Climate change impacts on water security in global drylands

Abstract

Water scarcity affects 1–2 billion people globally, most of whom live in drylands. Under projected climate change, millions more people will be living under conditions of severe water stress in the coming decades. This review examines observed and projected climate change impacts on water security across the world's drylands to the year 2100. We find that efficient water management, technology, and infrastructure, and better demand and supply management, can offer more equitable access to water resources. People are already adapting but need to be supported with coherent system-oriented policies and institutions that situate water security at their core, in line with the components of integrated water resources management. Dryland water governance urgently needs to better account for synergies and trade-offs between water security and other dimensions of sustainable development, to support an equitable approach in which no one gets left behind. Water scarcity affects 1–2 billion people globally, most of whom live in drylands. Under projected climate change, millions more people will be living under conditions of severe water stress in the coming decades. This review examines observed and projected climate change impacts on water security across the world's drylands to the year 2100. We find that efficient water management, technology, and infrastructure, and better demand and supply management, can offer more equitable access to water resources. People are already adapting but need to be supported with coherent system-oriented policies and institutions that situate water security at their core, in line with the components of integrated water resources management. Dryland water governance urgently needs to better account for synergies and trade-offs between water security and other dimensions of sustainable development, to support an equitable approach in which no one gets left behind. Drylands are the hyper-arid, arid, semi-arid, and dry sub-humid parts of the Earth, found on all continents. Grasslands, savannas, and woodlands in these environments are rich in biodiversity1Maestre F.T. Quero J.L. Gotelli N.J. Escudero A. Ochoa V. Delgado-Baquerizo M. García-Gómez M. Bowker M.A. Soliveres S. Escolar C. et al.Plant species richness and ecosystem multifunctionality in global drylands.Science. 2012; 335: 214https://doi.org/10.1126/science.1215442Crossref PubMed Scopus (636) Google Scholar and store substantial amounts of the world's terrestrial carbon in their soils and biomass. Drylands possess a varied and rich geological, cultural, and historical heritage2Teff-Seker Y. Orenstein D.E. The ‘desert experience’: evaluating the cultural ecosystem services of drylands through walking and focusing.People Nat. 2019; 1: 234-248https://doi.org/10.1002/pan3.28Crossref Scopus (6) Google Scholar,3Richards J. Mayaud J. Zhan H. Wu F. Bailey R. Viles H. Modelling the risk of deterioration at earthen heritage sites in drylands.Earth Surf. Process. Landforms. 2020; 45: 2401-2416https://doi.org/10.1002/esp.4887Crossref Scopus (4) Google Scholar and are home to approximately 40% of the world's human population4van der Esch S. ten Brink B. Stehfest E. Bakkenes M. Sewell A. Bouwman A. Meijer J. Westhoek H. van den Berg M. van den Born G.J. et al.Exploring Future Changes in Land Use and Land Condition and the Impacts on Food, Water, Climate Change and Biodiversity: Scenarios for the UNCCD Global Land Outlook. Policy Report. PBL Netherlands Environmental Assessment Agency, 2017Google Scholar (Figure 1; based on data from the Centre for International Earth Science Information Network5Center for International Earth Science Information Network (CIESIN), Columbia University Documentation for the Gridded Population of the World, Version 4 (GPWv4), Revision 11 Data Sets. NASA Socioeconomic Data and Applications Center (SEDAC), 2018Google Scholar. Dryland extent is based on Millennium Ecosystem Assessment delineation).6Millennium Ecosystem AssessmentMA Ecosystems. NASA Socioeconomic Data and Applications Center (SEDAC), 2005https://doi.org/10.7927/H4KW5CZ6Crossref Google Scholar Major land