case study on pakistan floods

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Pakistan case study: Coordinated and comprehensive response to the 2022 floods

Devastating floods in Pakistan affected 33 million people in 2022, with 8 million displaced, 13,000 injured and 1,700 killed – the latest in a series of increasingly frequent and severe climate-induced disasters. This case study explores how the empowered UN Resident Coordinator (RC) system was invaluable for responding to the complex crisis. Thanks to strengthened coordination capacities, including at the sub-national level the RC Office offered support to enable a swift humanitarian response, to augment the UN Office for the Coordination of Humanitarian Affairs (OCHA)’s limited in-country resources in the immediate aftermath. The RC also enabled a focus on a collaborative approach with international financial institutions (IFIs), including for long-term recovery. The Living Indus Initiative, which emerged from the strategic prioritization for Pakistan’s UN Sustainable Development Cooperation Framework led by the RC, became the blueprint for a long-term approach, ensuring that UN efforts went beyond a mere response to a one-off disaster.  

Read the full case study here. 

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Pakistan: Flood Damages and Economic Losses Over USD 30 billion and Reconstruction Needs Over USD 16 billion - New Assessment

Post-disaster needs assessment calls for urgent support to implement a recovery and reconstruction that ‘builds back better’.

ISLAMABAD, October 28, 2022 - A damage, loss, and needs assessment following the unprecedented floods in Pakistan calls for ‘ building back better ’, based on the principles of the poor first , transparency, inclusion, and climate resilience. The assessment estimates total damages to exceed USD 14.9 billion, and total economic losses to reach about USD 15.2 billion. Estimated needs for rehabilitation and reconstruction in a resilient way are at least USD 16.3 billion , not including much needed new investments beyond the affected assets, to support Pakistan’s adaptation to climate change and overall resilience of the country to future climate shocks.

Housing ; Agriculture and Livestock ; and Transport and Communications sectors suffered the most significant damage, at USD 5.6 billion, USD 3.7 billion, and USD 3.3 billion, respectively. Sindh is the worst affected province with close to 70 percent of total damages and losses, followed by Balochistan, Khyber Pakhtunkhwa, and Punjab.

The Ministry of Planning, Development and Special Initiatives led the Post-Disaster Needs Assessment (PDNA) , which was conducted jointly with the Asian Development Bank (ADB), the European Union (EU), the United Nations agencies with technical facilitation by the United Nations Development Programme (UNDP), and the World Bank. The PDNA, in addition to estimating damages, economic losses and recovery and reconstruction needs, also assesses broader macro-economic and human impacts and recommends principles along which to develop a comprehensive recovery and reconstruction framework.

The floods affected 33 million people and more than 1730 lost their lives . They are particularly impacting the poorest and most vulnerable districts. The situation is still evolving, with flood waters stagnant in many areas, causing water-borne and vector-borne diseases to spread, and more than 8 million displaced people now facing a health crisis . The crisis thus risks having profound and lasting impacts on lives and livelihoods. Loss of household incomes, assets, rising food prices, and disease outbreaks are impacting the most vulnerable groups. Women have suffered notable losses of their livelihoods, particularly those associated with agriculture and livestock.

The PDNA Human Impact Assessment highlights that the national poverty rate may increase by 3.7 to 4.0 percentage points, potentially pushing between 8.4 and 9.1 million more people below the poverty line .

Multidimensional poverty can potentially increase by 5.9 percentage points, implying that an additional 1.9 million households are at risk of being pushed into non-monetary poverty.

Compounding the existing economic difficulties facing the country, the 2022 floods are expected to have a significant adverse impact on output, which will vary substantially by region and sector. Loss in gross domestic product (GDP) as a direct impact of the floods is projected to be around 2.2 percent of FY22 GDP . The agriculture sector is projected to contract the most, at 0.9 percent of GDP. The damage and losses in agriculture will have spillover effects on the industry, external trade and services sectors.

The Government is providing immediate relief to the impacted communities and supporting the early recovery, while aiming to ensure macroeconomic stability and fiscal sustainability. Moving forward, as recovery and reconstruction spending rises, the loss in output could be mitigated. Yet, significant international support will be needed to complement Pakistan’s own commitment to increase domestic revenue mobilization and save scarce public resources, and to reduce the risk of exacerbating macroeconomic imbalances. 

Although the early loss and damage estimates may increase as the situation is continuously evolving on the ground, the PDNA lays the groundwork for an agenda for recovery and reconstruction that is designed to build back a better future for the most affected people in Pakistan . While the recovery will require massive efforts for the rehabilitation and reconstruction of damaged infrastructure, buildings and livelihoods, it will also be an opportunity to strengthen institutions and governance structures.

The report puts forth recommendations for developing a comprehensive recovery framework. While the primary focus will be on the affected areas, such framework presents an opportunity to embed systemic resilience to natural hazards and climate change in Pakistan’s overall development planning. This tragic disaster can be a turning point, where climate resilience and adaptation, increased domestic revenue mobilization and better public spending, and public policies and investments better targeted to the most vulnerable populations; all figure at the core of policy making going forward .

In the short term, targeted mechanisms such as social assistance and emergency cash transfers, provision of emergency health services, and programs to restore shelter and restart local economic activities, particularly in agriculture, should be prioritized. Reconstruction and rehabilitation should rest on key principles of: participatory, transparent, inclusive, and green recovery for long-term resilience—“ building back better ”; pro-poor, pro-vulnerable, and gender sensitive, targeting the most affected; strong coordination of government tiers and implementation by the lowest appropriate level; synergies between humanitarian effort and recovery; and a sustainable financing plan .

Given Pakistan’s limited fiscal resources, significant international support and private investment will be essential for a comprehensive and resilient recovery. The Pakistani authorities are committed to accelerate reforms to generate additional domestic fiscal resources and improve efficiency and targeting of public spending. Beyond the immediate needs of floods reconstruction, these reforms, while protecting the most vulnerable, will be important to generate fiscal space to invest more broadly into more climate-resilient infrastructure and adaptation to climate change, as well as to build buffers to face future shocks, while addressing macroeconomic imbalances. This commitment of the Government will also be key to mobilize further international support as well as to unlock private sector sources of financing—both of which will be absolutely critical to face the current climate change-induced shock.

The ADB, the EU, the UNDP and the World Bank are fully committed to working with the Government and people of Pakistan during the ensuing recovery phase, and to increase the country’s climate resilience.

• World Bank Mariam Altaf Tel : +92 (51) 9090000 [email protected]

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In a First Study of Pakistan’s Floods, Scientists See Climate Change at Work

A growing field called attribution science is helping researchers rapidly assess the links between global warming and weather disasters.

By Raymond Zhong

Pakistan began receiving abnormally heavy rain in mid-June, and, by late August, drenching downpours were declared a national emergency. The southern part of the Indus River , which traverses the length of the country, became a vast lake. Villages have become islands , surrounded by putrid water that stretches to the horizon. More than 1,500 people have died. Floodwaters could take months to recede.

The deluges were made worse by global warming caused by greenhouse-gas emissions, scientists said Thursday, drawing upon a fast-growing field of research that gauges the influence of climate change on specific extreme weather events soon after they occur — and while societies are still dealing with their shattering consequences.

As climate scientists’ techniques improve, they can assess, with ever-greater confidence and specificity, how human-induced changes in Earth’s chemistry are affecting the severe weather outside our windows, adding weight and urgency to questions about how nations should adapt.

The floods in Pakistan are the deadliest in a recent string of eye-popping weather extremes across the Northern Hemisphere: relentless droughts in the Horn of Africa , Mexico and China ; flash floods in West and Central Africa , Iran and the inland United States ; searing heat waves in India , Japan , California , Britain and Europe .

Scientists have warned for decades that some kinds of extreme weather are becoming more frequent and intense as more heat-trapping gases get pumped into the atmosphere. As the planet warms, more water evaporates from the oceans. Hotter air also holds more moisture. So storms like those that come with the South Asian monsoon can pack a bigger punch.

But Pakistan’s monsoon rains have long varied wildly from year to year, which made it hard to pin down precisely how much more severe this season was because of climate change, the authors of the new study said. Still, most of their computer models indicated that human-caused warming had intensified the rainfall to some extent, convincing them that it was a contributing factor.

The country might have experienced disastrously high rainfall this year even without global warming, said the study’s lead author, Friederike Otto, a climate scientist at Imperial College London. “But it’s worse because of climate change,” Dr. Otto said. “And especially in these highly vulnerable regions, small changes matter a lot.”

The study was produced by 26 scientists affiliated with World Weather Attribution , a research initiative that specializes in rapid studies of extreme events. This year, scientists with the group found that the heat that scorched India and Pakistan this spring had been 30 times as likely to occur because of greenhouse emissions. July’s extreme heat in Britain had been at least 10 times as likely, the group found . Next up is a study on this summer’s drought in Europe.

Attribution studies aim to link two distinct but related phenomena: climate and weather.

Climate is what happens to the weather over long periods and on a planetary scale. Direct weather records only go back a century or so in many places, which is why scientists use computer models and concepts from physics and chemistry to build out their understanding of the evolving climate. But the weather has always been variable, even without the influence of human activity. Attribution studies try to separate this natural variability from the larger shifts that fossil-fuel emissions are bringing about.

Attribution research “really helps us understand how weather sits within long-term climate change,” said Daithi A. Stone, a climate scientist with New Zealand’s National Institute of Water and Atmospheric Research.

Nearly two decades ago, Dr. Stone worked on the first study to estimate the fingerprints of climate change on a one-off event — in that case, Europe’s brutal 2003 heat wave, which killed tens of thousands of people . Since then, scientists worldwide have published 431 attribution studies on 504 extreme events, according to an informal tally of English-language research by the climate news site Carbon Brief .

The field is still expanding rapidly, by Carbon Brief’s count: Three-fifths of these studies were published in 2017 or later. A fifth were published this year or last.

“The diversity of tools we have at our disposal to look at it now,” Dr. Stone said, “is beyond what we might have imagined back then.”

To perform an attribution, scientists use mathematical models to analyze both the world as it is and the world as it might have been, had humans not spent decades pumping planet-warming gases into the atmosphere. With computer simulations, they can replay recent history dozens, even hundreds, of times in both worlds to see how often the event, and others like it, occur in each. The differences indicate how much global warming was likely responsible.

Researchers often perform this comparison using scores of climate models to ensure their conclusions are sound. They also check the simulations against records of actual events that have occurred in the past.

To examine this year’s flooding in Pakistan, the authors of the new study looked at two metrics: the maximum 60-day rainfall each year between June and September over the entire Indus River Basin, and the maximum five-day rainfall each year over the badly hit southern provinces of Sindh and Baluchistan.

The researchers found that several of their models did not realistically reproduce patterns in the actual rainfall data for Pakistan. And those that did gave divergent answers for how much more intense and more likely this year’s rainfall had become under present levels of global warming.

The models gave clearer answers when considering a higher level of warming, however. This gave the researchers confidence to say that climate change had probably made this year’s flooding worse, though they refrained from estimating by how much.

Recent improvements in the climate models helped the authors narrow their estimates, Dr. Otto said. “The uncertainty bars are smaller than they would have been five years ago,” she said, referring to the lines in statistical charts that show ranges of possible values. “But monsoon is still something that models really struggle with.”

Pakistan’s highly varied topography, from its southern coast to the high Himalayan peaks in the north, causes its climate to be shaped by many physical drivers, said another author of the study, Fahad Saeed, a climate scientist based in Islamabad, Pakistan, with the research group Climate Analytics.

“The representation of all these processes can get tricky when you’re applying a climate model,” Dr. Saeed said.

Scientists often find storms, droughts and wildfires tougher to attribute to global warming compared with extreme hot or cold spells. Those events involve not just temperatures, but also the circulation of air and complex interactions between land, sea and atmosphere. Even so, new and improved models, plus greater quantities of data, are helping to close the gaps.

“For us as climate scientists, our laboratory is our climate models,” said Andrew Hoell of the National Oceanic and Atmospheric Administration in Boulder, Colo. “And they’ve advanced in ways that have allowed us to do more-robust attribution studies.”

Today, models are continuing to get better at capturing weather and its drivers at progressively smaller scales, Dr. Hoell said. Scientists can start to think not just about drought over a large area, but evaporation in specific watersheds and reservoirs. Not just average rainfall, but individual tornadoes and thunderstorms.

Climate scientists have also begun using artificial intelligence and other computational techniques to scour weather data for new insights, said Dim Coumou, a climate researcher at the Dutch university VU Amsterdam. These methods can help scientists uncover the hidden mechanisms that drive complex weather patterns, leading to better attributions and forecasts of extreme events.

“There is just a lot of data that is getting more accessible for scientists,” Dr. Coumou said.

Weather records show that South Asia’s monsoon is whipsawing more between drier years and wetter ones — unwelcome news for farmers who must increasingly deal with either parched fields or inundated ones.

Anders Levermann, a physicist at the Potsdam Institute for Climate Impact Research in Germany, has proposed one explanation. The South Asian monsoon begins each spring when the land warms and draws in moisture-rich air from the Indian Ocean. When this air hits the mountains and cools, its cargo of vapor condenses into rain and, in the process, releases heat. The heat draws even more air toward the land from the sea, which keeps the monsoon going.

On a warmer planet, there is more moisture in this system, which means the rains are amplified. But if anything blocks this inflow, such as an atmospheric disturbance or heavy air pollution, then its weakening effects on the monsoon might also be amplified, Dr. Levermann said.

“That’s the bad thing about climate change,” he said. “It’s not just an increase in something or a decrease in something. It’s an increase in variability.”

