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• Published: 29 June 2020

Observed changes in dry-season water availability attributed to human-induced climate change

• Ryan S. Padrón   ORCID: orcid.org/0000-0002-7857-2549 1 ,
• Lukas Gudmundsson   ORCID: orcid.org/0000-0003-3539-8621 1 ,
• Bertrand Decharme   ORCID: orcid.org/0000-0002-8661-1464 2 ,
• Agnès Ducharne   ORCID: orcid.org/0000-0002-6550-3413 3 ,
• David M. Lawrence   ORCID: orcid.org/0000-0002-2968-3023 4 ,
• Jiafu Mao   ORCID: orcid.org/0000-0002-2050-7373 5 ,
• Daniele Peano   ORCID: orcid.org/0000-0002-6975-4447 6 ,
• Gerhard Krinner   ORCID: orcid.org/0000-0002-2959-5920 7 ,
• Hyungjun Kim   ORCID: orcid.org/0000-0003-1083-8416 8 &
• Sonia I. Seneviratne   ORCID: orcid.org/0000-0001-9528-2917 1  

Nature Geoscience volume  13 ,  pages 477–481 ( 2020 ) Cite this article

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Human-induced climate change impacts the hydrological cycle and thus the availability of water resources. However, previous assessments of observed warming-induced changes in dryness have not excluded natural climate variability and show conflicting results due to uncertainties in our understanding of the response of evapotranspiration. Here we employ data-driven and land-surface models to produce observation-based global reconstructions of water availability from 1902 to 2014, a period during which our planet experienced a global warming of approximately 1 °C. Our analysis reveals a spatial pattern of changes in average water availability during the driest month of the year over the past three decades compared with the first half of the twentieth century, with some regions experiencing increased and some decreased water availability. The global pattern is consistent with climate model estimates that account for anthropogenic effects, and it is not expected from natural climate variability, supporting human-induced climate change as the cause. There is regional evidence of drier dry seasons predominantly in extratropical latitudes and including Europe, western North America, northern Asia, southern South America, Australia and eastern Africa. We also find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.

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Wetting and drying trends under climate change

Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation

Global terrestrial water storage and drought severity under climate change

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Acknowledgements

R.S.P., L.G. and S.I.S. acknowledge partial support from the European Research Council (ERC) DROUGHT-HEAT project funded by the European Community’s Seventh Framework Programme (grant agreement FP7-IDEAS-ERC-617518) and from the European Union’s Horizon 2020 Research and Innovation Program (grant agreement 821003 (4C)). D.M.L. was supported in part by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computing Scientific Focus Area (RUBISCO SFA), which is sponsored by the Regional and Global Climate Modeling (RGCM) Program in the US Department of Energy Office of Science. J.M. was also supported by the RUBISCO SFA. Oak Ridge National Laboratory is managed by UT‐BATTELLE for DOE under contract number DE‐AC05‐00OR22725. D.P. acknowledges the European Union’s Horizon 2020 research and innovation program under Grant Agreement 641816 (CRESCENDO) that partially funded the CMCC simulations. H.K. acknowledges Grant-in-Aid for Specially Promoted Research 16H06291 and 18KK0117 from Japan Society for the Promotion of Science. The LS3MIP simulation of the Institut Pierre Simon Laplace (IPSL) was performed at the Très Grand Centre de Calcul (TGCC) under the allocation 2018- R0040110492 (project gencmip6) provided by GENCI (Grand Equipement National de Calcul Intensif). We acknowledge the World Climate Research Program’s Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project (CMIP), and we thank the climate modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank U. Beyerle, J. Sedlacek and L. Brunner for downloading and processing the CMIP5 and LS3MIP data.

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Institute for Atmospheric and Climate Science, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland

Ryan S. Padrón, Lukas Gudmundsson & Sonia I. Seneviratne

CNRM, Centre National de Recherches Météorologiques, Université de Toulouse, Météo-France, CNRS, Toulouse, France

Bertrand Decharme

Laboratory METIS (Milieux environnementaux, transferts et interaction dans les hydrosystèmes et les sols, Metis), Sorbonne Université, CNRS, EPHE, IPSL, Paris, France

Agnès Ducharne

Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA

David M. Lawrence

Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA

Fondazione Centro euro-Mediterraneo sui Cambiamenti Climatici, CMCC, Bologna, Italy

Daniele Peano

Institut des Géosciences de l’Environnement (IGE), CNRS, Université Grenoble Alpes, Grenoble, France

Gerhard Krinner

Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

Hyungjun Kim

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Contributions

R.S.P., L.G. and S.I.S. designed the study. R.S.P. performed the analysis and wrote the manuscript. B.D., A.D., D.M.L., J.M. and D.P. contributed to the land-surface model reconstructions. G.K., S.I.S. and H.K. coordinated the land-surface model experiments. H.K. produced the forcing dataset for the data-driven and land-surface model reconstructions. All authors discussed the results and read and reviewed the manuscript.

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Correspondence to Ryan S. Padrón .

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Extended data

Extended data fig. 1 agreement between reconstructions from data driven (ddm) and land surface models (lsm)..

Mean change in dry season water availability from the DDM and LSM reconstructions (that is mean of Fig. 1a, b of the main article). Shown are only grid cells where both reconstructions agree on the sign of change. Grey lines indicate tropical boundaries at 23.5°S and 23.5°N. Antarctica, Greenland and desert regions with annual P below 100 mm are masked in grey.

Extended Data Fig. 2 Temporal evolution of land area fraction with decrease in dry season water availability.

Δ(P – ET) is obtained as the difference between average P – ET from a 30-year period centered around the indicated year and average P – ET from the reference period 1902–1950. Lines indicate the DDM estimate, as well as the mean of individual LSM reconstructions and the mean of individual climate model simulations. The shaded area indicates the ensemble range of the 6 individual LSM reconstructions. The ensemble range of individual climate model simulations is not shown, but in the most recent period corresponds to 0.42–0.71 for models with full historical forcing (hist) and 0.46–0.54 for models with only natural historical forcing (histNat). Antarctica, Greenland and desert regions with annual P below 100 mm are omitted.

Extended Data Fig. 3 Sensitivity to the definition of the reference time period.

The reference period considered in Fig. 1 of the article is 1902–1950, whereas here we consider 4 alternative options: ( a , b ) 1902–1930, ( c , d ) 1911–1940, ( e , f ) 1921–1950 and ( g , h ) 1951–1980. Note that during the period 1951–1980 the influence of aerosol emissions was relatively high. Plots from the DDM reconstruction are shown on the left ( a , c , e , g ) and plots from the LSM reconstruction on the right ( b , d , f , h ). Grey lines indicate tropical boundaries at 23.5°S and 23.5°N. Antarctica, Greenland and desert regions with annual P below 100 mm are masked in grey.

Extended Data Fig. 4 Contribution of Δ(ΔTWS) to Δ(P – ET) from the DDM reconstruction (Fig. 1 a) and associated uncertainty.

a , Δ(ΔTWS) is the difference in average ΔTWS corresponding to the month with minimum P – ET between years in the periods 1985–2014 and 1902–1950. Note that based on the water balance Δ(P – ET) = Δ(ΔTWS) + ΔR. The ΔTWS reconstruction used in the article corresponds to the mean of 100 stochastic realizations, whereas no stochastic realizations of the R reconstruction are available. b , Fraction of stochastic realizations of Δ(ΔTWS) that result in positive Δ(P – ET) at each grid cell. Grey lines indicate tropical boundaries at 23.5°S and 23.5°N. Antarctica, Greenland and desert regions with annual P below 100 mm are masked in grey.

Extended Data Fig. 5 Agreement between reconstructions from six individual land surface models used for the mean LSM reconstruction (Fig. 1 b).

Fraction of reconstructions with positive Δ(P – ET) at each grid cell. Grey lines indicate tropical boundaries at 23.5°S and 23.5°N. Antarctica, Greenland and desert regions with annual P below 100 mm are masked in grey.

Extended Data Fig. 6 Sensitivity to the definition of dry season water availability.

Dry season water availability is represented by minimum monthly P – ET in Fig. 1 of the article, whereas here we use minimum 3-monthly P – ET. Grey lines indicate tropical boundaries at 23.5°S and 23.5°N. Antarctica, Greenland and desert regions with annual P below 100 mm are masked in grey.

Extended Data Fig. 7 Agreement in the sign of Δ(P– ET) between individual climate model simulations.

Fraction of individual climate model simulations with positive Δ(P – ET) at each grid cell for (a) simulations with full historical forcing and (b) simulations with only natural historical forcing. Grey lines indicate tropical boundaries at 23.5°S and 23.5°N. Antarctica, Greenland and desert regions with annual P below 100 mm are masked in grey.

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Padrón, R.S., Gudmundsson, L., Decharme, B. et al. Observed changes in dry-season water availability attributed to human-induced climate change. Nat. Geosci. 13 , 477–481 (2020). https://doi.org/10.1038/s41561-020-0594-1

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Received : 19 August 2019

Accepted : 18 May 2020

Published : 29 June 2020

Issue Date : July 2020

DOI : https://doi.org/10.1038/s41561-020-0594-1

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• Plants (Basel)

Drought Stress Impacts on Plants and Different Approaches to Alleviate Its Adverse Effects

Mahmoud f. seleiman.

1 Plant Production Department, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia; as.ude.usk@biahusn (N.A.-S.); as.ude.usk@aibiatolam (M.A.); as.ude.usk@yafer (Y.R.); as.ude.usk@601834 (H.H.A.-W.)

