5.2. Natural wetlands and water resource quantity

The 52 case studies reporting surface water resource quantity metrics that could be classified as headwater or floodplain are shown in figure 5 . Most (32 of 52) reported dry season flows, some (17 of 52) reported annual total flows and a few (3 of 52) reported wet season flows. Just over half of the studies (28 of 52) reported that wetlands (of both types) were associated with reduced surface water resources downstream, with less than a fifth (9 of 52) reporting an increase in surface water resources. Of these, most (8 of 9) were floodplains. For example, floodplains were associated with increased dry season flows on the White Volta River, Ghana (Nyarkoa et al 2013 ). In detailed studies of dambo headwater wetlands in Zimbabwe, it was found that dry season depletion of water is dominated by high evaporation from open water and emergent vegetation, thus limiting contributions to downstream river flow (McCartney and Neal 1999 ). Similarly, the water balances of large floodplains (Senegal, Sudd, Niger and Okavango) were dominated by high evaporation (Sutcliffe and Parks 1989 ). The one study reporting an increase in downstream water resource quantity from a headwater wetland in Zambia was for the wet season (Balek and Perry 1973 ).

Figure 5.  Numbers of case studies reporting changes in surface water resource quantity associated with the presence of natural headwater wetlands and floodplains for different flow metrics.

5.3. Natural wetlands and floods

Of the 38 natural wetland case studies reporting flood metrics, two multiple wetland studies reported increases in small floods in the presence of wetlands. The other 36, of which 15 were studies of headwater wetlands and 21 were studies of floodplains, are shown in figure 6 . Almost all (20 of 21) of the floodplain studies reported a decrease in flood magnitude; the one that reported no effect was perhaps due to the small size of wetland (Lacombe and McCartney 2016 ).

Figure 6.  Numbers of case studies reporting changes in flood magnitude resulting from the presence of natural headwater wetlands and floodplains. Case studies of small flood magnitude are shown as small white drips, whilst studies of large floods are shown as large black drips.

In contrast, almost three quarters (11 of 15) of headwater wetlands studies showed increased floods associated with their presence, whilst three report no effect. The only case study reporting a decrease in flood magnitude with a headwater wetland present is of a dambo in Malawi (Smith-Carrington 1983 ); even here there was an apparent duality as the dambo increased flood runoff initially after rainfall before buffering the peak flow. Detailed studies of dambos undertaken in Zimbabwe (McCartney 2000 ) concluded that these headwater wetlands had a small capacity to absorb rainfall at the start of the wet season, when water table levels were low, but soon became saturated and contributed to flood runoff thereafter.

5.4. Natural wetlands and groundwater

Twenty case studies investigated interactions between natural wetlands and underlying aquifers. Of these, 13 assessed groundwater recharge, with nine finding recharge occurred including floodplains of the Senegal River (Hollis 1996 ) and Komoguge–Yobe River, Nigeria (Goes 1999 ); four found recharge did not occur. Seven case studies assessed whether wetlands were groundwater discharge sites; five reported discharge occurred, whilst two reported it did not occur. Overall, the interaction between wetlands and underlying aquifers was site specific and no generalisations can be made from the evidence reported in our case studies.

5.5. Natural wetlands and water quality

Three case studies of natural wetlands reported changes to sediment in downstream water courses. All reported decreases; two reported −70.0% and −79.1%, the third study did not provide data. Seven case studies of natural wetlands reported changes to total nitrogen in downstream water course; all were decreases. Five of these reported numerical values, which ranged from −33.0% to −53.0%. Six case studies of natural wetlands reported changes to total phosphorus in downstream water courses; three reported decreases from −5.0% to −50.0%, one study of Natete wetland, Uganda (Kanyiginya et al 2010 ) reported an increase due possibly to remobilisation of phosphorus from sediments. Eight case studies of natural wetlands reported changes in heavy metals (cadmium, copper, iron, lead, manganese, uranium and zinc) in downstream water courses; all were decreases ranging from −61% to full removal (−100%).

6. Hydrological response to constructed wetland interventions

The searches produced 202 case studies reporting changes to water metrics resulting from the construction of wetlands. Metrics included sediment, ammonia, nutrients (nitrogen and phosphorus), BOD, COD, heavy metals (e.g. cadmium, lead, zinc, copper, iron, manganese, mercury), oil and grease, Escherichia coli , parasite eggs, Salmonellae and faecal coliforms. All case studies reported reductions in these metrics. Many case studies were concerned with the relative removal rates of pollutants from different designs of constructed wetlands or types of vegetation employed.

Figures 7 and 8 show some relationship between effectiveness of pollutant removal and wetland size. As catchment area is not a relevant variable, to compare case studies, the wetland size (m 2 ) was standardised by the input flow rate (m 3 d −1 ). There was a tendency towards improved pollutant removal with larger wetlands.

Figure 7.  Changes in BOD and COD with wetland size (as a function of input flow rate).

Figure 8.  Changes in heavy metals and suspended sediment with wetland size (as a function of input flow rate).

7. Hydrological response to other nature-based interventions

The searches returned 1218 publications referring explicitly to nature-based solutions, that tended to be constructed interventions rather than restoration of naturally occurring systems. These included green roofs, sustainable urban drainage and river channel restoration. However, the vast majority focused on direct and local water/climate impacts such as reducing temperatures, draining flood water or collecting water for public use or agriculture. Only nine publications provided quantitative results of impacts on downstream floods, water resource quantity or water pollution, yielding 13 case studies.

Three case studies of greenways linking cities and forests reported reduced runoff coefficients, reduced flood risk, and increased replenishment of subterranean water sources (Sy et al 2014 ). Three case studies of sustainable urban drainage, including semi-vegetated channels, soakaways and miniature bio-retention areas, showed reductions in nitrate, phosphate and COP (Fitchett 2017 ).

8. Discussion

8.1. utility of the database.

Most analyses of nature-based solutions have been based on case studies in north America or Europe (e.g. Kabisch et al 2017 ) and previous reviews have found only a few studies in Africa (Hanson et al 2017 ). However, the current review has revealed 492 case studies undertaken in African countries. It significantly extends existing databases, such as the global review of nature-based solutions for climate change adaptation (Chausson et al 2020 ), which contains 16 examples addressing water issues in Africa.

The conclusions drawn in this paper are based upon the results of studies found in the searches. We recognise the danger of over-generalisation and implying cause-effect, so use terms such 'generally associated with' to convey the balance of scientific evidence found. Forest and wetland land classes cover a vast range of ecosystem types, which do not necessarily work hydrologically in the same way, so results cannot always be transferred between types. Furthermore, Africa is very diverse in terms of climate, geology, topography, soils and other characteristics, such that the hydrological response to land cover alterations will vary in different settings, so local data and scientific understanding are vital to underpin local decisions and actions (Bullock and Acreman 2003 ).

Although it cannot replace robust context-specific analysis, the evidence for hydrological response to afforestation, reforestation and deforestation provides general guidance for the effectiveness of removing or planting trees or allowing forest regrowth. The action of restoring forests is associated with reduced risks from floods and sediment loads but often also reduced water resource quantities, potentially increasing risks of downstream water scarcity. A notable limitation of the current review was the lack of studies of tropical rain forests, particularly cloud forests, especially compared to the many studies in Amazonia (Chishugi et al 2017 ). Many of the forest studies were of deforestation and there were few of native forest restoration (reforestation). This is a significant research gap. However, if a nature-based solution involves restoration of natural forests, results of studies of deforestation of native trees could be used 'in reverse' to some extent, to assess the potential effects of reforestation, such as reduced sediment delivery in forested areas. However, outcomes may depend on the restoration process, as tree planting, for example, may cause some soil erosion or compaction in the short term, whereas natural regeneration may avoid this issue.

The evidence that forests, particularly non-native trees, can reduce water resource quantity supports the action of removing alien trees as a nature-based solution. This is consistent with the studies in South Africa (Van Wilgen et al 2012 , 2020 , Le Maitre et al 2016 ) that have demonstrated the detrimental impacts of alien species, including reductions in water resources, which underpins non-native vegetation removal as a nature-based solution within the Working for Wetlands programme supported by the South African government. Careful practices can avoid side-effects of vegetation removal, such as soil erosion or soil compaction. It should further be noted that planting any trees, whether native or not, in areas not naturally forested, e.g. in grasslands, or savannas, would not meet the IUCN definition of a nature-based solution as it could have negative impacts on biodiversity.

Whilst the presence of headwater wetlands is associated with larger downstream floods than when they are absent, the implication for a nature-based solution is not clear because headwater wetlands cannot readily be created or removed and there is little evidence on the effects of altered management (see section 8.5 ). In contrast, many floodplains have effectively been lost by building of embankments that separate floodplains from their rivers or dredging the river to increase its depth. The results of floodplain case studies can be used to assess flood risk reduction from reconnecting floodplains with their rivers, such as by removing embankments (e.g. Acreman et al 2003 ), though this may also reduce downstream water resource quantity.