Raymond Zhong is a climate reporter. He joined The Times in 2017 and was part of the team that won the 2021 Pulitzer Prize in public service for coverage of the coronavirus pandemic. More about Raymond Zhong

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Analysis of 2022 Pakistan floods identifies recovery strategies

Washington, DC— Researchers from Stanford University’s Natural Capital Project, including Carnegie collaborators Edgar Virgüez and Ken Caldeira, reviewed the impact of 2022’s flooding in Pakistan, offering insights on how to rebuild with future floods in mind and demonstrating that climate adaptation measures could have helped many of those impacted. Their findings are published in Environmental Research Letters .

Last summer, Pakistan’s Indus River overflowed and swept through the homes of at least 30 million people, killing at least 1,700 and displacing 8 million. The economic cost of the flood’s damage was estimated at $30 billion. The research team worked together to calculate the approximate depths of flooding in different areas and the number of people affected by the natural disaster. This data formed the baseline of their forward-looking analyses.

“We were motivated by these big floods that are happening now every year, to ask: how can we conduct a very high-level assessment of what it would cost to adapt livelihoods to a changing climate?” said first author Rafael Schmitt, a leading scientist at the Natural Capital Project , an interdisciplinary Stanford-led initiative to motivate greater investment in natural resources, including land, water, and biodiversity as national capital. “ This could help countries and international donors evaluate the cost-effectiveness of specific adaptation measures.”

A New Climate Adaptation Decision-Support Tool

The researchers addressed two main options for adapting to future flooding in Pakistan, both of which have been widely implemented across Asia: “moving up” by building elevated structures, or “moving over” by temporarily relocating when floods occur. The depth of flooding–and distance to dry–are important factors for determining which response makes sense. Locations with shallow flood depths that are far from dry land would favor elevating buildings, while flood depths of greater than two meters make elevated structures impractical and too costly.

The team integrated satellite data from flooded locations with hydrologic principles and demographic data on population density, housing, and other infrastructure. This produced a rapid overview of flood severity and exposure.

The researchers estimated that 26.6 million people in Pakistan were exposed to less than 1 meter of water, 7.4 million were exposed to water levels between 1 and 2 meters, and 5.7 million were exposed to more than 2 meters of flooding.

Based on this and proximity to dry land, the researchers determined that there were 5.1 million people for whom the “move over” would be the best solution, 6.3 million people who would be best served by “moving up,” and 27.5 million people for whom either “moving up” or “moving over” could work. Additionally, half a million people were categorized with retreat as their only option. These individuals experienced flood depths greater than 2 meters and they were far from dry land.

Focusing on those who experienced flood depths between 1 and 2 meters, the researcher’s analysis estimated adaptation costs between $1.5-$3.6 billion, in addition to the $5.8 billion to rebuild housing to the status quo. 

"This work demonstrates how a data-driven approach to policy and planning can help communities prepare for the oncoming challenges of climate change,” said Caldeira. “As scientists work hard to help develop climate change mitigation strategies, we can also apply our skills to provide information needed to assess risk and determine the best paths forward to prevent human catastrophes in a warming world.”

Prioritizing Equity and Resilience in Rebuilding Efforts

This research effort only looked at housing, but the team’s analytical tool could also be applied to other types of infrastructure, including roads, schools, and hospitals. And in the future, data from NASA’s Surface Water and Ocean Topography satellite could enhance its abilities.

“The study speaks to the potential to incorporate science-informed adaptation measures into reconstruction and disaster response, helping in investment prioritization,” said Virgüez. “This is particularly useful nowadays with the discussions on mechanisms to compensate countries of the Global South for climate-change-attributed damages.”

The researchers emphasized that tools such as theirs can help ensure that reconstruction funding is directed where it can make the greatest impact, not because it will benefit those with the most influence.  

“Countries of the Global South, like my native Colombia, would benefit from process-based model assessments at scale and in a timely manner that can guide the investments of scarce resources. Especially since many of these countries lack timely-generated data, which complicates strategic decision investments,” Virgüez added. 

An important outcome of the United Nations Climate Conference last year (COP27) was the creation of a new Loss and Damage Fund to provide financial support for countries that are most vulnerable to climate change. In this paper, the research team urged funders and governments to rebuild with adaptation in mind. To do that, they say, more science should also be directed toward understanding low-cost adaptation options.

“Flood models are data-intensive, and you need specialized knowledge to run them,” Schmitt concluded. “We need adaptation research that is easier to use and act on.”

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Review article, floods and flood management and its socio-economic impact on pakistan: a review of the empirical literature.

• 1 Department of Govt and Public Policy, Faculty of Contemporary Studies, National Defence University, Islamabad, Pakistan
• 2 Department of Earth and Environmental Sciences, Bahria University, Islamabad, Pakistan
• 3 School of Economics, Sapienza University of Rome, Rome, Italy
• 4 Department of Environmental Sciences, Faculty of Life Sciences and Informatics, Balochistan University of Information Technology, Engineering and Management Sciences, Quetta, Pakistan
• 5 School of Public Administration, Xiangtan University, Hunan, China
• 6 School of Public Administration, China University of Geosciences, Wuhan, China
• 7 The Faculty of Biosciences, Fisheries and Economics, UiT The Arctic University of Norway, Tromsø, Norway
• 8 Department of Earth Sciences, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
• 9 MARE-Marine and Environmental Sciences Centre—Sedimentary Geology Group, Department of Earth Sciences, Faculty of Sciences and Technology, University of Coimbra, Coimbra, Portugal

Flood is one of the most damaging natural disasters as the recent floods have shown their serious impact on Pakistan. Flood control and regulation policies are essential to reduce the risks of economic downturn, a threat to human existence, and to sustain the ecology. The severity of flood catastrophe activities represents a constant and severe issue in the world. Floods are rising year by year in severity and duration, causing negative impacts on the social and economic conditions of the nation concerned. While the frequency of floods cannot be avoided, their adverse impacts can be considerably reduced by adopting careful planning and efficient training. This paper reviews the socioeconomic impact of floods, and the existing condition of flood control policies outlines the flood protection problems and discusses opportunities for successful and efficient flood control in Pakistan. The paper also intends to propose several suggestions for efficient and sustainable flood control in Pakistan.

1 Introduction

Floods are one of the major sources of anthropological and ecological destruction. It affects the socio-economic conditions, worsens public health, generates unemployment, damages the ecosystem, etc. ( Allaire, 2018 ; Parida, 2019 ). Currently, public and private institutions are struggling to formulate and evaluate risk management and adjustment strategies, involving systems for flood prevention and advance alerts with urbanization patterns and land use planning under consideration in the wake of urban flooding. One major reason is the land adjudication and administration system of Pakistan is colonial in nature and lacks judicial augmentation, providing a chance for flawed urbanization ( Shafi et al., 2022 ). However, policymakers face substantial hiccups in the mitigation of natural disasters’ aftermath globally. In this wake, countries with stable economic structures and administration have reported fewer mortalities and lower socioeconomic damages as compared to developing countries ( Anbarci et al., 2005 ; Kahn, 2005 ).

Certain approaches are utilized to manage floods and mitigate their aftermath. Here, Effective Risk Avoidance involves a detailed understanding of the effects of floods on the public, the economy, and the efficiency of disaster management strategies. The realistic approaches focus on the potential risks and benefits analysis. Currently, prevention approaches are often decided based on active expert analysis of floods. However, cost-benefit analysis is seldom used in mitigation planning, possibly because of insufficient empirical evidence on a broad range of types of losses. Government and non-governmental sectors also transfer their resources from production to restoration and rehabilitation practices which slow down the growth of Gross Domestic Product (GDP) and overall Human Development Index (HDI) ( Sadia et al., 2013 ; Isik et al., 2021 ).

The South-Asian Subcontinent, with The Great Himalaya Glaciers, remains at primary risk. Though currently, the rainy season remains the major reason for the flooding in the region the presence of glaciers and the rise in average temperature remain a permanent threat to the region. Floods are the most common natural disaster in the region with 40% occurrence rate ( Chaudhry, 2017 ). Furthermore, urban flooding reasoned by solid waste management and decreases in urban vegetation has affected 9.6 million people in Bangladesh, India, and Nepal, with 6.8 million from India only. South Asia floods: 9.6 million people swamped as humanitarian crisis deepens ( IFRC, 2020 ).

It has been observed that the average global temperature has been rising at a higher rate since 1980. Due to this glaciers are melting rapidly, generating glacial lakes and associated hazards. Glacial Lake Outburst Floods (GLOFs) are extremely destructive because of large volumes of water flowing in narrow river channels. The greatest number of GLOFs, out of all the natural disasters that have occurred worldwide, have been reported in Central Asia ( Carrivick and Tweed, 2016 ; Nie et al., 2017 ; Mohanty and Maiti, 2021 ). Global warming as the sole reason GLOFS, the Hindukush-Karakoram-Himalaya regions of Pakistan, which contribute more than 50% of the entire flow of the Indus River System (a major water system), has observed a higher melting rate of glaciers. This condition has led to an increase in the frequency of glacial-related hazards in this Himalayan region. GLOFs which are either caused by the sudden failure of the “dams,” or in the absence of the dams release huge volumes of water and debris wreak havoc downstream. GLOFs have the potential to massively harm people living in the Himalayan region, especially Indus River Basin ( Ashraf et al., 2012 ; Ashraf et al., 2021 ; Ahmad et al., 2022 ).

Achieving sustainability in the country in terms of economic, social, political, and environmental issues is discussed more thoroughly nowadays because the phenomena of globalization as well as global warming are based to meet today’s requirements without compromising the ability of future generations ( Işık et al., 2021 ). The rising CO2 emission worldwide will be rising government spending as the result increases real GDP per capita. So, state policymakers are trying to limit or minimize CO2 emissions ( Işık et al., 2022 ). Pakistan is among the most vulnerable countries to floods and water-related disasters as Pakistan has the most glaciers outside the arctic circle. The climate changes and monsoon season have significant impacts on socio-economic degradation, specifically on agricultural production and livestock. The regular occurrence of flood catastrophes affects different regions of Pakistan (See Table 1 ). Floods are expensive environmental disasters, leading to property and agricultural land destruction. Floods are typically short-lived occurrences that can occur with a tiny alert ( Commission, 2007 ). Pakistan has experienced an unprecedented increase in floods in the last 20 years. Fifty-four (54) floods of differing intensity hit Pakistan, placing it 10th on Global Environment Risk Index ( Kreft et al., 2015 ; Rehman et al., 2015 ; Sardar et al., 2016 ). Pakistan is positioned within a hazard-prone region and is bare to a variety of natural catastrophes like floods ( Rafiq and Blaschke, 2012 ). The past of the region’s flooding is relatively lengthy. Many significantly disastrous floods caused considerable harm to economic development. Table 2 provides the history of floods in terms of losses incurred. Each flood is caused by heavy rainfall in the Indus River catchments and its main tributaries ( GoP Annual Flood Report, 2017 ). According to the World Health Organization (WHO) twenty (20) million residents in seventy-eight (78) areas were affected by 2010 floods, taking one thousand eight hundred (1800) life’s, causing damage, or destruction of nearly two million houses with a cumulative cost of $9.7 billion. Public infrastructure i.e., roads, bridges, hospitals, schools etc. , were immensely affected, deteriorating accessibility to health, education and mobility resulting in poverty, deprivation, and psychological and social trauma necessitating rehabilitation and restoration ( Sardar et al., 2016 ).

TABLE 1 . Most vulnerable districts of Pakistan for flood and flash flood ( NDMA, 2019 ).

TABLE 2 . Historical flood damages in Pakistan (period 1950–2017) ( GoP Annual Flood Report, 2017 ).

There are typically five forms of flooding frequently occurring in the country, such as flash floods, river floods, tidal floods, marine floods, and pluvial floods. The heavy rainfall in canals’ catchment areas triggers pluvial floods of canals or dams, and water goes out towards the dry land and affects the area ( Yaqub et al., 2015 ). Main floods in Pakistan are linked with the low depression monsoon rainfalls that form in the Bay of Bengal and spread west/northwest through India to Pakistan ( Kronstadt, 2010 ). Apart from Monsoon rains, meltdown of glaciers causes flashfloods in hilly areas rendering massive destruction. However, urban flooding is solely related to monsoon rains and unplanned urbanization restricting drainage passages and encroachments. Furthermore, coastal floods are mostly caused by tropical storms in South-East Sindh and Makran regions ( Yaqub et al., 2015 ). Pakistan faces severe floods from July to September period owing to heavy monsoon rains in all the regions of Pakistan inundating the Indus River Basin. Hydrologically, the region can be categorized into three main divisions: Indus Basin, Kharan Basin, and Makran Coastal Drainage Zone. Such basin’s flooding features differ significantly and require a detailed understanding ( Tariq and van de Giesen, 2012 ). The flood hazard map indicates the most vulnerable districts of Pakistan with major river systems (developed after ( NDMA, 2019 ) as shown in Figure 1 . A topographic map of Pakistan with recent flood events is shown in Figure 2 . The list of the most vulnerable districts of Pakistan concerning Flood and Flash Flood is shown in Table 1 . The geographical distribution of Pakistan’s 2010 floods’ direct and indirect damages is shown in Figure 3 and Figure 4 respectively.

FIGURE 1 . Flood hazard map indicates the most vulnerable districts of Pakistan with a major river system map developed after ( NDMA, 2019 ).

FIGURE 2 . Topographic map of Pakistan with recent flood events (Source: ESRI topographic layer used).

FIGURE 3 . Geographical distribution of Pakistan’s 2010 floods direct damages; Source: Pakistan floods 2010 preliminary damage and needs assessment ( Asian Development Bank, 2010 ).

FIGURE 4 . Geographical distribution of Pakistan’s 2010 floods indirect damages; Source: Pakistan floods 2010 preliminary damage and needs assessment ( Asian Development Bank, 2010 ).

