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    European rivers are fragmented by many more barriers than had been recorded

    Figure 1 | The weir at Pulteney Bridge, Bath, UK. Belletti et al.1 estimate that more than 1.2 million artificial constructions, such as weirs, dams and locks, alter the flow of Europe’s rivers and streams.Credit: Getty

    If you asked a child in Europe to draw a river, what would this picture look like? Would it resemble a natural, wild and scenic river, with braided and meandering flow paths in a vast floodplain, fringed by riverine vegetation? Or would it show a modern, well-managed river with houses lined up along the banks and boats passing by on a confined channel? Writing in Nature, Belletti et al.1 report a remarkably detailed survey of river barriers in Europe, which suggests that the second picture would be much more likely.

    Free-flowing rivers have become increasingly rare, because centuries of human activities have altered their passage and channels: dams and levees have been built to protect us from floods; weirs have been added (Fig. 1) to abstract water for irrigation or human use; locks and canals have been used to ensure and expand navigable waters; and river flows have been trapped or diverted for power-generating applications ranging from ancient waterwheels to modern hydroelectricity plants. Diverse in-stream structures have been constructed for these purposes, such as large concrete dams, wooden locks, small weirs and partially submerged fords. All of these interventions fragment the rivers and disturb the flow in various ways across different spatial and temporal scales, affecting the transport and delivery of sediments and nutrients2,3, and the migration and dispersal of aquatic organisms4.
    Researchers and water managers who want to investigate the consequences — both beneficial and harmful — of these modifications must first ask some fundamental questions. How many barriers have been installed, and what types? And, most importantly, where have they been built?
    Perhaps surprisingly, the answers are largely unknown. No comprehensive inventory of barriers has been available on a continental scale that includes structures less than 10 metres high, uses consistent, clearly defined terminology and does not under-represent certain barrier sizes and types or geographical regions. This is not least because of the long history of barrier construction and the general lack of documentation. Recent research5 has compiled global data for the locations of dams, but mostly only those that are larger than 10–15 m in height or visible in space-satellite imagery.
    The degree of connectivity of rivers worldwide has also been quantified6 using records for about 20,000 of the largest dams. The study not only accounted for longitudinal connectivity along the river, but also considered lateral interactions with the floodplain, temporal flow alterations, and vertical exchanges of water with the atmosphere and groundwater; such exchanges are often lost in cities if rivers are lined with concrete or forced into underground channels. According to that study, the main causes of the decline in the number and condition of free-flowing rivers are dam-related effects, such as river fragmentation, flow regulation and sediment entrapment. However, because the data underpinning this research did not take smaller barriers into account, the estimated 63% global loss of very long free-flowing rivers (greater than 1,000 km in length) probably represents only the tip of the iceberg.

    This type of knowledge gap motivated Belletti et al. to compile a pan-European atlas of river barriers for 36 countries. The primary aim was to quantify the density of artificial barriers (defined as any built structure that can cause longitudinal discontinuity) across the rivers of these countries. The results are a prerequisite for various approaches7 that analyse the level of river fragmentation.
    The authors took on the tedious and challenging task of compiling records from 120 local, regional and national databases. They curated the data, for example to remove duplicates and ensure consistency in the size categories and terminology, and then mapped out all the barriers to the European river network — a system that contains 1.65 million km of rivers.
    However, Belletti and co-workers recognized that there will be inherent biases in the source data, such as the omission of small or unusual barriers. They therefore made an impressive effort to test the quality of their data: they surveyed about 2,700 km of the river network in 26 countries by walking along selected river stretches during low-flow conditions. The researchers recorded the characteristics of each barrier observed, such as its location, size and whether it was abandoned or still in use. None of the 147 surveyed rivers was found to be free of obstructions, a concerning observation in itself. The findings from this monumental field trip were used to improve the precision of the calculated barrier density, correcting errors and biases in the existing records.
    Finally, Belletti and colleagues extrapolated their data to estimate the barrier density in countries and regions with missing data records, taking into account anthropogenic and environmental factors, such as the degree of urbanization and the amount of agriculture. Although each step of the study has its own shortcomings, as the authors discuss, the combination of approaches strengthens the overall quality of results and reduces uncertainties caused by the variability of the available data across large regions and across several scales in barrier size.
    Belletti et al. identified almost 630,000 unique barrier records, the majority of which were for ramps and bed sills, weirs and culverts. This is the most comprehensive inventory of river barriers ever created. Nevertheless, it still substantially under-represents reality: the number of barriers observed in the field study was, on average, 2.5 times that reported in the existing inventory. In fact, the authors estimate that there are more than 1.2 million artificial barriers obstructing Europe’s rivers and streams, possibly making it the most fragmented river network in the world.

    The authors estimate that barrier densities range from 5 barriers per 1,000 km in Montenegro to almost 20 barriers per km in the Netherlands. Their statistical model suggests that the average barrier density across Europe is 0.6 per km, which is similar to the value obtained from the field observations (0.74 per km), confirming the robustness of the modelling results. Central Europe has the highest abundance and density of barriers, whereas rivers in the Balkans in southeastern Europe, in parts of northern Scandinavia and in some remote areas in southern Europe remain relatively free-flowing. The authors point out, however, that these unfragmented rivers face new threats from a boom in hydropower development, which could put the biodiversity and ecosystem health of the rivers at risk8.
    Given the challenges of global environmental change, finding sustainable solutions to protect fluvial ecosystems and their associated services to humans will need a combination of actions — for example, measuring the ecological impacts of barriers; developing models of regional hydropower installations to find ways of minimizing the environmental toll on the river system while maximizing electricity production; and examining past and future trends in barrier construction and their effects. All of these require a large knowledge base and data that fit the scale, complexity and resolution of the questions to be asked. For example, some barrier types might interrupt sediment transport but pose no problem for a specific aquatic organism, whereas others might be detrimental to that organism despite not interrupting sediment movement.
    Belletti and colleagues’ river-barrier atlas for Europe is an excellent accomplishment, but more efforts like this are now needed. After all, river barriers and their effects are not confined to Europe, and data availability tends to be even more restricted in many other parts of the world. A large global network of scientists and stakeholders will need to join forces to compile data and develop tools (such as the Global Dam Watch initiative at http://globaldamwatch.org) before a complete assessment of the impacts of barriers — both large and small — on river ecosystems can be achieved. More