We have classified the change in water metrics simply as increase, decrease or unchanged (with quantitative values given where available). The societal implications of metric change will depend on many factors, such as the vulnerability of people to increases in flood flows in a river and the type of local water resource management infrastructure. For example, water supplies reliant on direct river abstraction will be vulnerable to during dry seasons, whereas annual flow volumes will be more critical for water supplied from reservoirs. Furthermore, flooding in the wrong place, e.g. homes, factories, hospitals and most agricultural land, is seen as negative, but in the right place floods can be very beneficial to African people, such as supporting floodplain fisheries and flood-recession agriculture (Acreman 1996 ).

We focus this review on blue water issues and did not cover green water, i.e. water in soils and vegetation, for which a wider set of nature-based solutions exist such as conservation agriculture (e.g. Assefa et al 2019 ). We recognise the need to consider all types of water on the planet—in the atmosphere, soil, surface water, ground water and ice (Gleeson et al 2020 )—in relation to global limits to anthropogenic water cycle modifications (Zipper et al 2020 )

Finally, it should be noted that we did not attempt to address nature-based solutions in coastal or marine environments, although we recognise that coastal ecosystems, such as saltmarshes, mangroves and reefs, can play a vital role in protecting from coastal flooding, erosion and salt water intrusion.

8.2. Comparison of results with other reviews

The evidence found from the searches is consistent with previous reviews. A systematic review of impacts of forest restoration on water yield (Filoso et al 2017 ) found that most studies reported a decrease in water yield resulting from an increase in forest area, including regrowth of native trees. In a general global assessment (Farley et al 2005 ), annual runoff was found to be reduced on average by 44% (±3%) and 31% (±2%) when grasslands and shrublands were afforested, respectively. To observe increases in low-flows following tree planting, the increase in evaporation must be smaller than the increase in infiltration—the 'infiltration trade-off hypothesis' (Bruijnzeel 2004 ); evidence outside Africa shows that this may occur only in limited cases for specific tree species, soil types, soil conditions (degraded or compacted), initial vegetation types and climate conditions (e.g. Bonell et al 2010 , Roa-Garcia et al 2011 , Zhang et al 2019 ). As noted above, we found in Africa that 8 out of 12 studies of deforestation of native or mixed forests resulted in decreases in dry season flow. Planting of fast-growing non-native species, such as eucalyptus and pines, has been widely reported to reduce water yield (Smith et al 2017 , Chausson et al 2020 ). We found strong evidence of this in Africa. Eucalyptus trees are known to be high water users as their deep roots can continue to take up water as they lower the water table (Calder et al 1993 ). The high water use of trees has been incorporated within water policy in South Africa, where afforestation is classified as a Streamflow Reduction Activity (SFRA) under the National Water Act of 1998 (Gush et al 2002 ), such that no forestry can be practiced without an SFRA licence (Edwards and Roberts 2006 ). The IPBES report on land degradation and restoration (Scholes et al 2018 ) reported that land degradation through loss of biodiversity can increase flood risk and soil erosion and also that planting trees in previously non-forested areas, such as grasslands and savannahs can result in loss of water yield.

Previous reviews have found that at small spatial scales (<20 km 2 ) forests can reduce flood flows, but not for the most extreme floods, and measured data for impacts in larger catchments (>100 km 2 ) are lacking (Dadson et al 2017 ). Stratford et al ( 2017 ) also found that studies of forest cover changes on large catchments were limited to modelling due to lack of empirical data.

A review of evidence of the role of wetlands in hydrological cycles (Bullock and Acreman 2003 ) and follow-up research (Acreman and Holden 2013 ) concluded that the relationship between wetlands and floods depends largely on available water storage. Catchments containing headwater wetlands, such as dambos in Africa, have greater floods than catchments without headwater wetlands. This is because the combination of rainfall, topography and soils leads to ground saturation at the start of the wet season simultaneously creating wetlands and generating rapid runoff (McCartney 2000 ). In contrast, downstream floodplains reduce floods as they tend to be dry before floods and have large storage volumes. The evidence we found from Africa was consistent with these findings.

A review of the potential for constructed wetlands for wastewater treatment and reuse in developing countries (Kivaisi 2001 ) found these to be effective and efficient for wastewater treatment, and additionally they are low cost, easily operated and maintained, and have a strong potential for application in developing countries, particularly by small rural communities. African case studies support this finding.

8.3. Forest types for which no studies were found in Africa

Some forest types for which case studies were lacking in Africa, including tropical rainforests and cloud forests, have been investigated elsewhere, although results may not be readily transferable because, for example, the climate of African rainforests is, on average, much drier than rainforests on other continents (Malhi et al 2013 ). For tropical forests, analysis by Bruijnzeel ( 1989 , 1990 , 2004 ) concluded that deforestation and conversion to annual cropping or grazing is generally followed by increased surface runoff during the wet season, and often by increased base flow water yield, though this is not always the case. Sometimes dry season streamflows decrease in catchments with extensive deforestation. Bruijnzeel ( 2004 ) concluded that this may be due to a higher proportion of impermeable surfaces within the catchment due to development (including urban areas), or to compaction and degradation of soils during deforestation or subsequent agricultural use, rather than loss of the trees per se .

Some studies show that evapotranspiration in cloud forests is low and large amounts of water are captured by trees from fog, which can make a significant contribution to water yield downstream (e.g. Gomez-Peralta et al 2008 ). Other studies have recorded a loss of water yield downstream following cloud forest clearance (López‐Ramírez et al 2020 ). However, it is difficult to draw generic conclusions due to a complex dependency on local climate and other factors. A Mexican cloud forest at the drier end of the spectrum, with higher evapotranspiration and lower cloud water capture, had lower annual water yield than an adjacent catchment that was converted to pasture but higher dry season base flows, as well as lower runoff during storm events (Bruijnzeel et al 2011 , Asbjornsen et al 2017 ); while conversion of cloud forest to pasture in northern Costa Rica had little effect on streamflow, although local storm flows were doubled (Bruijnzeel et al 2010 ). Extrapolation of results from elsewhere to Africa is thus extremely difficult. Sáenz and Mulligan ( 2013 ) used computer models to explore the role of cloud-affected forests in African river basins containing dams but did not explore the impact of forest loss in the delivery of water.

8.4. Comparison with modelling studies

In the absence of direct measurements of the effects of deforestation and afforestation, particularly at large scale, researchers have turned to the use of mathematical computer models. Modelling of catchments in Indonesia, Sri Lanka, Brazil and Tanzania (miombo woodland) found that the impacts of forest removal are highly seasonal; whilst typically increasing mean annual water yield, dry-season flows can decrease depending on pre- and post-forest removal surface conditions and groundwater response times (Peña-Arancibia et al 2019 ). Modelling of reforestation in Brazil generally decreased water quantity throughout the whole basin, though increases were noted in some parts of the basin (Ferreira et al 2019 ). Computer simulated deforestation of the Amazon region more generally could reduce discharge by 6%–36% (Stickler et al 2013 ). None of these model predictions were tested with observed data.

8.5. Management interventions

Most case studies of wetlands and a few of forests found for Africa concerned the presence or absence of features or interventions compared with a reference catchment, e.g. wetland v. no wetland, forest v. grassland. Associated management of forests and wetlands, such as pre-afforestation ploughing, thinning of trees or removal of undergrowth and draining or heavy grazing vegetation of natural wetlands, was rarely mentioned, so their hydrological implications could not be assessed. This is a significant research gap.

Much of the current discussion of nature-based solutions has focused on the benefits and disbenefits of active planting of trees or removal of non-native species. The evidence suggests that protection of existing native forests and other native vegetation types (i.e. no active intervention) could be effective in preventing the increased flood risk and sedimentation that would be associated with deforestation. Also avoidance of afforestation of land that is naturally grassland or savannah can prevent water resource quantity losses.

The type of vegetation planted in constructed wetlands can play an important role in their performance. In Uganda wetlands planted with Cyperus papyrus had higher COD removal rates than those planted with Phragmities mauritianus (Okurut et al 1999 ). Likewise, in Ethiopia, the nutrient removal efficiency of Typha was higher than Phragmites australis and Scirpus (Timotewos et al 2017 ).

Some wetlands are so effective at removing nutrients that these can build-up in the wetland soil to high levels and exceed the concentrations in the water input, therefore turning the wetland from a sink to a source. Because of this, water exiting the Natete wetland, Uganda, was found to have higher phosphorous than water entering (Kanyiginya et al 2010 ). This can be alleviated by periodical mechanical removal of sediment from the wetland.

8.6. Spatial and temporal aspects of nature-based solutions

Most studies found in this review reported downstream hydrological changes for specific single periods, so it was generally not possible to assess the evolution of effects over long periods. This is another research gap. Only a few studies reported how flow reductions resulting from afforestation varied with the age of the trees, such as the continued reduction in flows for 20 years after planting of pine trees in South Africa (Scott et al 2000 ). Similarly, most studies using flood metrics reported a single time period after deforestation. One exception was in Kapchorwa, Kenya, where the conversion from forest to agricultural land in the first five years caused about half of the total observed increases in discharge in relation to rainfall (Recha et al 2012 ).

In case studies of constructed wetlands, residence time was reported as important. For example, the effectiveness of COD reduction increased as retention times increased from 0.5 to 5 days in Arusha, Tanzania (Mtavangu et al 2017 ).

