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    Interbasin water transfers in the United States and Canada

    Interbasin water transfers have been defined many ways within the literature12,13,14 and by government agencies. For this study, we define an IBT as a human-mediated movement of surface water or groundwater from one sub-drainage area or subregion (HUC4) to another sub-drainage area or subregion through man-made or artificial pathways (e.g., canals, pipelines, aqueducts). Subregion15 and sub-drainage16 boundaries come from the United States Geological Survey (USGS) and Natural Resources Canada, respectively. We further narrow our IBT definition to exclude the transfer of treated water and wastewater due to the lack of data describing complex municipal water and wastewater distribution systems across Canada and the US. The movement of untreated (or “raw”) water between the intake location of a water distribution system and the water treatment facility is deemed an IBT if it traverses a basin boundary (i.e., sub-drainage or subregion boundary; e.g., Fig. 3a); however, if water within the distribution system crosses a basin boundary after treatment, we do not include this instance within our IBT datasets (Fig. 3b). We have also removed inconsequential drainage ditches that drain less than 0.5 square kilometers. Such drainage ditches constituted a significant fraction of previous US IBT datasets7, even though they have a negligible hydrologic, ecological, or societal impact.Fig. 3Examples of potential interbasin transfers of raw water (a) and treated water (b). Raw water transfers are represented by yellow lines, while a treated water transfer is represented by a magenta line. If raw water crosses a subregion boundary (blue lines), it is included in our dataset, as is the case for the Schoharie and Delaware Aqueducts that bring raw water for New York City public water supply (a). If only treated water crosses a subregion boundary, as is the case for Gwinnett County’s public water supply system in Georgia (b), then it is not included within our IBT datasets.Full size imageThe creation of our IBT data products involved four steps: i) data collection, ii) data standardization, iii) data visualization, and iv) data validation. The first three steps are described in this section (Methods), while data validation is described within the ‘Technical Validation’ section.Data collectionTo create a national IBT dataset, we started with potential IBTs identified by Dickson and Dzombak7. Dickson and Dzombak extracted all artificial flow paths that crossed subregion boundaries from the USGS National Hydrography Dataset (NHD). These IBTs were not verified and lacked descriptive details, such as water use purpose or transfer volume. Furthermore, the number of IBTs reported by Dickson and Dzombak is artificially large since it counts each instance a conveyance structure crosses a basin boundary as an individual IBT, even if it is part of one larger IBT project (e.g., Central Arizona Project). These records were paired with older IBT datasets produced by USGS8,9. Together, these datasets represent the most complete US IBT datasets to date. We filtered out records from the combined datasets that did not meet our IBT definition, were duplicates, or were verified as being either decommissioned or erroneous. We also connected flowlines that are part of the same IBT project.Next, we searched state and federal reports, data repositories, and websites for data describing the location, properties, and flow volumes of IBTs. Findings from these searches allowed us to remove erroneous records within our current dataset, as well as add new IBTs that were not captured by previous datasets. Mostly, though, our review of government records allowed us to confirm IBT records and to provide more complete documentation of already identified IBTs. Websites for federal agencies that have a role in building, administering, or maintaining records on IBTs, such as the USGS, US Bureau of Reclamation (USBR), US Army Corps of Engineers (USACE), and the Environmental Protection Agency (EPA), were searched for relevant records. Approval by USACE is required when building across a navigable waterway, which is sometimes required for IBTs. Much of the major federal water supply infrastructure in the Western US, including IBTs, were built and are currently operated by USBR. The EPA has records related to water distribution systems17, including water intake and treatment locations, which were used to identify IBT locations. The USGS gauge network reports time-series records for 79 IBTs. Relevant state websites for IBT data collection were identified through the survey of state-level water data platforms developed by Josset et al.18.After reviewing the scientific literature and publicly available government reports, data repositories, and websites, we contacted federal, state, and local representatives for additional data records and to verify our existing records. Federal employees at USGS and USBR reviewed and provided additional records for our initial IBT dataset. The USGS Water Use Science Project regularly collects water use and water infrastructure data from states. The USGS Water Use team helped us identify the state agency and contact person that would most likely maintain IBT data for each state.We sent IBT data requests to each state via email and phone calls. In cases where these attempts were unsuccessful, we filed an Open Records Act or Freedom of Information Act (FOIA) request to collect any remaining data we were missing. In cases where neither federal or state agencies maintained the data we sought, we contacted IBT operators directly. Direct contact with IBT operators was primarily done when collecting time-series flow data for irrigation districts and municipal water suppliers.Canadian IBT data were collected from an Access to Information Act records request. The Environment and Climate Change Canada (formerly, Environment Canada) had maintained records of IBTs throughout Canada until 2011. Several reports published by Environment Canada researchers10,11 document Canadian IBTs and their properties. These reports highlight select IBTs but do not provide complete IBT records. Our Access to Information Act request provided us an unpublished report and associated data from 2004 that described the full collection of IBTs in Canada.Data were collected between August 2019 and June 2022. Our data products reflect the most up-to-date data held by primary data collectors on the date of our request. The date each IBT entry was collected is reported in the IBT Inventory Dataset. We collected all time-series flow data available for each IBT, with some records going back as far as 1901.Data standardizationThe data we collected were in a variety of file formats and data types. We created a data standard, which we named the Interbasin Transfer Database Standard Version 1.0. (IBTDS 1.0), to provide a consistent way of representing and defining data for all IBTs. The standardized IBT Inventory Dataset follows a node-link structure. Nodes represent places of water diversion, water use, or change in flow (e.g., reservoir, channel junction). Links represent conveyance infrastructure or natural waterways that connect two or more nodes within an IBT project. Unique link identifiers (Link ID) connect two or more unique node identifiers (Node ID). One or more links constitute an IBT project. The owner/operator of each IBT project, as well as the year the IBT project was commissioned and decommissioned (if applicable), is reported within the IBT Inventory Dataset.Geospatial details are reported for each IBT project in the IBT Inventory Dataset and the IBT Geospatial Dataset. We obtained the precise latitude and longitude of each node using the various data sources noted previously, as well as visual inspection of high-resolution aerial imagery from Google Earth and Esri’s World Imagery layer. Precise geospatial information is reflected in the IBT Geospatial Dataset. The IBT Inventory Dataset lists the hydrologic and geopolitical boundaries that contain each node. For the US, the state and county name and the Federal Information Processing System (FIPS) Code is also provided for each node. Likewise, the province and Census Geographic Unit is given for each node in Canada. The IBT project name (e.g., Heron Bayou Drainage Ditch, Hennepin Canal) associated with each node and link segment is also reported.As is often the case with irrigation and drainage IBT projects, there are sometimes several relatively small, adjacent diversions/ditches along an IBT project. We focus on capturing the main components of the IBT, instead of representing dozens or even hundreds of connected small ditches that divert or collect water along the IBT project. Nonetheless, when the collective impact of these small water diversions or inputs may noticeably change IBT flows, we depict these small ditches together as a representative two-node pair connected by a link segment. One of the nodes represents approximately the middle of where these small ditches intersect with the main IBT channel. The other node is the approximate centroid of water users served by or areas drained by these small ditches. If one of the secondary channels is large relative to the main channel (i.e., ability to divert more than ~25% of the main channel flow based on channel top width or flow records), it is recorded with its own Node ID and Link ID (Fig. 4). Likewise, if a secondary channel has an official name granted by a government agency or its owner/operator, we also record this segment with its own Node IDs and Link ID(s).Fig. 4An example of an interbasin water transfer project in Arizona with major (yellow) and minor (orange) project components. The thick yellow lines represent primary components of the project that are recorded in our dataset and assigned a Link ID (white text label). The thin orange lines represent secondary or tertiary canals or ditches that are small relative to the main (yellow) project segments and are therefore not represented in our dataset. The blue lines represent HUC4 subregion boundaries.Full size imageWe record the primary, secondary, and tertiary purpose of each IBT project and these purposes are the same for all links within the IBT project. One of “water supply – public supply”, “water supply – irrigation”, “flood control”, “navigation”, “waste discharge”, “environmental flows”, “energy – hydroelectric”, “energy – thermoelectric”, “energy – mining”, “other”, or “unknown” is assigned to each IBT project based on online records, design documents, reports, and/or personal correspondence with local, state, or federal officials. Link infrastructural properties, such as whether the link is a lined canal, unlined canal, pipe/tunnel, or other structure, are recorded for each link segment.The average water transfer rate (m3/d) is reported for each link segment where this information is known. The average water transfer rate only represents flows for the identified link segment, not necessarily the entire IBT project since upstream/downstream diversions and inputs may mean flow rates are different in different portions of the project. The average water transfer rate is converted from the units provided to us but is otherwise left unchanged. The primary data records are often unclear or do not specify the time period used to estimate average water transfer rates. The IBT Inventory Dataset reports whether time-series data is available for each Link ID in the IBT Time-Series Flow Dataset.The IBTDS 1.0 data standard was also applied to the IBT Time-Series Flow Dataset. The unique Link ID identifying the location where the transferred flow rate was measured is recorded for each time-series entry, relating the time-series data records to the IBT Inventory Dataset. The recorded flow rate only represents water transfer rates for the given link segment where the measurement was made, not necessarily the entire IBT project. Time-series data describing IBT flow rates were recorded at various temporal resolutions, ranging from instantaneous gauge readings every 15 minutes to average annual records. The standardized time-series dataset converted all reported water transfers to a common measurement unit (m3) and temporal resolution (day). When available, a web link to the original data source is published with the standardized data. The original timestep which the data was collected is also reported for each entry.In a few instances, there is more than one flow measurement for a link segment. Measurements are typically reported by different agencies and the measurements do not always align perfectly, either in their quantity or frequency of their reporting. Unless one of the records is known to be erroneous or of inferior quality, both sets of records are standardized and reported. For example, USBR reports monthly water transfer volumes along the Central Arizona Project (Link ID: CAP.AZ.01), while USGS reports daily water transfer volumes for the same link segment.Data visualizationWe provide an online visualization of the IBT Geospatial Dataset using ArcGIS Online (https://virginiatech.maps.arcgis.com/apps/mapviewer/index.html?webmap=b2cfac9b70ea44e4938734da0b1a7c8e), which is also summarized in Fig. 1. Every IBT node and link segment in the IBT Inventory Dataset is included. An arrowhead at the end of a link segment depicts the flow direction of transferred water. Link segments imported into ArcGIS Online were initially represented as a straight path between connected nodes. When the IBT flowpath was visible from aerial imagery or the flowpath was available from existing sources (e.g., NHD or detailed engineering drawings), the exact path of transferred water was mapped; otherwise, the flowpath remained a straight line between connected nodes.State and federal agencies restricted some of the data we are able to share publicly. Specifically, we are not permitted to reveal the exact water intake and treatment locations of some public water suppliers. Instead of mapping the precise latitude and longitude of points of diversion, points of flow change, and points of use like with other IBTs, IBTs whose primary purpose is public water supply are depicted as a straight line connecting the centroids of subwatersheds (HUC12) where the IBT node is located. More

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    Qatar Peninsula’s vulnerability to oil spills and its implications for the global gas supply

    GIIGNL 2021 Annual Report (GIIGNL, 2021); https://giignl.org/publications/giignl-2021-annual-reportHofste, R. W., Reig, P. & Schleifer, L. 17 Countries, Home to One-Quarter of the World’s Population, Face Extremely High Water Stress (World Resources Institute, 2019)Abotalib, A. Z., Heggy, E., Scabbia, G. & Mazzoni, A. Groundwater dynamics in fossil fractured carbonate aquifers in Eastern Arabian Peninsula: a preliminary investigation. J. Hydrol. 571, 460–470 (2019).Article 
    CAS 

    Google Scholar 
    Mohieldeen, Y. E., Elobaid, E. A. & Abdalla, R. GIS-based framework for artificial aquifer recharge to secure sustainable strategic water reserves in Qatar arid environment peninsula. Sci. Rep. 11, 18184 (2021).Article 
    CAS 