Global Warming and climate change are serious issues, concerning Pakistan. Our article represents the impact of global warming and climate change. As evident the cloud bursting phenomenon is quite new for Pakistan, the same is the case with Glacier Bursts. Keeping floods as the focal point of the study we maintain this proposition that climate change is one of the primary reasons for wreaking havoc in Pakistan. With this background, this article examines the recent and emerging developments in catastrophe situations to evaluate the effects of floods on the socio-economic conditions of the higher flood-risk areas. The purpose of this study is to assess the socioeconomic cost of floods and to strengthen flood control policies in Pakistan, which is a resource-limited and vastly populated developing nation, and highly dependent on the agricultural sector. The paper utilizes a literature synthesis approach, extracting data from various resources ranging from published articles to government documents. Moreover, ESRI topographic layer was used to develop a topographic map of Pakistan. The study emphasizes that exploration of flood mitigation criteria is also needed as the floods in the country are becoming more regular and severe.

2 Material and methodology

This study reviews the existing literature on the flood, flood management, and socioeconomic cost in Pakistan focusing on riverine and extreme floods (2010). The theoretical framework of the study is shown in Figure 5 .

FIGURE 5 . Theoretical framework of the study.

The present study compiled and comprehensively analyzed numerous scientific and analytical reports, scholarly articles relevant to flood management studies, economic surveys of Pakistan, and other relevant reports released by different scholarly, consulting, and consultant institutions to extract and synthesize main studies on floods and flood management in Pakistan. A comprehensive empirical literature review was performed by using Google Scholar and a related search engine. The literature that has the greatest relevance to Pakistan was cited. The study also reported crucial findings and suggestions.

The past research suggests various review methods, empirical analysis, and meta-analysis ( Toya and Skidmore, 2007 ; Jonkman et al., 2008 ; McMullen and Lytle, 2012 ). The studies aim to create an empirical link by collecting data such as the impact of floods on GDP ( Kirigia et al., 2004 ; Rufat et al., 2015 ). But in the case of Pakistan, the data available is insufficient to either adopt or develop any complicated method, however empirical analysis of the facts and figures provided through reports, government documents, and policy papers, and correlate these with studies reviewed. The focus of this study remains to provide insight into the flood problem by reviewing it through data synthesis and textual analysis approach, which will access the impacts of floods. This study will establish an understanding of the importance of the topic, where impact analysis will ensure the need for extended studies conducted in the Netherlands and Africa ( Kirigia et al., 2004 ; Jonkman et al., 2008 ).

3 Floods and their impacts

Our study will steer through past research which includes a broad range of topics concerning measuring the impact of floods i.e., agriculture and livestock, impact on human health, the economic cost of floods, flood forecasting, flood warning mechanisms, and flood management.

As, the recent floods have devastated the country, and have inundated more than 40% of Pakistan, we can only speculate the losses in wholistic terms. It has been recorded that more than 30 million people have been displaced, with most parts of the Sindh province remaining under imminent threat. So currently, the estimates can only be compared in terms of Macro losses, like no. of people migrated, an area inundated, infrastructure destruction, etc. but the exact figures will remain ambiguous. As far as the scale and scope of the current flood are concerned, we can only conclude this fact that it has immensely damaged the country as compared to the flood of 2010.

3.1 Impact on agriculture and livestock

The impact of the flood on the agriculture sector can be divided into the following six categories: 1) Livestock evacuation in an urgent situation; 2) Avoidance of spring field exposure, allowing livestock to be sheltered or moved to certain other flood-free places; 3) Harm to crop and grass productivity in worst-affected areas with massive loss of pasture 4) Driven production loss and affected the performance of cultivation and agricultural land; 5) Destroyed irrigation structures and facilities at the farm; 6) Loss of advantageous soil invertebrates, in particular earthworms, elevated risk of animal disease, including infection of liver fluke ( Morris and Brewin, 2014 ). As agriculture remains the largest sector of Pakistan’s economy, employing 43 percent of the population, its yearly contribution to the GDP period 1969–2011 is shown in Figure 6 .

FIGURE 6 . Agriculture sector’s contribution to gross domestic product (GDP) period 2011–2019 (Economic Survey of Pakistan 2018–2019) ( Gop Pakistan Economic Survey, 2019 ).

Climate change typically has minor effects on the world food supply, but the consequences of climate change are widely distributed unevenly. Low-income economies, such as those in South Asia and Africa, experienced most of the casualties. By taking the data from 1989 to 2015 and by using the Feasible General Least Square (FGLS) model ( Ali et al., 2017 ) studied the climate changes impact on Pakistan’s major crop yields. The results showed that except for wheat, the impact of rainfall on the production of any other selected crop is negative ( Iqbal et al., 2018 ). Evaluated the impact of Pakistan’s 2010 flood on Khyber Pakhtunkhwa’s agriculture sector and found that after the flood, the family income of agricultural labor dropped, resultantly, in the usage of chemical fertilizers and other agricultural inputs also declined. The floods have adversely affected agricultural output where there was a considerable fall in wheat, maize, and sugar cane output. In Pakistan, the floods and heavy rains have not only affected agriculture crops, livestock, and forests but also devastated necessary facilities such as tube wells, domestic water storage facilities, animal shelters, private seeds inventories/pesticides, and agricultural equipment ( Iqbal et al., 2018 ). Baluchistan and KPK experienced mostly heavy rains, while Punjab and Sindh experienced mostly slow-rising floods on the canal. 2011, 2012, 2013, and 2014s floods damaged residential and agricultural properties, livestock, and crops. ( Ashraf et al., 2013 ). proposed that floods made food shortages and food insecurity for the citizens as they had to utilize polluted resources, particularly water.

Due to the 2010s flood, the agriculture industry has suffered a total loss of about Rs. 429 billion. For example, the profitability of cotton production decreased to 11.76 million bales as compared to the expected production of 14 million bales. Rates of the inputs of agricultural products such as urea, and chemicals, diesel had increased dramatically ( Bukhari and Rizvi, 2017 ). According to ( Rehman et al., 2015 ), twenty percent of the country’s overall landmass was inundated, affected by the 2010s flood, with cumulative damages of above USD 10 billion. The agriculture sector’s contribution to GDP is shown in Table 3 showing a significant decrease in the fiscal year 2010–11.

TABLE 3 . Agriculture sector’s contribution to gross domestic product (GDP) period 1969–2011 (Economic survey of Pakistan, 2010–2011) ( GoP Economic Survey, 2011 ).

The flood caused the loss of millions of livestock including around 200,000 dead in the 2010 flood in Pakistan. The final number of losses was higher. The Food and Agriculture Organization (FAO) announced that after the disaster, millions of surviving animals were confronting a food shortage situation that was alarming. The call for 5.7 million dollars has been made by UNO for emergency assistance for livestock. However, funds of 1.4 million dollars have been mobilized by FAO to secure feedstuff and the healthcare of livestock. Currently, the full scale and scope of the catastrophe are not clear, which will require more resource allocations once the situation becomes clearer ( Deen, 2015 ).

3.2 Impact on human health

Floods pose an enormous challenge to the healthcare system and its efficacy. For example, it can damage access to drinkable water by infiltrating the aquifers, thus increasing the transmission of waterborne diseases. The health concerns are classified as direct and indirect. Where direct effects arise from deep water and flooding penetration, including death, debris injury, environmental pollution, and hypothermia. Indirect effects include threats related to the water disruption to the natural and physical environment, including communicable diseases, obesity, famine-related diseases, and displaced population-related diseases. The number of people affected by the different diseases by the 2010’s flood is shown in Figure 7 ( Ahern et al., 2005 ; Du et al., 2010 ).

FIGURE 7 . Number of people affected by the different diseases by the 2010’s flood ( GoP, 2011 ).

The floods’ health effects could also be categorized as instantaneous medium and long-term. Flooding can also develop a high number of breeding grounds for insect and infection-borne diseases such as malaria. There have been various reports of increased risk throughout Asia, Africa, and Latin America in historically tropical countries. Public medical professionals and relief workers also warn after natural disasters that the dead bodies of affected people can trigger disease outbreaks such as cholera. The anxiety induced by such statements enables societies, local governments, and institutions to dispose of affected people quickly without identification. This leads to psychological stress for family members alive and causes legal issues including land, insurance claims, and inherited wealth ( Kondo et al., 2002 ; Morgan et al., 2005 ).

Reacher et al. (2004) evaluated the impact of floods on public health by taking the data of massive floods for the period of 12 October 2000 in the region of Lewes in the south of England. They found that floods are linked with an earache, psychological distress, and gastroenteritis. Psychological damage may illustrate some of the additional physical illnesses recorded by affected people, and likely even by children. Strategies to encourage the adaptation of the community to disasters, where flood management has deteriorated will provide logistical assistance for flood victims and adequate therapeutic help. However, in Bangladesh, studies conducted on the causes and spread of diarrhea at the expense of flooding. It highlighted the important demographic, economic, and social aspects from the preview of amenities provided by the system and how the provision of food and clean drinking water becomes essential during and after flooding ( Kunii et al., 2002 ).

The prevalence of diarrheal disease and its associated epidemiological factors were examined by ( Mondal et al., 2001 ), by applying a systematic random sampling analysis on the data of two identified flood-prone regions in West Bengal’s Midnapur area. The research found the diarrheal disease to be the most severe morbidity in flood-prone communities. Some habits, such as using pond water for utensil washing and cooking purposes, hand washing after soap-less defecation, inadequate washing hands before feeding, open area defecation, storing of drinkable water in large mouth containers, etc. , were found to be correlated with increased diarrhea attack levels, both in research and control community during flooding to the pre-flooded period ( Mondal et al., 2001 ).

Access to medical care and drugs is of central concern in the flood-affected areas of Pakistan, as is the reconstruction of community health facilities in the region. According to the WHO, 2010s flood affected more than 20 million people, many of whom were homeless. At that time, at least 8 million people required urgent humanitarian aid. More than 400 of the approximately 3000 clinics and hospitals in flood-affected areas had been affected or closed, thereby restricting the availability of urgent and daily healthcare. The availability to clean water for drinking and standards of health and safety were severely affected, though the risks of occurrences of waterborne diseases. Specific health issues, such as tuberculosis , skin diseases, severe respiratory diseases, and starvation, were of utmost concern ( WHO, 2010 ).

3.3 Economic cost of floods

The future of the world economy is more uncertain than it has ever been, and this uncertainty is sensitive to uncertainties relating to a range of economic policy decisions made by all parties involved, including governments ( Işık et al., 2019 ). Natural climatic risks have direct interaction with core macroeconomic factors and can affect economic development and market performance rapidly. Jonkman et al. (2008) described a framework established for the assessment of flood damage in the Netherlands and suggested that the economic loss resulting from the floods relies on the country’s vulnerable location, coastal zone, and economy. According to ( Toya and Skidmore, 2007 ), high-income economies, high schooling, more transparency, more robust financial structures, and reduced government suffer fewer casualties from natural disasters. They argue that private preference for safety nets rises because of increasing people’s wages because higher salaries encourage individuals to mitigate the danger by investing extra in precautionary measures.

With improved GDP growth, citizens could have improved facilities, alarming networks, and flood-prone precautionary and protective steps that can mitigate the effect of floods. Sadia et al. (2013) examined the impact of natural disaster deaths on Pakistan’s GDP per capita from the disaster by taking the data for the period 1975 to 2009, using the ordinary least square model, and found a strong positive impact on per capita GDP from disaster-related deaths, human capital, and life expectancy.

Ahmad et al. (2011) proposed that two levels of flood damage could be evaluated. The harm to facilities (infrastructure) and mortality can be called the first tragedy accompanied by second disasters like the families facing poverty due to the death of earning hands. The risk of the second catastrophe may be higher than that of the first. The risk of natural hazards along with people’s socio-economic insecurity presents a major threat to the system of Pakistan’s government.

Sardar et al. (2016) discuss three threats linked to floods: death, property destruction, and non-fatal community consequences, and calculated the effect of these disasters on Pakistan’s GDP growth for the duration 1972–2013. Their results showed that the per capita GDP development and emergency prevention reduce the severity of flood risks associated with it. Most notably, and contrary to evidence from several nations, flood intensity accentuates flood-related hazards in Pakistan which indicate a lack of understanding of previous flood experience. Concerning the flood-to-economic growth connection, their analysis showed that flood-related threats have a substantial negative effect on the economy’s GDP performance. Property loss causes economic development with the greatest effects.

3.4 Housing

According to the economic survey of Pakistan in 2011, approximately 392,786 houses were affected, and 728,192 were lost. In the districts of Muzaffargarh and Rajanpur in Punjab, Nowshera, and D. I. Khan in KPK and Jaffarabad, Jacobabad, Shikarpur, and Thatta in Sindh, the harm was more noticeable also shown in Figure 1 and Table 1 . The geographical distribution of Pakistan’s 2010 floods direct and indirect showed in Figure 3 and Figure 4 , respectively. The flood damages and reconstruction costs by sector as shown in Table 4 .

TABLE 4 . Flood damages and reconstruction cost by sectors (Rs. in Billion) ( Pakistan: Flood Impact Assessment, 2011 ).

4 Flood management in Pakistan

The flood prevention strategy is a relatively complicated problem in Pakistan. In each of the four provinces, the complexity of the issue differs because of their specific physiographic, climatic, geographical, and socioeconomic circumstances ( Chaudhri, 1981 ). Early severe flooding happened in 1950, 1956, and 1957 after independence. However, no systematic flood control program was implemented at the national level, owing to scarce funding and administrative structures. Protection and control of flooding remained the exclusive responsibility of regional governments until 1976. That improved after 1973 destroying floods that took 474 lives and caused damage of 160 billion Pakistani Rupees ( Tariq and van de Giesen, 2012 ).

4.1 Evolution of flood management system in Pakistan

In 1973 Pakistan faced severe floods which led to the establishment of the Federal Flood Commission (FFC) in 1977. The commission worked under the Ministry of Water and Power and was established to implement nationwide flood management, particularly concerning the Indus River Basin. The main functions of the FFC include developing national flood management measures; approving flood management plans drawn up by local governments and federal entities; examining flood damage to facilities in the public sector, and analysis of repair and rehabilitation plans; flood forecasting, and alert program enhancement measures; providing guidelines on standards for the management of flood protection reservoirs ( GoP Annual Flood Report, 2009 ).