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    Transboundary cooperation a potential route to sustainable development in the Indus basin

    1.
    Laghari, A. N., Vanham, D. & Rauch, W. The Indus basin in the framework of current and future water resources management. Hydrol. Earth Syst. Sci. 16, 1063–1083 (2012).
    Article  Google Scholar 
    2.
    Wada, Y. et al. Co-designing Indus water–energy–land futures. One Earth 1, 185–194 (2019).
    Article  Google Scholar 

    3.
    AQUASTAT Transboundary River Basin Overview—Indus (FAO, 2011); https://go.nature.com/2KxKRqB

    4.
    Aslam, M. Agricultural productivity current scenario, constraints and future prospects in Pakistan. Sarhad J. Agric. 32, 289–303 (2016).
    Article  Google Scholar 

    5.
    Karimi, P., Bastiaanssen, W. G. M., Molden, D. & Cheema, M. J. M. Basin-wide water accounting based on remote sensing data: an application for the Indus basin. Hydrol. Earth Syst. Sci. 17, 2473–2486 (2013).
    Article  Google Scholar 

    6.
    Akhter, M. in Imagining Industan—Overcoming Water Insecurity in the Indus Basin (eds Adeel, Z. & Wirsing, R. G.) 21–33 (Springer, 2017); https://go.nature.com/3pVNgvo

    7.
    Yu, W. et al. Indus Basin of Pakistan: Impacts of Climate Risks on Water and Agriculture (World Bank, 2013); https://go.nature.com/3kY7dxV

    8.
    Cheema, M., Immerzeel, W. & Bastiaanssen, W. Spatial quantification of groundwater abstraction in the irrigated Indus Basin. Groundwater 52, 25–36 (2014).
    CAS  Article  Google Scholar 

    9.
    Syvitski, J. P. et al. Anthropocene metamorphosis of the Indus Delta and lower floodplain. Anthropocene 3, 24–35 (2013).
    Article  Google Scholar 

    10.
    Adeel, Z. & Wirsing, R. G. in Imagining Industan—Overcoming Water Insecurity in the Indus Basin (eds Adeel, Z. & Wirsing, R. G.) 3–20 (Springer, 2017); https://go.nature.com/3pYJHF1

    11.
    Raman, D. Damming and infrastructural development of the Indus River basin: strengthening the provisions of the indus waters treaty. Asian J. Int. Law 8, 372–402 (2018).
    Article  Google Scholar 

    12.
    Archer, D. R., Forsythe, N., Fowler, H. J. & Shah, S. M. Sustainability of water resources management in the Indus Basin under changing climatic and socio economic conditions. Hydrol. Earth Syst. Sci. 14, 1669–1680 (2010).
    Article  Google Scholar 

    13.
    Just, R. E. & Netanyahu, S. Conflict and Cooperation on Trans-Boundary Water Resources (Springer, 1998).

    14.
    Qamar, M. U., Azmat, M. & Claps, P. Pitfalls in transboundary Indus Water Treaty: a perspective to prevent unattended threats to the global security. npj Clean Water 2, 22 (2019).
    Article  Google Scholar 

    15.
    Grill, G. et al. Mapping the world’s free-flowing rivers. Nature 569, 215–221 (2019).
    CAS  Article  Google Scholar 

    16.
    Wu, X. & Whittington, D. Incentive compatibility and conflict resolution in international river basins: a case study of the Nile Basin. Water Resour. Res. 42, W02417 (2006).
    Article  Google Scholar 

    17.
    Keskinen, M. et al. The water–energy–food nexus and the transboundary context: insights from large Asian rivers. Water 8, 193 (2016).
    Article  Google Scholar 

    18.
    Bhaduri, A. et al. Achieving Sustainable Development Goals from a water perspective. Front. Environ. Sci. 4, 64 (2016).
    Article  Google Scholar 

    19.
    Howells, M. et al. Integrated analysis of climate change, land-use, energy and water strategies. Nat. Clim. Change 3, 621–626 (2013).
    Article  Google Scholar 

    20.
    Liu, J. et al. Nexus approaches to global sustainable development. Nat. Sustain. 1, 466–476 (2018).
    Article  Google Scholar 

    21.
    Bleischwitz, R. et al. Resource nexus perspectives towards the United Nations Sustainable Development Goals. Nat. Sustain. 1, 737–743 (2018).
    Article  Google Scholar 

    22.
    Albrecht, T. R., Crootof, A. & Scott, C. A. The water–energy–food nexus: a systematic review of methods for Nexus assessment. Environ. Res. Lett. 13, 043002 (2018).
    Article  Google Scholar 

    23.
    Kaddoura, S. & El Khatib, S. Review of water–energy–food nexus tools to improve the nexus modelling approach for integrated policy making. Environ. Sci. Policy 77, 114–121 (2017).
    Article  Google Scholar 

    24.
    Siddiqi, A. & Wescoat, J. L. Energy use in large-scale irrigated agriculture in the Punjab province of Pakistan. Water Int. 38, 571–586 (2013).
    Article  Google Scholar 

    25.
    Stewart, J. et al. Indus River System Model (IRSM)—a Planning Tool to Explore Water Management Options in Pakistan: Model Conceptualisation, Configuration and Calibration (CSIRO Land & Water, 2018); https://go.nature.com/3q4rkyz

    26.
    Yang, Y. C. E., Ringler, C., Brown, C. & Mondal, M. A. H. Modeling the agricultural water–energy–food nexus in the Indus River basin, Pakistan. J. Water Resour. Plan. Manag. 142, 04016062 (2016).
    Article  Google Scholar 

    27.
    de Strasser, L., Lipponen, A., Howells, M., Stec, S. & Bréthaut, C. A methodology to assess the water energy food ecosystems nexus in transboundary river basins. Water 8, 59 (2016).
    Article  Google Scholar 

    28.
    Parrachino, I., Dinar, A. & Patrone, F. Cooperative Game Theory and its Application to Natural, Environmental, and Water Resource Issues: 3. Application to Water Resources Policy Research Working Papers (World Bank, 2006); https://go.nature.com/2UXhPCQ

    29.
    Singh, A., Jamasb, T., Nepal, R. & Toman, M. A. Cross-Border Electricity Cooperation in South Asia Policy Research Working Paper No. 7328 (World Bank, 2015).