    Google Scholar 
    Darwish, M. A. & Mohtar, R. Qatar water challenges. Desalination Water Treat. 51, 75–86 (2013).Article 
    CAS 

    Google Scholar 
    Hussein, H. & Lambert, L. A rentier state under blockade: Qatar’s water–energy–food predicament from energy abundance and food insecurity to a silent water crisis. Water 12, 1051 (2020).Article 

    Google Scholar 
    Water Sector (Kahramaa, accessed 30 August 2022); https://www.km.qa/Aboutus/Pages/Watersector.aspxAnnual Statistics Report 2020 (Kahramaa, 2021); https://www.km.qa/MediaCenter/Publications/Annual%20Statistics%20Report%202020%20English.pdf (2021)Dale, S. bp Statistical Review of World Energy 2021 (bp, 2022); https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2022-full-report.pdfEl Gamal, R. Qatar Petroleum signs deal for mega-LNG expansion. Reuters (8 February 2021).Global Gas Outlook to 2050 (McKinsey & Company, 2021); https://www.mckinsey.com/~/media/mckinsey/industries/oil%20and%20gas/our%20insights/global%20gas%20outlook%20to%202050/global-gas-outlook-2050-executive-summary.pdfSurkes, S. 2017 oil spill closed three desalination plants for three days, official reveals. The Times of Israel (19 March 2021).Aizhu, C. & Blanchard, B. China seals oil port after spill. Reuters (19 July 2010).Huynh, B. Q. et al. Public health impacts of an imminent Red Sea oil spill. Nat. Sustain. https://doi.org/10.1038/s41893-021-00774-8 (2021).Article 

    Google Scholar 
    Annual Statistical Bulletin (OPEC, 2021); https://asb.opec.orgEvtushenko, N., Ivanov, A. & Evtushenko, V. in Advances in Remote Sensing and Geo Informatics Applications (eds El-Askary, H. M. et al.) 343–347 (Springer, 2019).Sheppard, C. et al. The Gulf: a young sea in decline. Mar. Pollut. Bull. 60, 13–38 (2010).Article 
    CAS 

    Google Scholar 
    Worldwide Rig Counts—Current & Historical Data (Baker Hughes, 2021); https://rigcount.bakerhughes.com/intl-rig-countGarcia-Pineda, O. et al. Classification of oil spill by thicknesses using multiple remote sensors. Remote Sens. Environ. 236, 111421 (2020).Article 

    Google Scholar 
    Al Azhar, M., Temimi, M., Zhao, J. & Ghedira, H. Modeling of circulation in the Arabian Gulf and the Sea of Oman: skill assessment and seasonal thermohaline structure. J. Geophys. Res. Oceans 121, 1700–1720 (2016).Article 

    Google Scholar 
    Thoppil, P. G. & Hogan, P. J. A modeling study of circulation and eddies in the Persian Gulf. J. Phys. Oceanogr. 40, 2122–2134 (2010).Article 

    Google Scholar 
    Thoppil, P. G. & Hogan, P. J. Persian Gulf response to a wintertime shamal wind event. Deep Sea Res. 1 57, 946–955 (2010).Article 

    Google Scholar 
    Yu, Y., Notaro, M., Kalashnikova, O. V. & Garay, M. J. Climatology of summer shamal wind in the Middle East: summer shamal climatology. J. Geophys. Res. Atmos. 121, 289–305 (2016).Article 

    Google Scholar 
    Tahir, F., Baloch, A. A. B. & Ali, H. in Sustainability Perspectives: Science, Policy and Practice: A Global View of Theories, Policies and Practice in Sustainable Development (eds Khaiter, P. A. & Erechtchoukova, M. G.) 303–329 (Springer, 2020); https://doi.org/10.1007/978-3-030-19550-2_15Benzene (ATSDR, 2015); https://www.atsdr.cdc.gov/sites/toxzine/docs/benzene_toxzine.pdfAl-Amirah, A. S. The Nowruz oil spill in the Arabian Gulf: case study of Saudi Arabia. Geogr. Bull. 37, 16–32 (1985).Marhoon, Y. Qatar Response Plan Version 5 (OSRL, 2021); https://www.oilspillresponse.com/globalassets/external-links/covid-19-updates/emea—qatar-response-090420-1030.pdfGlobal LNG Market Outlook 2022–26 (Bloomberg, 2022); https://bbgmktg.turtl.co/story/global-lng-market-outlook/Commodity Markets (World Bank, accessed 23 August 2022); https://www.worldbank.org/en/research/commodity-marketsStapczynski, S. Global energy crunch is making gas too pricey for Asia. Bloomberg (17 June 2022).Yep, E. Factbox: Asia-Pacific economies face escalating energy crisis. S&P Global Commodity Insights (27 June 2022).Gill, J. Analysis: heat or eat? Winter protests loom as energy poverty sweeps Europe. Reuters (25 August 2022).Twidale, S. & Buli, N. EU gas price rockets higher after Russia halts Nord Stream flows. Reuters (5 September 2022).Water Security Mega Reservoirs Project (Kahramaa, accessed 11 October 2021); http://www.watermegareservoirs.qaNatural-gas prices are spiking around the world. The Economist (21 September 2021).Dagestad, K.-F., Röhrs, J., Breivik, Ø. & Ådlandsvik, B. OpenDrift v1.0: a generic framework for trajectory modeling. Geosci. Model Dev. 11, 1405–1420 (2018) https://doi.org/10.5194/gmd-11-1405-2018Barker, C. H. et al. Progress in operational modeling in support of oil spill response. J. Mar. Sci. Eng. 8, 668 (2020).Article 

    Google Scholar 
    Röhrs, J. et al. The effect of vertical mixing on the horizontal drift of oil spills. Ocean Sci. 14, 1581–1601 (2018).Keramea, P., Kokkos, N., Gikas, G. & Sylaios, G. Operational modeling of North Aegean oil spills forced by real-time met–ocean forecasts. J. Mar. Sci. Eng. 10, 411 (2022).Article 

    Google Scholar 
    Androulidakis, Y., Kourafalou, V., Robert Hole, L., Le Hénaff, M. & Kang, H. Pathways of oil spills from potential Cuban offshore exploration: influence of ocean circulation. J. Mar. Sci. Eng. 8, 535 (2020).Article 

    Google Scholar 
    Breivik, Ø., Bidlot, J.-R. & Janssen, P. A. E. M. A Stokes drift approximation based on the Phillips spectrum. Ocean Model. 100, 49–56 (2016).Article 

    Google Scholar 
    Li, Z., Spaulding, M. L. & French-McCay, D. An algorithm for modeling entrainment and naturally and chemically dispersed oil droplet size distribution under surface breaking wave conditions. Mar. Pollut. Bull. 119, 145–152 (2017).Article 
    CAS 

    Google Scholar 
    Tkalich, P. & Chan, E. S. Vertical mixing of oil droplets by breaking waves. Mar. Pollut. Bull. 44, 1219–1229 (2002).Article 
    CAS 

    Google Scholar 
    Li, Z., Spaulding, M., French McCay, D., Crowley, D. & Payne, J. R. Development of a unified oil droplet size distribution model with application to surface breaking waves and subsea blowout releases considering dispersant effects. Mar. Pollut. Bull. 114, 247–257 (2017).Article 
    CAS 

    Google Scholar 
    Sundby, S. A one-dimensional model for the vertical distribution of pelagic fish eggs in the mixed layer. Deep Sea Res. A 30, 645–661 (1983).Article 

    Google Scholar 
    Lehr, W., Jones, R., Evans, M., Simecek-Beatty, D. & Overstreet, R. Revisions of the ADIOS oil spill model. Environ. Model. Softw. 17, 189–197 (2002).Article 

    Google Scholar 
    Zodiatis, G. et al. The Mediterranean Decision Support System for Marine Safety dedicated to oil slicks predictions. Deep Sea Res. 2 133, 4–20 (2016).Article 

    Google Scholar 
    Amir-Heidari, P. & Raie, M. Probabilistic risk assessment of oil spill from offshore oil wells in Persian Gulf. Mar. Pollut. Bull. 136, 291–299 (2018).Article 
    CAS 

    Google Scholar 
    Batchelder, H. P. Forward-in-time-/backward-in-time-trajectory (FITT/BITT) modeling of particles and organisms in the coastal ocean. J. Atmos. Ocean. Technol. 23, 727–741 (2006).Article 

    Google Scholar 
    Ciappa, A. C. Reverse trajectory study of oil spill risk in Cyclades Islands of the Aegean Sea. Reg. Stud. Mar. Sci. 41, 101580 (2021).
    Google Scholar 
    Suneel, V., Ciappa, A. & Vethamony, P. Backtrack modeling to locate the origin of tar balls depositing along the west coast of India. Sci. Total Environ. 569–570, 31–39 (2016).Article 

    Google Scholar 
    Zelenke, B., O’Connor, C. & Barker, C. General NOAA Operational Modeling Environment (GNOME) Technical Documentation (NOAA OR&R, October 2012); https://response.restoration.noaa.gov/gnome_manualDe Dominicis, M., Pinardi, N., Zodiatis, G. & Archetti, R. MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting—part 2: numerical simulations and validations. Geosci. Model Dev. 6, 1871–1888 (2013).Article 

    Google Scholar 
    Fingas, M. in Oil Spill Science and Technology (ed. Fingas, M.) 243–273 (Elsevier, 2011); https://doi.org/10.1016/B978-1-85617-943-0.10010-3Madec, G. NEMO ocean engine. Zenodo (2017) https://doi.org/10.5281/zenodo.3248739Eager, R. E. et al. A climatological study of the sea and land breezes in the Arabian Gulf region. J. Geophys. Res. 113, D15106 (2008).Article 

    Google Scholar 
    MarineTraffic: Global Ship Tracking Intelligence (accessed 15 May 2021) https://www.marinetraffic.com/Etkin, D. S. et al. in Oil Spill Science and Technology 2nd edn (ed. Fingas, M.) 71–183 (Gulf Professional Publishing, 2017); https://doi.org/10.1016/B978-0-12-809413-6.00002-3Oil Tanker Spill Statistics 2021 (ITOPF, 2022); https://www.itopf.org/knowledge-resources/data-statistics/statistics/Quattrocchi, G. et al. An operational numerical system for oil stranding risk assessment in a high-density vessel traffic area. Front. Mar. Sci. 8, 585396 (2021).Article 

    Google Scholar  More

  • in

    Agricultural drought over water-scarce Central Asia aggravated by internal climate variability

    Dai, A. & Zhao, T. Uncertainties in historical changes and future projections of drought. Part I: estimates of historical drought changes. Climatic Change 144, 519–533 (2017).Article 

    Google Scholar 
    Greve, P. et al. Global assessment of trends in wetting and drying over land. Nat. Geosci. 7, 716–721 (2014).Article 

    Google Scholar 
    Jiang, J. et al. Tracking moisture sources of precipitation over central Asia: a study based on the water-source-tagging method. J. Clim. 33, 10339–10355 (2020).Article 

    Google Scholar 
    Seneviratne, S. I. et al. in Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).Li, Z., Chen, Y., Fang, G. & Li, Y. Multivariate assessment and attribution of droughts in Central Asia. Sci. Rep. 7, 1316 (2017).Article 

    Google Scholar 
    Li, Z., Chen, Y., Li, W., Deng, H. & Fang, G. Potential impacts of climate change on vegetation dynamics in Central Asia. J. Geophys. Res. Atmos. 120, 12345–12356 (2015).Article 

    Google Scholar 
    Deng, H. & Chen, Y. Influences of recent climate change and human activities on water storage variations in Central Asia. J. Hydrol. 544, 46–57 (2017).Article 

    Google Scholar 
    Seager, R., Nakamura, J. & Ting, M. Mechanisms of seasonal soil moisture drought onset and termination in the southern Great Plains. J. Hydrometeorol. 20, 751–771 (2019).Article 