No studies reported hydrological metrics for more than one location, so it was not possible to assess the changes upstream or downstream of this point. Forest cover was usually reported as a percentage change across the catchment so neither the specific location of changes in forest cover (e.g. headwaters) nor an index of fragmentation could be defined. The only exceptions were case studies reporting clear-felling.

8.7. Inter-catchment and regional scale impacts of nature-based solutions

Whilst this review focuses only on the direct downstream hydrological implications of water-related nature-based solutions, hydro-meteorological models have been employed to study water circulation at regional and global scales. For example, regional scale evaporation from agricultural activities and irrigation in the Sahel and Nile basin have been shown to increase moisture supply to the Yangtze, Yensisei, and Niger basins (Wang-Erlandsson et al 2018 ). Furthermore, deforestation of tropical regions has been reported to significantly affect precipitation at mid- and high latitudes (Avissar and Worth 2005 ). Results vary according to the scale of analysis; whilst deforestation within the Xingu River basin (a tributary of the Amazon) increased discharge locally, deforestation across the whole Amazon region reduced rainfall, decreasing discharge within the basin (Strickler et al 2013). It has been suggested that evaporation from the Sudd wetlands in South Sudan is important for rainfall generation in the Ethiopian Highlands (Hurst 1938 ). However, it has been argued more recently that the impact of Sudd evaporation on the regional hydrological budget of the Nile Basin is insignificant compared to the inter-annual rainfall variability, owing to the relatively small area covered by the wetland (Mohamed et al 2006 ).

9. Knowledge gaps

Previous authors have identified knowledge gaps on the effectiveness of nature-based solutions, especially on trade-offs and synergies concerning water management, biodiversity, human health, social and economic issues (Kabisch et al 2017 ), and on case studies in the Global South, as well as comparisons with non-nature-based alternatives (Chausson et al 2020 ). Most studies of changes in forest cover in Africa have been of commercial non-native species; more work on reforestation using native species is required. Published studies tend to describe binary situations, i.e. with/without interventions, and there is little information on the impacts of management, such as changing water levels within wetlands. More work is also needed on effects of the location and scale of nature-based solutions within catchments and how any resultant hydrological alterations may vary in space and time.

Many nature-based solutions are forms of naturalising engineering (rather than engineering nature), including green roofs and sustainable urban drainage. Only a few examples were found for Africa that assessed impacts of these types of intervention on downstream water metrics. No studies assessed the benefits of integrating nature-based solutions with traditional engineering approaches, such as using embankments, sluice gates and weirs to enhance floodplain flood water retention.

Key topics for future research include:

• hydrological effects of native forest protection and reforestation, including cloud forests and rainforests, and native savannah restoration
• effects of management such as grazing, drainage, tree thinning, undergrowth removal
• effects of the location of nature-based solutions within a catchment
• monitoring downstream at various locations to assess propagation of effects
• long term monitoring to assess changes over time following interventions, including seasonal and inter-annual variability
• studies of channel restoration, including reintroduction of meanders and woody debris, reconnection of rivers and floodplains
• continental scale assessment of hydrological effects beyond the catchment of interventions
• effects of combining nature-based solutions with traditional engineering solutions, including sustainable drainage systems, and other water management interventions.

10. Conclusions

This review considered evidence related to nature-based solutions to water risks in terrestrial and freshwater environments across Africa. It found 10 633 publications related to this topic. Of these, 150 reported primary empirical information on the effectiveness of water-related nature-based solutions, generating 492 case studies with a wide distribution across Africa. In general, forests and floodplain wetlands provide a potential nature-based solution for reducing floods and sediment generation, whilst constructed wetlands readily reduce water pollution. Generally, the presence of headwater wetlands and non-native forests was associated with reduced water resource quantity downstream, whilst the evidence is inconsistent for native forests, and there is a lack of evidence in Africa for cloud forests and tropical rainforests. Although there is a need for more studies, including more information on temporal and spatial scales of effects, the results from these publications collectively provide a basis for assessing the likely effectiveness of different nature-based solutions to water risk issues that can support policy and planning decisions.

A strategic approach to landscape or catchment management should consider all potential benefits and disbenefits of nature-based solutions, including water and non-water issues, such as carbon sequestration, food and fuel supply, as well as intrinsic benefits in terms of biodiversity and cultural value. However, local policy and management decisions should ideally be based on finer-scale, context-specific analysis using local knowledge. Our review can provide a guiding frame for such an analysis but should not be a substitute for it. Decisions should also be guided by socio-economic, cultural and political considerations as much as by an understanding of the biophysical dynamics of landscapes and catchments. Stakeholder views will be especially important in influencing policy and management decisions. Even so, an understanding of biophysical dynamics, including this review, can help to draw up potential portfolios of solutions and can provide foundational inputs to the policy discourse.

Acknowledgments

Funding for this work was provided by ABInBev via WWF-UK, and by WWF-Denmark. Prof Acreman acknowledges a research fellowship at the UK Centre for Ecology & Hydrology. Dr Edwards was supported by the UK Research and Innovation Economic and Social Research Council [ES/P011373/1] as part of the Global Challenges Research Fund.

Data availability statement

The data that support the findings of this study are available upon request from the lead author.

The data that support the findings of this study are available upon reasonable request from the authors.

Supplementary data

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ICESMART - 2015 (Volume 3 - Issue 19)

River water pollution:a case study on tunga river at shimoga-karnataka.

• Article Download / Views: 3,007
• Total Downloads : 16
• Authors : Dr. H. S. Govardhana Swamy
• Paper ID : IJERTCONV3IS19035
• Volume & Issue : ICESMART – 2015 (Volume 3 – Issue 19)
• Published (First Online): 24-04-2018
• ISSN (Online) : 2278-0181
• Publisher Name : IJERT

Dr. H. S. Govardhana Swamy

Professor & Head, Department of Civil Engineering RajaRajeswari College of Engineering,

Bengaluru, India

Abstract Tunga River has been one of the most prominent and important river of Karnataka in Shimoga District. Unfortunately, certain stretches of River Tunga are much polluted. Various urban centers are located on the banks of Tunga River, draw fresh river water for various activities. In almost the entire wastewater generated by these centers is disposed off into the river. The objective of the monitoring studies undertaken for water body is to assess variation in water quality with time. Four sampling stations were selected along the river for sampling purpose from August 2013 to August 2014.Water samples were analyzed in terms of physico-chemical water quality parameters.

Keywords Thunga River, water quality, point pollution, Physico-chemical parameters

INTRODUCTION

In nature, water is the essential fluid from which all life begins. All living things need water to maintain their life too. In domesticity, it is very useful, such as for washing and cleaning. In industry, it is the common solvent for Paper and water, textile and electroplating. Besides, the generation of electricity also requires water. It has many uses. However, it can be easily polluted. Pollutants deteriorate the quality of the water and render it unfit for its intended uses [1]. The pollution of rivers and streams with chemical contaminants has become one of the most critical environmental problems of the century. It is estimated that each year 10 million people die from drinking contaminated water. Water is one of the most common and precious resources on the earth without there would be no life on earth [2]. Pollution is a serious problem as almost 70% of Indias surface water resources and a growing number of its groundwater reserves have been contaminated The quality of water is described by its physical, chemical and microbiological characteristics. Therefore a regular monitoring of river water quality not only prevents outbreak of diseases and checks water from further deterioration, but also provides a scope to assess the current investments for pollution prevention and control. In this study, seasonal variations of physico-chemical and bacteriological characteristics of water quality in Tunga river was assessed in Shimoga town in Karnataka.

MATERIALS AND METHODS

Shimoga is town, situated between the North and South branches of river Tunga. It is located on the Bangalore Honnavar highway.Though it is a town of medium population, the temples and historically significant monuments of this town attracts a large number of tourist people resulting in a very high floating population. Because of this reason the river Tunga along Shimoga town stretch is prone to anthropogenic activities such as bathing, washing and disposal of wastes. The ground level in the town slopes towards river so that most of the storm and sewerage drains discharge into river Tunga. There are two stream monitoring stations and 15 drains located in this town stretch

Monitoring Stations

Station – S1

Station S1 is located on the north side of the river, near the Shimoga Thirthahalli new bridge. It is an upstream station and near this station water is being drawn for supply to the town.

Station – S2

This station is about 300 m downstream of station S1.The station S2 is located on a drain that enters the river from the industrial town areas. The flow in the drain is mainly comprised of industrial waste.

Station – S3

The station S3 is an most affected station and is positioned near the Vinayaka temple(Ramanna shetty park). It is downstream of the sewage disposal point from the station S3. A bathing ghat exists near this Station.

Station S4 is located on the south side of the river, near the Shimoga Bhadravathi new bridge. Two number of sewage drains dispose city sewage water in to the river directly.

Data Preparation

The data sets of 4 water quality monitoring stations which comprised of 10 water quality parameters monitored monthly over 2 years (2013-2014) are used for this study. The data is obtained from the water Quality Monitoring work of Tunga River Basin in Shimoga District,

Karnataka State Although there are more water quality parameters in these stations, only 10 most important parameters are chosen because of their continuity in measurement through the 12 years. The 10 selected water quality parameters include Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Chlorides (Cl), Total Dissolved Solids (TDS), Conductivity, Temperature and pH.