uses include agriculture and pastoralism, with the majority of livelihoods directly reliant upon natural resources. A number of megacities, including New Delhi, Beijing, Los Angeles, Cairo, Tehran, and Mexico City, all of which have complex and diversified economies, are also located in these water-limited environments.7Cherlet M. Hutchinson C. Reynolds J. Hill J. Sommer S. von Maltitz G. World Atlas of desertification: rethinking land degradation and sustainable land management.in: Cherlet M. Hutchinson C. Reynolds J. Hill J. Sommer S. Von Maltitz G. European Union. Publications Publications Office of the European Union, 2018Google Scholar Life can be very difficult for people living in dryland areas, particularly in developing regions, where around 70% of the world's drylands are found.8Plaza C. Zaccone C. Sawicka K. Méndez A.M. Tarquis A. Gascó G. Heuvelink G.B.M. Schuur E.A.G. Maestre F.T. Soil resources and element stocks in drylands to face global issues.Sci. Rep. 2018; 8: 13788https://doi.org/10.1038/s41598-018-32229-0Crossref PubMed Scopus (47) Google Scholar In many of these areas, people already face stark challenges related to poverty, food insecurity and malnourishment, poor access to healthcare, poor governance, economic hardship, and marginalization.9Stringer L.C. Reed M.S. Fleskens L. Thomas R.J. Le Q.B. Lala-Pritchard T. A new dryland development paradigm grounded in empirical analysis of dryland systems science.Land Degrad. Dev. 2017; 28: 1952-1961https://doi.org/10.1002/ldr.2716Crossref Scopus (40) Google Scholar These difficulties are often exacerbated by land degradation, flooding, drought, and climate change. Drylands in hot, tropical areas have already experienced temperature rises that are higher than the global average, and temperatures are projected to increase by 2°C–4°C by 2100 under higher emissions scenarios (Representative Concentration Pathways [RCP] 4.5 and 8.5).10Mirzabaev A. Wu J. Evans J. García-Oliva F. Hussein I.A.G. Iqbal M.H. Kimutai J. Knowles T. Meza F. Nedjraoui D. et al.Desertification.in: Shukla P.R. Skea J. Calvo Buendia E. Masson-Delmotte V. Pörtner H.-O. Roberts D.C. Zhai P. Slade R. Connors S. van Diemen R. Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems. 2019Google Scholar Understanding what these changes mean for water security in drylands is therefore vital. Several different measures are relevant to the assessment of observed and projected future water security in drylands, and because they consider slightly different aspects of the system, they can highlight different trends. Climatological indices measure the physical components of water security, and include the Aridity Index (AI), drought indices such as the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI), the Ecohydrological Index (EI), and soil moisture and terrestrial water storage (TWS). There are also measures that indicate biological responses to physical or climatological variables, such as changes to dryland vegetation indicated by the Normalized Difference Vegetation Index (NDVI). Box 1 explains these terms for each of the indices referred to in the main text in relation to observed and projected impacts of climate change on water security.Box 1The aridity paradox: Defining and delineating the drylandsDryland extent describes both the physical boundaries of dry areas (a climatological definition, commonly measured using the AI), and the extent of dryland vegetation (an ecological definition). Climatological and ecological definitions do not always delineate the same geographical areas when projecting future changes to dryland extent.The AI is the ratio of annual precipitation to potential evapotranspiration (PET). It has a long use history, defining drylands as areas with AI < 0.65.11UNEPWorld Atlas of Desertification. United Nations Environment Programme, Nairobi, Kenya1992Google Scholar Sub-categories include (1) dry sub-humid (0.5 ≤ AI < 0.65), (2) semi-arid (0.2 ≤ AI < 0.5), (3) arid (0.05 ≤ AI < 0.2), and (4) hyper-arid (AI < 0.05) areas (Figure 1). Cold (polar) drylands (not considered here) are where PET is <400 mm/year.12Spinoni J. Vogt J. Naumann G. Carrao H. Barbosa P. Towards identifying areas at climatological risk of desertification using the Köppen–Geiger classification and FAO aridity index.Int. J. Climatol. 