    30.
    Hasson, R., Löfgren, Å. & Visser, M. Climate change in a public goods game: investment decision in mitigation versus adaptation. Ecol. Econ. 70, 331–338 (2010).
    Article  Google Scholar 

    31.
    Dalin, C., Wada, Y., Kastner, T. & Puma, M. J. Groundwater depletion embedded in international food trade. Nature 543, 700–704 (2017).
    CAS  Article  Google Scholar 

    32.
    Kalair, A. R. et al. Water, energy and food nexus of Indus Water Treaty: water governance. Water-Energy Nexus 2, 10–24 (2019).
    Article  Google Scholar 

    33.
    Vinca, A. et al. The NExus Solutions Tool (NEST) v1.0: an open platform for optimizing multi-scale energy-water-land system transformations. Geosci. Model Dev. 13, 1095–1121 (2020).
    Article  Google Scholar 

    34.
    Mir, K. A., Purohit, P. & Mehmood, S. Sectoral assessment of greenhouse gas emissions in Pakistan. Environ. Sci. Pollut. Res. 24, 27345–27355 (2017).
    CAS  Article  Google Scholar 

    35.
    Ahmad, B. & Saqlain, S. People perception regarding possible impact of urbanization on environmental degradation in Islamabad. IAU Int. J. Soc. Sci. 8, 1–10 (2018).
    Google Scholar 

    36.
    Scott, C. A., Vicuña, S., Blanco-Gutiérrez, I., Meza, F. & Varela-Ortega, C. Irrigation efficiency and water-policy implications for river basin resilience. Hydrol. Earth Syst. Sci. 18, 1339–1348 (2014).
    Article  Google Scholar 

    37.
    Grafton, R. Q. et al. The paradox of irrigation efficiency. Science 361, 748–750 (2018).
    CAS  Article  Google Scholar 

    38.
    Baum, R., Luh, J. & Bartram, J. Sanitation: A global estimate of sewerage connections without treatment and the resulting impact on MDG progress. Environ. Sci. Technol. 47, 1994–2000 (2013).
    CAS  Article  Google Scholar 

    39.
    González-villareal, F. & Schultz, B. Final Report of IPOE for Review of Studies on Water Escapages Below Kotri Barrage Technical Report (ResearchGate, 2018); https://doi.org/10.13140/RG.2.2.28670.02885

    40.
    Casillas, C. E. & Kammen, D. M. The energy–poverty–climate nexus. Science 26, 1181–1182 (2010).
    Article  Google Scholar 

    41.
    GDP (current US$)—Pakistan (World Bank, 2020); https://go.nature.com/2KCSDzB

    42.
    Singh, A., Jamasb, T., Nepal, R. & Toman, M. Electricity cooperation in South Asia: barriers to cross-border trade. Energy Policy 120, 741–748 (2018).
    Article  Google Scholar 

    43.
    Rasul, G., Neupane, N., Hussain, A. & Pasakhala, B. Beyond hydropower: towards an integrated solution for water, energy and food security in South Asia. Int. J. Water Resour. Dev. https://doi.org/10.1080/07900627.2019.1579705 (2019).

    44.
    Lutz, A. F., Immerzeel, W. W., Kraaijenbrink, P. D., Shrestha, A. B. & Bierkens, M. F. Climate change impacts on the upper Indus hydrology: sources, shifts and extremes. PLoS ONE 11, e0165630 (2016).
    CAS  Article  Google Scholar 

    45.
    Maurer, J. M., Schaefer, J. M., Rupper, S. & Corley, A. Acceleration of ice loss across the Himalayas over the past 40 years. Sci. Adv. 5, eaav7266 (2019).
    CAS  Article  Google Scholar 

    46.
    Immerzeel, W. W., Van Beek, L. P. & Bierkens, M. F. Climate change will affect the Asian water towers. Science 328, 1382–1385 (2010).
    CAS  Article  Google Scholar 

    47.
    Biemans, H. et al. Importance of snow and glacier meltwater for agriculture on the Indo-Gangetic Plain. Nat. Sustain. 2, 594–601 (2019).
    Article  Google Scholar 

    48.
    Majhi, B. & Kumar, A. Changing cropping pattern in Indian agriculture. J. Econ. Soc. Dev. 14, 37–45 (2018).
    Google Scholar 

    49.
    Burek, P. et al. Development of the Community Water Model (CWatM v1.04)—a high-resolution hydrological model for global and regional assessment of integrated water resources management. Geosci. Model Dev. 13, 3267–3298 (2020).
    Article  Google Scholar 

    50.
    Huppmann, D. et al. The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp): an open framework for integrated and cross-cutting analysis of energy, climate, the environment, and sustainable development. Environ. Model. Softw. 112, 143–156 (2019).
    Article  Google Scholar 

    51.
    Messner, S. & Strubegger, M. User’s Guide for MESSAGE III IIASA Working Paper (IIASA, 1995).

    52.
    Riahi, K., Grübler, A. & Nakicenovic, N. Scenarios of long-term socio-economic and environmental development under climate stabilization. Technol. Forecast. Soc. Change 74, 887–935 (2007).
    Article  Google Scholar 

    53.
    Van Vliet, O. et al. Synergies in the Asian energy system: climate change, energy security, energy access and air pollution. Energy Econ. 34, S470–S480 (2012).
    Article  Google Scholar 