The first National Flood Protection Plan (NFPP-I) was developed after the creation of the FFC, with a spending timeline to be introduced throughout the 1978–1988 decade. A Federal Coordination Cell (now reshaped as FID Cell) was formed in 1982 to organize the Provincial Irrigation Departments ' operations, especially in the drainage region. In 1987 Dam Protection Council was set up to examine established dams via DSO WAPDA and proposals for new dams etc. ( GoP Annual Flood Report, 2009 ).

In Pakistan, flood control initiatives consist primarily of flood-protection embankments, spurs, studs, and sophisticated flood-prediction strategies. The provincial governments have developed numerous flood-protection systems to address local flood challenges ( Baig, 2008 ). According to Ahmed et al. (2014) flood risk reduction in Pakistan was handled primarily by federal and provincial authorities, which typically need to be reconsidered to find innovative methods and strategies to counter the threat. Flood management institutions and their responsibilities are presented in Figure 8 .

FIGURE 8 . Evolution of flood management and relief system in Pakistan.

4.2 Flood warning system in Pakistan

According to Jain et al. (2018) , Flood Forecasting and Warning System (FFWS) main aim is to inform the public and other stakeholders of an imminent flood as early and effectively as possible. In Pakistan, the mechanism of flood warning and control undertakes three phases: 1) The PMD tracks the monsoon weather pattern, which produces either from the west in the Arabian Sea or from the East in the Bay of Bengal, in the first stage. Their movements are monitored for the upper catchments lying in Pakistan or over the border, and estimates are generated one to 2 days in advance for expected rains and the severity of such rains. In the case of rains, the volume of rainfall is estimated and evaluated above the rim stations for their possible run-off relationship) after that is the stage of flood creation that starts with the generation of runoff from the rim stations and flows down into the Indus River and its tributary. Projected rainfall and flow data and real upstream flows are the hydro-meteorological portions of the flood prediction method 3) ultimately, the hydrological part of the forecasting network is to track and control the route of the flood wave below the rim station of the rivers at the downstream locations. This is handled by WAPDA and controlled in respective provinces by the irrigation departments ( Hussain, 2015 ).

The early warning system of Pakistan is efficient to some extent; however, the flood warning system only aims to provide information, rather protective measures. In our opinion, as we have also mentioned in the study, such acts can only help lessen the losses to be incurred. However, the implementation in the form of evacuation, protection, and migration is based upon the behavioral choices of the people of the area. We can mention the example of Mardan, where legal force was used to vacate the city during the 2022 floods. Thus, flood warning system calculates and provides relevant information. However, the impact must reach the grassroots level, furthermore, there is a strong need of creating a civic sense among the people of Pakistan. As can be seen in the case of Sawat River flash floods, it is speculated that most of the socio-economic loss incurred was caused by illegitimate activities, land grabbing on the riverbed, and around the torrent flow, which was against the River Protection Ordinance, 2002.

4.2.1 Flood forecasting division’s flood forecasting models

The FFD employs the Flood Early Warning System (FEWS) and the Indus Integrated Flood Analysis System (IFAS) for flood forecasts. In terms of urban areas, flood prediction and warning systems were developed in the Nallah Lai Basin ( Afsa et al., 2013 ; Sugiura et al., 2014 ). Since 2007 the FFD has used the flood forecasting framework FEWS built by Delft Hydraulic in the Netherlands. The FEWS contains (1) the rainfall-runoff interface Sacramento Soil Moisture Accounting (SAC-SMA) and (2) the SOBEK, an interface for hydraulic fluid routing ( Shrestha et al., 2019 ). The Layout contains data from forty-four (44) WAPDA telemetry stations. The rainfall-runoff process performance determines the entrance into the routing mechanism ( Awan, 2003 ). Early warning mechanism components are shown in Figure 9 .

FIGURE 9 . Early warning mechanism components ( Hussain, 2015 ).

From the perspective of South Asia, the hierarchical institutional structure Flash Flood Guidance System with Global Coverage (FFGS) can provide warnings about 6–24 h in advance for South Asian countries, including India, Nepal, Bhutan, Bangladesh, and Sri Lanka. However, the respective NDMA’s of these countries perform the same functions as Pakistan, Since Bangladesh and India are more densely populated than Pakistan, the riverbank protection in India and Bangladesh is much more rooted at the state level, and powers are transferred to the grassroots level for implementation. But, as the cultural roots of the subcontinent remain the same along with legal roots, the implementation and behavioral intention part remain at certain risk.

4.2.1.1 Criticism

The present flood forecasting method of the FEWS model, however, has minimal regional scope, and rainfall-runoff knowledge and downstream routing of the Tarbela and Kabul rivers are not integrated with the model. The tributaries included in the FEWS are not determined by the amount and rate of discharge necessary for reliable flood forecasting ( Shrestha et al., 2019 ). The FFD also introduces the IFAS established by the International Center for Water Hazard and Risk Management (ICHARM) under the Critical Reinforcing of Pakistan’s Flood Warning and Management Capacity Program and the Japan Aerospace Exploration Agency (JAXA), with UNESCO funding. More than thirty-nine (39) districts in Pakistan are protected by flood prediction and early warning services from the IFAS ( Ahmad, 2015 ; Mustafa et al., 2015 ).

Disaster management institutions in Pakistan are relatively new and need time to strengthen their foothold. National disaster management authority (NDMA) claims a preparedness-oriented approach, but at the core, the country’s disaster management system is still operating on a top-down approach. Practically, it is more relief-focused, and season-based planning is being implemented. Under the 18th amendment of the constitution of Pakistan, PDMAs are not legally bound to follow NDMA. As a result, NDMA just acts as a general policy-defining institution. Mutual coordination needs to be encouraged to cover potential oversights. District disaster management authorities are composed of officials from different local institutions and are virtually non-existent in the field. Thus, a dedicated DDMA is needed, which could act as a catalyst in disaster risk reduction ( Rana et al., 2021 ).

There is also a need for regular technical and institutional capacity assessments for effective disaster preparedness and response. Consequently, ad-hoc disaster risk management is happening in the study areas. More research could be conducted to identify potential weaknesses in these urban institutions. There is a need to improve local institutions’ image in front of communities as strong distrust further complicates flood risk reduction initiatives. Local institutions and communities need to work together to realize the full potential of the disaster management cycle and disaster risk reduction approach ( Rana et al., 2021 ). Flood management institutions and their responsibilities are shown in Figure 10 .

FIGURE 10 . Flood management institutions and their responsibilities developed after ( Ali, 2013 ; Rana et al., 2021 ).

To cope with the situation, there must be a multi-pronged approach, as suggested there is a strong need for water reservoirs, which can be fulfilled through water policy. Secondly, the early warning system and relevant institutions must reach the grassroots level to cope with the emergency in a better way. Thirdly, the whole management machinery of the area remains dependent upon a certain institution, Pakistan Administrative Services. There is a strong to segregate the departmental responsibilities and develop new departments ensuring implementation. Lastly, the citizens must have a civic sense or understanding of the nature of the information provided to them in the wake of floods.

In April 2018, Pakistan’s four provincial chief ministers endorsed the country’s first regional water policy. The National Water Policy’s goal is to address the growing water problem and include an overarching policy structure and recommendations for a robust action plan. The National Water Policy provides a specific policy structure and collection of water protection standards based on which the Provincial Governments will devise their development plans and water conservation, water improvement, and water management projects ( GoP National Water Policy, 2018 ).

5 Conclusion

Floods are a frequently occurring phenomenon due to heavy monsoon rains in Pakistan. The size and magnitude of the floods that Pakistan has confronted in the last few years would have been a problem for any nation. Recent severe floods have shown that there is a lack of adequate cooperation between flood control agencies, due in part to shortcomings in current technological capacities, such as warning signals, preparedness initiatives, disaster response, and systemic flood prevention measures. This is important to further develop flood monitoring and alert systems to reduce the damages of potential floods. Although Pakistan’s flood warning and detection systems have shown their effectiveness, the forecasting ability of the network is still weak. At the same time the institutions, NDMA and PDMA, operate at national and provincial levels, dispersing the rehabilitation responsibilities to local bureaucracy rather than establishing a grassroots-level structure with reference to small cities and villages. It also makes rehabilitation procedures weak and ineffective in most areas. Nonetheless, a cohesive response by the Pakistani community and the combined efforts of all the international and domestic agencies concerned remained crucial. Only providing damage reimbursements to flood victims is not the remedy; we need to get rid of this problem. Pakistan’s water management also needs to develop more reservoirs—lakes, and dams as a way to combat floods. The government should generate and incorporate robust public awareness initiatives to educate the public on flood risks and flood preparedness. In conclusion, to achieve effective flood control, a risk-based proactive strategy is needed.

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Open access funding provided by UiT The Arctic University of Norway.

Conflict of interest

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

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Keywords: major floods, flood management, social and economic cost, flood control, flood impacts

Citation: Manzoor Z, Ehsan M, Khan MB, Manzoor A, Akhter MM, Sohail MT, Hussain A, Shafi A, Abu-Alam T and Abioui M (2022) Floods and flood management and its socio-economic impact on Pakistan: A review of the empirical literature. Front. Environ. Sci. 10:1021862. doi: 10.3389/fenvs.2022.1021862

Received: 17 August 2022; Accepted: 22 November 2022; Published: 01 December 2022.

Reviewed by:

Copyright © 2022 Manzoor, Ehsan, Khan, Manzoor, Akhter, Sohail, Hussain, Shafi, Abu-Alam and Abioui. 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: Muhsan Ehsan, [email protected] ; Tamer Abu-Alam, [email protected]

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• Published: 14 March 2023

A framework for multi-sensor satellite data to evaluate crop production losses: the case study of 2022 Pakistan floods

• Faisal Mueen Qamer 1   na1 ,
• Sawaid Abbas 2 , 3   na1 ,
• Bashir Ahmad 4 ,
• Abid Hussain 1 ,
• Aneel Salman 5 ,
• Sher Muhammad 1 ,
• Muhammad Nawaz 4 ,
• Sravan Shrestha 1 ,
• Bilal Iqbal 4 &
• Sunil Thapa 1  

Scientific Reports volume  13 , Article number:  4240 ( 2023 ) Cite this article

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• Climate-change impacts
• Climate sciences
• Environmental sciences

In August 2022, one of the most severe floods in the history of Pakistan was triggered due to the exceptionally high monsoon rainfall. It has affected ~ 33 million people across the country. The agricultural losses in the most productive Indus plains aggravated the risk of food insecurity in the country. As part of the loss and damage (L&D) assessment methodologies, we developed an approach for evaluating crop-specific post-disaster production losses based on multi-sensor satellite data. An integrated assessment was performed using various indicators derived from pre- and post-flood images of Sentinel-1 (flood extent mapping), Sentinel-2 (crop cover), and GPM (rainfall intensity measurements) to evaluate crop-specific losses. The results showed that 2.5 million ha (18% of Sindh’s total area) was inundated out of which 1.1 million ha was cropland. The remainder of crop damage came from the extreme rainfall downpour, flash floods and management deficiencies. Thus approximately 57% (2.8 million ha) of the cropland was affected out of the 4.9 million ha of agricultural area in Sindh. The analysis indicated expected production losses of 88% (3.1 million bales), 80% (1.8 million tons), and 61% (10.5 million tons) for cotton, rice, and sugarcane. This assessment provided useful tools to evaluate the L&D of agricultural production and to develop evidence-based policies enabling post-flood recovery, rehabilitation of people and restoration of livelihood.

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Introduction.

There is increasing scientific evidence that human-induced climate change has caused severe environmental impacts and jeopardised global food security 1 , 2 , 3 . The frequency of floods and other extreme events has increased recently in South Asia and worldwide 4 causing significant loss and damage, particularly in Pakistan 5 . Since the independence of Pakistan in 1947, the recurrence of the major flood is almost a decade or less, mostly due to heavy monsoon rainfall in July and August causing severe losses in terms of human lives, agriculture, infrastructure, property, and economy. Three major floods occurred in the last decade in 2010, 2011, and 2012, where the 2010 floods caused inundation of over 70,000 km 2 and affected around 900,000 households 6 . The most recent’ 2022 Pakistan floods’ impacted approximately 33 million people, killing nearly 1500 people, and destroying critical infrastructure, agricultural land, and properties. In August 2022 Balochistan province of Pakistan received 590% more rainfall than normal while Sindh received 726% more rainfall than average for this month 7 . The World Weather Attribution group reports a 75% increase in heavy rainfall during the 60 days in the Indus River basin of Pakistan 8 .

The 2010, 2011, and 2022 floods in Pakistan affected approximately 55–60 million people with over 3500 deaths 6 , 9 , 10 . The floods in 2011 inundated over 21,000 km 2 area, displaced 5.9 million people and damaged 1500 km of the road network, 382 km of railway tracks, 500 km 2 of forests and over 16,000 km 2 of agricultural land 6 . The 2012 floods inundated 13,157 km 2 of the area in 22 districts of Pakistan damaging 2950 km 2 of agricultural land, 1681 km of the road network, and 110 km of railway track 9 .

The post-disaster damages assessment is extremely important in the context of global warming causing more frequent extreme events. The loss and damages (L&D) assessment is key to post-disaster recovery and rehabilitation under the conference of parties (COP) commitments 11 . Frameworks of L&D assessments enable evidence-based policies to reduce the risk of disaster and its impacts on various sectors. Adaptation of the L&D mechanism in the agriculture sector (Fig.  1 ) can help in monitoring and evaluating the economic impacts of disasters and support the compensation mechanisms. The damages are partial or complete destruction of physical assets while production losses refer to declines in the value of agricultural production resulting from a disaster. The production losses not only cause deficits in the income of impacted communities but may also result in near-term food shortages in the region and it is likely to slow down the post-disaster recovery if not properly managed.