2015; 35: 2210-2222https://doi.org/10.1002/joc.4124Crossref Scopus (70) Google Scholar The AI usually projects increasing aridity under climate change, leading to projections of widespread dryland expansion.13Huang J. Yu H. Guan X. Wang G. Guo R. Accelerated dryland expansion under climate change.Nat. Clim. Change. 2016; 6: 166-171https://doi.org/10.1038/nclimate2837Crossref Scopus (848) Google Scholar,14He B. Wang S. Guo L. Wu X. Aridity change and its correlation with greening over drylands.Agric. For. Meteorol. 2019; 278: 107663https://doi.org/10.1016/j.agrformet.2019.107663Crossref Scopus (12) Google Scholar However, while the AI has been decreasing over the last 50 years,15Berg A. McColl K.A. No projected global drylands expansion under greenhouse warming.Nat. Clim. Change. 2021; https://doi.org/10.1038/s41558-021-01007-8Crossref Scopus (2) Google Scholar dryland vegetation has been increasing globally.16Fensholt R. Langanke T. Rasmussen K. Reenberg A. Prince S.D. Tucker C. Scholes R.J. Le Q.B. Bondeau A. Eastman R. et al.Greenness in semi-arid areas across the globe 1981–2007 — an Earth Observing Satellite based analysis of trends and drivers.Remote Sens. Environ. 2012; 121: 144-158https://doi.org/10.1016/j.rse.2012.01.017Crossref Scopus (386) Google Scholar, 17Andela N. Liu Y. van Dijk A.I.J.M. de Jeu R.A.M. McVicar T. Global changes in dryland vegetation dynamics (1988-2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data.Biogeosciences. 2013; 10: 6657-6676https://doi.org/10.5194/bg-10-6657-2013Crossref Scopus (115) Google Scholar, 18Yang Y. Roderick M.L. Zhang S. McVicar T.R. Donohue R.J. Hydrologic implications of vegetation response to elevated CO2 in climate projections.Nat. Clim. Change. 2019; 9: 44-48https://doi.org/10.1038/s41558-018-0361-0Crossref Scopus (94) Google Scholar, 19Zhu Z. Piao S. Myneni R.B. Huang M. Zeng Z. Canadell J.G. Ciais P. Sitch S. Friedlingstein P. Arneth A. et al.Greening of the Earth and its drivers.Nat. Clim. Change. 2016; 6: 791-795https://doi.org/10.1038/nclimate3004Crossref Scopus (789) Google Scholar Hence, correspondence between changes in AI and changes in dryland vegetation over recent decades is limited.15Berg A. McColl K.A. No projected global drylands expansion under greenhouse warming.Nat. Clim. Change. 2021; https://doi.org/10.1038/s41558-021-01007-8Crossref Scopus (2) Google Scholar The AI overestimates the role of PET compared with rainfall,15Berg A. McColl K.A. No projected global drylands expansion under greenhouse warming.Nat. Clim. Change. 2021; https://doi.org/10.1038/s41558-021-01007-8Crossref Scopus (2) Google Scholar and neglects CO2 impacts on evapotranspiration and seasonality in rainfall and evapotranspiration. Increased annual PET due to higher temperatures may have little impact if temperature and actual evapotranspiration are not increasing during the wet season when there is vegetation growth. Given the AI's limitations, indices that incorporate the influence of plant physiology on evapotranspiration, such as precipitation minus actual evapotranspiration, soil moisture, runoff, and land water storage, may be more suitable for future projections. The EI is directly based on observations of land surface ecohydrological properties using Coupled Model Intercomparison Project Phase 5 (CMIP5) models.15Berg A. McColl K.A. No projected global drylands expansion under greenhouse warming.Nat. Clim. Change. 2021; https://doi.org/10.1038/s41558-021-01007-8Crossref Scopus (2) Google Scholar The EI aims to capture the role of vegetation responses under higher CO2 levels. Results show that EI decreases in some regions (reflecting increased aridity) and increases in others, better capturing observed dryland changes than the AI.The PDSI is a standardized index, generally spanning −10 (dry) to +10 (wet). Values lower than −3 represent severe to extreme meteorological drought. The PDSI incorporates prior precipitation, moisture supply, runoff, and evaporation demand at the surface level to estimate relative dryness.20Palmer W.C. Keeping track of crop moisture conditions, nationwide: the new crop moisture index.Weatherwise. 