    Google Scholar 
    Teuling, A. J. et al. Evapotranspiration amplifies European summer drought. Geophys. Res. Lett. 40, 2071–2075 (2013).Article 

    Google Scholar 
    Douville, H. et al. in Climate Change 2021: The Physical Science Basis (eds. Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).Dai, A. Increasing drought under global warming in observations and models. Nat. Clim. Change 3, 52–58 (2013).Article 

    Google Scholar 
    Barlow, M. & Hoell, A. Drought in the Middle East and Central–Southwest Asia during winter 2013/14. Bull. Am. Meteorol. Soc. 96, S71–S76 (2015).Article 

    Google Scholar 
    Peng, D., Zhou, T., Zhang, L. & Zou, L. Detecting human influence on the temperature changes in Central Asia. Clim. Dyn. 53, 4553–4568 (2019).Article 

    Google Scholar 
    Barlow, M. et al. A review of drought in the Middle East and Southwest Asia. J. Clim. 29, 8547–8574 (2016).Article 

    Google Scholar 
    Hoell, A., Funk, C. & Barlow, M. The forcing of Southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter. J. Clim. 28, 1511–1526 (2015).Article 

    Google Scholar 
    Jiang, J. & Zhou, T. Human‐induced rainfall reduction in drought‐prone northern central Asia. Geophys. Res. Lett. 48, e2020GL092156 (2021).Article 

    Google Scholar 
    Williams, A. P. et al. Contribution of anthropogenic warming to California drought during 2012–2014. Geophys. Res. Lett. 42, 6819–6828 (2015).Article 

    Google Scholar 
    Williams, A. P. et al. Large contribution from anthropogenic warming to an emerging North American megadrought. Science 368, 314–318 (2020).Article 

    Google Scholar 
    Samaniego, L. et al. Anthropogenic warming exacerbates European soil moisture droughts. Nat. Clim. Change 8, 421–426 (2018).Article 

    Google Scholar 
    García-Herrera, R. et al. The European 2016/17 drought. J. Clim. 32, 3169–3187 (2019).Article 

    Google Scholar 
    Mueller, B. & Zhang, X. Causes of drying trends in northern hemispheric land areas in reconstructed soil moisture data. Clim. Change 134, 255–267 (2016).Article 

    Google Scholar 
    Gu, X. et al. Attribution of global soil moisture drying to human activities: a quantitative viewpoint. Geophys. Res. Lett. 46, 2573–2582 (2019).Article 

    Google Scholar 
    Coats, S. et al. Internal ocean–atmosphere variability drives megadroughts in western North America. Geophys. Res. Lett. 43, 9886–9894 (2016).Article 

    Google Scholar 
    Deser, C. et al. Insights from Earth system model initial-condition large ensembles and future prospects. Nat. Clim. Change 10, 277–286 (2020).Article 

    Google Scholar 
    Hawkins, E. & Sutton, R. The potential to narrow uncertainty in regional climate predictions. Bull. Am. Meteorol. Soc. 90, 1095–1108 (2009).Article 

    Google Scholar 
    Deser, C., Knutti, R., Solomon, S. & Phillips, A. S. Communication of the role of natural variability in future North American climate. Nat. Clim. Change 2, 775–779 (2012).Article 

    Google Scholar 
    Murphy, J. M. et al. Transient climate changes in a perturbed parameter ensemble of emissions-driven Earth system model simulations. Clim. Dyn. 43, 2855–2885 (2014).Article 

    Google Scholar 
    Huang, X. et al. The recent decline and recovery of Indian summer monsoon rainfall: relative roles of external forcing and internal variability. J. Clim. 33, 5035–5060 (2020).Article 

    Google Scholar 
    Zhang, Y., Wallace, J. M. & Battisti, D. S. ENSO-like interdecadal variability: 1900–93. J. Clim. 10, 1004–1020 (1997).Article 

    Google Scholar 
    Power, S., Casey, T., Folland, C., Colman, A. & Mehta, V. Inter-decadal modulation of the impact of ENSO on Australia. Clim. Dyn. 15, 319–324 (1999).Article 

    Google Scholar 
    Henley, B. J. et al. A tripole index for the Interdecadal Pacific Oscillation. Clim. Dyn. 45, 3077–3090 (2015).Article 

    Google Scholar 
    Wu, L., Ma, X., Dou, X., Zhu, J. & Zhao, C. Impacts of climate change on vegetation phenology and net primary productivity in arid Central Asia. Sci. Total Environ. 796, 149055 (2021).Article 

    Google Scholar 
    FAO. Drought Characteristics and Management in Central Asia and Turkey (FAO Water Reports, 2017).Cai, W., Cowan, T., Briggs, P. & Raupach, M. Rising temperature depletes soil moisture and exacerbates severe drought conditions across southeast Australia. Geophys. Res. Lett. 36, L21709 (2009).Article 

    Google Scholar 
    Kidron, G. J. & Kronenfeld, R. Temperature rise severely affects pan and soil evaporation in the Negev Desert. Ecohydrology 9, 1130–1138 (2016).Article 

    Google Scholar 
    Xu, Y., Zhang, X., Hao, Z., Singh, V. P. & Hao, F. Characterization of agricultural drought propagation over China based on bivariate probabilistic quantification. J. Hydrol. 598, 126194 (2021).Article 

    Google Scholar 
    Bae, H. et al. Characteristics of drought propagation in South Korea: relationship between meteorological, agricultural, and hydrological droughts. Nat. Hazards 99, 1–16 (2019).Article 

    Google Scholar 
    Wang, W., Ertsen, M. W., Svoboda, M. D. & Hafeez, M. Propagation of drought: from meteorological drought to agricultural and hydrological drought. Adv. Meteorol. 2016, 127897 (2016).Article 

    Google Scholar 
    Hoell, A., Funk, C., Barlow, M. & Cannon, F. in Climate Extremes: Patterns and Mechanisms (eds Wang, S. et al.) 283–298 (American Geophysical Union, 2017).Wu, M. et al. A very likely weakening of Pacific Walker Circulation in constrained near-future projections. Nat. Commun. 12, 6502 (2021).Article 

    Google Scholar 
    Hoell, A., Barlow, M., Cannon, F. & Xu, T. Oceanic origins of historical southwest Asia precipitation during the boreal cold season. J. Clim. 30, 2885–2903 (2017).Article 

    Google Scholar 
    Jiang, J., Zhou, T., Chen, X. & Wu, B. Central Asian precipitation shaped by the tropical Pacific decadal variability and the Atlantic multidecadal variability. J. Clim. 34, 7541–7553 (2021).Article 

    Google Scholar 
    Barlow, M. A. & Tippett, M. K. Variability and predictability of Central Asia river flows: antecedent winter precipitation and large-scale teleconnections. J. Hydrometeorol. 9, 1334–1349 (2008).Article 

    Google Scholar 
    Hoell, A., Barlow, M. & Saini, R. Intraseasonal and seasonal-to-interannual Indian Ocean convection and hemispheric teleconnections. J. Clim. 26, 8850–8867 (2013).Article 

    Google Scholar 
    Rana, S., McGregor, J. & Renwick, J. Dominant modes of winter precipitation variability over Central Southwest Asia and inter-decadal change in the ENSO teleconnection. Clim. Dyn. https://doi.org/10.1007/s00382-019-04889-9 (2019).Article 

    Google Scholar 
    Jiang, J., Zhou, T., Chen, X. & Zhang, L. Future changes in precipitation over Central Asia based on CMIP6 projections. Environ. Res. Lett. 15, 054009 (2020).Article 

    Google Scholar 
    Huang, X. et al. South Asian summer monsoon projections constrained by the interdecadal Pacific oscillation. Sci. Adv. 6, eaay6546 (2020).Article 

    Google Scholar 
    Varis, O. Resources: curb vast water use in Central Asia. Nature 514, 27–29 (2014).Article 

    Google Scholar 
    Farah, P. in ENERGY: POLICY, LEGAL AND SOCIAL-ECONOMIC ISSUES UNDER THE DIMENSIONS OF SUSTAINABILITY AND SECURITY (eds Farah, P. & Rossi, P.) 179–193 (Imperial College Press & World Scientific Publishing, 2015).Wang, X., Chen, Y., Li, Z., Fang, G. & Wang, Y. Development and utilization of water resources and assessment of water security in Central Asia. Agric. Water Manag. 240, 106297 (2020).Article 

    Google Scholar 
    Peng, D., Zhou, T., Zhang, L., Zhang, W. & Chen, X. Observationally constrained projection of the reduced intensification of extreme climate events in Central Asia from 0.5 °C less global warming. Clim. Dyn. 54, 543–560 (2020).Article 

    Google Scholar 
    Pokhrel, Y. et al. Global terrestrial water storage and drought severity under climate change. Nat. Clim. Change 11, 226–233 (2021).Article 

    Google Scholar 
    Zhao, T. & Dai, A. CMIP6 model-projected hydroclimatic and drought changes and their causes in the 21st century. J. Clim. https://doi.org/10.1175/JCLI-D-21-0442.1 (2021).Balsamo, G. et al. ERA-Interim/Land: a global land surface reanalysis data set. Hydrol. Earth Syst. Sci. 19, 389–407 (2015).Article 

    Google Scholar 
    Rodell, M. et al. The Global Land Data Assimilation System. Bull. Am. Meteorol. Soc. 85, 381–394 (2004).Article 

    Google Scholar 
    Martens, B. et al. GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev. 10, 1903–1925 (2017).Article 

    Google Scholar 
    Preimesberger, W., Scanlon, T., Su, C.-H., Gruber, A. & Dorigo, W. Homogenization of structural breaks in the global ESA CCI soil moisture multisatellite climate data record. IEEE Trans. Geosci. Remote Sens. 59, 2845–2862 (2021).Article 

    Google Scholar 
    Dunn, R. J. H. et al. Development of an updated global land in situ‐based data set of temperature and precipitation extremes: HadEX3. J. Geophys. Res. Atmos. 125, e2019JD032263 (2020).Article 

    Google Scholar 
    Rohde, R., Muller, R., Jacobsen, R., Perlmutter, S. & Mosher, S. Berkeley Earth temperature averaging process. Geoinf. Geostat. 1, 2 (2013).
    Google Scholar 
    Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).Article 

    Google Scholar 
    Deser, C., Simpson, I. R., McKinnon, K. A. & Phillips, A. S. The Northern Hemisphere extratropical atmospheric circulation response to ENSO: how well do we know it and how do we evaluate models accordingly? J. Clim. 30, 5059–5082 (2017).Article 

    Google Scholar 
    Deser, C., Guo, R. & Lehner, F. The relative contributions of tropical Pacific sea surface temperatures and atmospheric internal variability to the recent global warming hiatus. Geophys. Res. Lett. 44, 7945–7954 (2017).Article 

    Google Scholar 
    Henley, B. J. Pacific decadal climate variability: indices, patterns and tropical–extratropical interactions. Glob. Planet. Change 155, 42–55 (2017).Article 

    Google Scholar 
    Kaplan, A. et al. Analyses of global sea surface temperature 1856–1991. J. Geophys. Res. Ocean. 103, 18567–18589 (1998).Article 

    Google Scholar 
    Huang, B. et al. Extended reconstructed sea surface temperature, Version 5 (ERSSTv5): upgrades, validations, and intercomparisons. J. Clim. 30, 8179–8205 (2017).Article 

    Google Scholar 
    Salzmann, M. & Cherian, R. On the enhancement of the Indian summer monsoon drying by Pacific multidecadal variability during the latter half of the twentieth century. J. Geophys. Res. Atmos. 120, 9103–9118 (2015).Article 

    Google Scholar 
    Ohlson, J. A. & Kim, S. Linear valuation without OLS: the Theil–Sen estimation approach. SSRN Electron. J. https://doi.org/10.2139/ssrn.2276927 (2013).Article 