Key elements of agricultural Loss & Damage assessment.

Satellite remote sensing is a powerful tool for assessing L&D caused by natural disasters such as floods, hurricanes, and earthquakes. Particularly for flood disaster, Synthetic Aperture Radar (SAR) satellites data can efficiently map flood extent 12 , 13 and optical satellites can be used to detect differences in vegetation cover before and after a flood to assess the damage caused by flooding 14 , 15 . Researchers have developed mathematical models to estimate flood losses based on the physical processes in a river basin and stage-damage relationship for different land use features for economic loss estimation 16 . As such, a novel index Disaster Vegetation Damage Index (DVDI) was also developed to map the post-flood crop-specific damage that occurred soon after the flood event 16 . In earlier work on crop loss assessments from Earth Observation, a Cyber Service system (RF-CLASS) was designed to estimate crop losses for insurance decision-making 17 . Likewise, the temporal differences in the satellite-derived Normalized Difference Vegetation Index (NDVI) have been applied for depicting changes in vegetation conditions to determine the impacts of extreme climate events on tropical secondary forest succession 18 , 19 . Another study developed an integrated approach by combining the NDVI, Land Surface Temperature (LST), and satellite-based estimates of rainfall to characterize vegetation moisture stress in land covers including forest, shrubland, agriculture and grass 20 , 21 .

Building on earlier work on L&D assessment and accommodating the recent advances in satellite remote sensing, we developed an approach for evaluating crop-specific post-disaster production losses, in the severely affected Sindh province of Pakistan. The tools and methodologies developed in this study will support evidence-based policies for food security and resilient reconstruction. This will also contribute to standardise reporting on climate change-related losses.

Materials and methods

Description of the study area.

The study area comprises the Sindh province of Pakistan (Fig.  2 ), with a total land area of ~ 14.1 million ha, of which ~ 35% (4.9 million ha) is agricultural land. Approximately one-fourth of the national economy comes from Sindh, of which 17% is contributed by the agriculture sector. The agricultural lands are irrigated by Indus Basin Irrigation System to grow various crops in the province. The major crops in the study area include cereal crops (wheat and rice), industrial crops (cotton and sugarcane), fruit crops (mango and guava), and horticultural crops (chilli, tomato, and sunflower). The climate of Sindh is Subtropical, with hot summers (May–August) and cold winters (December–January). Temperature ranges from 2 °C in winter to 46 °C in summer. Mean annual rainfall is about 150–180 mm but most of this amount falls during the monsoon season (July–September).

Location map of the study area and crop production zones in the Sindh Province of Pakistan, the maps were produced using the ArcGIS 10.7 ( www.esri.com ).

Remote sensing and ground-based rainfall estimates

The estimates of incidental rainfall were derived from the Integrated Multi-satellitE Retrievals for GPM (IMERG), GPM_L3/IMERG_V06, which is based on the unified algorithm combining data to generate a multi-satellite precipitation product 22 . The hourly rainfall product was used for spatially contiguous rainfall estimates as an alternative to scarcely distributed station data in the study area. The data were obtained and processed using the Google Earth Engine (GEE), a cloud computing platform, to derive daily estimates at a native spatial resolution of 0.1° (~ 1 km). The data was acquired from 1st August 2022 to 31st August 2022. Historic (1981–2010) and recent (August 2022) daily rainfall measurements from the ground stations (namely Mohenjo Daro, Sakran, Padidan, Larkana, Badin, Jacobabad, Nawabshah, and Rohri), in the study area, were acquired from Pakistan Meteorological Department (PMD). These data sets were used for relating the satellite-based rainfall estimates with ground observations. The daily rainfall estimates were also aggregated at the monthly interval to understand the spatial patterns of monthly accumulated rainfall during August 2022.

Flood extent mapping

Flood extent was mapped using pre- and post-event C-band Synthetic Aperture Radar (SAR) images from Sentinel-1B. The calibrated and ortho-corrected Level-1 Ground Range Detected (GRD) images at 10 m spatial resolution were obtained and processed using the ‘COPERNICUS/S1_GRD’ collection available on the GEE. Two sets of SAR images were acquired from, (1) May to July 2022, and (2) 22nd August to 3rd September 2022. Due to the specular reflectance of C-band signals, the backscatter from flooded areas or water bodies is significantly lower compared to other non-water areas, this enables rapid extraction of the flooded area from the SAR images 23 . Meticulous analysis of the pre-and post-flood images was performed to apply a parametric thresholding approach by splitting the histogram into the target and background classes to create binary maps indicating flooded and non-flooded areas 24 , 25 , 26 . Later, the binary images were processed to generate a flood extent map for subsequent analysis.

Delta NDVI analysis for changes in greenness and damage assessment

To assess the intensity and spatial patterns of the flood’s impact on in-season crops, pre and post-flood images of Sentinel-2 were assessed to estimate the loss in greenness. The NDVI (Eq.  1 ), a frequently used indicator of green biomass 27 , was calculated using the reflectance wavebands corresponding to the Red and Near Infra-Red portion of the electromagnetic spectrum. Changes in the NDVI are related to photosynthesis and leaf cell structure which indicates a plant’s vigour, greenness and productivity 28

where, \({NIR}_{\sigma }\) denotes the NIR reflectance band and \({Red}_{\sigma }\) corresponds to the Red reflectance bands.

To analyze and understand the phenology patterns associated with crop development phases, the NDVI was derived from all the available satellite images over the study area. It was noted that greenness over the cropland rapidly increases during August indicating a critical crop development phase during this period. Therefore, to incorporate the phenological differences and to compensate for the noise in the data, maximum NDVI value composite images (22nd August–3rd September) were developed for 2021 and 2022. A delta NDVI image (Eq.  2 ) was derived from the pre and post-flood NDVI composite images.

where \({NDVI}_{f}\) and \({NDVI}_{n}\) represents post and pre-flood NDVI composite images, respectively.

This delta NDVI image measures the loss and damage to cropland biomass, where the negative values correspond to the intensity of damage to cropland greenness or biomass due to flood-water inundation or incidental rainfall, while positive values show normal conditions. The resultant difference map was divided into eight classes representing extreme damage (< − 0.50], very severe damage (− 0.5 to − 0.4], severe damage (− 0.4 to − 0.3] moderate damage (− 0.3 to − 0.2], slight damage (− 0.2 to − 0.1], very slight damage (− 0.1 to 0], near normal (0–0.1) and normal (> 0.1). The loss and damage map was masked by the cropland mask derived from the ESA’s World Cover at 10 m resolution 29 . Later, to simplify the legend, the classes were lumped into three major classes representing severe loss (extreme damage and severe damage), mild loss (all other damage classes) and no loss (near normal and normal) for generating statistics at administrative levels. Then the percentage of loss or damage of cropland was aggregated at Tehsil and Districts level administrative boundaries for subsequent analysis. To distinguish the damage from continuous inundation and incidental rainfall, the loss and damage image was also masked by the flood extent map.

Other data sources

The cropland, non-cropland and other land use land cover masks were developed from the ESA WorldCover 10 m 2020 v100 ‘© ESA WorldCover project 2020/Contains modified Copernicus Sentinel data (2020) processed by ESA WorldCover consortium’. The dataset is produced with 11 classes using Sentinel-1 and Sentinel-2 data 30 .

The population density data were obtained from the standardized global population distribution at 1 km spatial resolution provided by the LandScan™ Global Population Distribution Dataset (ORNL) 31 . Other data sources and data used for this study include administrative boundaries, Agriculture sector data 32 , field-based damage reporting data by the Provincial Disaster Management Authority, Sindh (PDMA), and Pakistan Crop statistics: Pakistan Bureau of Statistics.

Analysis and aggregation of the data

Rigorous data analysis was performed to estimate and quantify loss and damages to cropland. The losses to agriculture and livestock were also converted to direct economic losses. For this, overlay analysis and zonal statistics of the flood extent map, NDVI loss and damage layer, incidental rainfall, and cropland masks were performed to map spatial extent and estimate area under flooded cropland, non-flooded cropland, agricultural damage due to incidental rain, severe and mild losses to the greenness of cropland. All the metrics were aggregated at district and tehsil (sub-district) boundaries to generate statistics for the administrative units. Percentage losses and damages were also calculated at the administrative units to understand the spatial spread of the flood’s impacts across the province. The loss and damage to the greenness of cropland were tabulated to rank the tehsil boundaries according to the majority of pixels belonging to the severity of the loss. Furthermore, maps were produced to portray the spatial distribution of flood extent and rainfall at the country level and detailed analysis and mapping were performed at the district and tehsil levels. This analysis framework is based on combining data from multiple satellites and ground-based information to assess and understand flood-induced damage and loss to cropland and livestock, and overall economic losses. The analysis was performed using the GEE and R.

Results and discussion

Above-normal rainfall in july and august across pakistan.

The 22nd Session of the South Asian Climate Outlook Forum (SACOF-22) was held in April 2022. According to the “Consensus Statement on the Seasonal Forecast over South Asia for the 2022 Southwest Monsoon Season”, the above-normal monsoon rainfall was projected in the South Asian region. An update of the consensus statement was also released in June 2022, reaffirming the extensive rainfall from July to September 2022. The national average rainfall in Pakistan for July 2022 was predominantly very high (+ 180%), with extremely high rains in Balochistan (+ 450%) and Sindh (+ 307%), the wettest for both in the last 62 years. The rainfall intensity was excessively increased in August 2022, the wettest ever August, with high above-average rainfall at the national level (+ 243%). Historically Sindh receives 150–180 mm of rainfall annually, which mostly comes in the monsoon season (July–September). Approximately six-fold rainfall was recorded in Balochistan (+ 590%) and Sindh received more than seven times the normal rainfall (+ 726%). The satellite-based rainfall estimates showed an extremely high intensity of monthly rainfall (~ 1000 mm) in the Sindh Province, nearly eight times its average rainfall in August (Fig.  1 ).

In August 2022, one of the most severe flash floods in the history of Pakistan was triggered due to above-normal monsoon rainfall in Balochistan, Sindh and southwest Punjab. The incidental and cascading rain-induced flooding started in July and both, rainfall intensity and flooding, progressively intensified in August which affected ~ 33 million people across the country. A sequence of flash floods started in July, and by the mid of August, one-third of the Sindh province was inundated by flood water. Moreover, the situation was further exacerbated by exceptionally high incidental rainfall (Fig. 4 ), for instance, 142 mm of rainfall was recorded in Naushahro Feroze District in a single day (11 August 2022), the highest monthly rainfall (1228 mm) in the province was recorded at the Padidan Town (Fig. 4 ) in the Naushahro Feroze District.

Flood water inundation

The flood extent mask for Pakistan (Fig. 4 b) was derived from the Sentinel-1 SAR images. Detailed and aggregated flood maps were also produced for effective visualization and hotspot analysis along with population intensity maps. Nearly one-fifth (18%, 2.5 million ha) of the total land area of the province was waterlogged due to rain-induced flooding. District-level assessment of flood water inundation indicated four severely affected districts (Figs. 3 , 4 , 5 ) including Jacobabad, Larkana, Qambar Shahdad Kot, and Shikarpur, where the flooded area covered around half of the district (Figs. 4 , 6 ). Due to the hill torrents in the Northeastern mountain ranges of Balochistan, the foothill areas in Balochistan and the north-western part of Sindh were severely affected by flash floods (Figs. 5 , 6 ). The situation was exacerbated by the heavy rainfall in the affected areas which included Jacobabad, Kashmore, Larkana, and Shikarpur (Fig. 6 ). The district where the flood water inundated around one-fourth of the district included Kashmore (31.54%), Naushahro Feroze (27.05%), Matiari (24.57%), Dadu (23.82%), Badin (23.41%), and Khairpur (22.87%). Analysis of the flood extent map and cropland mask from the ESA WorldCover 10 m v100 showed that ~ 1.1 million ha of the cropland area was inundated in the Sindh Province.

Source: Pakistan Meteorological Department (PMD).

Station-based records of rainfall during August ( a ) Monthly average rainfall across different weather stations in Sindh during August 2022 and historic average in August (1981–2010), ( b ) daily rainfall patterns during August 2022 recorded in corresponding districts across Sindh.

(Source: GPM -IMERG satellite data), ( b ) Fig.  1 : Flood extent in Pakistan on 28 August 2022 based on Sentinel-satellite data (Source: Sentinel-1 satellite data, the maps were produced using the ArcGIS 10.7 ( www.esri.com ).

( a ) Rainfall estimates for August 2022 in Pakistan

Flood water inundation ( a ) extent and patterns of flood-inundated areas in Jacobabad and Dera Murad Jamali on 28 August 2022 ( b ) ground condition information.

District-wise flood water inundation, ranked in descending order.

A visual comparison of the rainfall intensity patterns (Fig. 4 a) and flood extent map (Fig. 4 b) indicates two distinct regions, North West of Sindh and North Eastern Balochistan, were severely affected by flood-inundated water (Fig.  5 ). These foothill regions lie in arid zones and are characterised by a flash floods and/or flood water inundation. The flood water inundated the foothill area and emerged as a 100 km inland water lake. Whereas central Sindh experienced the highest intensity of incidental rainfall, the amount of inundated water is comparatively less. It was also noted that the waterlogged area continued to expand through the increased water discharge at the Guddu barrage and rainwater coming through the western mountain region of Balochistan province. This caused flooding around the Indus River due to which mobility in most parts of the province became limited and access was obstructed.