1968; 21: 156-161https://doi.org/10.1080/00431672.1968.9932814Crossref Google Scholar It is based on temperature data and a physical water balance model, so can capture global warming effects on drought through changes in PET. However, it does not compare well across regions, and is not amenable to assessing short timescales, making it difficult to correlate with specific water resources.21Dai A. Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900–2008.J. Geophys. Res. Atmospheres. 2011; 116https://doi.org/10.1029/2010JD015541Crossref Scopus (604) Google Scholar The Standardized Precipitation Index (SPI) characterizes meteorological drought on a range of timescales. The SPI can be calculated for periods of 1–36 months, using monthly input data, so can characterize drought at timescales corresponding with the temporal availability of different water resources (such as soil moisture, groundwater, river discharge, and reservoir storage). The SPI is more comparable across regions than the PDSI because it is calculated in relation to climatological norms for the location and season. However, the SPI does not consider evapotranspiration, so does not capture the effect of increased temperatures associated with climate change on moisture demand and availability.The SPEI is a drought index, calculated as the difference between precipitation and PET. By incorporating evaporation, it captures the main impact of increased temperatures on water demand. It can be calculated at different timescales (e.g., monthly or weekly). The SPEI is used to measure drought severity in terms of intensity and duration and can identify the onset and end of drought episodes. PET (or potential evaporation) describes the amount of evaporation that would occur if unlimited water were available. It is influenced by surface and air temperatures, radiation and wind, vegetation characteristics (such as ground cover and plant density), and soil type. By definition, annual potential evaporation exceeds annual precipitation in drylands. PET is estimated using various methods, such as the Penman-Monteith equation. The surface water balance, the difference between precipitation and actual evapotranspiration, describes the availability of surface water on land, while soil moisture is the water content stored in a given layer of soil. Global analyses rely on satellite data or model simulations because in situ observations are still unavailable for most of the world.TWS is the sum of continental water stored in vegetation, rivers, lakes and reservoirs, wetlands, soil, and groundwater. It is critical in the global water and energy budget, influencing water resource availability and water flux interactions among Earth system components.22Pokhrel Y. Felfelani F. Satoh Y. Boulange J. Burek P. Gädeke A. Gerten D. Gosling S.N. Grillakis M. Gudmundsson L. et al.Global terrestrial water storage and drought severity under climate change.Nat. Clim. Change. 2021; 11: 226-233https://doi.org/10.1038/s41558-020-00972-wCrossref Scopus (13) Google Scholar While groundwater is an important component of the dryland ecohydrological system, its role in TWS remains poorly quantified.23Yao Y. Tian Y. Andrews C. Li X. Zheng Y. Zheng C. Role of groundwater in the dryland ecohydrological system: a case study of the Heihe river basin.J. Geophys. Res. Atmospheres. 2018; 123: 6760-6776https://doi.org/10.1029/2018JD028432Crossref Scopus (16) Google Scholar The NDVI is based on global satellite data that characterize vegetation growth by assessing absorption and reflection of photosynthetically active radiation over a given time period, relative to the regional norm. The NDVI describes the relative density of vegetation and is used as an indicator of agricultural drought. Dryland extent describes both the physical boundaries of dry areas (a climatological definition, commonly measured using the AI), and the extent of dryland vegetation (an ecological definition). Climatological and ecological definitions do not always delineate the same geographical areas when projecting future changes to dryland extent. The AI is the ratio of annual