2 Department of Crop Sciences, Faculty of Agriculture, Menoufia University, Shibin El-Kom 32514, Egypt

Nasser Al-Suhaibani

3 Department of Agronomy, University of Agriculture Peshawar, Peshawar 25130, Pakistan; kp.ude.pua@bawan (N.A.); kp.ude.pua@lamka (M.A.)

4 Livestock research and development station, Surezai Peshawar, Peshawar 25000, Pakistan

Mohammad Akmal

Majed alotaibi, yahya refay, turgay dindaroglu.

5 Department of Forest Engineering, Faculty of Forestry, Kahramanmaras Sutcu Imam University, Kahramanmaras 46100, Turkey; rt.ude.usk@ulgoradnidyagrut

Hafiz Haleem Abdul-Wajid

Martin leonardo battaglia.

6 Department of Animal Sciences, Cornell University, Ithaca, NY 14850, USA

Drought stress, being the inevitable factor that exists in various environments without recognizing borders and no clear warning thereby hampering plant biomass production, quality, and energy. It is the key important environmental stress that occurs due to temperature dynamics, light intensity, and low rainfall. Despite this, its cumulative, not obvious impact and multidimensional nature severely affects the plant morphological, physiological, biochemical and molecular attributes with adverse impact on photosynthetic capacity. Coping with water scarcity, plants evolve various complex resistance and adaptation mechanisms including physiological and biochemical responses, which differ with species level. The sophisticated adaptation mechanisms and regularity network that improves the water stress tolerance and adaptation in plants are briefly discussed. Growth pattern and structural dynamics, reduction in transpiration loss through altering stomatal conductance and distribution, leaf rolling, root to shoot ratio dynamics, root length increment, accumulation of compatible solutes, enhancement in transpiration efficiency, osmotic and hormonal regulation, and delayed senescence are the strategies that are adopted by plants under water deficit. Approaches for drought stress alleviations are breeding strategies, molecular and genomics perspectives with special emphasis on the omics technology alteration i.e., metabolomics, proteomics, genomics, transcriptomics, glyomics and phenomics that improve the stress tolerance in plants. For drought stress induction, seed priming, growth hormones, osmoprotectants, silicon (Si), selenium (Se) and potassium application are worth using under drought stress conditions in plants. In addition, drought adaptation through microbes, hydrogel, nanoparticles applications and metabolic engineering techniques that regulate the antioxidant enzymes activity for adaptation to drought stress in plants, enhancing plant tolerance through maintenance in cell homeostasis and ameliorates the adverse effects of water stress are of great potential in agriculture.

1. Introduction

Plants are exposed to various environmental stresses during growth and development under natural and agricultural conditions. Among these, drought is one the most severe environmental stresses affecting plant productivity. About 80–95% of the fresh biomass of the plant body is comprised of water, which plays a vital role in various physiological processes including many aspects of plant growth, development, and metabolism [ 1 , 2 ]. As a result, some consider drought as the main environmental stress for different plants, particularly in drought prone areas [ 3 , 4 ], the single most critical threat to world food security in the future and the catalyst of important famines in the past [ 5 ]. The effects of drought in agriculture are aggravated due to the depletion of water resources and the increased food demand from an alarming world population growth [ 6 ]. The unpredictable nature of the drought is dependent upon various factors such as uneven and undependable distribution of rainfall, evapotranspiration, and water holding capacity around the rhizosphere [ 7 , 8 ]. Moreover, in some cases plants are unable to uptake water from the soil, even though enough moisture is present in the root zone [ 9 ], a phenomenon known as physiological drought or pseudo-drought [ 10 ].

Different molecular, biochemical, physiological, morphological and ecological traits and processes ( Figure 1 ) of the plants are impaired under drought stress conditions [ 11 ]. Plant yield and quality are adversely affected in water deficit environments [ 12 ]. Growth stages, age, plant species and drought severity and duration are the key factors that influence the plant responses to drought [ 13 ]. The resistance mechanism to drought, in turn, varies among plant species. Plants, therefore, have the ability to reduce their resource utilization and adjust their growth to cope against adverse environmental conditions like drought [ 14 , 15 ]. Various networks at the molecular level, such as those involved in signal transduction, are responsible for enhancing these responses against drought stress [ 16 , 17 ]. The stomatal regulation of plants through enhanced ion transport, transcription factor activities and abscisic acid (ABA) signaling are also involved in the molecular mechanisms of plant response to drought stress [ 18 , 19 ].

Morphological, physiological and biochemical dynamics of plants affected by water stress.

Under certain changing circumstances, there is a need to improve the drought tolerance of the plant. For enhancement of water-use efficiency, when physical adaptation of roots and leaves are not enough to cope with certain drought molecular signals including the gene coding regularity protein that expresses many other genes and signals through crosstalk according to different regulatory mechanisms [ 20 , 21 ]. To meet future food demand, fostering more work on drought-tolerant plants and the use of economical and beneficial agriculture practices will be of paramount importance [ 22 , 23 ].

2. Causes of Drought Stress in Plants

Global climate change is expected to accelerate in the future because of the continuous rising of air temperature and atmospheric CO 2 levels that ultimately alters the rainfall patterns and its distribution [ 24 , 25 ]. Although deficient water input from rainfall is usually the main driver for drought stress, the loss of water from soils through evaporation, which is driven by high temperature events, high light intensity and dry wind, can further aggravate an existing drought stress event [ 26 ]. Global climate change typically results in prevalent drought stress conditions over vast areas at a global scale. Alongside drought, salinity stress is also considered a primary cause of water deficit in plants [ 27 , 28 , 29 ]. Certain factors responsible for drought stress are briefly highlighted.

2.1. Global Warming

Some of the consequences derived from climate change could be beneficial for agricultural productivity. For example, higher rates of photosynthesis have been reported under elevated CO 2 , hence its presence in the atmosphere in elevated concentrations could enhance grain yields in the future [ 30 ]. However, in most cases, climate change has detrimental consequences both in natural and agricultural ecosystems. Increases in air temperatures can result in the melting of glaciers and potential flooding of agricultural lands with low or null slope [ 31 ]. Additionally, the loss of glaciers is causing the shrinkage of water reservoirs which limits the water availability to crops, a trend that is increasing with time. In fact, in various rain-fed agricultural areas around the world, the annual accumulated precipitation has decreased because of global warming [ 32 ]. Loss of water due to global warming is not only occurring in the soil, but also at the plant level. Internal water in plants up to great extent are lost to the atmosphere driven by the increased temperatures resulting from global warming, a phenomenon that further exacerbates the already existing water deficit problems in various agricultural systems around the world [ 33 ]. If expected increases in air temperature around 2 °C greater than present levels occur by the end of this century, approximately one fifth of the world population will be affected by severe water deficit [ 34 ].

2.2. Rainfall Anomalies

More stress is expected in areas where crop production is solely dependent on rainfall compared to areas that are being irrigated through canals, rivers and the water channel [ 35 ]. Thus, in rain-fed areas drought episodes are strongly correlated with the rainfall distribution across the year and high chances of water stress are observed in some years over a certain period of time [ 35 ]. Industrialization, deforestation and urbanization are the prominent anthropogenic activities that affect rainfall patterns, and thus water availability to plants, through its influence in climate change [ 36 ]. In Pakistan, erratic and more frequent rainfall occurs in early spring and winter, while more frequently drier and hotter seasons take place due to less and/or no rainfall in early fall and summer seasons. In summer in particular, the combination of greater atmospheric water demand for the plants, higher evaporation and transpiration rates, and less rainfall availability associated with this season amplifies the detrimental effects of drought stress in plant growth and development. However, rainfall distribution and intensity within and across the years play a prominent role in both the management of the water resources for plants and the occurrence of drought stresses in most cases [ 37 , 38 ].

2.3. Shifts in Monsoon Patterns

During the summer season, the monsoon system is considered as a source of rainfall in various areas of the world. Its occurrence is interlinked with temperature being the driving force [ 39 ]. It is expected that in rain-fed areas the amount of summer precipitations will decrease by 70% by the beginning of the XXII century if the prevailing situations continue [ 40 ]. According to estimations, high rainfall is expected due to linear increment in CO 2 concentration in atmosphere that will affect crop production adversely and will lead to massive floods and massive economic losses in the agriculture sector of densely populated countries [ 41 , 42 ]. Under such circumstances, monsoon rainfall variability is and will continue to affect the moisture level of the rhizosphere, thereby affecting plant productivity in particular areas of the world through dynamics in rainfall intensity, occurrence and duration. Remarkably, two thirds of the world population are currently facing food insecurity due to extreme variation between dry and wet seasonal rainfalls as a result of changes in the monsoon shifts [ 43 ]. Added to the intrinsically random and unpredicted nature of the rainfall patterns, and due to recent climate changes, shortening or extendibility of the rainy season may exacerbate present and future scenarios with both water deficit and/or water excess problems in some climatic zones [ 37 ]. Being agricultural, crop production practices need to be adopted accordingly during the monsoon behavior and shifted to sustainable crop production. Proper management and crop planning are two strategies to cope with quantitative shifts going from deficient to excessive and, vice versa, to monsoon patterns.