Damage to cropland

Sindh’s land area is ~ 14 million hectares of which ~ 35% (4.9 million ha) is used for agricultural purposes. Nationally, Sindh provides a significant proportion of summer crops including rice (42%), cotton (23%), and sugarcane (31%). The 2022 floods in Pakistan damaged the standing in-season crops, and huge quantities of grain in the storage, livestock, and infrastructure. The province is a production pocket of 14 Kharif season vegetables, 15 different fruits including major summer fruits, 5 different condiments and many cereal crops. This investigation did not estimate the specific crop type damages, nonetheless, an estimation of major crop losses and their spatial distribution was evaluated and discussed.

The mapping of flood water inundation and crop damage assessment showed that ~ 2.9 million ha (18% of Sindh’s total area) was inundated and ~ 57% (2.8 million ha) of the cropland was affected (Fig. 7 ). The flood struck at a key phase of crop development—the initial stage of plant growth. Temporal patterns of NDVI were analysed to understand the crops’ phenology patterns from June 2021 to 31st August 2022 (Fig. A1 ). The results indicated the critical crop development stage during August, where the NDVI values rise with a high rate of change, before reaching maturity or maximum seasonal growth (Fig. A1 ). A flat curve in August 2022 implied severe loss of crop greenness and damage (Fig. A1 due to flood water inundation and incidental rainfall (Fig. 3 ). Apart from the plant damage due to incidental rainfall at critical crop development phases, flood-induced water logging in cropland can also trigger abiotic stress in crops 33 by reducing light availability 34 , depletion of oxygen 35 , and changing the chemical properties of soil 36 . These alterations in the environment can significantly impede crop growth, vigour and yield 37 , 38 , 39 .

Loss and damage to cropland based on the NDVI difference ( a ) control or reference composite image, ( b ) composite image acquired during a flood event, ( c ) NDVI difference image indicating loss and damage to cropland. All the images were masked to cropland pixels. the maps were produced using the Google Earth Engine ( https://earthengine.google.com ).

The delta NDVI maps were used to calculate the losses in greenness over the cropland. The results (Fig. 6 c) were simplified into two classes indicating severe and moderate loss. It was noted that about ~ 36% of the cropland was severely affected while ~ 53% of the cropland was classified as moderately damaged. These losses included both the damages due to flood water inundation (one-third) and the remainder was directly damaged from torrential or incidental rainfall. The visual analysis of the NDVI changes (Fig. 6 ) along with rainfall and flood water inundation patterns suggested moderate damage to crops due to incidental rainfall but it was widely spread across the province. At the Tehsil level, the damage intensity ranges from ~ 90 to 50% (Fig.  8 ). According to the assessment, there were 50 Tehsils where the damage to the cropland was more than 50%. Nonetheless, it is important to discuss that the uncertainty in the NDVI-based analysis might prevail by changing the satellite images and composite period due to variation in crop development phases of the control image, emergence of herbaceous vegetation 39 , waterlogging tolerance of crops 38 , and death of the plants due to elongated flooded 38 . Moreover, in the mildly affected croplands, the production losses in yield could also vary with the duration of flooding and type and/or a variety of crops 40 , 41 .

Tehsil-wise loss and damage to cropland derived from the NDVI difference map.

Remote sensing-based vegetation indices have been used to derive indicators for crop development stages and impacts of flooding on crop growth conditions compared to pre-flood conditions 42 , 43 , 44 , 45 , 46 , 47 . Recently, a framework is developed for an integrated assessment of flood impacts on crop protection in the Yangtze River Basin 39 . However, this study investigated the post-flood damage at the end of the crop growing season by taking the difference in vegetation index between the normal year and flood-affected year 47 . Moreover, conventionally, flood impact studies neglect the effect of spatial–temporal variations and in-seasons crop damage assessment in severely flooded areas. This study developed the delta NDVI composite maps to determine the in-season crop loss by leveraging the power of GEE cloud computing and the availability of high temporal resolution of Sentinel-2 images.

Figure A2 shows rice, cotton, and sugarcane are the three major commercial crops cultivated throughout Sindh in the Summer season (Kharif crops). The distribution patterns of these primary crops in the province in very significant (Fig. A2 ). Interestingly, each of these crops is affected differently, for instance, the rice crop is mostly affected by the water logged in the north-western part. It is estimated that ~ 80% of the rice crop production (~ 1.9 million tons of rice) is lost due to flooding (Figs. 2 , 6 , 9 , A2 ). The rice production zone was severely waterlogged due to the flooding which can extinguish plants by limiting light availability and oxygen supply. Table 1 summarises the expected loss in crop production at the district level. On the other hand, the sugarcane crop is predominantly cultivated in the northeastern districts along the Indus River. There was lesser evidence of flood water logging in the sugarcane zone, probably due to the better drainage mechanism of this side of the river and partially due to the well-grown plant of the sugarcane crop. However, the dispersed population and flooding could generate an expected loss of 61% (10.5 million tons) of the crop by the end of the crop-growing season. It was important to note that the cotton crop zone was the least inundated, nonetheless, the loss of cotton crop was significantly high due to the incidental rainfall. The hotspot of rainfall intensity was exactly over the cotton crop zone which could have severely affected the sensitive plants of the cotton crop. The total loss in cotton crop production is expected to be 88% (3.5 million bales) because of flooding and continuously exceptionally heavy rainfall. Considering the commodity prices of summer 2022 48 , these three crops faced a direct loss of USD 1.30 billion (rice: USD 543 million, cotton: USD 485 million, sugarcane: USD 273 million).

Cropland area and intensity of the damage to cropland due to flood at Tehsil level.

These estimates of production losses could be exacerbated while considering the abandoned or unattended agricultural fields due to dislocated and suffering population. It would be difficult for small farmers to immediately recover from loss which might trigger a household transition from on-farm to off-form work for livelihood 49 , 50 . Apart from the losses and damages that can be termed economic, the floods have caused more non-economic losses and damages that are difficult to assess in economic terms. These noneconomic losses may be more significant for developing countries for which such losses should become a central aspect of climate change policy. When land is lost or rendered unsuitable for agriculture the rich landowners may suffer greater losses in economic terms.

The rapid assessment loss estimates through this approach closely match with the detailed Post-Disaster Needs Assessment 51 which reports cotton as the most affected crop followed by rice and sugarcane. It has been observed that rapid estimates of disaster losses for major events are more accurate than the small-scale local disaster loss events 51 . The true economic costs of climate change are difficult to quantify due to a lack of reliable data. The costs of climate change are often long-term and uncertain, making it difficult to accurately measure. The losses related to long-term impacts like reduction of soil productivity and indirect costs such as displacement and disruption to local economies may be difficult to quantify, while the intangible costs associated with loss and damage (such as emotional distress, loss of culture and traditional knowledge, etc.) cannot be measured.

Conclusion and recommendations

Numerous efforts are being made to reduce agriculture losses and damage to assets ahead of impending hazards by providing forecasts and early warning. However, the frequency of natural disasters has increased due to climate change and exacerbates food security issues across the globe, especially in developing economies. Therefore, apart from precise predictions of changing weather, e.g., floods, erratic and above-normal rainfall, and droughts; it is required to quickly evaluate the impacts of disasters to avoid their cascading effects. This study presented a multi-satellite/sensor-based framework to quantify the impacts of flooding, water logging and torrential/or incidental rainfall on in-season crops in the Sindh province of Pakistan. The province provides a significant portion of major crop production in the country including wheat (16%), rice (42%), cotton (23%), sugarcane (31%), vegetables and other horticulture crops.

It is equally important to translate climate-induced losses into the economic cost to quantify the benefits of the adaptation strategies. This can enable the implementation of resource allocation for a holistic climate change adaptation in public expenditure reporting. The information derived from this analytical framework can be incorporated into L&D assessment for informed decision-making not only during the catastrophe and rehabilitation of the affected people, but it can also help to timely plan for the economic losses and looming crisis of food security in the country. The framework could be extended and further developed to integrate economic losses of crop damage, loss of agriculture infrastructure and equipment and disruption in supplies and services. It is difficult to accurately attribute losses and damages to climate change due to the complexity of the climate and governance systems resulting in cumulative losses. Also, the costs of climate change are often long-term and uncertain, making it difficult to accurately measure.

Data availability

The satellite datasets were processed and obtained using the cloud computing platform, Google Earth Engine. All the datasets are available. The datasets analysed during the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

This paper and material used are based upon the work supported under the SERVIR HKH program of ICIMOD. We thank the anonymous reviewers for their constructive comments and suggestions. The boundaries, names, and designations indicated on these maps do not imply the expression of any ICIMOD opinion concerning the legal status of any country, territory, city, area, their associated authorities, or demarcations of their frontiers or boundaries. The views expressed herein are solely those of the authors and do not necessarily reflect those of the organizations mentioned above.

The research was supported by the International Centre for Integrated Mountain Development (ICIMOD).

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International Centre for Integrated Mountain Development (ICIMOD), Islamabad, Pakistan

Faisal Mueen Qamer, Abid Hussain, Sher Muhammad, Sravan Shrestha & Sunil Thapa

Smart Sensing for Climate and Development, Center for Geographical Information System, University of the Punjab, Lahore, Pakistan

Sawaid Abbas

Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong

Pakistan Agricultural Research Council (PARC), Islamabad, Pakistan

Bashir Ahmad, Muhammad Nawaz & Bilal Iqbal

Islamabad Policy Research Institute (IPRI), Islamabad, Pakistan

Aneel Salman

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F.M.Q., S.A.. and B.A. conceived, designed and wrote the paper. F.M.Q., and S.A. conducted the data analysis. A.H., A.S., S.M., M. N., S.S., B.I., and S. T. participated in processing, analysis, and discussion.

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Qamer, F.M., Abbas, S., Ahmad, B. et al. A framework for multi-sensor satellite data to evaluate crop production losses: the case study of 2022 Pakistan floods. Sci Rep 13 , 4240 (2023). https://doi.org/10.1038/s41598-023-30347-y

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Applying Spatial Analysis to Assess Crop Damage: A Case Study of the Pakistan 2022 Floods

Yamano, T and Gumma, M K and Panjala, P and Haq, N U and Fahad, M and Sato, N and Arif, B W and Saeed, U (2024) Applying Spatial Analysis to Assess Crop Damage: A Case Study of the Pakistan 2022 Floods. Working Paper. ADB publications, Philippines.

Global Research Program - Resilient Farm and Food Systems

Additional Information

This working paper was written by Takashi Yamano, principal economist, Economic Research and Development Impact Department (ERDI), Asian Development Bank (ADB); Murali Krishna Gumma, principal scientist and cluster leader, Global Burden of Diseases Study (GBDS), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT); Pranay Panjala, senior scientific officer, GBDS, ICRISAT; Nauman Ul Haq, remote sensing and geographic information system (GIS) specialist (independent consultant); Muhammad Fahad, agriculture and remote sensing specialist (independent consultant); Noriko Sato; senior natural resources specialist; Agriculture, Food, Nature, and Rural Development Sector Office; Sectors Group (SG-AFNR), ADB; Babur Wasim Arif, economist (independent consultant); and Umer Saeed, agriculture climate change specialist (independent consultant). The authors benefited from the contribution of the following ADB staff: Paolo Manunta, senior digital technology specialist (earth observation), Climate Change and Sustainable Development Department (CCSD); Martino Pelli, senior economist, ERDI; Nathan Rive, senior climate change specialist, CCSD; Asad Ali Zafar, senior project officer (water resources), Central and West Asia Department (CWRD); and Nasruminallah Mian, senior programs officer, CWRD. Kristine Joy V. Obedoza, senior operations assistant SG-AFNR, ADB provided support to the publication process; and Jill Gale de Villa, knowledge management specialist (independent consultant), provided substantial edits to this publication. The ground truthing surveys were designed and conducted by the following: Nauman Ul Haq and Muhammad Fahad with the support of the following staff from CAB International: Shakeel Ahmad, agriculture sector specialist; and Hamza Saeed, agriculture and remote sensing specialist. This report was produced and funded by two technical assistance (TA) projects: Using Frontier Technology and Big Data Analytics for Smart Infrastructure Facility Planning and Monitoring (TA 6721); and Strengthening Food Security Post-COVID-19 and Locust Attacks, Pakistan (TA 6663).

Pakistan is highly flood-prone and faces a growing risk of water-related disasters due to predicted impacts of climate change. From 1950 to 2021, each of the major floods claimed more than 400 lives in Pakistan, except the 1950 flood that claimed at least 2,000 lives. The latest flood in 2022 resulted in 1,678 deaths, which included 555 children. The Food and Agriculture Organization of the United Nations estimates that 55,000 square kilometers of land were flooded. This report presents how spatial analysis could be used to assess flood damage to agricultural production by applying the analysis to the 2022 Pakistan floods. It recommends that spatial analysis capacity should be established within government agencies to ensure better preparedness for mitigating damages of future water-related disasters. Using spatial analysis and a spectral mapping technique, the 2022 flood damage was assessed for four periods during June–September 2022 in Pakistan. The assessment conducted during the first half of September 2022 indicated that about 15% of crop areas were modestly or severely damaged. The accuracy of the technique was verified by cross-checking with data gathered at the actual locations on the ground. Subsequently, a monthly damage assessment system has been established and is circulating monthly reports to government agencies to help them prepare for future floods and other crop damage. Spatial mapping can also be used to assess the impact of crop disease, pest infestations, drought, and others, and to inform policy makers and decision makers about situations pertinent to the national food supply, export earnings, and crop insurance. Spatial mapping can provide estimations of crop health for a wider area and do so faster than ground estimations, which require large amounts of resources, such as labor and transport, and are difficult to implement after floods or other natural hazards. Key recommendations to facilitate the use of technology to enhance crop monitoring are as follows: (i) increase the number of geographic information system and remote sensing specialists in relevant government agencies such as crop reporting services and statistics offices; (ii) integrate the use of spatial analysis into statistical reporting systems to improve their accuracy and timeliness. The spatial analysis can provide preliminary results that can be verified by field observations; (iii) familiarize policy makers with and enable them to interpret spatial analysis results to help them make more effective decisions. Circulate periodic spatial analysis reports among policy makers to earn their trust in the analysis; and (iv) plan policy actions for early detection of crop damage, rapid field verifications, mobilization of adequate financial and material resources, and effective communications with affected populations. Images from spatial analysis can be released through media or posted on government websites.