    54.
    Kiani, B. et al. Optimal electricity system planning in a large hydro jurisdiction: will British Columbia soon become a major importer of electricity? Energy Policy 54, 311–319 (2013).
    Article  Google Scholar 

    55.
    Salmivaara, A. et al. Exploring the modifiable areal unit problem in spatial water assessments: a case of water shortage in monsoon Asia. Water 7, 898–917 (2015).
    Article  Google Scholar 

    56.
    Yang, Y.-C. E., Brown, C. M., Yu, W. H. & Savitsky, A. An introduction to the IBMR, a hydro-economic model for climate change impact assessment in Pakistan’s Indus River basin. Water Int. 38, 632–650 (2013).
    Article  Google Scholar 

    57.
    Kahil, T. et al. A continental-scale hydroeconomic model for integrating water-energy-land nexus solutions. Water Resour. Res 54, 7511–7533 (2018).
    Article  Google Scholar 

    58.
    Kim, S. H. et al. Balancing global water availability and use at basin scale in an integrated assessment model. Clim. Change 136, 217–231 (2016).
    Article  Google Scholar 

    59.
    Payet-Burin, R., Kromann, M., Pereira-Cardenal, S., Strzepek, K. M. & Bauer-Gottwein, P. WHAT-IF: an open-source decision support tool for water infrastructure investment planning within the water–energy–food-climate nexus. Hydrol. Earth Syst. Sci. 23, 4129–4152 (2019).
    Article  Google Scholar 

    60.
    Sridharan, V., Shivakumar, A., Niet, T., Ramos, E. P. & Howells, M. Land, energy and water resource management and its impact on GHG emissions, electricity supply and food production- Insights from a Ugandan case study. Environ. Res. Commun. 2, 085003 (2020).
    Article  Google Scholar 

    61.
    Saif, Y. & Almansoori, A. An optimization framework for the climate, land, energy, and water (CLEWS) nexus by a discrete optimization model. Energy Procedia 105, 3232–3238 (2017).
    Article  Google Scholar 

    62.
    Smakhtin, V. U., Revenga, C. & Doll, P. Taking Into Account Environmental Water Requirements in Global-scale Water Resources Assessments IWMI Research Reports (IWMI, 2004).

    63.
    Van Vuuren, D. P. et al. The representative concentration pathways: an overview. Clim. Change 109, 5 (2011).
    Article  Google Scholar 

    64.
    O’Neill, B. C. et al. The roads ahead: narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob. Environ. Change 42, 169–180 (2017).
    Article  Google Scholar  More

  • in

    Blue water footprint linked to national consumption and international trade is unsustainable

    1.
    Hoekstra, A. Y. & Wiedmann, T. O. Humanity’s unsustainable environmental footprint. Science 344, 1114–1117 (2014).
    ADS  CAS  PubMed  Google Scholar 
    2.
    WWAP The United Nations World Water Development Report 2015: Water for a Sustainable World (UNESCO, 2015).

    3.
    Shiklomanov, I. A. Appraisal and assessment of world water resources. Water Int. 25, 11–32 (2000).
    Google Scholar 

    4.
    Srinivasan, V., Lambin, E. F., Gorelick, S. M., Thompson, B. H. & Rozelle, S. The nature and causes of the global water crisis: syndromes from a meta-analysis of coupled human–water studies. Water Resour. Res. 48, W10516 (2012).
    ADS  Google Scholar 

    5.
    Coe, M. T. & Foley, J. A. Human and natural impacts on the water resources of the Lake Chad basin. J. Geophys. Res. 106, 3349–3356 (2001).
    ADS  Google Scholar 

    6.
    Gleeson, T., Wada, Y., Bierkens, M. F. P. & van Beek, L. P. H. Water balance of global aquifers revealed by groundwater footprint. Nature 488, 197–200 (2012).
    ADS  CAS  PubMed  Google Scholar 

    7.
    Wada, Y., van Beek, L. P. H. & Bierkens, M. F. P. Nonsustainable groundwater sustaining irrigation: a global assessment. Water Resour. Res. 48, W00L06 (2012).
    Google Scholar 

    8.
    Richter, B. Chasing Water: A Guide for Moving from Scarcity to Sustainability (Island, 2014).

    9.
    Richter, B. D. et al. Water scarcity and fish imperilment driven by beef production. Nat. Sustain. 3, 319–328 (2020).
    Google Scholar 

    10.
    Dudgeon, D. Prospects for sustaining freshwater biodiversity in the 21st century: linking ecosystem structure and function. Curr. Opin. Environ. Sustain. 2, 422–430 (2010).
    Google Scholar 

    11.
    Hanasaki, N. et al. An integrated model for the assessment of global water resources – Part 2: applications and assessments. Hydrol. Earth Syst. Sci. 12, 1027–1037 (2008).
    ADS  Google Scholar 

    12.
    Wada, Y. et al. Global monthly water stress: 2. Water demand and severity of water stress. Water Resour. Res. 47, W07518 (2011).
    ADS  Google Scholar 

    13.
    Hoekstra, A. Y., Mekonnen, M. M., Chapagain, A. K., Mathews, R. E. & Richter, B. D. Global monthly water scarcity: blue water footprints versus blue water availability. PLoS ONE 7, e32688 (2012).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    14.
    Brauman, K. A., Richter, B. D., Postel, S., Malsy, M. & Flörke, M. Water depletion: an improved metric for incorporating seasonal and dry-year water scarcity into water risk assessments. Elementa https://doi.org/10.12952/journal.elementa.000083 (2016).