3. Effect of Drought Stress on Plants

Depending on the dynamics in the environmental conditions, plants could face various stresses that may severely affect their growth and development [ 44 , 45 ]. Certain metabolic changes and gene expressions occur to enable the plants to survive under these circumstances [ 27 , 46 ]. Grain quality and yield could be greatly affected by drought stress, known as the most limiting stress in agriculture. Thus, investigating the plants’ ability to cope with water limitation is of great value and should continue to receive attention in the near future, especially in arid and semi-arid environments [ 47 ]. Currently, major staple crops are being intensively studied to identify the drought-responsive mechanisms to harvest maximum grain yields and quality, but future work should focus on the combined effect of both heat and drought stress impacts at the reproductive stages of main grain crops [ 48 ].

The optimal level of water availability is necessary for plants growth and development, fluctuation in soil moisture beyond optimal can affect grain yield and quality. On the other hand, less than optimal water availability in the rhizosphere hampers the plant growth, thereby inhibiting the plant nutrient uptake [ 49 ]. The latter has recently been responsible of huge reductions in the production of grain crops, and is only expected to become more severe due to global warming and variability in climate [ 50 , 51 ].

Water scarcity outbreaks are due to the occurrence of less or the absence of rainfall resulting in low soil moisture content and low water potential in aerial parts of the plant such as leaves and stems [ 52 ]. When this occurs, the rate of loss of water through transpiration from leaves surpasses the water uptake rate through roots in dry environments [ 53 ]. The roots strive to uptake more water through their expansion and this ultimately adapts plants to minimize stomatal loss of water when there is a water deficit [ 54 ]. Typical drought stress symptoms in plants include leaf rolling, stunning plants, yellowing leaves, leaf scorching, permanent wilting [ 55 ]. Moreover, plant response to a given water deficit is strongly dependent on the previous occurrence and intensity of other drought stress events [ 28 , 56 , 57 ] and the presence of other stresses [ 58 ].

Despite the adverse effects that water deficit has on plant performance, plants have the ability to respond to varying degrees of water deficit ( Figure 2 ). There is a strong correlation between plant growth and water availability as cell enlargement is more affected by water deficits than cell division [ 59 ]. Under these conditions, the growth of the plants is inhibited as a result in the reduction of the cell wall extensibility and turgor [ 60 ]. When drought conditions are severe, respiration can also decrease, although increments in respiration were observed under mild stress [ 61 ]. To cope against the water deficit, the osmotic adjustment of stressed plants is maintained through an increase in sugar content of roots and leaves, and relatively greater growth in roots compared to shoots has been observed in plants subjected to drought stress in the past [ 62 ].

Adverse effects and adaptations of plants to drought stress, modified from Ullah et al. [ 63 ]—means reduce; + means increase.

Environmental factors including drought duration, intensity and frequency, soil characteristics, growth conditions and stages, and plant species strongly influence the extent and duration of drought-related symptoms in plants [ 64 ]. Increases in the rate of leaves senescence and drooping, scorching and limp leaves, leaf rolling and brittleness, closed flowers and flower sagging, etiolation, wilting, turgidity, premature fall, senescence and yellowing of leaves are among the most ubiquitous symptoms of drought stress in plants [ 65 , 66 ]. Although less usual, twig cracks, branch dieback, necrosis, stunted growth, bark crack, shrub canopy and tree thinning represent other symptoms displayed by plants under drought conditions [ 67 ]. In some cases, plants may die under extreme drought stress. Whereas water deficiency typically has a profound impact on plant growth and development, water excess also affects plant performance and hampers growth and final yield [ 68 ]. When this occurs, excess water stress symptoms are soft fleshy leaves, leaves with rotten patches, fungus affected and moldy plant parts.

4. Plant Responses to Drought Stress

Different adaptive mechanisms that make plants more tolerant to the adverse effects of drought stress have been developed through evolution [ 69 ]. Stress avoidance, escape and tolerance are the three main survival strategies that plants utilize when exposed to drought stress. Thus, plants responses to drought stress vary from the molecular up to plant level [ 70 ]. The mechanisms of plant escape, avoidance and tolerance ( Figure 3 ) against drought stress are discussed in the following sections.

Schematic diagram of drought resistance mechanism in plants. RWC = relative water contents; WUE = water-use efficiency.

4.1. Escape Mechanism

To escape the detrimental effects of drought stress on plant productivity, some plants utilize mechanisms involving rapid plant development and shortening of the life cycle, self-reproduction, and seasonal growth before the beginning of the driest part of the year [ 71 ]. Among these mechanisms, early flowering is perhaps the best possible escape adaptive mechanism in plants [ 72 ], although this mechanism can imply a considerable reduction in the length of the plant growing period and the final plant productivity in some cases [ 73 ].

4.2. Avoidance and Tolerance Mechanisms

Under the avoidance strategy, plant water potential is maintained high through a reduction in the stomatal transpiration losses and the increase of water uptake from well-established root systems [ 74 ]. In other cases, xeromorphic characteristics such as the presence of hairy leaves and cuticles may help to maintain high water potentials in plant tissues [ 75 ]. However, overdevelopment of these structures has a value for the plant in terms of reductions in plant productivity and reduced average size of vegetative and reproductive parts of the plant [ 76 ].

On the other hand, an adaptive tolerance mechanism at the photosynthetic machinery level includes reductions in the plant leaf area and limitations in the expansion of new leaves. Similarly, trichomes production on either side of the leaves are exomorphic attributes that allow the plant to tolerate water deficits in dry environments [ 77 ]. These structures reduce the leaf temperature by increasing the rate of light reflection in the leaf and also by adding another extra layer of resistance to the water loss. Hence the rate of water loss through leaf transpiration is reduced [ 78 ]. However, it is broadly accepted that changes in the root system, including root size, density, length, proliferation, expansion and growth rate, represent the main strategy for drought-tolerant plants to cope against water deficits [ 79 ]. Other mechanisms like osmotic adjustment, antioxidant defense mechanism, solute accumulation, metabolic and biochemical dynamics of stomatal closure and increment in root shoot ratio are other common strategies that allow plants to tolerate the adverse effect of drought stress [ 80 ].

5. Approaches to Alleviate the Adverse Effects of Drought Stress

Use of best management practices related to sowing time, plant population, plant genotype, and soil and nutrient management can help to reduce grain yield losses in field crops subjected to drought stress [ 81 , 82 ]. However, use of transgenic plants with drought-tolerant events is perhaps the drought stress mitigation approach most heavily publicized and the one receiving more attention at present. Several efforts like breeding, molecular and genomic approaches are being undertaken to develop drought-tolerant plants through usual conventional breeding methods [ 83 ], with the focus to improve water extraction efficiency, water use efficiency, stomatal conductance, and osmotic adjustments, among others [ 84 ]. Other strategies include use of modern and more effective methods of irrigation, good planting practices, mulching, contouring, osmoprotectants and plants inoculations with certain microorganisms that enhance drought tolerance [ 85 ].

5.1. Selection and Breeding Strategies

Conventional and traditional breeding methods used up to the present were based on the empirical selection of yield [ 86 ]. The low heritability, on the one hand, and high genotype and environment interaction on the other, are the main factors defining the quantitative yield trait in major staple crops [ 87 ]. Thus, conventional breeding is in practice for yield improvement [ 88 ]. Knowledge of plant physiological processes is the prerequisite for selecting quantitative trait loci, locating gene sequences and quantitative trait loci introgression [ 89 ]. Due to irregular, undependable and unpredictable response of the drought, screening resistant cultivars is not possible in open conditions, however, it is manageable in sheltered and/or controlled conditions [ 90 ]. Conversely, the expression of randomly selected progenies for improved drought stress tolerance in diverse environments is an effective approach known as classical breeding [ 91 ]. The cultivars with low transpiration rates and unchanged WUE under non-stress conditions have no effect on final harvest [ 92 ]. Scientists are working on the genetic analysis of the root architecture, relative water contents, and osmotic potentials [ 93 ]. Focus need to be given to the yield contributing traits which are highly heritable that affects the grain yield under drought conditions but not under optimal conditions based on their feasibility to measure [ 94 ]. Nevertheless, they exhibit broad sense heritability for yield in water-limited agriculture systems and have often no interaction with grain yield [ 95 ]. When plants are subjected to drought stress, the most important factor that appears first under such circumstances is hampering of WUE which differs for varieties and cultivars [ 96 ]. Under these circumstances, plants decrease the stomatal density and leaf size thereby minimizing water loss and maintains the internal water balance [ 97 ]. Hence certain genotypes and cultivars, which are drought susceptible and unable to adjust to environmental conditions, resulted in low WUE [ 98 ]. Therefore, through a breeding approach, WUE could be enhanced for sustainable crop product in biomass per unit of water utilized [ 99 ].

Drought resistance is induced directly or indirectly in the crop species through traits’ genetic variability and thus has the improvement capability through selection in breeding. Marker assisted selection (MAS) and genomic selection (GS) are the two main approaches of genomic assisted breeding. For the prior approach, an initial step is to identify the molecular markers associated with the trait of interest, the prerequisite for selection in breeding programs. However, GS depends on progress of selection models based on genetic markers present on the whole genome and selection of genome estimated breeding values (GEBVs) in breeding populations through phenotyping training population. The MAS is a key part for many crops breeding programs over a few decades, GS being relatively new because it has only recently been applied to crops.