Analysis of samples

The water samples were collected from each of the five selected stat ions according to the standard sampling methods (IS: 2488, 1966 APHA, 1998).Samples for estimating dissolved oxygen (DO) and biochemical oxy gen demand (BOD) were collected separately in BOD(glass) bottles. Water temperature was recorded on the spot using thermometers.

RESULT AND DISCUSSION

Temperature was found to be ranged between 14 0C (minimum) to 280C (maximum) with average value of 210+9.90C from all the sites. Impinging solar radiation and the atmospheric temperature brings interesting spatial and temporal changes in natural waters. The rise in temperature of water accelerates chemical reactions, reduces solubility of gases, amplifies taste and odour and elevates metabolic activity of organisms (Usharani et al., 2010).

pH of the aquatic system is an important indicator of the water quality and the extent pollution in the watershed areas. pH was recorded to be varying from 6.43 (minimum) to 9.13 (maximum) with an average value of 7.78+1.91 from all the sites (Jonnalagadda et al.,2001). It has been mentioned that the increasing pH appear to be associated with increasing use of alkaline detergents in residential areas and alkaline material from wastewater in industrial areas (Chang, H., 2008)

Conductivity is a good and rapid method to measure the total dissolved ions and is directly related to total solids. Higher the value of dissolved solids, greater the amount of ions in water (Bhatt.,1999). The range of Electrical conductivity from all the sites was recorded as 340.00

µmhos (minimum) to 734.00 µmhos (maximum) with an average value of 537.00+278.60 µmhos

The value of Dissolved Oxygen is remarkable in determining the water quality criteria of an aquatic system. In the system where the rates of respiration and organic decomposition are high, the DO values usually remain lower than those of the system, where the rate of photosynthesis is high (Mishra et al., 2009). During the study period DO was found to be ranging between 4.90 mg/l (minimum) to 8.50 mg/l (maximum) from all the sites with an average value of 6.70+2.55 mg/l.

Biochemical Oxygen Demand is a measure of the oxygen in the water that is required by the aerobic organisms. The biodegradation of organic materials exerts oxygen tension in the water and increases the biochemical oxygen demand (Abida, 2008).BOD has been a fair measure of cleanliness

of any water on the basis that values less than 1-2 mg/l are considered clean, 3 mg/l fairly clean, 5 mg/l doubtful and 10 mg/l definitely. During the study period BOD varied from 3.00 mg/l (minimum) to 8.00 mg/l (maximum) with an average value of 5.50+3.54 mg/l at all the sites.

Chemical Oxygen Deand is a measure of the oxidation of reduced chemicals in water. It is commonly used to indirectly measure the amount of organic compounds in water. The measure of COD determines the quantities of organic matter

found in water. This makes COD useful as an indicator of organic pollution in surface water (King et al., 2003).COD pointing to a deterioration of the water quality likely caused by the discharge of municipal waste water (Mamais et al., 1993). In the present study COD was found to be ranging from 11 mg/l (minimum) to 24 mg/l (maximum) with average value of 17.50+9.19 at all the sites.

Alkalinity of water is a measure of weak acid present. Total alkalinity of water is due to presence of mineral salt present in it. Alkalinity was ranged between 123.00 mg/l (minimum) to 240.00 (maximum) mg/l with average value of 181.50+82.73 mg/l from all the sites.

Total hardness is the parameter of water quality used to describe the effect of dissolved minerals (mostly Ca and Mg), determining suitability of water for domestic, industrial and drinking purpose attributed to presence of bicarbonates, sulphates, chloride and nitrates of calcium and magnesium (Taylor, 1949). The variation in Total hardness during study period at all the sites was recorded as

mg/l to 475.00 mg/l with average value of 352.50+173.24 mg/l

Chlorides occur naturally in all types of water. High concentration of chloride is considered to be the indicators of pollution due to organic wastes of animal or industrial origin. Chlorides are troublesome in irrigation water and also harmful to aquatic life (Rajkumar, 2004). The levels of chloride in the present study were ranging from 18.00 mg/l (minimum) to 32.00 mg/l (maximum) with an average value of 25.00±9.90 mg/l at all the sites.

Fluoride concentration is an important aspect of hydrogeochmistry, because of its impact on human health. The recommended concentration of Fluoride in drinking water is 1.50 mg/l. The values recorded in this study was ranged between 0.40 mg/l (minimum) to 1.20 (maximum) mg/l with an average value of 0.80±0.57 mg/l from all the sites.

Table 1: Physico-chemical qualities of river water

Where D.O.= Dissolved Oxygen, BOD= Biochemical Oxygen Demand, COD= Chemical Oxygen Demand, TH= Total Hardness.

The present study concluded that river water of study area was moderately polluted in respect to analyzed parameters. pH, total hardness, chloride and fluoride were found within permissible limit but the higher values of BOD and COD in present study attributed river water was not fit for drinking purpose. It needs to aware local villagers to safeguard the precious river and its surrounding

APHA. Standard methods for the examination of water and wastewater.18thEdition, Washingoton, D.C 1992

Abida, B. and Harikrishna Study on the Quality of Water in Some Streams of Cauvery River, E- Journal of Chemistry, 5, (2): 377-384. 2008.

Eletta O. A.A Llnd Adekola F.A.. Studies Of The Physical and

Chemical Properties Of Asa River Water, Kwara State, Nigeria. Science Focus Vol, 10 (l), 2005 pp 72 76.

Jonnalagadda, S.B., and Mhere,G. Water quality of the odzi river in the eastern highlands of zimbabwe.Water Research, 35(10): 2371- 2376. 2001

Meitei, N.S., Bhargava and Patil, P.M. Water quality of Purna river in Purna Town, Maharashtra state. J. Aqua. Biol., 19- 77, 2005

Manjappa,S.,Suresh,B., Arvinda, H.B., Puttaiah, E.T., Thirumala,S. Studies on environmental status of Tungabhadra river near Harihar, Karnataka (India),J. Aquqa. Biol, vol 23(2): 67-72,2004

Mishra, A., Mukherjee, A. and Tripathi, B.D. Seasonal and Temporal Variation in Physico- Chemical and Bacteriological Characteristics of River Ganga in Varansi. Int. J.Environ. Res., 3(3): 395-402.2009

Rajkumar, S., Velmurugan, P., Shanthi, K., Ayyasamy, P.M. and Lakshmanaperumalasamy, P.(2004). Water Quality of Kodaikanal lake, Tamilnadu in Relation to PhysicoChemical and Bacteriological Characteristics, Capital Publishing Company, Lake 2004, pp.339- 346

Trivedi, R.K. and Goel, P.K. Chemical and biological methods

for water pollution studies. Environ. Publication, Karad. Maharashtra, India ,1994.

Usharani, K., Umarani,K., Ayyasamy, P.M., Shanthi, K.Physico- Chemical and Bacteriological Characteristics of Noyyal River and Ground Water Quality of Perur, India. J. Appl. Sci. Environ. Manage. Vol.14(2) 29-35,2009

ACKNOWLEDGEMENT

I would like to thank principal of RajaRajeswari College of Engineering and Management of RajaRajeswari Group of Institutions for extending encouragement and support to present the paper in the International Conference at T.John College of Engineering, Bangaluru

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New approach to monitoring freshwater quality can identify sources of pollution, predict their effects

by University of Cambridge

The source of pollutants in rivers and freshwater lakes can now be identified using a comprehensive new water quality analysis, according to scientists at the University of Cambridge and Trent University, Canada.

Microparticles from car tires , pesticides from farmers' fields, and toxins from harmful algal blooms are just some of the organic chemicals that can be detected using the new approach, which also indicates the impact these chemicals are likely to have in a particular river or lake.

Importantly, the approach can also point to the origin of specific organic matter dissolved in the water, because it has a distinct composition depending on its source.

It uses a technique called high-resolution mass spectrometry to analyze water samples : within an hour this provides a comprehensive overview of all the organic molecules present. The paper is published in the journal Science .

Water quality is strongly determined by the diversity of organic matter dissolved in it—termed "chemodiversity." The scientists say that the thousands of different dissolved organic compounds can keep freshwater ecosystems healthy, or contribute to their decline, depending on the mixture present.

"Traditional approaches to monitoring water quality involve taking lots of different measurements with many devices, which takes a lot of time. Our technique is a very simple way to get a comprehensive overview of what's going on in a particular river or lake," said Jérémy Fonvielle, a researcher in the University of Cambridge's Department of Biochemistry and co-author of the paper.

To understand what drives this chemodiversity, the team reviewed studies of dissolved organic matter in freshwater samples from rivers and lakes across Europe and northern Canada.

For example, water analysis of Lake Erie in Canada revealed high levels of phosphorus pollution. By looking at the composition of individual molecules in the water sample, researchers identified agricultural activities as the source of this pollution, rather than wastewater effluent.

"Whereas before, we could measure the amount of organic nitrogen or phosphorus pollution in a river, we couldn't really identify where pollution was coming from. With our new approach we can use the unique molecular fingerprint of different sources of pollution in freshwater to identify their source," said Dr. Andrew Tanentzap at Trent University School of the Environment, co-author of the report.

Traditional approaches involve separately measuring many indicators of ecosystem health, such as the level of organic nutrients or particular pollutants like nitrogen. These can indicate the condition of the water, but not why this state has arisen.