    15.
    Mekonnen, M. M. & Hoekstra, A. Y. Four billion people facing severe water scarcity. Sci. Adv. 2, e1500323 (2016).
    ADS  PubMed  PubMed Central  Google Scholar 

    16.
    Vörösmarty, C. J., Green, P., Salisbury, J. & Lammers, R. B. Global water resources: vulnerability from climate change and population growth. Science 289, 284–288 (2000).
    ADS  PubMed  Google Scholar 

    17.
    Oki, T. & Kanae, S. Global hydrological cycles and world water resources. Science 313, 1068–1072 (2006).
    ADS  CAS  PubMed  Google Scholar 

    18.
    Burek, P. et al. Water Futures and Solution – Fast Track Initiative (Final Report) (IIASA, 2016).

    19.
    Alcamo, J. et al. Global estimates of water withdrawals and availability under current and future ‘business-as-usual’ conditions. Hydrol. Sci. J. 48, 339–348 (2003).
    Google Scholar 

    20.
    WWAP The United Nations World Water Development Report 2019: Leaving No One Behind (UNESCO, 2019).

    21.
    Vörösmarty, C. J., Hoekstra, A. Y., Bunn, S. E., Conway, D. & Gupta, J. Fresh water goes global. Science 349, 478–479 (2015).
    ADS  PubMed  Google Scholar 

    22.
    Hoekstra, A. Y. & Chapagain, A. K. Globalization of Water: Sharing the Planet’s Freshwater Resources (Blackwell, 2008).

    23.
    Hoekstra, A. Y. The global dimension of water governance: why the river basin approach is no longer sufficient and why cooperative action at global level is needed. Water 3, 21–46 (2011).
    Google Scholar 

    24.
    Naylor, R. et al. Losing the links between livestock and land. Science 310, 1621–1622 (2005).
    CAS  PubMed  Google Scholar 

    25.
    Hoekstra, A. Y. & Mekonnen, M. M. The water footprint of humanity. Proc. Natl Acad. Sci. USA 109, 3232–3237 (2012).
    ADS  CAS  PubMed  Google Scholar 

    26.
    Allan, J. A. Virtual water: a strategic resource: global solutions to regional deficits. Groundwater 36, 545–546 (1998).
    CAS  Google Scholar 

    27.
    Lenzen, M. et al. International trade of scarce water. Ecol. Econ. 94, 78–85 (2013).
    Google Scholar 

    28.
    Hoekstra, A. Y. Water footprint assessment: evolvement of a new research field. Water Resour. Manag. 31, 3061–3081 (2017).
    Google Scholar 

    29.
    Boulay, A. M., Hoekstra, A. Y. & Vionnet, S. Complementarities of water-focused life cycle assessment and water footprint assessment. Environ. Sci. Technol. 47, 11926–11927 (2013).
    ADS  CAS  PubMed  Google Scholar 

    30.
    Hoekstra, A. Y. A critique on the water-scarcity weighted water footprint in LCA. Ecol. Indic. 66, 564–573 (2016).
    Google Scholar 

    31.
    Pfister, S. et al. Understanding the LCA and ISO water footprint: a response to Hoekstra (2016) ‘A critique on the water-scarcity weighted water footprint in LCA’. Ecol. Indic. 72, 352–359 (2017).
    PubMed  PubMed Central  Google Scholar 

    32.
    Chenoweth, J., Hadjikakou, M. & Zoumides, C. Quantifying the human impact on water resources: a critical review of the water footprint concept. Hydrol. Earth Syst. Sci. 18, 2325–2342 (2014).
    ADS  Google Scholar 

    33.
    Dolganova, I. et al. The water footprint of European agricultural imports: hotspots in the context of water scarcity. Resources 8, 141 (2019).
    Google Scholar 

    34.
    Finogenova, N. et al. Water footprint of German agricultural imports: local impacts due to global trade flows in a fifteen-year perspective. Sci. Total Environ. 662, 521–529 (2019).
    ADS  CAS  PubMed  Google Scholar 

    35.
    Feng, K., Hubacek, K., Pfister, S., Yu, Y. & Sun, L. Virtual scarce water in China. Environ. Sci. Technol. 48, 7704–7713 (2014).
    ADS  CAS  PubMed  Google Scholar 

    36.
    Yano, S., Hanasaki, N., Itsubo, N. & Oki, T. Water scarcity footprints by considering the differences in water sources. Sustainability 7, 9753 (2015).
    Google Scholar 

    37.
    Hoekstra, A. Y. & Chapagain, A. K. Water footprints of nations: water use by people as a function of their consumption pattern. Water Resour. Manag. 21, 35–48 (2007).
    Google Scholar 

    38.
    Fader, M. et al. Internal and external green-blue agricultural water footprints of nations, and related water and land savings through trade. Hydrol. Earth Syst. Sci. 15, 1641–1660 (2011).
    ADS  Google Scholar 

    39.
    Chen, Z.-M. & Chen, G. Q. Virtual water accounting for the globalized world economy: national water footprint and international virtual water trade. Ecol. Indic. 28, 142–149 (2013).
    Google Scholar 

    40.
    Wang, R. & Zimmerman, J. Hybrid analysis of blue water consumption and water scarcity implications at the global, national, and basin levels in an increasingly globalized world. Environ. Sci. Technol. 50, 5143–5153 (2016).
    ADS  CAS  PubMed  Google Scholar 

    41.
    Vanham, D. The water footprint of the EU: quantification, sustainability and relevance. Water Int. 43, 731–745 (2018).
    Google Scholar 

    42.
    Galli, A. et al. Integrating ecological, carbon and water footprint into a ‘Footprint Family’ of indicators: definition and role in tracking human pressure on the planet. Ecol. Indic. 16, 100–112 (2012).
    Google Scholar 

    43.
    Ercin, E., Chico, D. & Chapagain, A. K. Vulnerabilities of the European Union’s economy to hydrological extremes outside its borders. Atmosphere 10, 593 (2019).
    ADS  Google Scholar 

    44.
    Feng, K., Siu, Y. L., Guan, D. & Hubacek, K. Assessing regional virtual water flows and water footprints in the Yellow River Basin, China: a consumption based approach. Appl. Geogr. 32, 691–701 (2012).
    Google Scholar 