Molecular markers are involved in MAS that map close to quantitative trait loci (QTL) or specific genes that are linked with the particular target trait and could be used identify the individual with desirable alleles [ 100 ]. The QTL mapping or genome-wide association approaches are used to select marker trait association through accurate, reliable trait evaluation and dense molecular markers. Through these methods, QTLs for the traits linked with drought resistance are identified in various crops i.e., wheat [ 101 ], maize [ 102 ], sorghum [ 103 ], rice [ 104 ], soybean [ 105 ], pearl millet [ 106 ] and many other crops.

The genomic selection uses all the markers available for a population of GEBVs and GS models are used for selection of elite lines without phenotyping [ 100 ]. Contrary to MAS, the knowledge of QTLs is not the prerequisite for GS [ 107 ]. However, GS needs higher density marker data than MAS. This is possible through availability of low cost and genome wide marker coverage genotyping approaches [ 108 ]. GS is being applied for drought resistance induction breeding in maize by the international maize and wheat improvement center (CIMMYT) [ 109 ]. Research efforts through this approach are on course in other crops i.e., sugarcane, legumes and wheat [ 110 , 111 , 112 ].

5.2. Molecular and Genomic Perspective

Biochemical and molecular factors involved in the induction of processes to ameliorate the negative impacts of water stress include transcription, stress responsive genes ( Table 1 ) and abscisic acid [ 113 ]. Concurrently to the increased tolerance to drought deficits, breeding programs are also interested to kept other stresses under control through transgenic expression of different stress responsive genes [ 114 , 115 ]. However, the increased expression of these genes is frequently associated with a deceleration in the plant growth rate, this could narrow down its practical use. Thus, the molecular and genetic bases for drought resistance still needs attention to successfully contend with these circumstances [ 116 ]. In this sense, genomic and related technological tools could highlight the genes that mitigate the stress effect so that efforts are conducive to maintain those genes in successive breeding programs [ 117 ]. The molecular level of stress-tolerant genes is in cross talk quantitative loci traits showing their interaction and cloning of the genes that are related to stress [ 118 ]. In general, it is accepted that a combination of selection through marker assessment, molecular and traditional breeding as an integrated approach is the best alternative for the improvement of the abiotic stress tolerance in plants genetic engineering [ 119 , 120 ].

Genes responsible for drought tolerance in plants.

6. Drought-Resistance Induction

Plants adopt various approaches and strategies to alleviate the adverse effects of drought stress. Agriculturists are also using various strategies for drought stress tolerance, among which the application of exogenous regulators, chemicals, synthetic hormones and compounds are of great value to increase drought resistance at different plant growth stages.

6.1. Seed Priming

Seed priming has been referred to as the most important short-term approach to alleviate the adverse effect of drought on plants [ 126 ] ( Table 2 ). The objective of this pre-sowing technique is to initiate the germination process in the metabolic machinery of the seed and prepare the seed for radicle protrusion without radicle emergence taking place during the process [ 127 ]. The germination process of prime seeds is more efficient, which results in higher germination rates and uniformity compared to non-primed seeds [ 128 ]. In crops like wheat, maize and chickpea seed priming is used to alleviate the adverse effect of drought stress [ 126 , 127 , 128 ]. Recently, the directly seeded rice (DSR) method used in rice grown in aerobic conditions resulted in an increment in the drought severity and frequency [ 129 ]. Under water scarce conditions, different osmotica were used for DSR with the result that CaHPO4 and KCL osmopriming enhanced crop yield and productivity. Better germination and stands were observed in primed seeds in water scant areas [ 128 , 130 ]. Optimal stand, better yield, ability to withstand drought, early and synchronized germination followed by emergence are linked with seed priming. It is reported that primed seed enhanced WUE by 44% in wheat crop than non-primed seeds under water stress conditions. High grain yield with early emergence and flowering resulted in primed seeds in water limited environments. Similarly, osmopriming with KNO3 and hydropriming enhanced yield of certain crops in water scarcity [ 131 ].

Tolerance mechanisms in different field crops through seed-priming treatments.

RWC: Relative water contents, LPO: Lipid peroxidation, LA: Leaf area, SNP: sodium nitroprusside.

6.2. Plant Growth Regulators

Application of natural and synthetic plant growth regulators ( Table 3 ) can improve drought tolerance in plants [ 142 ]. The reduction in the length and weight of the hypocotyl in seedlings due to water stress can be mitigated with the application of gibberellic acid (GA), which helps to maintain the internal water balance and the protein synthesis in drought stressed plants [ 143 ]. The stomatal conductance, as well as the photosynthesis and the respiration rates in wheat and cotton and maize were increased in water-scant areas following application of GA, and this resulted in higher grain yields compared to treatments where GA was not applied [ 143 , 144 ]. Exogenous application of abscisic acid, uniconazole, brassinolide and jasmonic acid can also improve crop productivity under drought [ 145 , 146 ]. Another active cytokinin, benzyladenine, is a hormone that regulates the drought resistance mechanism in various plants, including maize, wheat, cotton, chickpea barley and rice soluble sugar, soluble protein content, and the activities of superoxide dismutase, peroxidase, and catalase in the leaves were increased by uniconazole and brassinoloide in drought stress conditions [ 147 ].

Tolerance mechanisms to drought enhancement through phytohormones in different field crops.

Abbreviations: WUE: Water use efficiency, APX: Ascorbate peroxidase, CAT: Catalase, SOD; Superoxidase dismutase, ROS: Reactive oxygen species.

Salicylic acid, an exogenously applied substance also improves drought tolerance and enhances growth and final harvest of the plants under water scarcity [ 148 ]. An enhancement in the catalase activity of wheat was observed through salicylic acid application under water-scarce conditions [ 149 ]. Use of salicylic acid and its derivatives in foliar and seed treatment applications increased the drought tolerance mechanism in wheat crop subjected to drought stress. Research shows that application of salicylic acid in wheat indirectly increased the accumulation of proline through an increment in the abscisic acid content [ 148 , 149 ]. In maize ( Zea mays L.), polyamines contents are increased under drought stress conditions. Phytohormones such as ethylene and brassinolide (BR) are also of great importance to cope with various environmental stresses, especially drought stress. It enhances plant tolerance to biotic and abiotic stresses, through a complex pathway to regulate the plant defense system, by activating BZR1/BES1 transcription factors. It also regulates reactive oxygen species (ROS) production in plants under stress, and unbalancing of ROS scavenging leads to oxidative bursts, which have adverse effects on plants [ 150 , 151 ].

6.3. Osmoprotectants

The multiple range of plant stresses that reduce plant growth and productivity are regulated ( Table 4 ) by osmoprotectants signaling. These substances accumulate during the time when growing conditions are not suitable for plant growth and development, and are responsible for maintaining the internal physiological processes that ensure plant survival under optimal conditions such as water scarcity [ 161 , 162 ]. Among others, important osmoprotectants in plants subjected to water stress include proline, trehalose, mannitol, fruton, and glycinebetaine [ 163 ]. These compounds, typically used for seed treatment or exogenously applied at different growth stages of established crops, protect the subcellular structure, increase the activity of antioxidant enzymes and mediate the osmotic adjustment in water-stressed plants [ 164 , 165 ]. Foliar application of proline also enhances the internal free proline in plants thereby increasing their drought tolerance [ 166 ]. Finally, use of polyamines like spermidine have also demonstrated to be efficient to increase plant tolerance to water stress in crops like barley ( Hordeum vulgare L.) and wheat [ 167 ].

Osmoprotectants significance in drought tolerance mechanisms different plants species.

ROS: Reactive oxygen species.

6.4. Silicon, An Abundant Element on Earth

The most abundant element on the earth surface, silicon, could be used as a mineral nutrient to increase plant resistance ( Table 5 ) to various levels and degrees of stresses [ 173 ] and the overall mechanical strength of both stressed and non-stressed plants [ 174 ]. Moreover, exogenous application of silicon has demonstrated the capacity to increase the relative water contents in sorghum and sunflower [ 173 , 174 ]. Additionally, and compared to the unfertilized control, wheat plants applied with silicon not only maintained higher relative water contents but also increased the shoot dry matter when exposed to water stress conditions. Thus, silicon application decreased the shoot to root ratio through root growth facilitation. Furthermore, silicon application to wheat increased the photosynthesis rate, stomatal conductance and the antioxidant defense compared to plants with no silicon application [ 175 ]. Thus, silicon application in crops exposed to drought conditions can play an important role in maintaining the growth of roots and transport of water under drought stress [ 173 , 176 ].

Silicon activates the antioxidants activity and improves drought tolerance mechanisms plants.

Abbreviations: CAT: Catalase, SOD; Superoxidase dismutase, GR: Glutathione reductase, POD: Peroxidase, APX: Ascorbate peroxidase, MDA: Malondialdehyde.

6.5. Selenium As An Antioxidative Protectant

The plants exposed to water stress deficit produce ROS that can cause and oxidative damage to the biomolecules such as carbohydrates, proteins, lipids and nucleic acids; and therefore, reducing the photosynthesis, respiration and growth of plants [ 182 ]. Selenium (Se) application can result in compatible solutes in the plants grown under water deficit; and thereby reducing the oxidative stress in plants. The cellular dehydration of the plants is reduced through the accumulation of these osmolytes [ 183 ]. Senescence is stimulated in the plants as a result of an oxidative stress protection that produces the ROS enzymes under Se application to the plants [ 184 , 185 ]. Protective enzymatic activities are also activated through Se application in plants [ 186 ]. The application of Se enhances the production and synthesis of proline and peroxidase through antioxidant effect. Its application in plants can decrease the membrane degradability and enhance ROS enzymes activity [ 184 , 185 , 187 ]. Moreover, Se application can enhance plant growth, reduce oxidative stress damage, increases oxidative stress under light stress, antioxidants production due to senescence and regulating water balance of the plants to tolerate drought stress [ 188 ].