Dissolved organic matter is one of the most complex mixtures on Earth. It consists of thousands of individual molecules, each with their own unique properties. This matter influences many processes in rivers and lakes, including nutrient cycling , carbon storage, light absorption, and food web interactions—which together determine ecosystem function.

Sources of dissolved organic matter in freshwater include urban runoff, agricultural runoff, aerosols and wildfires.

"It's possible to monitor the health of freshwater through the diversity of compounds that are present. Our approach can, and is, being rolled out across the UK," said Tanentzap.

Fonvielle will now apply this technique to analyzing water samples from farmland drainage ditches in the Fens, as part of a project run by the University of Cambridge's Center for Landscape Regeneration to understand freshwater health in this agricultural landscape.

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• Published: 31 January 2020

Pollution exacerbates China’s water scarcity and its regional inequality

• Ting Ma   ORCID: orcid.org/0000-0002-4362-9330 1 , 2 , 3   na1 ,
• Siao Sun   ORCID: orcid.org/0000-0002-6860-3639 4   na1 ,
• Guangtao Fu   ORCID: orcid.org/0000-0003-1045-9125 5 ,
• Jim W. Hall   ORCID: orcid.org/0000-0002-2024-9191 6 ,
• Yong Ni   ORCID: orcid.org/0000-0002-7636-8683 1 , 2 , 7 ,
• Lihuan He   ORCID: orcid.org/0000-0002-0270-1164 7 ,
• Jiawei Yi   ORCID: orcid.org/0000-0003-0325-7146 1 , 2 ,
• Na Zhao 1 , 2 ,
• Yunyan Du 1 , 2 ,
• Tao Pei   ORCID: orcid.org/0000-0002-5311-8761 1 , 2 , 3 ,
• Weiming Cheng 1 , 2 ,
• Ci Song   ORCID: orcid.org/0000-0003-2146-6259 1 , 2 ,
• Chuanglin Fang 2 , 4 &
• Chenghu Zhou   ORCID: orcid.org/0000-0003-3331-2302 1 , 2  

Nature Communications volume  11 , Article number:  650 ( 2020 ) Cite this article

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• Sustainability

Inadequate water quality can mean that water is unsuitable for a variety of human uses, thus exacerbating freshwater scarcity. Previous large-scale water scarcity assessments mostly focused on the availability of sufficient freshwater quantity for providing supplies, but neglected the quality constraints on water usability. Here we report a comprehensive nationwide water scarcity assessment in China, which explicitly includes quality requirements for human water uses. We highlight the necessity of incorporating water scarcity assessment at multiple temporal and geographic scales. Our results show that inadequate water quality exacerbates China’s water scarcity, which is unevenly distributed across the country. North China often suffers water scarcity throughout the year, whereas South China, despite sufficient quantities, experiences seasonal water scarcity due to inadequate quality. Over half of the population are affected by water scarcity, pointing to an urgent need for improving freshwater quantity and quality management to cope with water scarcity.

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Introduction

The survival and development of human society depends on water, and the global demand has increased by nearly eightfold over the period 1900–2010 1 , 2 , driven by population growth, expanding irrigated croplands, economic development, and dietary shifts 2 , 3 , 4 , 5 , 6 , 7 , 8 . Increasing water demands in combination with their geographic and temporal mismatch with freshwater availability have rendered water scarcity a widespread problem in many parts of the world, which occurs when demand for freshwater exceeds available supply 9 , 10 . Particularly in China, with per capita available water resource amounting to only one fourth of the world average 11 , 12 , 13 , water scarcity is one of the most significant threats that challenge sustainable development 14 , 15 , 16 . The uneven distributions of water and population create inequality in water scarcity 13 , with some regions in North China facing extreme water pressures to an extent that is not revealed by national average figures. As a result of rising conflicts among regional and sectoral water uses, policy attention on mitigating water scarcity is growing in China 16 , 17 , 18 .

Understanding water scarcity should underpin sustainable water resources management 10 , 19 , 20 . Many previous studies have assessed China’s water scarcity at regional and national levels 21 , 22 , 23 , 24 , or in a global context 4 , 25 , 26 , 27 . Previous water scarcity assessments mostly focused on the quantity of water available for water supplies 3 , 26 , 28 , 29 , 30 , 31 , 32 , but neglected the fact that inadequate water quality may pose a significant constraint on water usability 33 , 34 . The dramatic economic development in recent decades in China has come at an environmental cost, where widespread land use changes, increasing volumes of untreated wastewater from households, and industry and agricultural runoff have led to severe pollution of the aquatic environment 12 , 14 , 18 , 35 , 36 , 37 . In a few earlier water scarcity assessments for Chinese cities and river basins, the water quality issue was included by comparing the gray water footprint (i.e., the amount of water required to dilute pollutants in wastewater to meet environmental water quality standards) with water availability 22 , 24 , 34 , 38 . Later, China’s water scarcity was analyzed at the national level based on this gray water footprint concept, however, using a rather coarse spatial resolution for 31 provincial-level administrative units 39 . A recent study assessed the implications of pollution for water scarcity by explicitly considering sectoral water quality requirements in comparison to available water quality 34 .

Despite a recognized need, nationwide assessment of water quality as a contributing factor to water scarcity in China has not yet been implemented at a high spatial resolution, probably due to a limited coverage of water quality data 20 , 40 . The impact of inadequate water quality on water scarcity and its regional inequality remains unclear. While most large-scale water scarcity assessments were implemented at either grid cell or watershed scale 4 , 25 , 26 , 27 , 30 , 31 , 32 , 39 , the effect of using different spatial resolutions on water scarcity and accompanied uncertainty still present a great knowledge gap.

To address these, we quantified China’s present-day water scarcity, by examining needs for human water uses meeting both quantity and quality requirements at various temporal and spatial scales, in the meantime, taking into account environmental flow requirement (EFR). We compiled nationwide datasets consisting of water availability, water quality (measured by three typical water quality indicators, including the chemical oxygen demand, COD; ammonium nitrogen, NH + 4 -N; and electrical conductivity, EC), and sector-specific water withdrawal (for irrigation, industry, domestic use, and eco-environmental compensation use). All the datasets contain multiple geographic and temporal scales: at the 0.25 × 0.25 arc-degree grid cell, the first-order, second-order, and third-order basin levels on the annual, seasonal, and monthly basis for the 5-year period: 2012–2016 (Methods section). We then assessed the impact of inadequate water quality on water scarcity across four different geographic levels at three time scales. The results are crucially important for informing policy-making for regional water scarcity adaptation and alleviation.

Quality-included water scarcity at various geographic scales

Quantity-based water scarcity (referred to as WSqua, see Methods section), quality-based water scarcity (also pollution-induced water scarcity, abbreviated as WSpol), and water scarcity based on the combined effect of both quantity and quality (referred to as WScom) in present-day China exhibit geographical variations (Fig.  1 ). At the grid cell level, WScom tends to increase areas under water scarcity and intensify water scarcity in many places in comparison to WSqua (Fig.  1b–d ). A total of 28.8% and 32.0% of China’s area suffer WSqua and WScom (WSqua > 1 and WScom > 1, see methods for the equations), respectively. Water scarce areas are mainly distributed in North China. Over half areas in the Huai, Hai, Yellow, and Liao River basins, and 45.4% areas in the Songhua River basin are under WScom. In the Northwest River basin with large wild and unpopulated regions, water scarcity mainly occurs in west Xinjiang province with large irrigated croplands. While not under WSqua, a number of grid cells in the middle and lower reaches of Yangtze River and on the southeast coasts face WScom. This implies that in South China, water shortage is only relevant when quality issue is considered, though quality-induced water scarcity alone is not significant.

a Spatial distributions of river basins in this study. b Quantity-based water scarcity (WSqua). c Pollution-induced water scarcity (WSpol). d Combined water scarcity, including both quality and quantity effects (WScom). Estimated water scarcity was based on the average of annual assessments during 2012–2016 at a spatial resolution of 0.25 × 0.25 arc-degree ( n  = 15997). The graph at the lower left corner in a represents the sampling locations of water quality. Maps of grid cell-level WScom at other time scales are shown in Supplementary Fig.  2 . NA, no data or water scarcity is <10 −5 . Source data are provided as a Source Data file.

Water scarcity assessments at the basin levels, in which the heterogeneity of water availability, withdrawal, and quality within a basin is neglected, show some consistency with the high-resolution grid cell-based results. That is, basins with higher percentages of grid cells under water scarcity tend to be more water stressed (Fig.  2 ). The third-order, second-order, and first-order basins under WScom constitute respectively 64.6%, 59.2%, and 70.0% of the total numbers of basins of corresponding levels. At the first-order basin level, the four basins in South China are mostly under low WScom (WScom < 1, with the exception for the Southeast River basin slightly >1), whereas the other six basins in North China face both WSqua and WScom. In the most water-stressed Hai and Huai River basins with dense population and intensive agricultural activities, WSqua is >5, indicating that human water withdrawal (not accounting EFR) is larger than local available water resource. Areas where water withdrawal exceeds water availability have long been relying on exploitation of nonrenewable fossil groundwater and inter-basin water transfers, e.g., the south-to-north water transfer project 17 , 18 . Consequently, groundwater overexploitation has resulted in abrupt decline of groundwater tables, which is unsustainable and leads to a series of eco-environmental problems. Inter-basin water diversion is usually energy consuming and cost intensive, and may have adverse eco-environmental impacts on the source basins 17 . In the Hai River basin, which is home to nearly 10% of the Chinese population, the inclusion of water quality dimension has led to more than doubling the value of WScom in comparison to WSqua, indicating a significant effect of degraded water quality on exacerbating water scarcity.

a The third-order basin level ( n  = 209). b The second-order basin level ( n  = 76). c The first-order basin level ( n  = 10). Maps of WScom at other time scales for these three basin levels are shown in Supplementary Figs.  3 – 5 . Source data are provided as a Source Data file.