    Google Scholar 
    Mann, H. B. Nonparametric tests against trend. Econometrica 13, 245–259 (1945).Article 

    Google Scholar 
    Kendall, M. G. Rank Correlation Methods (Hafner Publishing Company, 1955). More

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    Negotiating Nile infrastructure management should consider climate change uncertainties

    Based on 29 climate projections, we find that both the sign and magnitude of potential changes in naturalized streamflow of the Nile in 2021–2050 are highly uncertain. These uncertainties spark the need for an adaptive and cooperative approach. We show that cooperative adaptive management of the GERD yields compromise solutions with economy-wide benefits to Ethiopia, Sudan and Egypt compared with a proposal discussed in Washington, D.C. in 2020 (Fig. 1). Under an example compromise solution (Fig. 1), the mean (based on 29 projections) discounted (at 3%) real gross domestic product (GDP) increases by US$0.77, 0.67 and 0.18 billion in 2020–2045 for Ethiopia, Sudan and Egypt, respectively, relative to the Washington draft proposal. These benefits are more pronounced under extreme climate scenarios, with rises in discounted real GDP of up to US$15.8, 6.3 and 3.0 billion over 2020–2045 for Ethiopia, Sudan and Egypt, respectively. Our results should be complemented by evaluating the impacts on ecology, groundwater and riparian populations.Fig. 1: Ethiopian, Sudanese and Egyptian economic and river system performance under the best-performing designs of an adaptive GERD operating approach, considering 29 climate change projections for 2020–2045.Each line of the parallel coordinates plot shows the performance achieved by one of the Pareto-efficient adaptive designs or policies, that is, a policy that, if further improved for one performance metric, would imply a reduction in one or more other performance metrics. All change values are calculated from a baseline in which the GERD is operated based on the Washington draft proposal. The upward direction on each axis indicates better performance (that is, a ‘perfect adaptive plan’ would be a straight line across the top); diagonal lines between neighbouring axes imply tradeoffs, whereas horizontal ones show synergies. The firm power values are calculated based on a 90% reliability, and the real GDP values are discounted at a 3% rate. bcm, billion cubic metres.Full size image More

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    Cooperative adaptive management of the Nile River with climate and socio-economic uncertainties

    IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).Wigley, T. M. L. & Raper, S. C. B. Natural variability of the climate system and detection of the greenhouse effect. Nature 344, 324–327 (1990).Article 

    Google Scholar 
    Crowley, J. T. Causes of climate change over the past 1000 years. Science 289, 270–277 (2000).Article 
    CAS 

    Google Scholar 
    Wang, W. C., Yung, Y. L., Lacis, A. A., Mo, T. A. & Hansen, J. E. Greenhouse effects due to man-made perturbations of trace gases. Science 194, 685–690 (1976).Article 
    CAS 

    Google Scholar 
    Paris Agreement (United Nations Framework Convention on Climate Change, 2015).Rio+20 United Nations Conference on Sustainable Development The Future We Want: Outcome Document of the United Nations Conference on Sustainable Development (United Nations, 2012).Basheer, M. et al. Collaborative management of the Grand Ethiopian Renaissance Dam increases economic benefits and resilience. Nat. Commun. 12, 5622 (2021).Article 
    CAS 

    Google Scholar 
    Agreement between the Republic of the Sudan and the United Arab Republic for the Full Utilization of the Nile Waters (International Water Law Project, 1959); http://internationalwaterlaw.org/documents/regionaldocs/uar_sudan.htmlCascão, A. E. & Nicol, A. GERD: new norms of cooperation in the Nile Basin? Water Int. 41, 550–573 (2016).Article 

    Google Scholar 
    Salman, S. The Grand Ethiopian Renaissance Dam: the road to the declaration of principles and the Khartoum document. Water Int. 41, 512–527 (2016).Article 

    Google Scholar 
    Tawfik, R. The Grand Ethiopian Renaissance Dam: a benefit-sharing project in the Eastern Nile? Water Int. 41, 574–592 (2016).Article 

    Google Scholar 
    Wheeler, K. G., Jeuland, M., Hall, J. W., Zagona, E. & Whittington, D. Understanding and managing new risks on the Nile with the Grand Ethiopian Renaissance Dam. Nat. Commun. https://doi.org/10.1038/s41467-020-19089-x (2020).Wheeler, K. et al. Exploring cooperative transboundary river management strategies for the Eastern Nile Basin. Water Resour. Res. https://doi.org/10.1029/2017WR022149 (2018).Wheeler, K. G. et al. Cooperative filling approaches for the Grand Ethiopian Renaissance Dam. Water Int. 41, 611–634 (2016).Article 

    Google Scholar 
    Basheer, M. et al. Quantifying and evaluating the impacts of cooperation in transboundary river basins on the water–energy–food nexus: the Blue Nile Basin. Sci. Total Environ. 630, 1309–1323 (2018).Article 
    CAS 

    Google Scholar 
    Basheer, M. Cooperative operation of the Grand Ethiopian Renaissance Dam reduces Nile riverine floods. River Res. Appl. 47, 805–814 (2021).Article 

    Google Scholar 
    Elagib, N. A. & Basheer, M. Would Africa’s largest hydropower dam have profound environmental impacts? Environ. Sci. Pollut. Res. 28, 8936–8944 (2021).Article 
    CAS 

    Google Scholar 
    Joint Statement of Egypt, Ethiopia, Sudan, the United States and the World Bank (United States Department of the Treasury, 2020); https://home.treasury.gov/news/press-releases/sm891Edrees, M. Letter dated 11 June 2021 from the Permanent Representative of Egypt to the United Nations addressed to the Secretary-Genera (United Nations, 2021); https://digitallibrary.un.org/record/3931750?ln=enAmde, T. A. Letter dated 14 May 2020 from the Permanent Representative of Ethiopia to the United Nations addressed to the President of the Security Council (United Nations, 2020); https://digitallibrary.un.org/record/3862715?ln=enTaye, M. T., Willems, P. & Block, P. Implications of climate change on hydrological extremes in the Blue Nile Basin: a review. J. Hydrol. Reg. Stud. 4, 280–293 (2015).Article 

    Google Scholar 
    Di Baldassarre, G. et al. Future hydrology and climate in the River Nile Basin: a review. Hydrol. Sci. J. 56, 199–211 (2011).Article 

    Google Scholar 
    Bhattacharjee, P. S. & Zaitchik, B. F. Perspectives on CMIP5 model performance in the Nile River headwaters regions. Int. J. Climatol. 35, 4262–4275 (2015).Article 

    Google Scholar 
    Haasnoot, M., Kwakkel, J. H., Walker, W. E. & ter Maat, J. Dynamic adaptive policy pathways: a method for crafting robust decisions for a deeply uncertain world. Glob. Environ. Change 23, 485–498 (2013).Article 

    Google Scholar 
    Hui, R., Herman, J., Lund, J. & Madani, K. Adaptive water infrastructure planning for nonstationary hydrology. Adv. Water Resour. 118, 83–94 (2018).Article 

    Google Scholar 
    Marchau, V. A. W. J., Walker, W. E., Bloemen, P. J. T. M. & Popper, S. W. (eds) Decision Making under Deep Uncertainty: From Theory to Practice (Springer, 2019).Smith, M. et al. Adaptation’s Thirst: Accelerating the Convergence of Water and Climate Action (Global Commission on Adaptation, 2019).Hallegatte, S. Strategies to adapt to an uncertain climate change. Glob. Environ. Change 19, 240–247 (2009).Article 

    Google Scholar 
    Reed, P. M. et al. Multisector dynamics: advancing the science of complex adaptive human–Earth systems. Earth’s Future 10, e2021EF002621 (2022).Article 

    Google Scholar 
    Walker, W. E., Haasnoot, M. & Kwakkel, J. H. Adapt or perish: a review of planning approaches for adaptation under deep uncertainty. Sustainability 5, 955–979 (2013).Article 

    Google Scholar 
    Kwadijk, J. C. J. et al. Using adaptation tipping points to prepare for climate change and sea level rise: a case study in the Netherlands. WIREs Clim. Change 1, 729–740 (2010).Article 

    Google Scholar 
    Kwakkel, J. H., Walker, W. E. & Marchau, V. Adaptive airport strategic planning. Eur. J. Transp. Infrastruct. Res. 10, 249–273 (2010).Kwakkel, J. H., Haasnoot, M. & Walker, W. E. Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world. Climatic Change 132, 373–386 (2015).Article 

    Google Scholar 
    Zeff, H. B., Herman, J. D., Reed, P. M. & Characklis, G. W. Cooperative drought adaptation: integrating infrastructure development, conservation, and water transfers into adaptive policy pathways. Water Resour. Res. https://doi.org/10.1002/2016WR018771 (2016).Fletcher, S., Lickley, M. & Strzepek, K. Learning about climate change uncertainty enables flexible water infrastructure planning. Nat. Commun. 10, 1782 (2019).Article 

    Google Scholar 
    Cohen, J. S. & Herman, J. D. Dynamic adaptation of water resources systems under uncertainty by learning policy structure and indicators. Water Resour. Res. 57, e2021WR030433 (2021).Article 

    Google Scholar 
    Ricalde, I. et al. Assessing tradeoffs in the design of climate change adaptation strategies for water utilities in Chile. J. Environ. Manage. 302, 114035 (2022).Article 

    Google Scholar 
    Pachos, K., Huskova, I., Matrosov, E., Erfani, T. & Harou, J. J. Trade-off informed adaptive and robust real options water resources planning. Adv. Water Resour. 161, 104117 (2022).Article 

    Google Scholar 
    Gold, D. F., Reed, P. M., Gorelick, D. E. & Characklis, G. W. Power and pathways: exploring robustness, cooperative stability, and power relationships in regional infrastructure investment and water supply management portfolio pathways. Earth’s Future 10, e2021EF002472 (2022).Beh, E. H. Y., Maier, H. & Dandy, G. C. Adaptive, multiobjective optimal sequencing approach for urban water supply augmentation under deep uncertainty. Water Resour. Res. https://doi.org/10.1002/2014WR016254 (2015).O’Neill, B. C. et al. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev. 9, 3461–3482 (2016).Article 

    Google Scholar 
    Wainwright, C. M. et al. ‘Eastern African Paradox’ rainfall decline due to shorter not less intense Long Rains. NPJ Clim. Atmos. Sci. 2, 34 (2019).Article 

    Google Scholar 
    Rowell, D. P., Booth, B. B. B., Nicholson, S. E. & Good, P. Reconciling past and future rainfall trends over East Africa. J. Clim. 28, 9768–9788 (2015).Article 

    Google Scholar 
    Riahi, K. et al. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).Article 

    Google Scholar 
    KC, S. & Lutz, W. The human core of the Shared Socioeconomic Pathways: population scenarios by age, sex and level of education for all countries to 2100. Glob. Environ. Change 42, 181–192 (2017).Article 

    Google Scholar 
    Crespo Cuaresma, J. Income projections for climate change research: a framework based on human capital dynamics. Glob. Environ. Change 42, 226–236 (2017).Article 

    Google Scholar 
    Water Level (Copernicus Global Land Service, 2022); https://land.copernicus.eu/global/products/wlInselberg, A. in Trends in Interactive Visualization: State-of-the-Art Survey (eds Liere, R. et al.) 49–78 (Springer, 2009).Goulden, M., Conway, D. & Persechino, A. Adaptation to climate change in international river basins in Africa: a review. Hydrol. Sci. J. 54, 805–828 (2009).Article 

    Google Scholar 
    Dasgupta, P. The Economics of Biodiversity: The Dasgupta Review (HM Treasury, 2021).François, B., Vrac, M., Cannon, A. J., Robin, Y. & Allard, D. Multivariate bias corrections of climate simulations: which benefits for which losses? Earth Syst. Dyn. 11, 537–562 (2020).Article 

    Google Scholar 
    Cannon, A. J., Sobie, S. R. & Murdock, T. Q. Bias correction of GCM precipitation by quantile mapping: how well do methods preserve changes in quantiles and extremes? J. Clim. 28, 6938–6959 (2015).Article 