6.6. Potassium: A Vital Regulator

Potassium (K) application under drought stress condition ameliorates the adverse effect ( Table 6 ) of the water deficit and maintains the plant productivity. Under drought stress condition, the plants uptake more potassium for their internal regulatory mechanism [ 189 ]. The increase of K by plants cause an oxidative damage, and therefore can form ROS during the photosynthesis process [ 190 ]. Thus, the reason of the high K demand by plants grown under stress is to maintain the CO 2 fixation during photosynthesis process. Under plant stress, the increment of ROS in plants can be due to CO 2 reduction [ 191 ]. The photosynthesis process was impaired, and carbohydrate metabolism was also affected through ROS production when plants were grown under water deficit conditions [ 192 ]. The low photosynthesis rate was observed in plants grown under drought stress with the lower dose of K application than higher dose of K [ 193 ]. Therefore, adequate K is needed for plants to maintain their physiological processes. It is also observed that the low grain yield of crops grown under water deficit condition could be enhanced through K application. The application of K as soil amendment or as foliar application is beneficial for the optimal physiological processes of plants [ 194 , 195 ]. Consequently, K application is of great importance for getting optimal yield production of crops grown under rained and/or water deficit environments [ 196 ].

Potassium application mitigates the adverse effects in plants subjected to water deficit stress.

6.7. Plant Microbes Crosstalk

The microorganisms also play a vital role in reducing the adverse effects of drought stress ( Table 7 ) and thereby improving plant productivity [ 202 ]. The oxidative damage in the plants grown under different environmental stresses can be reduced through the microorganisms ( Figure 4 ) and enabling the cereals to cope with drought conditions. Among them, plant growth-promoting rhizobacteria (PGPR) is responsible for drought stress effect mitigation in dry environments [ 203 ]. The PGPR inoculation into the plants can increase the drought tolerance of those crops [ 204 ], because these PGPR make colonies in the root-zones and enhance the plant growth under different circumstances [ 205 ]. They also can solubilize various micronutrients to make them available for the plant uptake [ 202 , 206 ]. PGPR also enhances the plant resistance to different abiotic stresses [ 207 ]. The Bacillus species assembles solutes that enable maize plants to cope with drought and prevent degeneration [ 208 ]. In rice plants, the biotic and abiotic stresses were mitigated through phyllosphere bacteria inoculation [ 209 ]. The inoculation of Bacillus amyloliquefaciens , Azospirillum brasilense , Rhizobium leguminosarum , Mesorhizobium cicero bacterials strains improved homeostasis in plants and increased growth, biomass and drought tolerance index [ 210 ]. Similarly, Trichoderma sp. was reported to be a beneficial for drought stress [ 211 ], particularly Trichoderma harizianum was noted to be a beneficial application for rice drought tolerance [ 212 ].

Schematic representation of the interaction among microbes, soil and plant, modified from Andreote et al. [ 213 ].

Effect of microbes on plant adaptive mechanism for mitigation of drought stress.

6.8. Hydrogel: A Water Absorbing Polymer

Hydrogel is a polymer, and its application to the soil in agriculture systems can reduce the need for frequent irrigation [ 228 ]. Plants can survive and sustain their life cycle through hydrogel conditioning in arid and semi-arid environments, where the shortage of water is a serious issue [ 229 ]. The water limitation is not covered with the rainfall occurrence, and hence there is a demand to protect the available soil moisture from damage and loss to overcome soil degradation [ 230 ]. Due to hydrogel soil amendment, soil physical, chemical and biological traits are enhanced with positive effects on the plant growth and development [ 231 ]. Through its application to soil, it increases the plant survival time under drought stress, which was decreased due to the loss of the water and the hydraulic conductance in soil [ 232 ]. The survival time of the plants was increased with the hydrogel application since it resulted in sufficient soil moisture. Therefore, its application into the soil, particularly in arid and semi-arid environments and drought-affected areas, is beneficial for water saving in rhizosphere [ 233 ]. Apart from this, the hydraulic conductivity of the polymer amended soil is less than the plain soil. Similarly, water loss through evaporation in polymer-amended soil was lower than the soil with no hydrogel amendment [ 234 ].

6.9. Nanoparticles; Coping Drought Stress

Nanoparticles (NPs) are characterized by its particle shape, tunable pore size, potential reactivity and high surface area [ 235 ]. In plants, the cellular organelles are targeted, and certain contents are released through the nanoparticle target [ 235 , 236 ]. The activity of antioxidants enzymes i.e., SOD, CAT and POD were regulated and enhanced ( Table 8 ) by the application of nanoparticles [ 237 ]. For example, the activity of SOD in plants was increased by the application of TIO2 NPs [ 238 ]. In agriculture, different trace elements and their oxides of NPs were used for enhancing drought stress resistance in different plants ( Table 8 ). The negative effects of abiotic stress such as drought, chilling stress, salinity and heavy metal toxicity were mitigated through silicon nanoparticles (Si-NPs) application [ 235 , 239 ]. Growth and physio- and biochemical traits such as proline, chlorophyll, carbohydrates, carotenoids and relative water contents were significantly improved in different plant species when NPs were applied such as silica and ZnO nanoparticles [ 235 ]. Si-NPs also enhanced the drought resistance in wheat plants [ 240 , 241 ]. Similarly, the salinity and drought stress in plants were also mitigated by ZnO nanoparticles application (235). During the early stage of growth, the application of ZnO NPs stimulated the seed reservoirs for sapling and enhanced the drought resistance in plants [ 242 ]. Ferrous in combination with Zn were also reported to have a beneficial effect on plant resistance to drought stress. Plants grown under drought stress were mitigated through TIO 2 nanoparticles, consequently activated different compounds and ameliorated the adverse effects of water deficit [ 243 , 244 ]. To improve drought stress in plants, other NPs such as silver (Ag) and copper (Cu) were used in lentil for mitigated drought stress negative effects. Nano-silica could also enhance the drought tolerance in different plants [ 235 ]. The increase of SOD and POD activity in wheat crop as drought resistance mechanism was observed through ZnO NPs. The drought resistance in wheat was also enhanced under Zn and Cu NPs [ 241 , 245 ].

Drought stress tolerance enhancement in plants through Nanoparticles application.

6.10. Metabolic Engineering and Stress Tolerance Strategy

One of the most optimal solutions for coping drought stress is the drought tolerant crops development [ 252 ]. Thus, a great challenge is to enhance the drought tolerance without a significant effect on grain yield. The drought tolerance induction in plants through metabolic engineering, thereby enhancing stress related metabolites, is considered as an optimal strategy [ 253 ]. In arid and semi-arid regions, the successful breeding for drought tolerance through raffinose biosynthesis engineering pathway is one of the classic strategies. The accumulation of raffinose and galactinol in plants grown under water deficit is stimulated through galactinol synthase (AtGolS) gene with specific gene AtGolS2 that is stimulated under drought stress in particular [ 254 ]. The expression of this gene in plants enhances the raffinose and galactinol level, thereby enhancing drought tolerance in plants as well as protecting them from an oxidative stress. Both the raffinose and galactinol exhibits the potential to protect cell under environmental stresses through ROS scavenger and compatible solutes [ 254 ]. In this respect, the increment in raffinose and galactinol levels under metabolome analysis of rice and soybean indicated their response to drought stress. Crop plant transformation through AtGolS2 application activates the plants’ resistance to stress under dry environments. Different studies suggest that the application of AtGolS2 in transgenic plants not only increase drought tolerance but improves also grain yield [ 255 ]. Thus, AtGolS2 metabolic engineering is considered a useful approach and a significant tool to increase grain yield under water deficit conditions [ 256 ].

7. Conclusions

Under recent climatic changes, both the biotic and abiotic stresses are a serious threat for global food security and plant production sustainability. Among the abiotic stresses, drought stress is gaining attention due to its adverse effect on plant growth and development and significant reduction in plant yield and biomass causing global food insecurity. Drought stress affects plants through the life cycle i.e., from germination till maturity. Certain physiological, metabolic and biochemical processes are affected by drought stress that hampers plant productivity. To tackle the adverse effect of the drought stress on plants, certain mechanisms are adopted by the plants which enhance drought tolerance. Thus, there is need to explore the untapped adaptation characters in different plants and their incorporation to the genotypes that may tolerate the adverse effect of drought stress in order not to affect its productivity. Breeding technologies has greater potential for increasing plant performance and production under water deficit. Certain approaches are receiving greater attention for coping drought in arid and semi-arid environments.

Growth pattern and structural dynamics, reduction in transpiration loss through stomatal conductance altering and distribution, leaf rolling, root to shoot ratio dynamics, root length increment, accumulation of compatible solutes, enhancement in transpiration efficiency, osmotic and hormonal regulation and delayed senescence are the strategies that can be adopted by plants grown under water deficit.

To improve drought stress tolerance in plants, certain breeding strategies, molecular and genomics perspectives with special emphasis on the omics technology alteration i.e., metabolomics, proteomics, genomics, transcriptomics, glyomics and phenomics approaches are of great value. Other practices that include seed priming, growth hormones, osmoprotectants, silicon (Si), selenium (Se) and potassium application are worth using in scant water conditions in plants. Despites this, the beneficial effect of microbes, hydrogel, nanoparticles applications and metabolic engineering techniques also regulates the antioxidant enzymes activity for adaptation to drought stress in plants, enhancing plant tolerance through maintenance in cell homeostasis and ameliorates the adverse effects of water stress in plants. These innovative strategies provide better understanding of and potentially increase plant productivity in dry environments in order to reduce the threat to global food security.