precipitation to potential evapotranspiration (PET). It has a long use history, defining drylands as areas with AI < 0.65.11UNEPWorld Atlas of Desertification. United Nations Environment Programme, Nairobi, Kenya1992Google Scholar Sub-categories include (1) dry sub-humid (0.5 ≤ AI < 0.65), (2) semi-arid (0.2 ≤ AI < 0.5), (3) arid (0.05 ≤ AI < 0.2), and (4) hyper-arid (AI < 0.05) areas (Figure 1). Cold (polar) drylands (not considered here) are where PET is <400 mm/year.12Spinoni J. Vogt J. Naumann G. Carrao H. Barbosa P. Towards identifying areas at climatological risk of desertification using the Köppen–Geiger classification and FAO aridity index.Int. J. Climatol. 2015; 35: 2210-2222https://doi.org/10.1002/joc.4124Crossref Scopus (70) Google Scholar The AI usually projects increasing aridity under climate change, leading to projections of widespread dryland expansion.13Huang J. Yu H. Guan X. Wang G. Guo R. Accelerated dryland expansion under climate change.Nat. Clim. Change. 2016; 6: 166-171https://doi.org/10.1038/nclimate2837Crossref Scopus (848) Google Scholar,14He B. Wang S. Guo L. Wu X. Aridity change and its correlation with greening over drylands.Agric. For. Meteorol. 2019; 278: 107663https://doi.org/10.1016/j.agrformet.2019.107663Crossref Scopus (12) Google Scholar However, while the AI has been decreasing over the last 50 years,15Berg A. McColl K.A. No projected global drylands expansion under greenhouse warming.Nat. Clim. Change. 2021; https://doi.org/10.1038/s41558-021-01007-8Crossref Scopus (2) Google Scholar dryland vegetation has been increasing globally.16Fensholt R. Langanke T. Rasmussen K. Reenberg A. Prince S.D. Tucker C. Scholes R.J. Le Q.B. Bondeau A. Eastman R. et al.Greenness in semi-arid areas across the globe 1981–2007 — an Earth Observing Satellite based analysis of trends and drivers.Remote Sens. Environ. 2012; 121: 144-158https://doi.org/10.1016/j.rse.2012.01.017Crossref Scopus (386) Google Scholar, 17Andela N. Liu Y. van Dijk A.I.J.M. de Jeu R.A.M. McVicar T. Global changes in dryland vegetation dynamics (1988-2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data.Biogeosciences. 2013; 10: 6657-6676https://doi.org/10.5194/bg-10-6657-2013Crossref Scopus (115) Google Scholar, 18Yang Y. Roderick M.L. Zhang S. McVicar T.R. Donohue R.J. Hydrologic implications of vegetation response to elevated CO2 in climate projections.Nat. Clim. Change. 2019; 9: 44-48https://doi.org/10.1038/s41558-018-0361-0Crossref Scopus (94) Google Scholar, 19Zhu Z. Piao S. Myneni R.B. Huang M. Zeng Z. Canadell J.G. Ciais P. Sitch S. Friedlingstein P. Arneth A. et al.Greening of the Earth and its drivers.Nat. Clim. Change. 2016; 6: 791-795https://doi.org/10.1038/nclimate3004Crossref Scopus (789) Google Scholar Hence, correspondence between changes in AI and changes in dryland vegetation over recent decades is limited.15Berg A. McColl K.A. No projected global drylands expansion under greenhouse warming.Nat. Clim. Change. 2021; https://doi.org/10.1038/s41558-021-01007-8Crossref Scopus (2) Google Scholar The AI overestimates the role of PET compared with rainfall,15Berg A. McColl K.A. No projected global drylands expansion under greenhouse warming.Nat. Clim. Change. 2021; https://doi.org/10.1038/s41558-021-01007-8Crossref Scopus (2) Google Scholar and neglects CO2 impacts on evapotranspiration and seasonality in rainfall and evapotranspiration. Increased annual PET due to higher temperatures may have little impact if temperature and actual evapotranspiration are not increasing during the wet season when there is vegetation growth. Given the AI's limitations, indices that incorporate the influence of plant physiology on evapotranspiration, such as precipitation minus actual evapotranspiration, soil moisture, runoff, and land water storage, may be more suitable for future projections. The EI is directly based on observations of land surface ecohydrological properties using Coupled Model Intercomparison Project Phase 5 (CMIP5) models.15Berg A. McColl K.A. No projected global drylands expansion under greenhouse warming.Nat. Clim. Change. 