    Google Scholar 
    Mehrotra, R. & Sharma, A. A resampling approach for correcting systematic spatiotemporal biases for multiple variables in a changing climate. Water Resour. Res. 55, 754–770 (2019).Article 

    Google Scholar 
    Vrac, M. & Friederichs, P. Multivariate-intervariable, spatial, and temporal-bias correction. J. Clim. 28, 218–237 (2015).Article 

    Google Scholar 
    Beck, H. E. et al. MSWEP v2 global 3-hourly 0.1° precipitation: methodology and quantitative assessment. Bull. Am. Meteorol. Soc. 100, 473–500 (2019).Article 

    Google Scholar 
    Sheffield, J., Goteti, G. & Wood, E. F. Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J. Clim. 19, 3088–3111 (2006).Article 

    Google Scholar 
    Walker, D. P., Marsham, J. H., Birch, C. E., Scaife, A. A. & Finney, D. L. Common mechanism for interannual and decadal variability in the East African Long Rains. Geophys. Res. Lett. 47, e2020GL089182 (2020).King, J. A. & Washington, R. Future changes in the Indian Ocean Walker Circulation and links to Kenyan rainfall. J. Geophys. Res. Atmos. 126, e2021JD034585 (2021).Article 

    Google Scholar 
    Allen, R. G., Pereira, L. S., Raes, D. & Smith, M. FAO Irrigation and Drainage Paper: Crop Evapotranspiration (FAO, 1998).Liang, X., Lettenmaier, D. P., Wood, E. F. & Burges, S. J. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res. 99, 14415–14428 (1994).David, C. H. et al. River network routing on the NHDPlus dataset. J. Hydrometeorol. 12, 913–934 (2011).Article 

    Google Scholar 
    Lin, P. et al. Global reconstruction of naturalized river flows at 2.94 million reaches. Water Resour. Res. 55, 6499–6516 (2019).Article 

    Google Scholar 
    Development of the Eastern Nile Water Simulation Model (Deltares, 2013).Gill, M. A. Flood routing by the Muskingum method. J. Hydrol. 36, 353–363 (1978).Article 

    Google Scholar 
    Lehner, B. & Grill, G. Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrol. Process. 27, 2171–2186 (2013).Article 

    Google Scholar 
    Tomlinson, J. E., Arnott, J. H. & Harou, J. J. A water resource simulator in Python. Environ. Model. Softw. 126, 104635 (2020).Article 

    Google Scholar 
    Wurbs, R. A. Generalized Models of River System Development and Management (IntechOpen, 2011).Basheer, M., Sulieman, R. & Ribbe, L. Exploring management approaches for water and energy in the data-scarce Tekeze-Atbara Basin under hydrologic uncertainty. Int. J. Water Resour. Dev. 37, 182–207 (2021).Article 

    Google Scholar 
    Basheer, M. & Elagib, N. A. Sensitivity of water–energy nexus to dam operation: a water–energy productivity concept. Sci. Total Environ. 616–617, 918–926 (2018).Article 

    Google Scholar 
    Basheer, M. et al. Filling Africa’s largest hydropower dam should consider engineering realities. One Earth 3, 277–281 (2020).Article 

    Google Scholar 
    Jeuland, M., Wu, X. & Whittington, D. Infrastructure development and the economics of cooperation in the Eastern Nile. Water Int. https://doi.org/10.1080/02508060.2017.1278577 (2017).Lofgren, H., Lee, R., Robinson, S., Thomas, M. & El-Said, M. A Standard Computable General Equilibrium (CGE) Model in GAMS (International Food Policy Research Institute, 2002).Armington, P. S. A theory of demand for products distinguished by place of production. Staff Pap. 16, 159–178 (1969).Article 

    Google Scholar 
    Siddig, K., Elagra, S., Grethe, H. & Mubarak, A. A Post-separation Social Accounting Matrix for the Sudan (International Food Policy Research Institute, 2018); https://doi.org/10.2499/1024320695Al-Riffai, P. et al. A Disaggregated Social Accounting Matrix: 2010/11 for Policy Analysis in Egypt (International Food Policy Research Institute, 2016); http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/130736Ahmed, H. A., Tebekew, T. & Thurlow, J. 2010/11 Social Accounting Matrix for Ethiopia: A Nexus Project SAM (International Food Policy Research Institute, 2017); http://ebrary.ifpri.org/utils/getfile/collection/p15738coll2/id/131505/filename/131720.pdfChepeliev, M. Gtap-Power data base: version 10. J. Glob. Econ. Anal. 5, 110–137 (2020).Article 

    Google Scholar 
    Jiang, L. & O’Neill, B. C. Global urbanization projections for the Shared Socioeconomic Pathways. Glob. Environ. Change 42, 193–199 (2017).Article 

    Google Scholar 
    Fouré, J., Bénassy-Quéré, A. & Fontagné, L. Modelling the world economy at the 2050 horizon. Econ. Transit. Inst. Change 21, 617–654 (2013).
    Google Scholar 
    Gidden, M. J. et al. Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century. Geosci. Model Dev. 12, 1443–1475 (2019).Article 
    CAS 

    Google Scholar 
    Knox, S., Meier, P., Yoon, J. & Harou, J. J. A Python framework for multi-agent simulation of networked resource systems. Environ. Model. Softw. 103, 16–28 (2018).Article 

    Google Scholar 
    Deb, K. & Jain, H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints. IEEE Trans. Evol. Comput. 18, 577–601 (2014).Article 

    Google Scholar 
    Hadka, D. Platypus. GitHub https://github.com/Project-Platypus/Platypus (2016).Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C. M. & Da Fonseca, V. G. Performance assessment of multiobjective optimizers: an analysis and review. IEEE Trans. Evol. Comput. 7, 117–132 (2003).Article 

    Google Scholar 
    Basheer, M. et al. Balancing national economic policy outcomes for sustainable development. Nat. Commun. 13, 5041 (2022).Article 
    CAS 

    Google Scholar 
    Breiman, L. Random Forests. Mach. Learn. 45, 5–32 (2001).Article 

    Google Scholar 
    Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
    Google Scholar 
    Basheer, M., Nechifor, V., Calzadilla, A., Harou, J. J., Data related to a study on adaptive management of Nile infrastructure. Zenodo https://doi.org/10.5281/zenodo.5914757 (2022). More

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    Benchmarking the performance of water companies for regulatory purposes to improve its sustainability

    Efficiency estimationTo compute the efficiency scores of WCs based on the DEA-CSW approach, the methodology proposed by Wu et al.25 was employed. It was assumed that there are n units (left( {j = 1,..,,d,..,,n} right)) ((WC = left{ {d|d,is,a,water,company} right})) and each WC uses m inputs (left( {i = 1,….,,m} right)) to produce s outputs (left( {r = 1,….,,s} right)).To evaluate the efficiency of WCd, the basic DEA-CCR model proposed by Charnes et al.17 was used (Model 1):$$Max,E_d = mathop {sum}limits_{r = 1}^s {u_{rd}y_{rd}}$$
    (1)
    s.t.$$mathop {sum}limits_{r = 1}^s {u_{rd}y_{rj}} – mathop {sum}limits_{i = 1}^m {omega _{id}x_{ij} le 0}$$$$mathop {sum}limits_{i = 1}^m {omega _{id}x_{id} = 1}$$$$begin{array}{*{20}{c}} {u_{rd} ge 0} & {r = 1,2, ldots ,s} end{array}$$$$begin{array}{*{20}{c}} {omega _{id} ge 0} & {i = 1,2, ldots ,m} end{array}$$where (u_{rd}) is the weight of the output r for the WCd (observation evaluated) and (omega _{id}) is the weight of the input i for the water company evaluated (WCd). Model (1) is an output-oriented DEA model because within a regulatory framework, the objective of WCs is to improve the quality of their services (outputs) keeping constant economic costs (inputs).Model (1) selects the set of input and output weights that maximize the efficiency of WCd. In other words, the efficiency score for the water company d in the DEA-CCR model ((E_d)) is the best that the WCd can obtain. The WCd is efficient if (E_d = 1) and is not efficient (i.e. has room for improvement) if (E_d ,, left| { mp 3} right|$$
    (9)
    Table 3 Correlations (Pearson coefficient) between input and output variables.Full size tableTable 4 provides an overview of the statistical data employed to compute the efficiency scores of the WCs evaluated in Chile.Table 4 Main descriptive statistics of variables used to evaluate the efficiency of water companies.Full size table More

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    Effects of population growth on Israel’s demand for desalinated water