Acknowledgments

The Deanship of Scientific Research at King Saud University through the research group number RG-1441-323 is acknowledged.

Author Contributions

Conceptualization: M.F.S. and M.A. (Mohammad Akmal) Data curation: M.F.S., N.A., M.A. (Mohammad Akmal), N.A-S., M.A. (Majed Alotaibi), Y.R., T.D. and M.L.B. Investigation: M.F.S., N.A., M.A. (Mohammad Akmal), N.A-S., M.A. (Majed Alotaibi), Y.R., T.D., H.H.A-W. and M.L.B. Resources: M.F.S., N.A., M.A. (Mohammad Akmal), N.A-S., M.A. (Majed Alotaibi), Y.R. and M.L.B. Software: M.F.S., N.A., M.A. (Majed Alotaibi). and M.L.B. Writing—original draft: M.F.S. and N.A. Writing—review and editing: M.F.S., N.A-S., N.A., M.A. (Mohammad Akmal), M.A. (Majed Alotaibi), Y.R., T.D. and M.L.B. All authors have read and agreed to the published version of the manuscript.

The Deanship of Scientific Research at King Saud University through the research group number RG-1441-323 funded this work.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Palmer Index/Palmer Drought Severity Index

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• John E. Oliver  

Part of the book series: Encyclopedia of Earth Sciences Series ((EESS))

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In 1965 Wayne C. Palmer, a scientist in the Office of Climatology, Weather Bureau, US Department of Commerce, Washington, DC, published a research paper entitled “Meteorological drought”. Applications of the analytic procedures set forth in this paper have become widely known as the Palmer Index or the Palmer Drought Severity Index (PDSI). It is a hydrologic or persistent climatological drought index, since it attempts to quantify the scope, severity, and frequency of prolonged periods of abnormally dry weather. It works reasonably well for this purpose.

The Palmer indexing procedure was developed to help fulfill the need to define and quantify droughts. This need is very real to agencies at all levels of government since drought means various things to people, depending on their specific problems related to it. To a farmer drought means a shortage of soil moisture in the rooting zone of crops. To the hydrologist or urban water system engineer it means low levels in groundwater,...

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Bibliography

National Oceanic and Atmospheric Administration, National Climatic Data Center, 1985. Atlas of Monthly Palmer Moisture Anomaly Indices (1895–1930) for the Contiguous United States . Historical Climatic Series 3–8. Asheville, NC: NOAA, National Climatic Data Center.

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National Oceanic and Atmospheric Administration, National Climatic Data Center, 1985. Atlas of Monthly Palmer Moisture Anomaly Indices 1931–1984 for the Contiguous United States . Historical Climatic Series 3–9. Asheville, NC: NOAA, National Climatic Data Center.

Palmer, W.C., 1965. Meteorological Drought . Weather Bureau Research Paper No. 45. Washington, DC: US Department of Commerce.

Palmer, W.C., 1968. Crop moisture index. Weekly Weather and Crop Bulletin , 55 (20): 8–9.

Strommen, N.S., 1981. The Palmer drought index — a management tool. Weekly Weather and Crop Bulletin , 68 (6): 10.

US Department of Agriculture, 1976. Droughts that made U.S. history. Weekly Weather and Crop Bulletin , 62 (27): 15–17.

Cross-references

Arid Climates

Aridity Indexes

Evaporation

Evapotranspiration

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Newman, J.E., Oliver, J.E. (2005). Palmer Index/Palmer Drought Severity Index. In: Oliver, J.E. (eds) Encyclopedia of World Climatology. Encyclopedia of Earth Sciences Series. Springer, Dordrecht . https://doi.org/10.1007/1-4020-3266-8_159

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Original research article, agricultural drought and its potential impacts: enabling decision-support for food security in vulnerable regions.

• 1 Centre for Environmental Management, University of the Free State, Bloemfontein, South Africa
• 2 Department of Geography and Environmental Science, University of Fort Hare, Alice, South Africa

Increasing demand for food and environmental stressors are some of the most challenging problems that human societies face today and these have encouraged new studies to examine drought impacts on food production. Seeking to discuss these important issues in the South African context, this study analyzed the impacts of drought on food security in one of the country's largest commercial agricultural land (Free State Province). Earth observation and crop data were acquired from Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) and GrainSA databases, respectively for years 2011/2012–2020/2021 over Free State Province. Two crops namely, maize and sorghum were obtained from the database and analyzed accordingly to quantify drought impacts on the two crops. The result reveals that the years 2015 and 2018 were affected by extreme drought events (<10%) where the majority of the study area was impacted. Years 2011, 2016, 2018, and 2019 were severely affected by drought (>30%) and impacted the agricultural sector in the study area. Findings further revealed that maize production observed the lowest recorded in the year 2014 and 2015 with about 223,600 and 119,050 tons, respectively. More so, results further showed that sorghum production recorded the lowest production in years 2019, 2016, and 2015 with about 23,600, 24,640, and 24,150 tons, in that order during the period of study. The results confirm the impacts of drought on maize and sorghum productions in the year 2015 and other years that recorded the lowest productions during drought years. This development might have impacted food security in the study area, and this outcome will enable decision-making bodies on food security to enhance improved strategy in vulnerable areas.

Introduction

Drought's key characteristics, such as their inherently wide spatial and temporal extent, the large number of people impacted, or the massive economic loss, have caused logistic and financial challenges all over the world ( Berhan et al., 2013 ; Enenkel et al., 2015 ). Droughts and associated food shortages are high on humanitarian relief groups' priority lists, and the bulk of online disaster platforms focus on disaster that strikes quickly (for instance, floods, hurricanes, earthquakes, or other storms) and little to no attention focus on drought and its occurrences. The difficulty of operational drought forecasting systems to produce valid predictions about the location, magnitude, and type of assistance needed in the medium to long term, i.e., several months ahead of time, is a serious flaw ( Khadr, 2016 ; Hao et al., 2018 ; Kreibich et al., 2019 ). Even in cases where predictions were made, such as warnings of severe drought conditions in Sub-Saharan Africa ( Ahmed, 2020 ; Fava and Vrieling, 2021 ), there is still a lack of response on the ground ( Enenkel et al., 2015 ). Furthermore, large-scale drought predictions have failed in industrialized countries such as the United States ( Schiermeier, 2013 ; Anderson et al., 2018 ; Daigh et al., 2018 ). This is exacerbated by the fact that there is no universally agreed definition of drought ( Enenkel et al., 2015 ), and climate change impacts on global drought patterns ( Enenkel et al., 2015 ; Salami et al., 2021 ), as well as global food security ( Dhankher and Foyer, 2018 ; Purakayastha et al., 2019 ). Simultaneously, teleconnections must be considered, such as the impact of anomalies in sea surface temperatures on drought episodes in Sub-Saharan Africa, which have influenced the complexity of already sophisticated models and evaluations. Furthermore, because different types of drought, such as meteorological, agricultural, and hydrological, have varied socio-economic consequences, a single physically measurable drought parameter for all of these scenarios is not attainable ( Orimoloye et al., 2019 ; Ekundayo et al., 2020 , 2021 ).

In recent decades, significant progress has been made in sustaining global food production. Nonetheless, feeding 9.8 billion people by 2050 would be a challenge, particularly in drought-prone and arid regions of the developing world ( He et al., 2019 ). Droughts, for example, are a regular occurrence in Sub-Saharan Africa, particularly South Africa ( Orimoloye et al., 2021a , b ), and can be exacerbated by other variables (such as heat waves, floods, and violence; Ropo et al., 2017 ). Food production shocks (i.e., unexpected losses and increases in price) have been more common in all sectors including food industries during the last five decades ( Cottrell et al., 2019 ; He et al., 2019 ). Extreme weather causes half of these shocks ( Cottrell et al., 2019 ), with disproportionate effects on countries with little coping capability, such as farmers' ability to diversify food production or governments' ability to import food or provide insurance. The 2017 Kenya drought, for example, prompted a national emergency and left about 2.5 million people hungry ( Gichure, 2017 ; He et al., 2019 ). The impact of increased drought risk due to climate change ( Naumann et al., 2018 ; He et al., 2019 ) can be mitigated through more effective adaptation methods, measures and innovative research, which will aid progress toward achieving the second United Nations Sustainable Development Goal (SDG; i.e., zero hunger). If multiple interrelated SDG goals are to be achieved at the same time (e.g., SDG2 to ensure food security, SDG6 to ensure water security, and SDG13 to foster resilience), synchronous challenges emerge, as they interact across a range of spatial and temporal scales, resulting in diverse trade-offs, synergies, and even competing policy responses with scale-dependent impacts ( Obersteiner et al., 2016 ; Gao and Bryan, 2017 ). Understanding the interactions between drought and food security is critical for policymakers and stakeholders to develop adaptation policies that effectively reduce the effects of drought on agricultural production and increase societal resilience to future drought-induced emergencies, all while meeting competing demands and enhancing environmental sustainability.