2021; https://doi.org/10.1038/s41558-021-01007-8Crossref Scopus (2) Google Scholar The EI aims to capture the role of vegetation responses under higher CO2 levels. Results show that EI decreases in some regions (reflecting increased aridity) and increases in others, better capturing observed dryland changes than the AI. The PDSI is a standardized index, generally spanning −10 (dry) to +10 (wet). Values lower than −3 represent severe to extreme meteorological drought. The PDSI incorporates prior precipitation, moisture supply, runoff, and evaporation demand at the surface level to estimate relative dryness.20Palmer W.C. Keeping track of crop moisture conditions, nationwide: the new crop moisture index.Weatherwise. 1968; 21: 156-161https://doi.org/10.1080/00431672.1968.9932814Crossref Google Scholar It is based on temperature data and a physical water balance model, so can capture global warming effects on drought through changes in PET. However, it does not compare well across regions, and is not amenable to assessing short timescales, making it difficult to correlate with specific water resources.21Dai A. Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900–2008.J. Geophys. Res. Atmospheres. 2011; 116https://doi.org/10.1029/2010JD015541Crossref Scopus (604) Google Scholar The Standardized Precipitation Index (SPI) characterizes meteorological drought on a range of timescales. The SPI can be calculated for periods of 1–36 months, using monthly input data, so can characterize drought at timescales corresponding with the temporal availability of different water resources (such as soil moisture, groundwater, river discharge, and reservoir storage). The SPI is more comparable across regions than the PDSI because it is calculated in relation to climatological norms for the location and season. However, the SPI does not consider evapotranspiration, so does not capture the effect of increased temperatures associated with climate change on moisture demand and availability. The SPEI is a drought index, calculated as the difference between precipitation and PET. By incorporating evaporation, it captures the main impact of increased temperatures on water demand. It can be calculated at different timescales (e.g., monthly or weekly). The SPEI is used to measure drought severity in terms of intensity and duration and can identify the onset and end of drought episodes. PET (or potential evaporation) describes the amount of evaporation that would occur if unlimited water were available. It is influenced by surface and air temperatures, radiation and wind, vegetation characteristics (such as ground cover and plant density), and soil type. By definition, annual potential evaporation exceeds annual precipitation in drylands. PET is estimated using various methods, such as the Penman-Monteith equation. The surface water balance, the difference between precipitation and actual evapotranspiration, describes the availability of surface water on land, while soil moisture is the water content stored in a given layer of soil. Global analyses rely on satellite data or model simulations because in situ observations are still unavailable for most of the world. TWS is the sum of continental water stored in vegetation, rivers, lakes and reservoirs, wetlands, soil, and groundwater. It is critical in the global water and energy budget, influencing water resource availability and water flux interactions among Earth system components.22Pokhrel Y. Felfelani F. Satoh Y. Boulange J. Burek P. Gädeke A. Gerten D. Gosling S.N. Grillakis M. Gudmundsson L. et al.Global terrestrial water storage and drought severity under climate change.Nat. Clim. Change. 2021; 11: 226-233https://doi.org/10.1038/s41558-020-00972-wCrossref Scopus (13) Google Scholar While groundwater is an important component of the dryland ecohydrological system, its role in TWS remains poorly quantified.23Yao Y. Tian Y. Andrews C. Li X. Zheng Y. Zheng C. Role of groundwater in the dryland ecohydrological system: a case study of the Heihe river basin.J. Geophys. Res. Atmospheres. 