    Expansion of desalinationWhile reliance on desalination may allow Israel to meet basic domestic and agricultural needs, doing so will have considerable environmental consequences. Foremost, increased production of desalinated water will lead to a correspondingly steep rise in energy demand. The world’s most efficient desalination facilities currently require 3–3.5 kWh to desalinate 1 m3 of seawater10,11,12. Assuming the lower end of this bound, under the high-growth scenario, Israel will need an additional 11 TWh per year, or about 15% of the country’s current electrical generation. For comparison’s sake, this amount of electricity would require the equivalent of a 1600 MW natural gas power plant operating with an 80% capacity factor. Of course, technological improvements can be expected to make the desalination process less energy intensive, but the rate of reduction is expected to be limited13. We emphasize that these numbers include only the electricity required for the reverse osmosis process. They do not include the cost or energy associated with pumping water from the Mediterranean, distribution within Israel, and eventual wastewater treatment, all of which are energy intensive in their own right14. While renewable energy generation holds great promise, it could take decades before Israel has a low-carbon electricity system. Indeed, Israeli pledges at the Glasgow COP 26 envision only 30% of electricity coming from renewable sources by 203015. Should Israel pursue a solar PV-based decarbonization strategy, it will require substantial amounts of open space, in a country that already suffers from land shortages12. If solar PV is to become a main source of electricity generation in Israel, then demand will far exceed what is viable to produce on rooftops. At present, Israel generates over 90% of its electricity from fossil fuels, mostly natural gas and in the near-term, desalination will lead to increased greenhouse gas emissions14.The construction of new desalination facilities has the potential to negatively affect Israel’s coastal landscape and aquatic coastal ecosystem. At present, Israel’s major desalination plants are all located along the country’s Mediterranean shoreline, with the future Haifa and Sorek II plants also planned for the coast. Significant future construction has the potential to limit public access to coastal recreation areas. While the construction of future desalination facilities at inland locations may alleviate the environmental impact on Israel’s coast, the feasibility of such construction is still being evaluated. An inland approach could increase the energy requirements for desalination, since it would require pumping seawater further inland. Moreover, scientists and environmentalists have voiced concerns that increased reliance on the pumping of seawater and discharge of brine following desalination over the long term has the potential to damage Israel’s coastal ecosystems, including plant and animal life16,17,18. For almost two decades Israel’s Oceanic and Limnological Research Institute has carefully monitored the effects of desalination facilities in these areas and has yet to detect signs of consequential ecological damage19,20. Notwithstanding, this is an issue that requires continuous observation and analysis.A transition to desalinated water as the primary source of drinking water also raises a number of potential health concerns. Notably, desalinated water is lacking in certain minerals, such as magnesium, considered essential for human health21,22. The long-term consequences of consuming water that does not contain these elements are unknown21,22.Sustainability of treated wastewater for agricultureDespite the boon that treated wastewater has been to Israeli farmers—ensuring a steady supply of low-cost water—leading voices within the scientific community have raised potential environmental and health concerns that question the sustainability of Israel’s practices23,24,25,26.Treated wastewater, including Israel’s relatively high-quality effluents, remains high in salt content, which can lead to reduced plant yield and increase the risk of long-term soil degradation26,27,28. In particular, recent research has demonstrated that irrigation water with a high relative fraction of sodium can cause irreversible breakdowns in soil structure, such that the affected land can no longer support agricultural production. Long-term use of saline water also has the potential to pollute Israel’s aquifers27.Treated wastewater is additionally known to contain various chemical compounds—ranging from pharmaceuticals to heavy metals—that may present risks to human health. When used for agriculture, pharmaceuticals and heavy metal compounds can be taken up by food crops and consumed by people29,30,31,32. Crucially, the health consequences of long-term exposure to these compounds are uncertain and further research in this area is needed33.Should Israel determine that reliance on treated wastewater for agriculture is too great a liability, this would create a twofold stress for the country’s water infrastructure. First, additional water supplies would be required to sustain the country’s farmers, with the only viable alternative likely being the production of additional desalinated water. Given current energy prices, however, the cost of using desalinated water appears to be prohibitively expensive for most crops25,34. Israel would then face a choice between continuing to support local agricultural production, despite the high costs, or moving to import required food supplies, which could be expensive and present potential national security risks. Second, Israel would have to find an environmentally acceptable method of discharging the large quantities of wastewater previously allocated to agriculture. If reusing treated effluent for agriculture is no longer viable, Israel will need to adjust its water treatment infrastructure.One plausible scenario for coping with increased quantities of domestic wastewater is the possibility of treating this water to a higher level so that it can be re-used as drinking water, as has been done in potable reuse programs for years in American states like California, Virginia, and Colorado35. Expanded potable reuse could also lead to a decrease in Israel’s demand for desalinated water, lowering energy costs and greenhouse gas emissions while ameliorating pressure on Israel’s coastal landscape and ecosystems. Treating wastewater to a higher level could also enable continued use by farmers, albeit at a higher cost.Effect of climate change minimal compared to population riseOur analysis shows that the expected effects of climate change on Israel’s water supply are likely to be minimal compared to those of population growth. An assumed 20% decline in production from natural water resources by 2065 (“Methods””), represents a decrease of 245 million m3 per year in comparison to 2020 levels. Even if we consider a larger decline in natural sources due to climate change, the lost capacity pales in comparison to the increased demand from population growth, which is an order of magnitude larger. That is, our projections show that Israel’s water supply will remain precarious even if the worst consequences of global climate change do not materialize. Of course, even if climate change’s effects on Israel’s drinking water may be small compared to that caused by population growth, any change in precipitation patterns also has the potential to raise the risk of forest fires, cause increased flooding, and affect the region’s wildlife.Security concerns and regional cooperationIn past military conflicts, Israel’s coastal desalination facilities have been a target for both rocket and cyber-attacks. Thus far, Israel’s Iron Dome and other defense systems have withstood these challenges. Nonetheless, should a desalination plant be forced offline for a prolonged period of time, it could potentially disrupt water supply.It is also important to note Israel’s obligations to provide fixed quantities of water to the Palestinian Authority and Jordan, pursuant to the Oslo II Accords and the 1994 peace treaty with Jordan. While it is beyond the scope of this analysis, Israel’s neighbors are themselves under intense pressure to meet the water demands of growing populations. Unlike Israel, Palestine and Jordan are already suffering from major deficits in supply, with access severely limited. Moreover, Israel’s neighbors are less well positioned to increase desalination capacity. Water scarcity in Jordan, Palestine, and other countries in the region has the potential to cause significant unrest, representing a major security concern for Israel and its neighbors. The possibility of Israel supplying desalinated water to its neighbors has often been suggested as a possible component of regional peace building36. In fact, in 2021 Israel agreed to double its annual water supply to Jordan to 100 MCM37. Any additional steps to the export of water to Jordan or Palestine would, however, add an additional component of stress to an Israeli water system that will already be facing unprecedented demand driven by population growth.The sustainability of any future plan to address Israeli water scarcity could be bolstered by steps to increase cooperation between Israel and its neighbors. At present, for example, significant quantities of untreated wastewater flow from the West Bank into Israel38,39,40. Likewise, sewage discharge from Gaza into the Mediterranean has in the past caused fouling of membranes at Israel’s Ashkelon desalination plant, even forcing the plant to go offline41. Capture and treatment of wastewater within Palestine would have the dual benefit of increasing potential irrigation supplies for Palestinian farmers while reducing pollution of transboundary water resources42. Increased water access, of course, also has the potential to decrease water-driven security risks in the region.Ecological concernsThe projections presented here only consider how an increase in water demand could impact future demand from desalination. We do not examine how rising population levels might limit access to water resources for recreational purposes. Nonetheless, we can expect that a larger population will put increased strain on access to Israel’s streams, rivers, and lakes43. Likewise, reduced natural flows are liable to stress the flora and fauna in the country’s national parks and nature reserves43. A recent report by Israel’s State Comptroller revealed that the country’s compliance with the UN Convention on Biodiversity is woefully inadequate, with the country failing to meet 74% of the convention’s measurable objectives44. Providing nature with reliable and reasonable water flows will be critical to preserving the country’s unique ecosystems, but increasingly difficult given the anticipated growth in anthropogenic demands.Technological ImprovementsThe trends discussed here are robust even if dramatic technological improvements allow Israel to greatly reduce per capita water consumption. For instance, if we assume a 30% decline in per capita consumption, a truly dramatic change considering historical values and Israel’s already impressive water conservation practices (Methods), Israel would still need to produce 2.3 billion m3 of desalinated water in 2065 for the high-growth scenario. This constitutes a 350% increase in capacity compared to 2020 levels and would require significant infrastructure investment.Global BellwetherThe extent to which Israel is able to meet the water demands of a growing population in the face of increasingly insufficient natural supplies could provide valuable insight for regions and governments facing similar pressures. The population growth rate in the American Southwest, for instance, has far outpaced that of the U.S. as a whole, with water resources in the region already extremely stressed. In contrast to Israel, the American Southwest lacks the advantages of a centralized water authority. Additionally, many of the population centers in the American Southwest are far removed from potential sources of desalinated water, making the challenge of water delivery even greater and the value of efficiency and wastewater treatment and reuse higher. Likewise, middle-income countries facing acute water scarcity (e.g., Brazil, South Africa) may look to Israel’s experience as they seek to increase water supplies for growing populations.Hydrological stability is typically considered a prerequisite for sustainability. In water-scarce regions, projected climate change-driven precipitation decreases matter. But the anticipated shortages caused by population growth appear to matter far more. Desalination offers a possible way-out of such conundrums. But for the foreseeable future, the absence of low-carbon electricity to power this energy-intensive process means that relying on desalination technology will contribute to increased greenhouse gas emissions. Should Israel struggle in its effort to meet growing water demand, or be unable to do so without significantly increasing carbon emissions, it will provide a stark warning of the challenges ahead.Water in the context of other constraints on israeli population growthWhile many technologically-optimistic managers perceive desalination as a panacea for providing water supply under conditions of steady population growth, in other areas of life, solutions are more elusive. This is particularly true in designing infrastructure that utilizes land resources, such as housing, agriculture, and the production of raw materials for construction.To meet projected demand for residential housing between 2020–2030, Israel will need to add an additional 560,000 housing units to present stock. Due to the nature of exponential growth functions, however, demand will grow to over 1.05 million housing units between 2050–2060. Supplying the corresponding housing and infrastructure is expected to put further pressure on Israel’s open spaces, which are already disappearing at a rate of 30 km2 a year8. The depletion of open spaces, including agricultural lands, could also pose a threat to Israel’s food security in the future. Already, official figures cite current Israeli food imports at around 64% of total calories consumed by the population45 with some experts calculating even greater dependence on food imports46. Besides expanding the carbon footprint of Israel’s food supply, such significant reliance on imported crops increases the country’s vulnerability and exposure to global shocks in the food markets during times of international turbulence or military conflict. More

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    Unprecedented droughts are expected to exacerbate urban inequalities in Southern Africa

    Loon, A. F. V. et al. Drought in the Anthropocene. Nat. Geosci. 9, 89–91 (2016).Article 

    Google Scholar 
    Diffenbaugh, N. S., Swain, D. L. & Touma, D. Anthropogenic warming has increased drought risk in California. Proc Natl Acad. Sci. USA 112, 3931–3936 (2015).Article 
    CAS 

    Google Scholar 
    Qiu, J. China drought highlights future climate threats. Nature 465, 142–143 (2010).Article 
    CAS 

    Google Scholar 
    Xu, K. et al. Spatio-temporal variation of drought in China during 1961–2012: a climatic perspective. J. Hydrol. 526, 253–264 (2015).Article 

    Google Scholar 
    Van Loon, A. F. & Van Lanen, H. A. J. Making the distinction between water scarcity and drought using an observation-modeling framework. Water Resour. Res. 49, 1483–1502 (2013).Article 

    Google Scholar 
    Yuan, X., Wang, L. & Wood, E. F. Anthropogenic intensification of Southern African flash droughts as exemplified by the 2015/16 season. Bull. Am. Meteorol. Soc. 99, S86–S90 (2018).Ray, B. & Rajib, S. Urban Drought (Springer, 2019).Zhang, X. et al. Urban drought challenge to 2030 sustainable development goals. Sci. Total Environ. 693, 133536 (2019).Article 
    CAS 

    Google Scholar 
    Not a drop to spare. Nat. Sustain 1, 151–152 (2018).Anandharuban, P. & Elango, L. Spatio-temporal analysis of rainfall, meteorological drought and response from a water supply reservoir in the megacity of Chennai, India. J. Earth Syst. Sci. 130, 17 (2021).Article 

    Google Scholar 
    Millington, N. Producing water scarcity in São Paulo, Brazil: the 2014–2015 water crisis and the binding politics of infrastructure. Polit. Geogr. 65, 26–34 (2018).Article 

    Google Scholar 
    NASA. Turkey experiences intense drought. https://earthobservatory.nasa.gov/images/147811/turkey-experiences-intense-drought (2021).Muller, M. Cape Town’s drought: don’t blame climate change. Nature 559, 174–176 (2018).Article 
    CAS 

    Google Scholar 
    Loftus, A. Working the socio‐natural relations of the urban waterscape in South Africa. Int. J. Urban Reg. Res. 31, 41–59 (2007).Article 

    Google Scholar 
    Swyngedouw, E. Power, nature, and the city. The conquest of water and the political ecology of urbanization in Guayaquil, Ecuador: 1880–1990. Environ. Plan. A 29, 311–332 (1997).Article 

    Google Scholar 
    Swyngedouw, E. Social Power and the Urbanization of Water: Flows of Power (Oxford Univ. Press, 2004).Hewitt, K. Interpretations of Calamity from the Viewpoint of Human Ecology Vol. 1 (Allen & Unwin, 1983).Baudoin, M.-A., Vogel, C., Nortje, K. & Naik, M. Living with drought in South Africa: lessons learnt from the recent El Niño drought period. Int. J. Disaster Risk Reduct. 23, 128–137 (2017).Article 

    Google Scholar 
    Vogel, C., Moser, S. C., Kasperson, R. E. & Dabelko, G. D. Linking vulnerability, adaptation, and resilience science to practice: pathways, players, and partnerships. Glob. Environ. Change 17, 349–364 (2007).Article 

    Google Scholar 
    Ahlers, R., Cleaver, F., Rusca, M. & Schwartz, K. Informal space in the urban waterscape: disaggregation and co-production of water services. Water Altern. 7, 1–14 (2014).
    Google Scholar 
    Hungerford, H. & Smiley, S. L. Comparing colonial water provision in British and French Africa. J. Hist. Geogr. 52, 74–83 (2016).Article 

    Google Scholar 
    Myers, G. African Cities: Alternative Visions of Urban Theory and Practice (Zed Books, 2011).Progress on Household Drinking Water, Sanitation and Hygiene 2000–2017: Special Focus on Inequalities Vol. 1 (UNICEF and WHO, 2019).Cain, A. Informal water markets and community management in peri-urban Luanda, Angola. Water Int. 43, 205–216 (2018).Article 