Recently, South Africa observed drought events that affected various sectors including agriculture and water resources. The National Disaster Management Center has declared a drought disaster due to the persistent drought conditions in the South African provinces including Free State Province and national resources are being mobilized to assist affected individuals including farmers ( Tembile, 2021 ). South Africa is facing severe pressure with respect to water security due to an increased water demand with increasing population, poor planning and management of water resources, limited investment into water reservoir infrastructure, and recurring droughts over the past decade. Droughts are common in South Africa, however, in recent years there has been a trend toward more multi-year droughts. Summer rainfall time series for several portions of South Africa, particularly the Eastern Cape and neighboring KwaZulu Natal Province, show greater multi-year droughts from the late 1970's to the late 1970's than from 1950 to the late 1970's ( Blamey et al., 2018 ). After a prolonged drought from 2015 to 2018, the Western Cape Province was named a disaster region in February 2018 ( Pienaar and Boonzaaier, 2018 ; Orimoloye et al., 2019 ; Mahlalela et al., 2020 ). Drought disaster zones were proclaimed in the Eastern Cape and Free State provinces in 2019, following severe water shortages in several urban and rural areas ( Mahlalela et al., 2020 ; Orimoloye et al., 2021a ).

Assessing agricultural drought and its potential impacts on food security in vulnerable regions is very crucial especially in drought-prone areas. The implications of agricultural droughts on food supplies may be quantified, which helps policymakers make more sustainable agricultural decisions. It necessitates a thorough evaluation of the relationships between spatiotemporal drought fluctuations, farming systems, irrigation effects, and water resource availability. Various techniques of dealing with such issues have been reported. Survey methodology, for example, is useful for gathering first-hand information on how the drought has affected crop production and how farmers have reacted to drought ( Campbell et al., 2011 ; Savari et al., 2021 ). In this paper, I, therefore, concentrate on agricultural drought impacts on food production in Free State Province South Africa. Findings from this study will enable decision support for food security in the affected areas. Despite the challenges associated with climate hazards such as drought disasters, recent technological, and methodological developments are helping to rapidly improve agricultural outputs ( Balogun et al., 2020 ; Dyosi et al., 2021 ). The emergence of space-based information is providing valuable outcomes at the high spatial and temporal resolutions with accurate maps, this can help smallholder-dominated farmers to plan for future drought events. Findings from this study can help in building greater resilience to drought and mitigate its scourges on agricultural sectors, societies, and economies.

Data and Methods

As presented in Figure 1 , the study took place in the Free State Province of South Africa. The Republic of South Africa is divided into nine provinces, one of which is the Free State. Bloemfontein is South Africa's judicial capital and the province's largest city. In the study area, there are a few additional notable towns, predominantly mining, and agricultural communities. The province is located between 26.6 ° S and 30.7 ° S latitudes, and 24.3 ° E and 29.8 ° E Greenwich meridian lengths. The climate of the province is mostly semi-arid, according to the Köppen climatic classification. The geography of the province is complex, with all surfaces above 1,000 m reaching 1,800 m in the north-eastern and eastern Free State. The province is divided into five municipal districts for administrative purposes (Fezile Dabi, Lejweleputswa, Motheo, Thabo Mofutsanyane and Xhariep). However, in November, December, and January, the region enjoys monthly mean sunlight hours of around 319.5, 296.5, and 296.3 h, respectively, with annual sunshine hours and total precipitation of ~3,312.3 and 559 mm, respectively. The region receives the least amount of rain (0 mm) in July and the most amount of rain (70 mm) in January, which correspond to the winter and summer seasons, respectively ( Orimoloye et al., 2021b ). In June, daily mean temperatures vary from 17 to 29°C. In January, daily mean temperatures range from 17 to 29°C. During the months of June and July, the coldest temperatures occur at night. The vegetation dominant in the area is grassland. A better understanding of the spatiotemporal evaluation of drought events will help to identify drought-affected areas and its potential impacts on food security in the Free State Province.

Figure 1 . Map of the study area.

The Terra product from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to determine the occurrence of drought in the study area. Temperature and precipitation were acquired from NASA's Prediction of Worldwide Energy Resource database; MODIS was downloaded via the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS; Abdi et al., 2019 ; AppEEARS Team., 2020 ). The MODIS instrument is used by both the Terra and Aqua missions. It has a 2,330 km viewing swath and views the whole Earth's surface every 1–2 days. Its detectors collect data with three spatial resolutions of 250, 500, and 1,000 m and measure 36 spectral bands between 0.405 and 14.385 m. MODIS data, along with data from other sensors aboard the Terra and Aqua satellites, is relayed to ground stations via the Tracking and Data Relay Satellite System (TDRSS). The data will subsequently be forwarded to the EOS (Earth Observing System) Data and Operations System at Goddard Space Flight Center (EDOS; AppEEARS Team., 2020 ; Hu, 2020 ). The MODIS Adaptive Processing System (MODAPS) produces level 1A, level 1B, geolocation, and cloud mask products, as well as high-level MODIS land surface and atmosphere products, which are divided into three DAACs (Distributed Active Archive Centers) for distribution to the research and application community ( Sundaresan et al., 2014 ). The MODIS direct broadcast signal can be used to gather regional data directly from the satellite by users with a compatible x-band receiving device. The data (MOD13Q1 and the layers of interest: EVI and pixel reliability) was requested using an area sample, and the output was configured as GeoTIFF with geographic projection ( Kring, 2007 ; Sundaresan et al., 2014 ). The VIs were created at 16-day intervals, with low-quality data removed using a MODIS-specific compositing process based on product QA. The Pixel Reliability Quality Assurance (QA) layer of MOD13Q1 was used to mask or correct pixels affected by atmospheric disturbances such as clouds. The layer classifies the efficiency of the vegetation index from−1 to 5, although for this analysis, good, and poor values are classed as 0 and 1, respectively. In the pixel reliability bands, poor and marginal data are accepted as acceptable accuracy and were considered for the investigation. Agricultural information was acquired from GrainSA database.

The drought conditions in the region were determined using the Vegetation Condition Index (VCI) based on the relative Normalized Vegetation Difference Index (NDVI) modification with regard to the minimum historical NDVI value as indicated by Kogan (1995) . As a result, the VCI compares the current Vegetation Index (VI), such as the NDVI or the Enhanced Vegetation Index (EVI), to the values found inside a given pixel in past years during the same time period. The VCI was calculated using Equation 1 as shown below.

where VCI ijk is the VCI value for the pixel i during week/month/ day of the years (DOY j ) for year k , VI ijk is the weekly/monthly/DOYs VI value for pixel i in week/month/DOY j for year k whereby both the NDVI or EVI can be utilized as VI, VI i , min and VI i, max is the multiyear minimum and maximum VI, respectively, for pixel i .

The resulting percentage of the measured VI value in previous years was placed in the middle of the two extremes (minimum and maximum). As a result, lower and higher values indicate poor and good drought conditions, respectively. The method utilized in this study, namely, estimating drought occurrences with VCI using R programming, is based on EVI, which has several key values or benefits over other vegetative indices, such as NDVI. First, no reflected light distortions are caused by airborne particles; second, no reflected light distortions caused by ground cover vegetation. Adapted from UN-SPIDER recommended practices ( http://www.unspider.org/advisory-support/recommended-practices/recommended-practice-drought-monitoring ), Figure 2 shows the planning, pre-processing, and data processing operations. Maize and sorghum yields were analyzed using Microsoft excel to identify their trends and also determine the potential impacts of drought on crop yields.

Figure 2 . Flow chart.

Evaluation of drought events and its potential impacts on food production Free State Province has been presented in this study. Results reveal that drought patterns and severity varied from one place to another, which shows that the impacts can be varied especially on agricultural sector between the years 2011 and 2020. Information in Figure 3 presents drought episodes over the study area for the period of study using space-based information to quantify drought potential impacts on food security in the affected areas. From the findings, it was noted that the year 2015 and 2018 were extremely affected by drought events, this connotes that the affected years would have been impacted in terms of food production and other water-reliant sectors. It has been noted previously that there is a significant increase in mild drought events in the Free State Province, from shorter time steps (first decade) to longer time steps (third decade; Botai et al., 2016 ). During the year 2015, the Free State Province appears to have had more droughts. Drought categories have substantial implications for a variety of sectors, including agriculture and water. According to a study, drought reduced agricultural productivity in South Africa by 8.4% in 2015. The livestock industry, for example, had a 15% drop in national herd stock as a result of the drought ( Matlou et al., 2021 ). The result further reveals that years 2017 was severely affected by drought where some areas are more impacted than others. This variability may be due to several factors, such as topography, rainfall amount, human and natural activities ( Ayanlade et al., 2018 ). Drought periods affect the agricultural sector the most compared to other sectors (mining, manufacturing, construction, trade, transport, finance, and community service; Matlou et al., 2021 ).

Figure 3 . Drought events for the year 2011–2020.

Years 2011 and 2019 were moderately affected by drought as presented in Figure 3 and Table 1 . Farmers may lose resources such as capital if drought damages their crops during these years. If the farmers water supply is insufficient, they may be forced to spend more money on irrigation or drill more wells, or produce lower yields during the affected years ( Baudoin et al., 2017 ; Kuwayama et al., 2019 ). Ranchers may have to pay more money on livestock feed and water. Results further reveal that years 2012 and 2014 observed no drought episodes which connote that these 2 years may not be directly affected by drought except the prolonged drought events from the previous years ( Nguyen et al., 2018 ). Extreme climate events, including prolonged drought, may establish long-lasting effects on soil biotic and abiotic properties, thus influencing ecosystem functions including primary productivity in subsequent years ( Nguyen et al., 2018 ).