Seasonal and sectoral water scarcity

As all the influencing factors for water scarcity, i.e., water resources availability, water withdrawal, and water quality show seasonal variations, water scarcity levels also present seasonal differences (Fig.  3 ). The climate in China is mostly controlled by the Pacific and Indian Ocean monsoons, so that in most regions 70–80% of annual precipitation falls between four consecutive months (i.e., May to August, or June to September 41 ). Overall, spring is the most water scarce season, as the season is relatively dry (Supplementary Fig.  1 ), and the agricultural water demand is high in this early growing season. Seasonal water scarcity maps show significant spatial differences (Supplementary Figs.  2 – 5 ). WScom occurs in the middle reach of Yangtze River basin and lower reach of Southwest River basin in spring when a large quantity of irrigation water is needed, but not in other seasons. Many third-order basins in North China are under WScom in all the months throughout the year. A few third-order basins in South China, which do not face annual WScom, however, still suffer WScom in dry seasons or months. Figure  3 also shows that seasonal water scarcity is sensitive to the geographic scale. In the most water scarce spring, basins under WScom comprise 70.0%, 69.7%, and 71.3% of the total numbers of basins at the first-order, second-order, and third-order basin levels, respectively; 39.3% gird-cells suffer WScom. The season with the least number of geographic units under WScom is summer or autumn, depending on the geographic scale.

Estimates were made across four different geographic scales at three temporal scales (Y, yearly; W–A, seasonal from winter throughout autumn; and J–D, monthly from January throughout December. Winter corresponds the months from December to February). The level of water scarcity is defined in Methods section. Source data are provided as a Source Data file.

Proportions of sectoral water scarcity levels in the first-order basins are provided in Supplementary Fig.  6 . Agriculture is the sector where water scarcity has the greatest relevance, because it is the most water consuming sector that represents ~67% of the total water withdrawal at the national level. On the annual basis, agricultural water withdrawal always comprises the largest share of the total water withdrawal in the first-order basins. Agriculture-induced WScom is occasionally smaller than industry or domestic sector-induced WScom in 6.6% and 8.6% of the second-order and third-order basins, respectively. As a result of seasonal variations in sectoral water withdrawals (in particular in agricultural water withdrawal), sectoral water scarcity proportions also show great seasonality. Contributions of water scarcity from agricultural water withdrawal are usually most significant in spring and summer (Supplementary Fig.  6 ). Since domestic and industrial water uses usually have priority over agriculture when competition between sectoral water uses intensifies, agriculture is the most vulnerable sector to water scarcity 42 , 43 , 44 . However, due to its high water use volume and intensity, the potential for agricultural water conservation is also high. Therefore, one of the keys for addressing water scarcity is sustainable agricultural water use and management 9 , 45 , while ensuring food security.

Population under water scarcity at multiple scales

In China, ~80% of the human population live in 10% of the land area. Water scarce regions are densely populated, because water demands are closely related to human activities, while some of these densely populated areas are also in drier parts of the country. Superimposing the population distribution map on the results of our water scarcity assessment enables the number of people living in water scarcity conditions to be estimated 19 , 26 . The numbers of people facing different water scarcity levels based on assessments at different temporal and geographic scales are shown in Fig.  4 . On an annual basis, about 51.3%, 75.2%, 86.6%, and 86.1% of a total population of 1.36 billion in China live in WScom conditions according to the assessments based on the first-order, second-order, third-order basin, and grid cell scales, respectively (Fig.  4a ). A higher spatial resolution estimation generally corresponds to a larger number of people facing water scarcity. On the first-order basin scale, people who face WScom live in the six basins in North China plus the Southwest River basin, while on the grid cell scale, people living in highly populated areas in other basins in South China also suffer WScom. The inclusion of WSpol in the assessment makes between 2.3–5.7% more people under WScom in China (in comparison to those facing WSqua), depending on different geographic scales.

Estimates were made according to quantity-based and quality-included water scarcity assessments across four geographic scales on three temporal scales. a Annual basis. b Seasonal basis. c Monthly basis. Source data are provided as a Source Data file.

When seasonal variability is considered, about 65.1%, 97.7%, 96.1%, and 92.9% of the population are under WScom for at least one season, with increasing geographic resolutions from the first-order basin to grid cell scales (Fig.  4b ). A total of 100%, 99.9%, 98.8%, and 94.7% of the population live in WScom for at least 1 month, based on assessments of the above four geographic scales, respectively. These numbers are much larger than those from annual estimates, implying that annual estimates may underestimate water scarcity severity 26 , 29 , 31 . All of the ten first-order basins face WScom for at least 1 month. In the least water-stressed Southeast River basin, where the annual WScom is <0.1, WScom occurs in December when the monthly natural water resource availability is the least and pollution discharges in cities (e.g., Xining and Lhasa) are remarkable.

About 51.3%, 82.6%, 94.4%, and 91.6% of the population face severe WScom (WScom > 2) for at least 1 month according to assessments at the four geographic scales with increasing resolutions (Fig.  4c ). The number of people under severe WSqua for at least 1 month (WSqua > 2) ranges between 0.62 and 1.24 billion. These estimates bracket a previous estimate of 0.9 billion from Mekonnen and Hoekstra’s global study of water quantity 26 , yet provide an uncertainty range originating from changing geographic scales. A total of 0.34–0.82 billion people are subject to severe monthly WScom all year round. Of all the people who face severe monthly WScom, 0.34 billion people live in five basins in North China at the first-order basin level, while 0.82 billion people also include those who live in the Songhua River basin and South China according to the third-order basin scale assessment.

Regional inequality of water scarcity

As specified previously, water scarcity in basins in North China is generally more severe than South China. Given limited total available water resources (~2.77 trillion m 3 annually on average in China 41 ), a greater level of inequality corresponds to more severe water scarcity in a few regions and more people under water scarcity, if the water scarcity level is held constant at the national level. The curves of cumulative proportions of water withdrawal and water availability (sorted in an increasing order of the ratio of water withdrawal to water availability) on the annual basis are far from the 45 degree line, which represents perfect water withdrawal equality, confirming high inequality in spatial water scarcity in China (Fig.  5a ). The curves taking into account water quality requirements are even further from the equality line than those considering only water quantity, implying that the inclusion of water quality dimension aggravates water scarcity inequality in China. On the graph for first-order basins, basins in South China are located on the bottom of curves where WSqua or WScom values are relatively low, whereas basins in North China are on the top of the curves with higher WSqua and WScom values. Graphs showing inequality of water scarcity for different time scales are shown in Supplementary Figs.  7 – 10 .

a Cumulative probability of water availability against cumulative portability of water withdrawals on the annual basis, sorted by increasing magnitudes of the ratio of water withdrawal to availability according to different geographic scales. b Disparities in water scarcity levels among regions. Theil’s L index is used to indicate regional water scarcity disparities, and the 95% confidence interval (CI) of Theil’s L index was calculated based on the normal approximation (Y, yearly; W–A, seasonal from winter throughout autumn; and J–D, monthly from January throughout December. Winter corresponds the months from December to February). Source data underlying b are provided as a Source Data file.

The Theil’s L index (Methods section) provides a quantitative measure for inequality of water scarcity levels at different temporal and geographic scales (Fig.  5b ). A higher Theil’s index corresponds to a greater inequality. The Theil’s index for WScom is always higher than for WSqua. A finer resolution assessment for water scarcity corresponds to a higher Theil’s index. The Theil’s indices also present seasonal variabilities. The greatest regional inequality occurs in the most water scarce spring. The month with the greatest regional water scarcity inequality falls between March and May, depending on the geographic scales. Because natural water bodies have a self-cleansing capacity that can remove polluting substances by a series of chemical and biological self-purification processes and such a capacity is often related to water availability, water pollution is also about quantities. Therefore, quality-induced regional inequality appears to be larger in high water scarce seasons or months. This also explains greater regional inequality in WScom than in WSqua.

This research provides a comprehensive analysis of China’s present water scarcity levels at various geographic and temporal scales, for the first time including the implications of water quality. The results show that the inclusion of water quality in water scarcity assessment leads to aggravated water scarcity, as well as greater water scarcity inequality in China. North China often suffers from water scarcity from both insufficient water quantity and inadequate quality throughout the year, whereas South China is subject to seasonal water scarcity mainly due to water quality degradation. Chinese state and local government have invested thousands of billions of Chinese Yuan to enhance wastewater treatment and control pollution sources dedicated to environmental restoration in the recent decade 37 . Contributions of the investments on the improved surface water quality (characterized mainly by COD and NH + 4 -N concentrations) and the regional difference were quantified in a recent study 46 . Notwithstanding a recent trend in improved water quality, our results show that quality still presents a great issue for achieving safe water supply in China.