    Google Scholar 
    van den Berg, C. & Danilenko, A. Performance of Water Utilities in Africa (World Bank, 2017).https://doi.org/10.1596/26186Alda-Vidal, C., Kooy, M. & Rusca, M. Mapping operation and maintenance: an everyday urbanism analysis of inequalities within piped water supply in Lilongwe, Malawi. Urban Geogr. 39, 104–121 (2018).Article 

    Google Scholar 
    Rusca, M., Boakye-Ansah, A. S., Loftus, A., Ferrero, G. & van der Zaag, P. An interdisciplinary political ecology of drinking water quality. Exploring socio-ecological inequalities in Lilongwe’s water supply network. Geoforum 84, 138–146 (2017).Article 

    Google Scholar 
    Smiley, S. L. Heterogeneous water provision in Dar es Salaam: the role of networked infrastructures and alternative systems in informal areas. Environ. Plan. E 3, 1215–1231 (2020).
    Google Scholar 
    Smith, L. The murky waters of the second wave of neoliberalism: corporatization as a service delivery model in Cape Town. Geoforum 35, 375–393 (2004).Article 

    Google Scholar 
    Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).Article 
    CAS 

    Google Scholar 
    O’Neill, B. C. et al. Achievements and needs for the climate change scenario framework. Nat. Clim. Change 10, 1074–1084 (2020).Article 

    Google Scholar 
    Rao, N. D., van Ruijven, B. J., Riahi, K. & Bosetti, V. Improving poverty and inequality modelling in climate research. Nat. Clim. Change 7, 857–862 (2017).Article 

    Google Scholar 
    Wilson, R. S., Herziger, A., Hamilton, M. & Brooks, J. S. From incremental to transformative adaptation in individual responses to climate-exacerbated hazards. Nat. Clim. Change 10, 200–208 (2020).Article 

    Google Scholar 
    Castree, N. Changing the Anthropo(s)cene: geographers, global environmental change and the politics of knowledge. Dialogues Hum. Geogr. 5, 301–316 (2015).Article 

    Google Scholar 
    Rusca, M., Messori, G. & Di Baldassarre, G. Scenarios of human responses to unprecedented social‐environmental extreme events. Earths Future 9, e2020EF001911 (2021).Article 

    Google Scholar 
    White, G. F. Human Adjustment to Floods Department of Geography Research Paper No. 29 (Univ. of Chicago,1945).Burton, I., Kates, R. & White, G. The Environment as Hazard (Oxford Univ. Press, 1993).Masih, I., Maskey, S., Mussá, F. E. F. & Trambauer, P. A review of droughts on the African continent: a geospatial and long-term perspective. Hydrol. Earth Syst. Sci. 18, 3635–3649 (2014).Article 

    Google Scholar 
    Climate Change Profile: Mozambique (Ministry of Foreign Affairs of the Netherlands, 2018).Dai, A. & Zhao, T. Uncertainties in historical changes and future projections of drought. Part I: estimates of historical drought changes. Clim. Change 144, 519–533 (2017).Article 

    Google Scholar 
    Cook, B. I. et al. Twenty-first century drought projections in the CMIP6 forcing scenarios. Earths Future 8, e2019EF001461 (2020).Article 

    Google Scholar 
    Abiodun, B. J., Makhanya, N., Petja, B., Abatan, A. A. & Oguntunde, P. G. Future projection of droughts over major river basins in Southern Africa at specific global warming levels. Theor. Appl. Climatol. 137, 1785–1799 (2019).Article 

    Google Scholar 
    Cook, B. I., Mankin, J. S. & Anchukaitis, K. J. Climate change and drought: from past to future. Curr. Clim. Change Rep. 4, 164–179 (2018).Article 

    Google Scholar 
    Rusca, M. et al. The urban metabolism of waterborne diseases: variegated citizenship, (waste) water flows, and climatic variability in Maputo, Mozambique. Ann. Am. Assoc. Geogr. 112, 1159–1178 (2022).
    Google Scholar 
    Barros, C. P., Chivangue, A. & Samagaio, A. Urban dynamics in Maputo, Mozambique. Cities 36, 74–82 (2014).Article 

    Google Scholar 
    Biza, A., Kooy, M., Manuel, S. & Zwarteveen, M. Sanitary governmentalities: producing and naturalizing social differentiation in Maputo City, Mozambique (1887–2017). Environ. Plan. E https://doi.org/10.1177/2514848621996583 (2021).Jenkins, P. City profile: Maputo. Cities 17, 207–218 (2000).Article 

    Google Scholar 
    Rusca, M. et al. Space, state-building and the hydraulic mission: crafting the Mozambican state. Environ. Plan. C 37, 868–888 (2019).
    Google Scholar 
    Weststrate, J. et al. The regulation of onsite sanitation in Maputo, Mozambique. Util. Policy 61, 100968 (2019).Article 

    Google Scholar 
    Zuin, V. & Nicholson, M. The impact of pro-poor reforms on consumers and the water utility in Maputo, Mozambique. Water Altern. 14, 158–185 (2021).
    Google Scholar 
    Governo sufoca fornecedores privados que garantiram água por muitos anos nos bairros de expansão do Grande Maputo. Política Moçambicana (CDD, 2021); https://cddmoz.org/governo-sufoca-fornecedores-privados-que-garantiram-agua-por-muitos-anos-nos-bairros-de-expansao-do-grande-maputo-2/Cortez, E. et al. Costs and Consequences of the Hidden Debt Scandal of Mozambique (Centro de Integridade Pública and Chr. Michelsen Institute, 2021).WWF. Cape Town’s groundwater under the spotlight. https://africa.panda.org/?32522/Cape-Towns-groundwater-under-the-spotlight (2020).Robins, S. ‘Day Zero’, hydraulic citizenship and the defence of the commons in Cape Town: a case study of the politics of water and its infrastructures (2017–2018). J. South. Afr. Stud. 45, 5–29 (2019).Article 

    Google Scholar 
    Savelli, E., Rusca, M., Cloke, H. & Di Baldassarre, G. Don’t blame the rain: social power and the 2015–2017 drought in Cape Town. J. Hydrol. https://doi.org/10.1016/j.jhydrol.2020.125953 (2021).Enqvist, J. P. & Ziervogel, G. Water governance and justice in Cape Town: an overview. WIREs Water 6, e1354 (2019).Article 

    Google Scholar 
    Wilkinson, P. City profile: Cape Town. Cities 17, 195–205 (2000).Article 

    Google Scholar 
    Miraftab, F. Governing post-apartheid spatiality: implementing city improvement districts in Cape Town. Antipode 39, 602–626 (2007).Article 

    Google Scholar 
    Our Shared Water future: Cape Town’s Water Strategy (Water and Sanitation Department of the City of Cape Town, 2020); https://resource.capetown.gov.za/documentcentre/Documents/City%20strategies,%20plans%20and%20frameworks/Cape%20Town%20Water%20Strategy.pdfWater Outlook 2018 (Department of Water and Sanitation City of Cape Town, 2018); http://resource.capetown.gov.za/documentcentre/Documents/City%20research%20reports%20and%20review/Water%20Outlook%202018%20-%20Summary.pdfBig Six Monitor (CSAG, 2022); https://cip.csag.uct.ac.za/monitoring/bigsix.htmlAlzate González, L. D. & Peñaloza Lanza, R. A. Day Zero: The Role of Social Movements in the Face of Cape Town’s Water Crisis. MSc thesis, Linnaeus Univ. (2019).Ellis, E. Victory in court for Philippi Horticultural Area. Daily Maverick https://www.dailymaverick.co.za/article/2020-02-18-victory-in-court-for-philippi-horticultural-area/ (2020).Grasham, C. F., Korzenevica, M. & Charles, K. J. On considering climate resilience in urban water security: a review of the vulnerability of the urban poor in sub‐Saharan Africa. WIREs Water 6, e1344 (2019).Article 

    Google Scholar 
    Harris, 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. 26, 561–582 (2017).Article 

    Google Scholar 
    Wutich, A. & Ragsdale, K. Water insecurity and emotional distress: coping with supply, access, and seasonal variability of water in a Bolivian squatter settlement. Soc. Sci. Med. 67, 2116–2125 (2008).Article 

    Google Scholar 
    Truelove, Y. (Re-)Conceptualizing water inequality in Delhi, India through a feminist political ecology framework. Geoforum 42, 143–152 (2011).Article 

    Google Scholar 
    Wutich, A. Intrahousehold disparities in women and men’s experiences of water insecurity and emotional distress in urban Bolivia. Med. Anthropol. Q. 23, 436–454 (2009).Article 

    Google Scholar 
    Mehta, L. in The Limits to Scarcity: Contesting the Politics of Allocation (ed Metha, L.) 13–30 (Routledge, 2010).Kaika, M. Constructing scarcity and sensationalising water politics: 170 days that shook Athens. Antipode 35, 919–954 (2003).Article 

    Google Scholar 
    Cohen, D. A. The rationed city: the politics of water, housing, and land use in drought-parched São Paulo. Public Cult. 28, 261–289 (2016).Article 

    Google Scholar 
    Rusca, M., Alda-Vidal, C., Hordijk, M. & Kral, N. Bathing without water, and other stories of everyday hygiene practices and risk perception in urban low-income areas: the case of Lilongwe, Malawi. Environ. Urban. 29, 533–550 (2017).Article 

    Google Scholar 
    Björkman, L. Pipe Politics, Contested Waters (Duke Univ. Press, 2015).Anand, N. Municipal disconnect: on abject water and its urban infrastructures. Ethnography 13, 487–509 (2012).Article 

    Google Scholar 
    Jaglin, S. Differentiating networked services in Cape Town: echoes of splintering urbanism? Geoforum 39, 1897–1906 (2008).Article 

    Google Scholar 
    Drysdale, R. E., Bob, U. & Moshabela, M. Socio-economic determinants of increasing household food insecurity during and after a drought in the District of iLembe, South Africa. Ecol. Food Nutr. 60, 25–43 (2021).Article 
    CAS 

    Google Scholar 
    Austin, K. F., Noble, M. D. & Berndt, V. K. Drying climates and gendered suffering: links between drought, food insecurity, and women’s HIV in less-developed countries. Soc. Indic. Res. 154, 313–334 (2021).Article 

    Google Scholar 
    Musemwa, M. in African Cities (eds Locatelli, F. & Nugent, P.) 157–185 (Brill, 2009).Chitonge, H. Cities beyond networks: the status of water services for the urban poor in African cities. Afr. Stud. 73, 58–83 (2014).Article 

    Google Scholar 
    Satur, P. & Lindsay, J. Social inequality and water use in Australian cities: the social gradient in domestic water use. Local Environ. 25, 351–364 (2020).Article 

    Google Scholar 
    Taylor, V., Chappells, H., Medd, W. & Trentmann, F. Drought is normal: the socio-technical evolution of drought and water demand in England and Wales, 1893–2006. J. Hist. Geogr. 35, 568–591 (2009).Article 

    Google Scholar 
    Kallis, G. Droughts. Annu. Rev. Environ. Resour. 33, 85–118 (2008).Article 

    Google Scholar 
    Heynen, N., Kaika, M. & Swyngedouw, E. In the Nature of Cities: Urban Political Ecology and the Politics of Urban Metabolism Vol. 3 (Taylor & Francis, 2006).Tiwale, S., Rusca, M. & Zwarteveen, M. The power of pipes: mapping urban water inequities through the material properties of networked water infrastructures–the case of Lilongwe. Malawi Water Altern. 11, 314–335 (2018).
    Google Scholar 
    Giglioli, I. & Swyngedouw, E. Let’s drink to the great thirst! Water and the politics of fractured techno‐natures in Sicily. Int. J. Urban Reg. Res. 32, 392–414 (2008).Article 

    Google Scholar 
    Kallis, G. & Coccossis, H. Managing water for Athens: from the hydraulic to the rational growth paradigm. Eur. Plan. Stud. 11, 245–261 (2003).Article 