Table 1 . Potential drought impacts on agricultural products between 2011 and 2020.

Information in Figures 4 , 5 present agricultural productions between year 2011 and 2020 for maize and sorghum productions, respectively. Since agricultural drought is caused by below-average precipitation and/or above-average temperatures and wind, which evaporate moisture from soils and plants, this in turn influences crops yield ( Madadgar et al., 2017 ; Leng and Hall, 2019 ; Orimoloye et al., 2021d ). The study area recorded the lowest maize yield in year 2015 with about 1191 tons, followed by year 2014 with about 2,236 tons. The lowest maize production recorded in year 2015 corroborates with the extreme drought event in the same year ( Figure 3 and Table 1 ). The primary direct economic impact of drought in the agricultural sector is crop failure and pasture losses and this can severely affect income ( Madadgar et al., 2017 ; Liu et al., 2018 ; Leng and Hall, 2019 ; Orimoloye et al., 2021a , c ). Findings further reveal that years 2016, 2019, and 2020 recorded 5,110, 4,700, and 4,492 tons, respectively. This is further supported by drought evaluations where these 3 years observed moderate drought episodes, this may also be influenced by the drought events. Studies have shown that yield loss risk tends to grow faster when experiencing a shift in drought severity from moderate to severe conditions ( Leng and Hall, 2019 ; Orimoloye et al., 2021a , d ). This analysis shows that variability in drought trends plays an important role in determining drought impacts, through reducing or amplifying drought-driven yield loss risk ( Leng and Hall, 2019 ).

Figure 4 . Maize for year 2011–2020.

Figure 5 . Sorghum for year 2011–2020.

Sorghum production between year 2011 and 2020 is presented in Figure 4 . Total average yield (t/ha) for sorghum show that 0.9 (2016), 1.3 (2015), and 2.2 (2013) were recorded in the study area. Year 2013 recorded 139,200 tons of sorghum yields while years 2015, 2016, and 2018 recorded the lowest sorghum production with about 24,150, 24,640, and 23,600, respectively during the period ( Figure 4 ).

Drought is an extreme stage of the hydrological cycle that occurs when water availability is lower than typical ( Orimoloye et al., 2019 ; Adedeji et al., 2020 ). Droughts typically begin with a lack of precipitation (meteorological drought), which can be aggravated by increased evapotranspiration owing to high temperatures, which can spread to the land surface and result in reduced soil moisture (agricultural drought) and streamflow (called hydrological drought). Water stress during drought slows down crop root growth, delays maturation and reduces agricultural productivity ( Ge et al., 2012 ; Piscitelli et al., 2021 ). Drought occurrence is critical because crop yield susceptibility to water stress varies by development stage, which is linked to the fundamental biophysical principles of crop growth ( Oliveira and Araújo, 2021 ). As a result, drought impacts on agricultural productivity must be assessed independently for particular growth stages, which is more relevant for agricultural water management ( Orimoloye et al., 2021d ). Space-based assessments of drought are important tools for estimating drought impacts on crop yields ( Derese et al., 2018 ; Orimoloye et al., 2021c ) but these are inherently scale-dependent, ranging from the farm level at the local level to the global scale. This highlights the need for space-based information approaches ( Orimoloye et al., 2021c ) to simultaneously consider the joint distribution of the spatial and temporal footprint of drought. Such approaches can be combined with model-based large ensembles for more robust quantification of agricultural risk, this can also consider whether risk assessments are transferable across scales.

Drought tolerance may arise from extra copies of key genes, and sorghum's efficient photosynthetic pathway may be cobbled together from existing photosynthetic genes and duplicated genes that shifted their function over millions of years in order to withstand drought episodes (Citations). Droughts in the study area, infestation, insects, birds, and diseases, a lack of varieties with farmers' preferred traits and high yield potential, limited policy support, a lack of improved seed system, poor sorghum production practices and crop input application, and poor soil fertility may all have contributed to the decline in sorghum productivity ( Derese et al., 2018 ). Among the sorghum production constraints listed, severe drought in the post-flowering stage may be the most significant over time. A large number of farmers in the affected area may need to produce medium-maturing sorghum cultivars with high grain and biomass yields that can be planted at normal planting times yet avoid post-flowering drought ( Azu et al., 2021 ; Abreha et al., 2022 ).

Analysis from this study revealed spatio-temporal distributions of drought and crop trends over the study area ( Table 1 ). From the findings, drought event implications on agricultural products were identified, it was noted that the years that experienced drought episodes witnessed a decline in crop yields. For instance, the year 2015 observed extreme drought, both crops explored in the study experienced a drop in their yields, this also repeated in the year 2018 with potential drought impacts on agricultural productions ( Madadgar et al., 2017 ; Liu et al., 2018 ; Leng and Hall, 2019 ). Persistent drought episodes can influence food insecurity as this has been recorded in previous studies ( Cottrell et al., 2019 ; He et al., 2019 ). This can sometimes cause problems for downstream agriculture, particularly when the growing season for crops and peak food demand periods do not coincide. The amount to which trade-offs exist, however, is determined by the duration and spatial footprint of droughts.

Improved Decision-Support for Agricultural Droughts in Vulnerable Region

There are a number of new technological developments that could support drought risk reduction. Here we will focus on space-based information that could be better integrated to improve decision-support especially in combatting drought disasters. The approach used in this study will improve agricultural drought monitoring in the drought-affected area ( Enenkel et al., 2015 ; Brandt et al., 2017 ). This will help in gaining a better understanding of the uncertainty of long-term drought forecasts and how this information can be integrated with satellite-derived soil moisture and its potential influence on food security. For example, year 2015 observed extreme drought where both crops explored in the study observed declined in productions, this also repeated in the year 2018 with potential drought impacts on agricultural productions. These years can be examined to know how drought events have affected the area especially, agricultural production and to suggest possible practices to avert future occurrence. More so, integration of non-environmental information that can contribute to drought impact may be considered.

The most important question is: what can science do to help people make better decisions regarding drought hazards? The integrated and modification of existing technologies, including various satellite-based systems and people's experiences, is one logical and promising option. Organizations like AppEEARS (Application for Extracting and Exploring Analysis Ready Samples), USGS (United States Geological Survey), EUMETSAT (European Organization for the Exploitation of Meteorological Satellites), and NOAA (National Oceanic and Atmospheric Administration) provide a wide range of satellite-derived datasets that are operational, near real-time, and free of charge (or with a minimal and low-cost receiving station). Datasets obtained from sensors, in addition to some of the more regularly used remote sensing products, can be delivered at a spatial resolution that is worth considering to complement or replace in-situ observations. Local measurement flaws including inadequate coverage and lack of spatial consistency are frequently compensated for using these databases. The interaction of drought-inducing main climatic elements (rainfall, temperature, soil moisture, evapotranspiration, and vegetation) is reasonably well-understood ( Enenkel et al., 2015 ; Afuye et al., 2021a , b ). One key issue is that large-scale planning necessitates accurate drought forecasts several months in advance, which are currently insufficient ( Yaseen and Shahid, 2021 ). Another concern is that agricultural drought is only one of several potential causes of food insecurity. High degrees of vulnerability induced by interacting socio-economic factors, such as political turmoil and rising or fluctuating food costs, often encourage famine. In fact, the methods for monitoring environmental anomalies and their socioeconomic consequences are hardly comparable. Researchers should engage more closely with end-users in a multi-disciplinary manner in order to establish a holistic drought monitoring system. This strategy will help by identifying the current weak links and suggesting future mitigation strategies.

This study presented agricultural drought and its potential impacts in order to enable decision-support for food security in vulnerable societies. Analysis from this study revealed spatio-temporal distributions of drought and crop trends over the study area. The outcomes from this study revealed drought event implications on agricultural products, it was also noted that the years that experienced drought episodes witnessed a decline in crop yields. For example, year 2015 observed extreme drought, both crops explored in the study experienced a decrease in agricultural productions, this was also repeated in the year 2018 with potential drought impacts on agricultural productions during the same period. The consequence of drought is a translation of failure of early warning, local action, disaster preparedness and lack of external support. The approach for monitoring drought anomalies and their agricultural impact is hardly comparable. Scientists should engage more closely with the affected parties (farmers and water-reliant sectors), end-users in a multi-disciplinary manner in order to establish a holistic drought monitoring system. This strategy will help by identifying the current weak links and suggesting future mitigation strategies. Consequently, it is necessary to appraise drought disasters by incorporating climate information, environmental and economic implications of drought in the study area and the surrounding environments, this will help in identifying the contributing factors and the actual impacts of its occurrences in the region.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: agricultural drought, Earth observation data, food security, potential impacts, decision-support

Citation: Orimoloye IR (2022) Agricultural Drought and Its Potential Impacts: Enabling Decision-Support for Food Security in Vulnerable Regions. Front. Sustain. Food Syst. 6:838824. doi: 10.3389/fsufs.2022.838824

Received: 18 December 2021; Accepted: 13 January 2022; Published: 11 February 2022.

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Copyright © 2022 Orimoloye. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Israel R. Orimoloye, orimoloyeisrael@gmail.com ; orcid.org/0000-0001-5058-2799

This article is part of the Research Topic

Feeding the Growing Cities of Sub-Saharan Africa: Challenges of Urban Food Systems, Food Security, Urban Agriculture, and Sustainability