The metric WSpol used in this study for measuring quality-induced water scarcity, i.e., the ratio of water required for dilution to obtain adequate quality for sectoral water uses to water availability 34 , is useful in guiding policy-making to identify basins where water supplies are mostly threatened by degraded water quality. At the third-order basin level (at which aquatic environment restorations are often planned and managed in China), prominent examples of water quality inferior to level IV (according to the Environmental Quality Standard for Surface Water in China 47 ) include sub-basins in Hai River, Yellow River, and Liao River basins (Supplementary Fig.  11 ). Given that the investment budget into aquatic environment restoration is limited each year, our results suggest that the need for water quality improvement in the Hai River sub-basins is the most urgent due to the severe scarcity (WSpol > 2). The impact of water quality on domestic and production water uses can also be analyzed using the concept of water carrying capacity, which refers to the maximum population or economic scale that can be sustainably supported by available water resources 48 .

The water carrying capacity, in terms of a multiplier of present-day population or economic scale, is analyzed in Supplementary Note  1 , and similar conclusions can be derived as those from WSqua and WScom assessments. For instance, at the first-order basin level on an annual basis, the quality-included carrying capacities in all the six North China basins and the Southeast River basin is <1, indicating an insufficient capacity of water resources for sustaining the population and economic activities in these basins. While the quantity is sufficient for supporting human’s water needs and EFR in the Southeast River basin, its inadequate water quality makes the quality-included carrying capacity <1 (Supplementary Note  1 , Supplementary Fig.  12 ).

While most global water scarcity studies performed in single- or multi-model settings have estimated water uses based on FAO AQUASTAT country-specific data or model simulations 8 , 26 , 31 , 32 , the regional-scale statistics used in this study allow for more accurate high-resolution sectoral water withdrawal downscaling in China. We estimate that the number of people facing WScom is between 0.70 and 1.36 billion, which presents large uncertainty when different temporal and geographic scales are considered. Most previous water scarcity assessments recommended a grid cell-based assessment, claiming that it is able to consider spatial variations of water resources and withdrawals within basins 3 , 26 , 32 . However, this high-resolution approach sometimes differs from the real world, because the distance between water abstraction and water use can be substantial and not captured within a grid cell 10 . For instance, large cities have extensive urban water supply systems, sometimes hundreds of kilometers distant from water sources 49 ; many river basins (e.g., the Yellow River basin) have implemented integrated basin-scale water resources allocation in order to address sub-regional and sectoral water use competition. Previous studies also highlighted that annual assessments hide the intra-annual variability of both water availability and uses, and may underestimate the extent of water scarcity 19 , 26 , 29 , 32 . However, because reservoirs are common on Chinese rivers 8 , 10 , 50 , occasionally seasonal or monthly water scarcity in many basins may have been addressed or reduced by seasonal flow regulations. Hence, assessment at a finer geographic or temporal resolution does not necessarily correspond to a better water scarcity estimate unless it takes account of infrastructure operation.

Therefore, we argue here that it is essential to conduct water scarcity analyses at different temporal and geographic scales, unless sufficient evidence supports a specific scale. Analyses at different geographic and temporal scales provide lower and upper bounds of water scarcity levels due to uncertainty in practical water uses and management. Our estimates of water scarcity intervals at various spatiotemporal scales also provide insights in the extent to which a corresponding measure (i.e., water resources allocations between seasons or sites) can be useful in coping with water scarcity. For instance, in basins where people suffer water scarcity in all the months, seasonal flow regulation will not be effective in reducing water scarcity. Because human interventions (e.g., man-made reservoirs and human water uses), as well as legal and institutional arrangements may all result in changes in water scarcity 8 , more detailed information from improved monitoring, and management reporting needs to be incorporated in future water scarcity assessment to reduce uncertainty.

The role of seasonal variability for EFR in water scarcity assessment has been highlighted in recent studies 39 , 51 . Here, we present seasonal and monthly water scarcity with a fixed proportion of EFR for consistency with annual analyses. The inclusion of seasonal variability for EFR has an effect on seasonal water scarcity (Supplementary Note  2 , Supplementary Fig.  13a ), because the proportion of EFR directly impacts water resources availability for human uses. Nevertheless, regional inequality of monthly water scarcity is insensitive to seasonal variability for EFR in this case (Supplementary Fig.  13b ). It has to be recognized that we do not differentiate groundwater withdrawal and quality from surface water in this research, because of a lack of nationwide groundwater quality data. Quality from both surface water and groundwater for sectoral water uses is represented by in situ surface water quality. This will not have any impact on WSqua. However, in regions where surface water quality is inadequate for specific uses and a significant proportion of groundwater is exploited, WSpol is expected lower in reality, as groundwater quality is often superior to surface water. Our research, which does not focus on the effect of large engineering approaches on water scarcity, does not consider water scarcity condition changes due to water transfers across basins (e.g., south-to-north water transfer project).

Given the fact that over half of the population in China are currently facing WScom, even when seasonal and locally grid cell water scarcity (that can be solved by adequate seasonal within-basin water resources allocations) is not taken into account, water use efficiency improvement 41 , water conservation 18 , 52 , physical and virtual water transfers across basins 17 , 53 , and aquatic environmental restoration 14 , 18 , 37 are probably the key solutions for alleviating water scarcity in China, which is essential for sustainable socio-economic development and eco-environmental protection. High regional inequality of water scarcity in China urges locally specific policies for water demand management. In the meantime, inter-basin water transfers can directly mitigate water scarcity by supplying extra water sources to water scarce basins. Water scarcity assessment with a finer resolution corresponds to a greater inequality, indicating that water allocations within and between basins will be effective in reducing water scarcity inequality. However, the impact of water transfers on both source basins (e.g., social and eco-environmental impacts) and receiving basins (e.g., non-native species invasions and spreading of chemical/biological contaminants) needs to be carefully analyzed to minimize negative consequences.

The urgent need to further improve inland water quality in China, especially in northern basins, has been pointed out 14 , 35 , 36 , 37 , 54 —mostly because water pollution presents a great risk to public health and ecosystem services—and our results show evidence of this need from the perspective of providing adequate water supplies to population, economy, and ecosystems based on a quality-included water scarcity analysis.

The challenge of WScom that China faces is also shared by many other countries, as freshwater pollution is a worldwide problem in both developing and developed countries 39 . The methodology in this research could help to assess the magnitude of the challenge in other countries, thereby helping to formulate effective policies to achieve sustainable water supply. However, at present, inadequate water quality data availability makes it challenging to develop a global WScom assessment.

Assessment of water scarcity considering water quality

For a target region, quantity-based water scarcity WSqua is measured as the ratio of regional water withdrawal to water availability, considering a balance between human uses of freshwater and ecosystem protection:

where D i is water withdrawal for sector i , Q is water availability, EFR is the environmental flow requirement, which is defined as 80% of water availability, following previous studies 19 , 26 . Adapting from van Vliet et al. 34 , a dilution approach is applied to translate inadequate water quality into extra water quantity required so that it can be compared with water availability for water scarcity assessment. Quality-based water scarcity WSpol is calculated as the ratio of water required for dilution to obtain adequate quality for water uses to water availability:

where dq i is extra water required for dilution to obtain acceptable quality for water use sector i , dq i,j indicates the amount of dilution water for sector i based on water quality parameter j , C j is actual water quality level of parameter j , and C max i , j is the maximum water quality threshold based on parameter j for water use sector i . Equation ( 3 ) is slightly different from its original form developed by van Vliet et al. 34 . Instead of diluting all the available water to obtain water quantity needed for a sectoral water use, we estimate the extra amount of water by diluting the volume of the sectoral water withdrawal. Quality constraint for EFR is not considered in this study.

Combined water scarcity WScom taking into account both water quantity and quality dimensions is calculated:

In this study, water scarcity is classified into four levels based on the value of WSqua and WScom: low (<1.0), moderate (1.0–1.5), significant (1.5–2.0), and severe (>2.0), which is consistent with many previous studies 19 , 26 , 39 , 55 . The mean of WSqua or WScom values in 5 years from 2012 to 2016 is reported to represent the present-day water scarcity levels in China, because high-density water quality monitoring data are only available in this recent period. The inter-annual variabilities of WSqua and WScom are thus not discussed in this study.

Water quality requirements for sectoral water uses

Water withdrawal is mainly for four major sectoral uses in China: agriculture, industry, domestic uses, and eco-environmental compensation. Quality requirements for each sectoral water use C max in Eq. ( 3 ) are defined according to three typical water quality measures—COD (the permanganate index), NH + 4 -N, and EC. For agricultural water use, EC = 0.7 dS m −1 , which indicates a salinity constraint for crops, suggested by FAO 56 is considered as the maximum water quality threshold for irrigation. Maximum water quality thresholds for quality requirements for other sectoral uses are based on COD and NH + 4 -N concentrations according to the Environmental Quality Standard for Surface Water in China 47 : COD = 6.0 and NH + 4 -N = 1.0 mg L −1 for domestic uses (water quality level I–III), COD = 10.0 and NH + 4 -N = 1.5 mg L −1 for industrial uses (water quality not inferior to level IV), and COD = 15.0 and NH + 4 -N = 2.0 mg L −1 for eco-environmental compensation (water quality not inferior to level V). These thresholds of water quality parameters represent the minimum water quality requirements for sector-specific uses.