2018; 123: 6760-6776https://doi.org/10.1029/2018JD028432Crossref Scopus (16) Google Scholar The NDVI is based on global satellite data that characterize vegetation growth by assessing absorption and reflection of photosynthetically active radiation over a given time period, relative to the regional norm. The NDVI describes the relative density of vegetation and is used as an indicator of agricultural drought. By definition, precipitation in drylands balances evaporation from the land and vegetation surfaces. As a result, water is a key limiting factor that shapes the drylands, with these systems being highly sensitive to precipitation and PET dynamics. Globally, water scarcity already affects between 1 and 2 billion people, the vast majority of whom live in drylands, where the gap between the demand for and supply of water is the highest in the world. This challenge means that the impacts of climate change, combined with water management decisions, will have profound impacts on drylands and their inhabitants into the future. Projected climate changes indicate that, in a matter of just a few decades, millions more people (approximately half the world's population in total) will be living under conditions of high water stress.24Byers E. Gidden M. Leclère D. Balkovic J. Burek P. Ebi K. Greve P. Grey D. Havlik P. Hillers A. et al.Global exposure and vulnerability to multi-sector development and climate change hotspots.Environ. Res. Lett. 2018; 13: 055012https://doi.org/10.1088/1748-9326/aabf45Crossref Scopus (62) Google Scholar This will have impacts not just in dryland areas but also for neighboring countries and beyond, particularly because water and its impacts do not respect national political and administrative boundaries. The impacts of climate change on water security in drylands go beyond access to clean water and sanitation; they are highly intertwined with many other dimensions of sustainable development, including eradicating hunger and reducing poverty, peace, and security, gender equality, education, and health25Pradhan P. Costa L. Rybski D. Lucht W. Kropp J.P. A systematic study of sustainable development goal (SDG) interactions.Earth's Future. 2017; 5: 1169-1179https://doi.org/10.1002/2017EF000632Crossref Scopus (279) Google Scholar (Figure 2). For example, water scarcity can negatively affect women more than men because of women's key role in household water provisioning in many developing countries26Harris L. Kleiber D. Goldin J. Darkwah A. Morinville C. Intersections of gender and water: comparative approaches to everyday gendered negotiations of water access in underserved areas of Accra, Ghana and Cape Town, South Africa.J. Gend. Stud. 2017; 26: 561-582https://doi.org/10.1080/09589236.2016.1150819Crossref Scopus (28) Google Scholar resulting in more time spent by female household members, including children, in fetching water for domestic consumption. Climate change affects the structure and functioning of multiple ecosystem attributes across the world's drylands,27Berdugo M. Delgado-Baquerizo M. Soliveres S. Hernández-Clemente R. Zhao Y. Gaitán J.J. Gross N. Saiz H. Maire V. Lehmann A. et al.Global ecosystem thresholds driven by aridity.Science. 2020; 367: 787https://doi.org/10.1126/science.aay5958Crossref PubMed Scopus (104) Google Scholar with important implications for agriculture and vegetation productivity, as well as the livelihoods they support. Increased water scarcity due to climate change will make attainment of the Sustainable Development Goals (SDGs) more difficult in many drylands, especially in the developing world.10Mirzabaev A. Wu J. Evans J. García-Oliva F. Hussein I.A.G. Iqbal M.H. Kimutai J. Knowles T. Meza F. Nedjraoui D. et al.Desertification.in: Shukla P.R. Skea J. Calvo Buendia E. Masson-Delmotte V. Pörtner H.-O. Roberts D.C. Zhai P. Slade R. Connors S. van Diemen R. Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems. 2019Google Scholar Improved knowledge about new emerging hotspots of climate change-driven water insecurity will be critical for measuring progress toward the achievement of the SDGs.28Gain A.K. Giupponi C. Wada Y. Measuring global water security towards sustainable development goals.Environ. Res. Lett. 2016; 11: 124015https://doi.org/10.1088/1748-9326/11/12/124015Crossref Scopus (65) Google Scholar Taking into account the magnitude and importance of these emerging challenges, this review focuses