    45.
    Zhuo, L., Mekonnen, M. M. & Hoekstra, A. Y. The effect of inter-annual variability of consumption, production, trade and climate on crop-related green and blue water footprints and inter-regional virtual water trade: a study for China (1978–2008). Water Res. 94, 73–85 (2016).
    CAS  PubMed  Google Scholar 

    46.
    Rushforth, R. R. & Ruddell, B. L. A spatially detailed blue water footprint of the United States economy. Hydrol. Earth Syst. Sci. 22, 3007–3032 (2018).
    ADS  Google Scholar 

    47.
    Hou, S. et al. Blue and green water footprint assessment for China—a multi-region input–output approach. Sustainability 10, 2822 (2018).
    Google Scholar 

    48.
    Dalin, C., Wada, Y., Kastner, T. & Puma, M. J. Groundwater depletion embedded in international food trade. Nature 543, 700–704 (2017).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    49.
    Scanlon, B. R. et al. Groundwater depletion and sustainability of irrigation in the US High Plains and Central Valley. Proc. Natl Acad. Sci. USA 109, 9320–9325 (2012).
    ADS  CAS  PubMed  Google Scholar 

    50.
    Marston, L., Konar, M., Cai, X. & Troy, T. J. Virtual groundwater transfers from overexploited aquifers in the United States. Proc. Natl Acad. Sci. USA 112, 8561–8566 (2015).
    ADS  CAS  PubMed  Google Scholar 

    51.
    Siebert, S. et al. Groundwater use for irrigation – a global inventory. Hydrol. Earth Syst. Sci. Discuss. 7, 3977–4021 (2010).
    ADS  Google Scholar 

    52.
    Rosa, L., Chiarelli, D. D., Tu, C., Rulli, M. C. & D’Odorico, P. Global unsustainable virtual water flows in agricultural trade. Environ. Res. Lett. 14, 114001 (2019).
    ADS  CAS  Google Scholar 

    53.
    Qu, S. et al. Virtual water scarcity risk to the global trade system. Environ. Sci. Technol. 52, 673–683 (2018).
    ADS  CAS  PubMed  Google Scholar 

    54.
    Liu, W. et al. Savings and losses of global water resources in food-related virtual water trade. WIREs Water 6, e1320 (2019).
    Google Scholar 

    55.
    Han, M. Y., Chen, G. Q. & Li, Y. L. Global water transfers embodied in international trade: tracking imbalanced and inefficient flows. J. Clean. Prod. 184, 50–64 (2018).
    Google Scholar 

    56.
    Carr, J. A., D’Odorico, P., Laio, F. & Ridolfi, L. Recent history and geography of virtual water trade. PLoS ONE 8, e55825 (2013).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    57.
    Carr, J. A., D’Odorico, P., Laio, F. & Ridolfi, L. On the temporal variability of the virtual water network. Geophys. Res. Lett. 39, L06404 (2012).
    ADS  Google Scholar 

    58.
    Konar, M., Dalin, C., Hanasaki, N., Rinaldo, A. & Rodriguez-Iturbe, I. Temporal dynamics of blue and green virtual water trade networks. Water Resour. Res. 48, W07509 (2012).
    ADS  Google Scholar 

    59.
    Hoekstra, A. Y. & Mekonnen, M. M. Imported water risk: the case of the UK. Environ. Res. Lett. 11, 055002 (2016).
    ADS  Google Scholar 

    60.
    Richter, B. D., Davis, M. M., Apse, C. & Konrad, C. A presumptive standard for environmental flow protection. River Res. Appl. 28, 1312–1321 (2012).
    Google Scholar 

    61.
    Hoekstra, A. Y., Chapagain, A. K., Aldaya, M. M. & Mekonnen, M. M. The Water Footprint Assessment Manual: Setting the Global Standard (Earthscan, 2011).

    62.
    Schewe, J. et al. Multimodel assessment of water scarcity under climate change. Proc. Natl Acad. Sci. USA 111, 3245–3250 (2014).
    ADS  CAS  PubMed  Google Scholar 

    63.
    Poff, N. L. et al. The ecological limits of hydrologic alteration (ELOHA): a new framework for developing regional environmental flow standards. Freshw. Biol. 55, 147–170 (2010).
    Google Scholar 

    64.
    Tessmann, S. A. in Environmental Use Sector: Reconnaissance Elements of the Western Dakotas Region of South Dakota Study (Water Resources Institute, South Dakota State Univ., 1980).

    65.
    Suweis, S., Carr, J. A., Maritan, A., Rinaldo, A. & D’Odorico, P. Resilience and reactivity of global food security. Proc. Natl Acad. Sci. USA 112, 6902–6907 (2015).
    ADS  CAS  PubMed  Google Scholar 

    66.
    Brauman, K. A., Siebert, S. & Foley, J. A. Improvements in crop water productivity increase water sustainability and food security—a global analysis. Environ. Res. Lett. 8, 024030 (2013).
    ADS  Google Scholar 

    67.
    Mekonnen, M. M., Hoekstra, A. Y., Neale, C. M. U., Ray, C. & Yang, H. S. Water productivity benchmarks: the case of maize and soybean in Nebraska. Agric. Water Manag. 234, 106122 (2020).
    Google Scholar 

    68.
    Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).
    ADS  CAS  PubMed  Google Scholar 

    69.
    Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    70.
    Hoekstra, A. Y. Water for animal products: a blind spot in water policy. Environ. Res. Lett. 9, 091003 (2014).
    ADS  Google Scholar 

    71.
    Mekonnen, M. M. & Fulton, J. The effect of diet changes and food loss reduction in reducing the water footprint of an average American. Water Int. 43, 860–870 (2018).
    Google Scholar 

    72.
    Kummu, M. et al. Lost food, wasted resources: global food supply chain losses and their impacts on freshwater, cropland, and fertiliser use. Sci. Total Environ. 438, 477–489 (2012).
    ADS  CAS  PubMed  Google Scholar 