    Google Scholar 
    Vitz, M. A City on a Lake (Duke Univ. Press, 2018).Kimari, W. & Ernstson, H. Imperial remains and imperial invitations: centering race within the contemporary large-scale infrastructures of east Africa. Antipode 52, 825–846 (2020).Article 

    Google Scholar 
    Anand, N. Hydraulic City: Water and the Infrastructures of Citizenship in Mumbai (Duke Univ. Press, 2017).Pihljak, L. H., Rusca, M., Alda-Vidal, C. & Schwartz, K. Everyday practices in the production of uneven water pricing regimes in Lilongwe, Malawi. Environ. Plan. C 39, 300–317 (2021).
    Google Scholar 
    Nevarez, L. Just wait until there’s a drought: mediating environmental crises for urban growth. Antipode 28, 246–272 (1996).Article 

    Google Scholar 
    Tomaz, P., Jepson, W. & de Oliveira Santos, J. Urban household water insecurity from the margins: perspectives from northeast Brazil. Prof. Geogr. 72, 481–498 (2020).Article 

    Google Scholar 
    Bakker, K. Neoliberal versus postneoliberal water: geographies of privatization and resistance. Ann. Assoc. Am. Geogr. 103, 253–260 (2013).Article 

    Google Scholar 
    Furlong, K. Trickle-down debt: infrastructure, development, and financialisation, Medellín 1960–2013. Trans. Inst. Br. Geogr. 45, 406–419 (2020).Article 

    Google Scholar 
    Bakker, K. J. Privatizing water, producing scarcity: the Yorkshire drought of 1995. Econ. Geogr. 76, 4–27 (2000).Article 

    Google Scholar 
    Saurií, D. Lights and shadows of urban water demand management: the case of the metropolitan region of Barcelona. Eur. Plan. Stud. 11, 229–243 (2003).Article 

    Google Scholar 
    Ozan, L. A. & Alsharif, K. A. The effectiveness of water irrigation policies for residential turfgrass. Land Use Policy 31, 378–384 (2013).Article 

    Google Scholar 
    Albiac, J., Hanemann, M., Calatrava, J., Uche, J. & Tapia, J. The rise and fall of the Ebro water transfer. Nat. Resour. J. 46, 727–757 (2006).
    Google Scholar 
    Jaffee, D. & Case, R. A. Draining us dry: scarcity discourses in contention over bottled water extraction. Local Environ. 23, 485–501 (2018).Article 

    Google Scholar 
    Breyer, B., Zipper, S. C. & Qiu, J. Sociohydrological impacts of water conservation under anthropogenic drought in Austin, TX (USA). Water Resour. Res. 54, 3062–3080 (2018).Article 

    Google Scholar 
    Hackman, R. California drought shaming takes on a class-conscious edge. The Guardian https://www.theguardian.com/us-news/2015/may/16/california-drought-shaming-takes-on-a-class-conscious-edge (2015).Milbrandt, T. Caught on camera, posted online: mediated moralities, visual politics and the case of urban ‘drought-shaming’. Vis. Stud. 32, 3–23 (2017).Article 

    Google Scholar 
    Schwartz, K., Tutusaus Luque, M., Rusca, M. & Ahlers, R. (In)formality: the meshwork of water service provisioning. WIREs Water 2, 31–36 (2015).Article 

    Google Scholar 
    Hawkins, P. & Muxímpua, O. Developing Business Models for Fecal Sludge Management in Maputo Water and Sanitation Program Report (International Bank for Reconstruction and Development/The World Bank, 2015).Greater Maputo: Urban Poverty and Inclusive Growth (World Bank, 2017); https://openknowledge.worldbank.org/handle/10986/29828Di Baldassarre, G. et al. Integrating multiple research methods to unravel the complexity of human‐water systems. AGU Adv. 2, e2021AV000473 (2021).Article 

    Google Scholar 
    Garb, Y., Pulver, S. & VanDeveer, S. D. Scenarios in society, society in scenarios: toward a social scientific analysis of storyline-driven environmental modeling. Environ. Res. Lett. 3, 045015 (2008).Article 

    Google Scholar 
    Wiebe, K. et al. Scenario development and foresight analysis: exploring options to inform choices. Annu. Rev. Environ. Resour. 43, 545–570 (2018).Article 

    Google Scholar 
    Rusca, M. & Di Baldassarre, G. Interdisciplinary critical geographies of water: capturing the mutual shaping of society and hydrological flows. Water 11, 1973 (2019).Article 

    Google Scholar 
    Raju, E., Boyd, E. & Otto, F. Stop blaming the climate for disasters. Commun. Earth Environ. 3, 1 (2022).Article 

    Google Scholar 
    Cronin, P., Ryan, F. & Coughlan, M. Undertaking a literature review: a step-by-step approach. Br. J. Nurs. 17, 38–43 (2008).Article 

    Google Scholar 
    Walsh, D. & Downe, S. Meta‐synthesis method for qualitative research: a literature review. J. Adv. Nurs. 50, 204–211 (2005).Article 

    Google Scholar 
    White, G. F. Changes in Urban Occupance of Flood Plains in the United States Vol. 57 (Univ. of Chicago, 1958).Adger, W. N. Vulnerability. Glob. Environ. Change 16, 268–281 (2006).Article 

    Google Scholar 
    Cutter, S. L. Vulnerability to environmental hazards. Prog. Hum. Geogr. 20, 529–539 (1996).Article 

    Google Scholar 
    Cutter, S. L., Boruff, B. J. & Shirley, W. L. Social vulnerability to environmental hazards. Soc. Sci. Q. 84, 242–261 (2003).Article 

    Google Scholar 
    Pelling, M. The Vulnerability of Cities: Natural Disasters and Social Resilience (Routledge, 2012).Wisner, B., Blaikie, P., Cannon, T. & Davis, I. At Risk: Natural Hazards, People’s Vulnerability and Disasters (Routledge, 2004).Adger, W. N., Quinn, T., Lorenzoni, I., Murphy, C. & Sweeney, J. Changing social contracts in climate-change adaptation. Nat. Clim. Change 3, 330–333 (2013).Article 

    Google Scholar 
    O’Brien, K. Global environmental change II: from adaptation to deliberate transformation. Prog. Hum. Geogr. 36, 667–676 (2012).Article 

    Google Scholar 
    Pelling, M. & Dill, K. Disaster politics: tipping points for change in the adaptation of sociopolitical regimes. Prog. Hum. Geogr. 34, 21–37 (2010).Article 

    Google Scholar 
    Robinson, J. Comparisons: colonial or cosmopolitan? Singap. J. Trop. Geogr. 32, 125–140 (2011).Article 

    Google Scholar 
    Robinson, J. Ordinary Cities: Between Modernity and Development (Routledge, 2013).Myers, G. From expected to unexpected comparisons: changing the flows of ideas about cities in a postcolonial urban world. Singap. J. Trop. Geogr. 35, 104–118 (2014).Article 

    Google Scholar 
    Adelekan, I. et al. Disaster risk and its reduction: an agenda for urban Africa. Int. Dev. Plan. Rev. 37, 33–43 (2015).Article 

    Google Scholar 
    Dodman, D., Leck, H., Rusca, M. & Colenbrander, S. African urbanisation and urbanism: implications for risk accumulation and reduction. Int. J. Disaster Risk Reduct. 26, 7–15 (2017).Article 

    Google Scholar 
    Kareem, B. et al. Pathways for resilience to climate change in African cities. Environ. Res. Lett. 15, 073002 (2020).Article 

    Google Scholar 
    Lawhon, M., Ernstson, H. & Silver, J. Provincializing urban political ecology: towards a situated UPE through African urbanism. Antipode 46, 497–516 (2014).Article 

    Google Scholar 
    Simone, A. Straddling the divides: remaking associational life in the informal African city. Int. J. Urban Reg. Res. 25, 102–117 (2001).Article 

    Google Scholar 
    Berman, B. Structure and process in the bureaucratic states of colonial Africa. Dev. Change 15, 161–202 (1984).Article 

    Google Scholar 
    Robinson, J. Comparative urbanism: new geographies and cultures of theorizing the urban. Int. J. Urban Reg. Res. 40, 187–199 (2016).Article 

    Google Scholar 
    Randolph, G. F. & Storper, M. Is urbanisation in the Global South fundamentally different? Comparative global urban analysis for the 21st century. Urban Stud. https://doi.org/10.1177/00420980211067926 (2022).Kim, Y.-H., Min, S.-K., Zhang, X., Sillmann, J. & Sandstad, M. Evaluation of the CMIP6 multi-model ensemble for climate extreme indices. Weather Clim. Extrem. 29, 100269 (2020).Article 

    Google Scholar 
    Beguería, S., Vicente‐Serrano, S. M., Reig, F. & Latorre, B. Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int. J. Climatol. 34, 3001–3023 (2014).Article 

    Google Scholar 
    INE. População recendida por área de residência e categoria censitária, segundo sexo e idade. Maputo Província. http://www.ine.gov.mz/iv-rgph-2017/maputo-provincia/quadro-1-populacao-recenseada-por-area-de-residencia-e-categoria-censitaria-segundo-sexo-e-idade-maputo-provincia-2017.xlsx/view (2017).City of Cape Town by Numbers (COGTA, 2020); https://www.cogta.gov.za/ddm/wp-content/uploads/2020/11/City-of-CT-September-2020.pdfMcDonald, D. A. World City Syndrome: Neoliberalism and Inequality in Cape Town (Routledge, 2012).Morange, M., Folio, F., Peyroux, E. & Vivet, J. The spread of a transnational model: ‘gated communities’ in three Southern African cities (Cape Town, Maputo and Windhoek). Int. J. Urban Reg. Res. 36, 890–914 (2012).Article 

    Google Scholar 
    Baez, J. E., Caruso, G., Niu, C. & Myers, C. Mozambique Poverty Assessment: Strong But Not Broadly Shared Growth (World Bank, 2018).Andersen, J. E., Jenkins, P. & Nielsen, M. Who plans the African city? A case study of Maputo, part 1 – the structural context. Int. Dev. Plan. Rev. 37, 329 (2015).Article 

    Google Scholar 
    City of Cape Town Open Data Portal (COCT, 2020); https://web1.capetown.gov.za/web1/OpenDataPortal/Notisso, P. F. Aplicação do Modelo WEAP Na Avaliação de Alocação de áGua do Reservatório dos Pequenos Libombos, Moçambique. PhD dissertation, Universidade Federal de Goiás (2020).Kadibadiba, T., Roberts, L. & Duncan, R. Living in a city without water: a social practice theory analysis of resource disruption in Gaborone, Botswana. Glob. Environ. Change 53, 273–285 (2018).Article 

    Google Scholar 
    March, H. & Sauri, D. When sustainable may not mean just: a critical interpretation of urban water consumption decline in Barcelona. Local Environ. 22, 523–535 (2017).Article 

    Google Scholar 
    Scheba, S. & Millington, N. Crisis temporalities: intersections between infrastructure and inequality in the Cape Town water crisis. Int. J. Urban Reg. Res. (2018).Brewis, A. et al. Community hygiene norm violators are consistently stigmatized: evidence from four global sites and implications for sanitation interventions. Soc. Sci. Med. 220, 12–21 (2019).Article 

    Google Scholar 
    Brewis, A., Workman, C., Wutich, A., Jepson, W. & Young, S. Household water insecurity is strongly associated with food insecurity: evidence from 27 sites in low- and middle-income countries. Am. J. Hum. Biol. 32, e23309 (2020).Article 

    Google Scholar 
    Kallis, G. Coevolution in water resource development: the vicious cycle of water supply and demand in Athens, Greece. Ecol. Econ. 69, 796–809 (2010).Article 

    Google Scholar 
    Mehta, L. Contexts and constructions of water scarcity. Econ. Polit. Wkly. 38, 5066–5072 (2003).
    Google Scholar 
    Mehta, L. Whose scarcity? Whose property? The case of water in western India. Land Use Policy 24, 654–663 (2007).Article 

    Google Scholar  More