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The 2022 Pakistan floods

Introduction

More than one-third of Pakistan is under water due to unprecedented levels of flooding. Estimates suggest that 1,265 people have been killed, with 6,000+ injured.  

The scale of the tragedy is already being compared to the devastating floods of 2010 when more than 2,000 people were killed, marking the event as the deadliest in Pakistan’s history.

There are four provinces in Pakistan: Balochistan, Khyber Pakhtunkhwa, Punjab, and Sindh plus the Islamabad Capital Territory. The Sindh province is bisected by the Indus, Pakistan’s largest river, which flows from the upstream northern highlands of the Himalayas down to the Arabian Ocean.

Glacial meltwater from the Himalayas and Karakoram mountain range plus snow melt and monsoon rains all supply the Indus with water. The Indus is 3,200 km long and has a large discharge of 5,533 m 3 /s (approximately twice as much as the river Nile in Egypt, placing it 52 nd in the world). Flooding often occurs in the southeast of the country, in the Sindh province.

Figure 1 a topographic map of Pakistan, the Sindh provincial capital is Karachi

However, the average discharge for the Indus does not accurately depict the situation in Pakistan because there are extreme spikes in flow, discharge, and flood water at times throughout the year. For example, last week the Indus burst its banks and as much as 17,000 m 3 /s of water was discharged. This was caused by Pakistan receiving 190% more rainfall from June to August (compared to average rainfall for this time period over the past 30 years).

The Sindh province to the south of the country has been severely impacted, as it has a wide flat central plain (the Indus river valley), covering 51,800 km 2 .

Sindh province

The main economic industry of Sindh is agriculture, which the Indus river has supported for millennia.

The flow of the Indus is typically high between mid-July and mid-August due to environmental factors.  However, this year rainfall in Sindh has been exceptionally heavy in recent months.

Figure 2 rainfall is well above average in most regions across Pakistan © BBC

Is climate change to blame?

Recent heavy rainfall is only part of the story. This flood event is widely being reported as a climate-related disaster due to extreme changes in monsoon behaviour, precipitation patterns, and melting glaciers.

These contributing factors have been accentuated by increases in global temperature. The UN secretary general, António Guterres, emphasised the link to climate change saying “today, it’s Pakistan. Tomorrow, it could be your country” signalling to the world that more needs to be done in the fight against climate change.

The monsoon rainfall was particularly heavy this year due to changes in air temperature across the Arabian Ocean. It is likely that climate change affected the intensity of the monsoon as record amounts of rain fell across the country throughout August (as much as 500-700% more than usual).

The IPCC has reported that South Asia has warmed by around 0.7°C since 1900. This leads to heavy monsoon rain because the warmer atmosphere holds more moisture.

The likelihood of seeing phenomena that may cause severe monsoon conditions is likely to increase. This year, the La Niña event in the Pacific and meanders in the jet stream created perfect conditions for the unusual monsoon rains.

Glacial melt is a growing problem around the world. In Pakistan this is a particular problem as the country has more glaciers than anywhere else in the world, (there are 7,000) excluding the polar regions. This year there has been triple the usual amount of glacial lake outbursts, causing catastrophic flooding.

Table 1 a brief summary of the 2022 Pakistan floods

Further work

• BBC Pakistan floods: One third of country is under water - minister
• Publishing Service UK Government Pakistan Toponymic fact file 2019
• Reuters South Pakistan braces for yet more flooding as waters flow down from north
• BBC Pakistan floods: Time running out for families in Sindh
• NASA World of Change: Seasons of the Indus River
• BBC Pakistan floods: Map and satellite photos show extent of devastation
• CNN Pakistan's melting glaciers are 'erupting' and worsening floods
• The Conversation Pakistan floods: what role did climate change play?

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The 2022 Pakistan floods (1)

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Today's Paper | April 30, 2024

Adb asks pakistan to use spatial mapping to mitigate damages.

ISLAMABAD: A case study by the Asian Development Bank (ADB) has presented real-time crop assessments of the 2022 massive floods in Pakistan and strongly recommended developing spatial analysis capacity within government agencies to ensure better preparedness for mitigating damages of future water-related disasters.

The case study of the ‘Pakistan 2022 Floods’, released this week, observed that spatial mapping could also be used to assess the impact of crop disease, pest infestations, drought, and others and to inform policymakers and decision-makers about situations pertinent to the national food supply, export earnings, and crop insurance.

The study suggests spatial mapping can also provide estimations of crop health for a wider area and do so faster than ground estimations, which require large amounts of resources, such as labour and transport, and are difficult to implement after floods or other natural hazards.

Among its key recommendations to facilitate the use of technology to enhance crop monitoring, the study recommended increasing the number of geographic information system and remote sensing specialists in relevant government agencies such as crop reporting services and statistics offices and integrating spatial analysis into statistical reporting systems to improve their accuracy and timeliness.

The use of technology can also familiarise policymakers and enable them to interpret spatial analysis results to help them make more effective decisions and plan policy actions for early detection of crop damage, rapid field verifications, mobilisation of adequate financial and material resources, and effective communication with the affected population.

The study also suggests that early detection, rapid field verification, and timely resource mobilisation can mitigate damage and help policymakers plan for robust recoveries from crop damage. The experience of the 2022 floods highlights the importance of these preparations and the need for using visual presentations of spatial analysis to communicate with the public and affected communities.

According to the ADB study, Using spatial analysis and a spectral mapping technique, the 2022 flood damage was assessed for four periods during June-September 2022 in Pakistan. The assessment conducted during the first half of September 2022 indicated that about 15 per cent of crop areas were modestly or severely damaged. The accuracy of the technique was verified by cross-checking with data gathered at the actual locations on the ground.

The study says that more than a year before the 2022 floods, the ADB started working with Pakistan government agencies and local consultants to provide them with spatial information technology skills and equipment so that they could conduct crop damage assessments.

The study reminds us that climate change is expected to increase the frequency and magnitude of floods and other extreme weather events in the future. Thus, the Government of Pakistan must be prepared to mitigate the damage. It is crucial to plan how to use real-time crop damage assessments such as spatial analysis to plan for immediate disaster assistance and recovery efforts.

The study indicated that the crop stress maps of the 2022 floods were shared with the national and provincial ministries and international organisations. Such reports were a novelty to them and were first received with scepticism and many questions.

Their responses indicated the importance of damage assessment per type of crop (rice, wheat, maise, pulses, and others), whereas the maps at the time were generic, and the intended audience needed a better understanding of the system.

The study says establishing a reliable crop stress reporting system will help government agencies prepare for future floods. For this purpose, in February 2023, the ADB project team started sharing monthly reports with relevant government agencies, which were asked to comment on the reports. Because agriculture policy is a provincial matter, monthly reports were developed for each province and shared with national and provincial government agencies.

Published in Dawn, April 28th, 2024

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The 2022 Pakistan floods

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Climate change and extreme weather

GCSE geography specifications require you to understand the links between climate change and extreme weather events. This article looks at the 2022 floods in Pakistan as a case study.

• Volume 34, 2022/ 2023
• Natural disasters
• Weather systems
• (Global) Physical Geography

Alice Mollison

Scientists believe that the 2022 floods in Pakistan, which displaced more than 30 million people, are linked to climate change, with some areas having three times the usual amount of rainfall following a period of extremely high temperatures. It is a fact that countries which contribute the least carbon dioxide emissions are often most affected by climate change. While Pakistan contributes only 0.7% of global greenhouse gases it is the eighth most vulnerable country in the world to the effects of climate change.

In August and September 2022, Pakistan was hit by major floods causing thousands of deaths, injury, disease and homelessness. The pictures on our screens at that time showed the misery and devastation caused by the floods. At least 1,700 people were killed, of whom 600 were children. Land was submerged by floodwater for many months, leading to widespread disease and malnutrition.

Again, children were the most badly affected. Millions lost their homes in the flood and became homeless.

Figure 2 shows that all areas of Pakistan had more rainfall than usual in 2022, but that Sindh Province was particularly badly hit, with more than five times the usual amount of rain. Sindh Province is important for its agricultural output, producing rice, cotton, and sugarcane.

What caused the floods?

A large proportion of Pakistan’s population live close to the Indus river, the discharge of which is fed by the summer melt of the glaciers of the Himalayan and Karakoram mountains. In addition, the annual monsoon brings heavy rainfall between July and September. Over 70% of the country’s rain is brought by the monsoon. Rivers flood every year but sometimes the floods are particularly bad, and 2022 saw some of the worst floods ever experienced. At times 17,000 cumecs of water were flowing in the Indus river, about three times its usual discharge, and one third of Pakistan was under water, with a 100-kilometre long lake forming in the Sindh Province.

A number of factors contributed to the severity of the floods, all of which are linked to climate change.

Average temperatures have risen by 0.7°C in South Asia since 1900, but in Pakistan over the past 30 years they have risen by about 0.3°C each decade, higher than the global average. Along with these long-term trends, there was a heatwave in the spring of 2022, with temperatures regularly exceeding 40°C. Temperatures even reached 51°C in Jacobabad, a city in the Sindh Province. Scientists think that climate change has made these heatwaves 30 times more likely to occur.

Each year between July and September heavy monsoon rains are brought by low-pressure systems that move over Pakistan. However, the 2022 heatwave meant the air rose more rapidly than usual, causing particularly low pressure. Warmer air can also hold more moisture (about 6% more for each 1°C rise), leading to heavier than normal rainfall. The 2022 monsoons were the country’s most severe since records began in 1961, with three times the average annual rainfall across the country.

Another consequence of the heatwave was that glaciers in the Himalayas and Karakoram mountains melted more rapidly, and Pakistan has 7,000 glaciers in its northern regions. This meant there was more glacial meltwater in the rivers and also that there were three times more glacial lake outbursts than usual.

■ Scientists also think that a weather phenomenon called La Nina contributed to increased rainfall in Pakistan. La Nina causes surface cooling of the Pacific Ocean west of South America and alters wind patterns, pushing more warm water towards Asia, and this increases rainfall. La Nina usually occurs in cycles and lasts for 2 years, but in 2022 it lasted into a third year. Scientists are still exploring whether climate change led to the 2022 La Nina.

The heavy monsoon rain together with the glacial melt water led to vast amounts of water in the rivers, filling the tributaries which flow into the Indus causing widespread flooding.

Immediate impacts of the floods

■ 1,700 people died, including 600 children

■ 33 million people were affected, 15 million of these in Sindh Province

■ 1,000 health facilities damaged in Sindh

■ 1.8 million homes across Pakistan were damaged and many were destroyed. Mud brick homes were particularly vulnerable

■ Increase in incidence of disease, especially diarrhoea, dengue fever, malaria and typhoid

■ 50% of sanitation and hygiene facilities destroyed in Sindh

■ Mental health, especially of women, suffered due to lack of toilet facilities

■ 22,000 schools were damaged or destroyed

■ Infrastructure damaged, including 150 bridges and 3,500 roads, and no electricity for more than 10 days

■ 700,000 livestock killed

■ 3.6 million acres of crops destroyed, particularly rice and sugar cane in Sindh

■ Food insecurity

The last extreme flooding event was in 2010, affecting about one million people. After these floods there were plans to improve flood warning systems, but five changes of government since then has made it hard to implement the plans and the country’s flood warning and disaster management systems are still not very effective.

In 2022, four times more land was flooded and twice as many people were affected. It has been suggested that human activity exacerbated the effects of the flood. A large number of people live in poverty and there has been long-term urbanisation in areas at risk of flooding, particularly in the Sindh Province, where 52% of people live in urban areas, which means there is more rapid surface runoff.

Longer-term impacts of the floods

Many people were affected by the 2022 floods and the country has seen significant economic losses, including severe impacts on agricultural output. In addition, there are major concerns about long-term malnutrition and ill health from waterborne diseases, and the United Nations has suggested that the death toll from these could be higher than the deaths from the flood itself.

Despite huge amounts of emergency aid including food and sanitation supplies, most farmers have been unable to plant the food crops which were due to be harvested in 2023, meaning families will have to rely on international aid and food will have to be imported throughout the year.

Pakistan is the fourth-largest exporter of rice in the world, and the huge loss of rice has had global consequences, causing shortages and price increases, particularly in countries such as Indonesia and Benin, which rely on rice imports from Asia.

During the last 20 years, there has been a significant fall in the amount of poverty in Pakistan, linked to the move from farming to secondary and tertiary industries and to successful social welfare projects. However, 43% of the population is still employed in agriculture and many people earn less than £2.70 per day. Even before the floods the country was facing a growing economic crisis caused by multiple factors including rapidly rising prices for imported goods, many years of high spending on the military, not generating enough money through taxes and a major reliance on big loans from other countries which it hasn’t been able to repay. Consequently the floods were truly a disaster for Pakistan.

Glacial lake outburst When glaciers melt, water builds up in lakes in front of the ice, trapped by sediment (moraine) previously deposited by the glacier. These lakes may burst if, for example, the lake gets too large to be supported by the moraine.

Heatwave A heatwave is an extended period of much hotter weather than usual.

Low-pressure system When a large area of air is rising, cooling and condensing, bringing rainfall.

Exam practice

For an extreme weather event you have studied, assess whether the social impacts were greater than the environmental impacts. (8 marks)

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Geography online: Global food insecurity

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Case study: Exploring a small-scale ecosystem

Case Study - 2010 Pakistan floods

GloFAS demonstrated its potential by detecting a number of flooding events of the past 3 year in major world rivers, with forecast lead time often larger than 10 days A striking example is that of the severe floods that hit Pakistan in summer of 2010, triggered by exceptional monsoon rain beginning at the end of July. The flooding covered approximately one-fifth of the total land area of Pakistan, directly affecting about 20 million and causing a death toll close to 2000 people. On that occasion, forecasts on 28 July 2010 showed probabilities up to 100% of exceeding the severe alert level (i.e., 20 yr return period) in most of the Indus River basin, with peak flow traveling downstream in the first half of August 2010.