    73.
    Rockström, J. et al. Managing water in rainfed agriculture—the need for a paradigm shift. Agric. Water Manag. 97, 543–550 (2010).
    Google Scholar 

    74.
    Chukalla, A. D., Krol, M. S. & Hoekstra, A. Y. Green and blue water footprint reduction in irrigated agriculture: effect of irrigation techniques, irrigation strategies and mulching. Hydrol. Earth Syst. Sci. 19, 4877–4891 (2015).
    ADS  CAS  Google Scholar 

    75.
    Mueller, N. D. et al. Closing yield gaps through nutrient and water management. Nature 490, 254–257 (2012).
    ADS  CAS  PubMed  Google Scholar 

    76.
    Mekonnen, M. M. & Hoekstra, A. Y. Water footprint benchmarks for crop production: a first global assessment. Ecol. Indic. 46, 214–223 (2014).
    Google Scholar 

    77.
    Vanham, D., Mekonnen, M. M. & Hoekstra, A. Y. The water footprint of the EU for different diets. Ecol. Indic. 32, 1–8 (2013).
    Google Scholar 

    78.
    West, P. C. et al. Leverage points for improving global food security and the environment. Science 345, 325–328 (2014).
    ADS  CAS  PubMed  Google Scholar 

    79.
    Mekonnen, M. & Hoekstra, A. A global assessment of the water footprint of farm animal products. Ecosystems 15, 401–415 (2012).
    CAS  Google Scholar 

    80.
    Mekonnen, M. M. et al. Water, energy, and carbon footprints of bioethanol from the U.S. and Brazil. Environ. Sci. Technol. 52, 14508–14518 (2018).
    ADS  CAS  PubMed  Google Scholar  More

  • in

    Clean water to prevent kidney disease

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  • in

    Organic wastewater treatment by a single-atom catalyst and electrolytically produced H2O2

    1.
    Miklos, D. B. et al. Evaluation of advanced oxidation processes for water and wastewater treatment—a critical review. Water Res. 139, 118–131 (2018).
    CAS  Article  Google Scholar 
    2.
    Chuang, Y.-H., Chen, S., Chinn, C. J. & Mitch, W. A. Comparing the UV/monochloramine and UV/free chlorine advanced oxidation processes (AOPs) to the UV/hydrogen peroxide AOP under scenarios relevant to potable reuse. Environ. Sci. Technol. 51, 13859–13868 (2017).
    CAS  Article  Google Scholar 

    3.
    Hodges, B. C., Cates, E. L. & Kim, J.-H. Challenges and prospects of advanced oxidation water treatment processes using catalytic nanomaterials. Nat. Nanotechnol. 13, 642–650 (2018).
    CAS  Article  Google Scholar 

    4.
    Glaze, W. H., Kang, J.-W. & Chapin, D. H. The chemistry of water treatment processes involving ozone, hydrogen peroxide and ultraviolet radiation. Ozone Sci. Eng. 9, 335–352 (1987).
    CAS  Article  Google Scholar 

    5.
    Katsoyiannis, I. A., Canonica, S. & von Gunten, U. Efficiency and energy requirements for the transformation of organic micropollutants by ozone, O3/H2O2 and UV/H2O2. Water Res. 45, 3811–3822 (2011).

    6.
    Neyens, E. & Baeyens, J. A review of classic Fenton’s peroxidation as an advanced oxidation technique. J. Hazard. Mater. 98, 33–50 (2003).
    CAS  Article  Google Scholar 

    7.
    Nidheesh, P. V. Heterogeneous Fenton catalysts for the abatement of organic pollutants from aqueous solution: a review. RSC Adv. 5, 40552–40577 (2015).
    CAS  Article  Google Scholar 

    8.
    Pham, A. L.-T., Lee, C., Doyle, F. M. & Sedlak, D. L. A silica-supported iron oxide catalyst capable of activating hydrogen peroxide at neutral pH values. Environ. Sci. Technol. 43, 8930–8935 (2009).
    CAS  Article  Google Scholar 

    9.
    Lyu, L., Zhang, L., Wang, Q., Nie, Y. & Hu, C. Enhanced Fenton catalytic efficiency of γ-Cu–Al2O3 by σ-Cu2+–ligand complexes from aromatic pollutant degradation. Environ. Sci. Technol. 49, 8639–8647 (2015).
    Article  Google Scholar 

    10.
    Costa, R. C. C. et al. Novel active heterogeneous Fenton system based on Fe3-xMxO4 (Fe, Co, Mn, Ni): the role of M2+ species on the reactivity towards H2O2 reactions. J. Hazard. Mater. 129, 171–178 (2006).
    CAS  Article  Google Scholar 

    11.
    Gao, L. et al. Intrinsic peroxidase-like activity of ferromagnetic nanoparticles. Nat. Nanotechnol. 2, 577–583 (2007).
    CAS  Article  Google Scholar 

    12.
    Navalon, S., Alvaro, M. & Garcia, H. Heterogeneous Fenton catalysts based on clays, silicas and zeolites. Appl. Catal. B 99, 1–26 (2010).
    CAS  Article  Google Scholar 

    13.
    Navalon, S., Dhakshinamoorthy, A., Alvaro, M. & Garcia, H. Heterogeneous fenton catalysts based on activated carbon and related materials. ChemSusChem 4, 1712–1730 (2011).
    CAS  Article  Google Scholar 

    14.
    Bataineh, H., Pestovsky, O. & Bakac, A. pH-induced mechanistic changeover from hydroxyl radicals to iron(IV) in the Fenton reaction. Chem. Sci. 3, 1594–1599 (2012).
    CAS  Article  Google Scholar 

    15.
    Lin, S.-S. & Gurol, M. D. Catalytic decomposition of hydrogen peroxide on iron oxide: kinetics, mechanism, and implications. Environ. Sci. Technol. 32, 1417–1423 (1998).
    CAS  Article  Google Scholar 