Data sources and data processing

Annual provincial-level natural water availability data from 2012 to 2016 (ref. 57 ) are downscaled to monthly grid cell values based on Variable Infiltration Capacity (VIC) hydrologic model simulation results 58 . The VIC simulation results, which have been validated with gauge measurements across China, provide a grid cell-level estimate for monthly water availability (including both subsurface and surface runoff) with a spatial resolution of 0.25 × 0.25 arc-degree. The annual statistical data of water availability are firstly downscaled to the grid cell level on the annual basis by letting water resources in grid cells proportional to those from VIC model simulation results (Supplementary Fig.  14a ). The grid cell-level annual water availability is then disaggregated into monthly values proportional to simulated monthly runoff in corresponding grid cells. The average annual freshwater availability in the period 2012–2016 in mainland China is ~2.91 trillion m 3 , ~5% more than the long-term average ~2.77 trillion m 3 and can roughly represent the average annual water resource availability condition in China.

Annual sectoral water withdrawal data at the province-level in China for the period 2012–2016 (ref. 57 ) are downscaled to monthly grid cell data based on multisourced information. Agricultural water withdrawal is mainly for irrigation, and is hence disaggregated based on relevant information including crop land uses (Supplementary Fig.  14b ) and net irrigation requirements. Net irrigation requirements are calculated as the difference between the reference crop evapotranspiration and effective precipitation at the grid cell level, which are derived mainly from meteorological data. Annual industrial water withdrawal is downscaled based on maps of the industrial gross domestic product (GDP) at the grid cell level (Supplementary Fig.  14c ). The maps of industrial GDP are generated by disaggregating province-level data through a proportional sharing method based on areas of industrial lands weighted by nighttime brightness 59 . Industrial water withdrawals are assumed uniformly distributed in all the months within a year. Annual domestic water withdrawal data are disaggregated according to spatial urban and rural population distributions and monthly water use factors. Rural population is disaggregated based on rural residential areas in grid cells, and urban population is disaggregated based on urban areas in grid cells weighted by nighttime light (similar to industrial GDP downscaling) (Supplementary Fig.  14d ). A monthly factor for domestic water use, which is a function of temperature, is introduced to consider seasonal water use variations following previous studies 32 , 60 . Eco-environmental compensation water withdrawal is mainly used for irrigating green spaces, and replenishing dry rivers and lakes in urbanized areas 57 , and only represents 2% of the total water withdrawal in China. As it is difficult to discern green spaces and water bodies in urbanized areas based on the available land use maps, we assume that water withdrawal for eco-environmental compensation is proportional to the size of urbanized areas in grid cells (Supplementary Fig.  14e ). Eco-environmental compensation water withdrawals are assumed uniformly distributed in all the months within a year (see Supplementary Notes  3 and  4 for detailed methodology and equations for sectoral water withdrawal downscaling).

Water quality data are collected from the national environmental monitoring network, which covers China’s major inland rivers and lakes. Monthly observations of COD, NH + 4 -N, and EC are available for 2630 sampling sites (with an average spatial density of 2.74 sampling sites per 10 4  km 2 , Fig.  1a ) for the period 2012–2016 (Supplementary Note  5, Supplementary Table  1 ). Based on the regional assemblage of site-level measurements, we use an inverse distance weighting function with an exponent of 1 to interpolate the spatial water quality parameters 61 at the grid cell level. We assemble site-level water quality data in second-order basins in which the majority (~75%) of grid cells are covered, and make the spatial interpolation for these grid cells. For the remaining ~25% of grid cells, the spatial interpolation of water quality parameters is made within first-order basins due to the lack of site-level observations in corresponding second-order basins. The cross-validation, which estimates water quality in grid cells containing sampling sites based on measurements in other grid cells, is applied to test the validity of the interpolated water quality parameters by comparing with the actual measurements. The results show that the interpolation provides sufficiently accurate water quality estimations with high R-square and low root-mean-square error (RMSE ; R 2  = 0.81 and RMSE = 1.11 mg L −1 for COD; R 2  = 0.80 and RMSE = 1.13 mg L −1 for NH + 4 -N; and R 2  = 0.90 and RMSE = 0.74 dS m −1 for EC). At the grid cell level, the mean value of a monthly water quality parameter in one season or 1 year (weighted by monthly water availability) is used to represent the corresponding seasonal or annual water quality. Water quality at a basin level is represented by the mean of water quality parameters in grid cells within corresponding basins (weighted by grid cell water availability).

Weighted Theil’s L Index for regional inequality

We used the Theil’s L index T L , i.e., the mean log deviation, to measure the inequality of water scarcity among n regions. T L is weighted by water withdrawal:

where WS i is the water scarcity index (either WSqua or WScom) in geographic unit i , and WW i is the amount of water withdrawal in geographic unit i .

Reporting summary

Further information on research design is available in the  Nature Research Reporting Summary linked to this article.

Data availability

Detailed information regarding the data that support the findings of this study can be found in Supplementary Table  1 . The source data underlying Figs.  1b–d , 2 – 4 , and 5b , and Supplementary Figs.  1 – 6 , 12 , and 13 are provided as a Source Data file. The additional data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

All computer codes used in the current study are available upon reasonable request.

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Acknowledgements

This work was jointly supported by the National Key Research and Development Program of China (2017YFB0503600), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA20040401), the National Natural Science Foundation of China (41421001, 41525004, and 41771418), and the Key Research Program of Frontier Science of the Chinese Academy of Sciences (QYZDY-SSW-DQC007).

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These authors contribute equally: Ting Ma, Siao Sun

Authors and Affiliations

State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

Ting Ma, Yong Ni, Jiawei Yi, Na Zhao, Yunyan Du, Tao Pei, Weiming Cheng, Ci Song & Chenghu Zhou

University of Chinese Academy of Sciences, Beijing, 100049, China

Ting Ma, Yong Ni, Jiawei Yi, Na Zhao, Yunyan Du, Tao Pei, Weiming Cheng, Ci Song, Chuanglin Fang & Chenghu Zhou

Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China

Ting Ma & Tao Pei

Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

Siao Sun & Chuanglin Fang

Centre for Water Systems, University of Exeter, Exeter, EX4 4QF, UK

Guangtao Fu

Environmental Change Institute, University of Oxford, Oxford, UK

Jim W. Hall

China National Environmental Monitoring Center, Beijing, 100012, China

Yong Ni & Lihuan He

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T.M., S.S., C.F., and C.Z. designed research, T.M., S.S., Y.N., L.H., J.Y., N.Z., Y.D., T.P., W.C., and C.S. performed research, T.M., S.S., Y.N., and C.Z. analyzed data, T.M., S.S., G.F., and J.W.H wrote the manuscript, and all coauthors contributed to the interpretation of the results and to the text. All authors read the manuscript and approved the submission.

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Correspondence to Ting Ma , Yong Ni or Chenghu Zhou .

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Ma, T., Sun, S., Fu, G. et al. Pollution exacerbates China’s water scarcity and its regional inequality. Nat Commun 11 , 650 (2020). https://doi.org/10.1038/s41467-020-14532-5

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The Port of San Diego has joined San Diego County and the cities of San Diego and Imperial Beach in declaring a local emergency related to the ongoing Tijuana River Valley pollution crisis, officials said Wednesday.

“Clean water and clean air are basic quality of life expectations and are needed now in our South Bay,” Frank Urtasun, chairman of the Board of Port Commissioners, said in a statement Wednesday.

“After many years of deteriorating conditions, we are now seeing some steps in the right direction. Recently, we learned of $156 million in critical annual funding secured by Congressman Scott Peters for the South Bay International Wastewater Treatment Plant.

“With our emergency declaration and continued regional collaboration, the Port of San Diego will continue to push for additional funding to ensure this public health, environmental, and economic crisis is solved,” Urtasun continued.

Port officials said over 100 billion gallons of untreated sewage, toxic chemicals, trash, sediment and other pollutants have flowed into the Tijuana River Valley and into the Pacific Ocean off the coast of Imperial Beach.

The flow “is causing serious public health issues from polluted waters and airborne toxins, (to) ongoing beach closures in Imperial Beach and Coronado, and negative impacts on the South Bay economy. Contaminated flows are directed through treatment plants under the jurisdictions of the U.S. and Mexico federal governments. However, these facilities have failing and aging infrastructure,” port officials said.

The port said the U.S. International Boundary and Water Commission operates the South Bay International Wastewater Treatment Plant , and additional funding is needed to improve and expand the plant.

“The Port of San Diego is on the front lines of this fight as the state’s trustee for beach and submerged lands in Imperial Beach,” Commissioner Dan Malcolm said.

“This crisis is sickening our South Bay communities and our beaches have been closed for nearly 850 days and counting. This environmental and public health nightmare must end! Our emergency declaration is a statement that we are still in this fight, and we will not stop advocating for every dime that is needed to stop the sewage once and for all.”