20-day ensemble streamflow prediction (ESP) on 28 July 2010

It shows a 20-day ensemble streamflow prediction for a dynamic reporting point in the Indus River, few kilometers downstream the city of Sukkur, in the Sindh province of Pakistan. Forecasts show a sharp rise of discharge in the river, with expected peak of the ensemble mean on the 10 August, hence 13 days after the prediction was issued. The uncertainty range increases with the lead time, though it almost completely exceeds the severe alert level from the 8 to the 12 August.

Satellite images of the Indus River

Satellite images of the Indus River on 10 July 2010 (top) and on 11 August 2010 (bottom). Top panel also shows, with purple shadings, the maximum probability of exceeding the severe threshold in a 20-day forecast range (forecast on 28 July 2010).

Read more about the case study

Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F. GloFAS – global ensemble streamflow forecasting and flood forecasting Hydrol. Earth Syst. Sci., 17, 1161-1175, doi:10.5194/hess-17-1161-2013, 2013.

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Climate change risks fuelling antibiotic-resistant ‘superbugs’

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Michael Peel

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Antibiotic-resistant “superbugs” are among the greatest public health threats of our age — and researchers fear that climate change will make them still more dangerous.

Higher temperatures, more flooding, rising pollution, and growing population crowding are all forecast to stoke bacterial resilience to existing drugs.

These problems add urgency to international efforts to tackle antimicrobial resistance (AMR) by developing new medicines, and by blocking the pathways through which pathogen immunity spreads. They also mean climate change will loom large when governments gather on the sidelines of the UN General Assembly , in September, to discuss ways to combat AMR.

“There are currently no good estimates of how much worse climate-related disasters will make the burden of resistance — but it is clear that the risks are very large,” says Anthony McDonnell, a senior policy analyst at the Center for Global Development, a Washington-based think-tank. “This area requires far more research to enable us to determine the tools needed to deal with this worrying inevitably.” 

AMR refers to changes in bacteria, viruses, fungi, and parasites over time, as they evolve to develop resistance to the existing drugs used to tackle them. While the evolution itself is a natural response, it is accelerated by the extra exposure pathogens receive to medicines used too frequently or carelessly.

AMR contributed to almost 5mn deaths globally in 2019 and was directly responsible for more than a quarter of them, according to a 2022 study. It could result in $1tn extra annual healthcare costs by 2050 and $1tn to $3.4tn gross domestic product losses per year by 2030, the World Bank has estimated.

“The climate crisis has numerous impacts on ecosystems, human health, animal health and food production, which also affect AMR,” according to a report titled “Bracing for Superbugs” published last year by the UN Environment Programme.

AMR is most harmful in lower- and middle-income countries that are more vulnerable to the effects of climate change, such as flooding. Anti-microbial resistance to enteric fever — the waterborne disease also known as typhoid — has risen over the past 30 years in 75 countries in which it is endemic, according to a study published in The Lancet Global Health journal in February.

The results showed how rising resistance was a “pressing public health issue, jeopardising our ability to treat enteric fever effectively”, said Annie Browne, a spatial modeller and the lead author, on the study’s publication. 

Pakistan, which suffered devastating floods in 2022, has a particularly stark problem with enteric fever AMR. Resistance of one typhoid-causing bacterium to the cephalosporin antibiotics used to combat it had risen as high as 61 per cent in the country by 2019, the researchers found.

‘The impact of AMR is disproportionately felt in regions where resources are limited, exacerbating inequalities,” added Sadia Shakoor, associate professor of microbiology at the Aga Khan University in Karachi, Pakistan, also involved in the research.

One problem is that global heating will tend to speed the growth of bacteria and their so-called horizontal gene transfer — the process by which they exchange genetic material between each other. Higher temperatures are “intimately linked” to AMR because of these twin associations, according to a paper published in the International Journal of Environmental Research and Public Health last year.

Greater rainfall and flooding will also increase the risks of horizontal gene transfer due to contamination of water supplies, either directly with antibiotics or human excreta containing traces of the drugs. Wastewater is a “reservoir for antibiotic-resistance genes” (ARGs), according to the environmental research journal’s paper.

Another proposed cause of the spread of AMR in wastewater is pollution by microplastics — fragments of debris from consumer products or industrial waste. They are believed to act as breeding grounds for bacteria, allowing them to form “biofilms” that facilitate the transfer of antibiotic-resistant genes.

Other pollutants may also play roles in the spread of AMR. These include heavy metals, such as those found in high concentrations in the UK’s River Tyne, due to historical mining and industrial activity, according to a 2022 paper published in the journal Environmental Pollution. Researchers found elevated levels of bacterial species that carry “gene cassettes” prone to spreading antibiotic resistance.

A further concern is that AMR could flourish because people’s immune systems will be weakened by climate change-related socio-economic effects. These include food shortages and population displacement due to natural disasters, or regions becoming uninhabitable because they are too hot.

Climate change and antimicrobial resistance are the two most pressing . . . challenges facing us today Alistair Farley, Ineos Oxford Institute

However, experts believe that various changes in activity could help to curb the role of pollution in stoking AMR. These include better monitoring of wastewater composition, stricter limits on antibiotic residue discharges, and more research to establish accurately which pollution sources are the most damaging.

More broadly, scientists working on AMR urge the implementation of measures to mitigate the impact that floods and other extreme weather events will have on communities’ access to clean water and good sanitation.

The price of not acting, experts warn, is that essential medicines we have relied on for many years will become ineffective.

“Climate change and antimicrobial resistance are the two most pressing and interlinked global health challenges facing us today,” argues Alistair Farley, scientific lead at the UK’s Ineos Oxford Institute for antimicrobial research.

“It’s a Catch 22 situation, where increased global rates of infections and increased antibiotic consumption will ultimately lead to the drugs no longer working,” he says.

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Case Study – The Indus River Basin Pakistan

Cambridge iGCSE Geography > The Natural Environment > Rivers > Case Study – The Indus River Basin Pakistan

Background Information

The river and river basin.

The Indus River is one of the longest rivers in the world, originating from the Tibetan Plateau and flowing through China, India, and Pakistan before emptying into the Arabian Sea. The river basin spans four countries: China, India, Afghanistan, and Pakistan, with the majority of its area lying in Pakistan, covering around 70% of the country. The river basin is home to over 200 million people. The river plays a pivotal role in Pakistan’s economy, especially agriculture , as it forms the backbone of the country’s irrigation system. Additionally, the Indus provides the main drinking water supply in Pakistan, and it is also relied on by many heavy industries to support production processes.

The Indus River

The River Indus and its tributaries have been heavily modified to exploit and use its water. Two mega-dams (Tarbela and Mangla) have been constructed, and 320 barrages provide irrigation water and help control water that falls during the annual monsoon. Despite these interventions, heavier monsoon rains continue to cause significant flood events.

The Tarbela Dam holding back the Tarbela reservoir

The increasing population pressure, effects of climate change, and ongoing deterioration of the basin’s ecosystems have heightened flood risks. This situation is exacerbated by insufficient flood planning and management within the Indus floodplain.

The Indus River plays a pivotal role for countless individuals; thus, its flooding can lead to catastrophic outcomes. From 1950 to 2012, the Indus River basin in Pakistan witnessed 22 significant floods. These calamities resulted in the unfortunate loss of over 9,300 lives, impacted upwards of 10,000 villages, and led to direct economic setbacks of roughly $20 billion.

The 2010 floods stand out as the most detrimental in Pakistan’s history. They swept through every province and region, claiming 1,600 lives and inflicting damages exceeding $10 billion. The floods submerged nearly 38,600 km², destroyed nearly 2 million dwellings, and necessitated over 20 million individuals abandoning their homes and livelihoods. As a result of this disaster, Pakistan’s GDP growth rate plummeted from a previous 4% to a staggering -2.5%, ushering in a period of stunted economic growth.

Opportunities Presented by the River Indus

• Agriculture : The Indus Plains are fertile and support the cultivation of wheat, rice, sugarcane, and cotton. The river provides essential water for irrigation.
• Hydroelectric Power: The river’s flow is harnessed for generating electricity. Projects like the Tarbela and Mangla dams are prime examples.
• Transportation: Historically, the river has been a significant transportation route for goods and people.
• Fisheries: The river and its tributaries support a vibrant fishing industry, providing livelihoods for thousands.
• Tourism : Areas surrounding the river, especially in the northern regions, are picturesque and attract tourists.

Associated Hazards – Flooding

The Indus River frequently floods, especially during the monsoon season during July and August. However, floods, such as those in 2010, combined human and natural factors.

• Natural Causes: Heavy monsoon rains (some areas can receive over 280mm in 36 hours in exceptional circumstances), rapid run-oof from steep valley sides, glacial melts, and snowmelt from the Himalayas.
• Human Causes: Deforestation and degraded ecosystems in the catchment areas leads to increased runoff, urbanisation in floodplain areas, and inadequate maintenance of embankments and drainage canals and many levees could not withstand the sustained flood pressure resulting in large sections failing. The Indus Basin lacks an effective flood management policy.

River Management

Hard engineering solutions:.

• Dams and Reservoirs: Examples include the Tarbela Dam and Mangla Dam. These structures store excess water and allow controlled release, reducing the risk of flooding downstream. The dams effectively held back floodwater in 2010. However, sedimentation has reduced the storage capacity of both reservoirs.
• Embankments and Levees: Raised structures are built along the riverbanks to prevent floodwaters from spilling into adjacent lands. There are 6000km of artificial levees providing the most flood protection and over 14000 spurs, stone walls or levees constructed to divert water flow at essential locations.
• Channel Straightening: By making the river channel straighter, water can flow faster, reducing the flooding risk in certain areas.

Soft Engineering Solutions:

• Afforestation: Planting trees in the river’s catchment areas can reduce runoff and decrease the risk of flooding.
• Floodplain Zoning: Designating areas near the river as zones where development is restricted or controlled can minimise flood damage.
• Flood Forecasting and Warning Systems: These systems provide early warnings to residents, allowing them to prepare or evacuate in case of impending floods.
• Community Education: Training and educating local communities about flood risks and preparedness measures can significantly reduce the impact of floods.

The Indus River Basin is a vital lifeline for Pakistan, offering numerous opportunities. However, the associated hazards, particularly flooding, pose significant challenges. A mix of hard and soft engineering solutions is crucial for sustainable management and mitigation of risks in the basin.

The Indus River, originating from the Tibetan Plateau, flows through China, India, and Pakistan, with its basin spanning four countries and housing over 200 million people. It’s vital for Pakistan’s economy, particularly agriculture and water supply.

Two mega-dams (Tarbela and Mangla) and 320 barrages have been constructed to exploit the river’s water. Still, heavier monsoon rains often result in flooding, with the 2010 floods being the most catastrophic in Pakistan’s history.

The river offers agriculture, hydroelectric power, transportation, fisheries, and tourism opportunities. It’s crucial for crops like wheat, rice, and cotton and for generating electricity with projects like the Tarbela and Mangla dams.

Associated hazards include frequent flooding from natural causes like heavy monsoon rains and human causes like deforestation and urbanisation in floodplain areas. From 1950 to 2012, significant floods in the basin led to over 9,300 lost lives and around $20 billion in damages.

River management combines hard engineering solutions, such as dams, embankments, and channel straightening, with soft engineering solutions like afforestation, floodplain zoning, and community education. Both approaches are vital for sustainable risk mitigation in the basin.

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Kenya flood death toll rises as more torrential rain forecast

Total deaths reach 76 and more than 130,000 displaced as weeks of flooding also affects east African neighbours

Seventy-six people in Kenya have died because of flooding triggered by torrential downpours since March, the government has said, warning residents “to brace for even heavier rainfall”.

Kenya and its east African neighbours have been battered by stronger than usual rain in recent weeks, compounded by the El Niño weather system.

Flash floods have submerged roads and neighbourhoods, leading to the displacement of more than 130,000 people across 24,000 households, many of them in the capital, Nairobi, the government spokesperson, Isaac Mwaura, said.

“We deeply regret to announce the tragic loss of an additional six lives in the last 12 hours, bringing the total to 76,” he said on Saturday, adding that 29 people had sustained injuries and 19 had been reported missing.

“Nairobi is currently experiencing the highest impact, with a significant death toll of 32 and 16,909 households displaced.”

Mwaura said all five dams comprising the Seven Forks hydropower project along the Tana river, Kenya’s longest, were at total capacity.

“There is a prediction of a massive overflow downstream within the next 24 hours. Residents in these areas are advised to move to higher grounds,” he said.

The monsoons have caused havoc across neighbouring Tanzania as well, with at least 155 people killed in flooding and landslides.

“The situation here is really scary,” said Khatibu Kapara, a resident of Dar es Salaam’s Jangwani neighbourhood.

“Many people including myself have been affected by floods. Many people have lost their property due to floods, their houses have been surrounded” by water, the 35-year-old said.

In Burundi , one of the world’s poorest countries, about 96,000 people had been displaced by months of relentless rain, the United Nations and the government said this month.

There have also been heavy storms in Uganda , causing riverbanks to overflow, with two deaths confirmed and several hundred villagers displaced.

Late last year, more than 300 people died in rains and floods in Kenya, Somalia and Ethiopia, just as the region was trying to recover from its worst drought in four decades, which left millions of people hungry.

El Niño is a naturally occurring climate pattern typically associated with increased heat worldwide, leading to drought in some parts of the world and heavy rains elsewhere.

The UN’s World Meteorological Organization said in March that the latest El Niño was one of the five strongest ever recorded.

• El Niño southern oscillation
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