    16.
    Campos-Martin, J. M., Blanco-Brieva, G. & Fierro, J. L. G. Hydrogen peroxide synthesis: an outlook beyond the anthraquinone process. Angew. Chem. Int. Ed. Engl. 45, 6962–6984 (2006).
    CAS  Article  Google Scholar 

    17.
    Lu, Z. et al. High-efficiency oxygen reduction to hydrogen peroxide catalysed by oxidized carbon materials. Nat. Catal. 1, 156–162 (2018).
    CAS  Article  Google Scholar 

    18.
    Kim, H. W. et al. Efficient hydrogen peroxide generation using reduced graphene oxide-based oxygen reduction electrocatalysts. Nat. Catal. 1, 282–290 (2018).
    Article  Google Scholar 

    19.
    Siahrostami, S. et al. Enabling direct H2O2 production through rational electrocatalyst design. Nat. Mater. 12, 1137–1143 (2013).
    CAS  Article  Google Scholar 

    20.
    Choi, C. H. et al. Tuning selectivity of electrochemical reactions by atomically dispersed platinum catalyst. Nat. Commun. 7, 10922 (2016).
    CAS  Article  Google Scholar 

    21.
    Xia, C., Xia, Y., Zhu, P., Fan, L. & Wang, H. Direct electrosynthesis of pure aqueous H2O2 solutions up to 20% by weight using a solid electrolyte. Science 366, 226–231 (2019).
    CAS  Article  Google Scholar 

    22.
    Chen, Z. et al. Development of a reactor with carbon catalysts for modular-scale, low-cost electrochemical generation of H2O2. React. Chem. Eng. 2, 239–245 (2017).
    Article  Google Scholar 

    23.
    Murayama, T. & Yamanaka, I. Electrosynthesis of neutral H2O2 solution from O2 and water at a mixed carbon cathode using an exposed solid-polymer-electrolyte electrolysis cell. J. Phys. Chem. C. 115, 5792–5799 (2011).
    CAS  Article  Google Scholar 

    24.
    Yamanaka, I. & Murayama, T. Neutral H2O2 synthesis by electrolysis of water and O2. Angew. Chem. Int. Ed. Engl. 47, 1900–1902 (2008).
    CAS  Article  Google Scholar 

    25.
    Bojdys, M. J., Müller, J.-O., Antonietti, M. & Thomas, A. Ionothermal synthesis of crystalline, condensed, graphitic carbon nitride. Chemistry 14, 8177–8182 (2008).
    CAS  Article  Google Scholar 

    26.
    Liu, J., Zhang, T., Wang, Z., Dawson, G. & Chen, W. Simple pyrolysis of urea into graphitic carbon nitride with recyclable adsorption and photocatalytic activity. J. Mater. Chem. 21, 14398–14401 (2011).
    CAS  Article  Google Scholar 

    27.
    Natarajan, T. S., Thomas, M., Natarajan, K., Bajaj, H. C. & Tayade, R. J. Study on UV-LED/TiO2 process for degradation of rhodamine B dye. Chem. Eng. J. 169, 126–134 (2011).
    CAS  Article  Google Scholar 

    28.
    He, Z. et al. Photocatalytic degradation of rhodamine B by Bi2WO6 with electron accepting agent under microwave irradiation: mechanism and pathway. J. Hazard. Mater. 162, 1477–1486 (2009).
    CAS  Article  Google Scholar 

    29.
    Fu, H., Pan, C., Yao, W. & Zhu, Y. Visible-light-induced degradation of rhodamine B by nanosized Bi2WO6. J. Phys. Chem. B 109, 22432–22439 (2005).
    CAS  Article  Google Scholar 

    30.
    Yamanaka, K. Anodically electrodeposited iridium oxide films (AEIROF) from alkaline solutions for electrochromic display devices. Jpn. J. Appl. Phys. 28, 632 (1989).

    31.
    Feng, D. et al. Zirconium-metalloporphyrin PCN-222: mesoporous metal–organic frameworks with ultrahigh stability as biomimetic catalysts. Angew. Chem. Int. Ed. Engl. 51, 10307–10310 (2012).
    CAS  Article  Google Scholar  More

  • in

    Improved forecasts of atmospheric rivers through systematic reconnaissance, better modelling, and insights on conversion of rain to flooding

    1.
    Zhu, Y. & Newell, R. E. A proposed algorithm for moisture fluxes from atmospheric rivers. Mon. Weather Rev. 126, 725–735 (1998).
    Article  Google Scholar 
    2.
    Ralph, F. M., Dettinger, M. D., Cairns, M. M., Galarneau, T. J. & Eylander, J. Defining “Atmospheric River”: how the glossary of meteorology helped resolve a debate. Bull. Am. Meteor. Soc 99, 837–839 (2018). This article provides the definition of an atmospheric river.
    Article  Google Scholar 

    3.
    Ralph, F. M. et al. (eds) In Atmospheric Rivers p. 286 (Springer, 2020).

    4.
    Ralph, F. M., Neiman, P. J. & Rotunno, R. Dropsonde observations in low‐level jets over the Northeastern Pacific Ocean from CALJET‐1998 and PACJET‐2001: mean vertical‐profile and atmospheric‐river characteristics. Mon. Weather Rev. 133, 889–910 (2005).
    Article  Google Scholar 

    5.
    Browning, K. A. & Pardoe, C. W. Structure of low-level jet streams ahead of mid-latitude cold fronts. Quart. J. Roy. Meteor. Soc. 99, 619–638 (1973).
    Article  Google Scholar 

    6.
    Sodemann, H. & Stohl, A. Moisture origin and meridional transport in atmospheric rivers and their association with multiple cyclones. Monthly Weather Rev. 141, 2850–2868 (2013).
    Article  Google Scholar 

    7.
    Ralph, F. M. et al. Dropsonde observations of total integrated water vapor transport within North Pacific atmospheric rivers. J. Hydrometeor. 18, 2577–2596 (2017).
    Article  Google Scholar 

    8.
    Browning, K. A. Conceptual models of precipitation systems. Weather Forecasting 1, 23–41 (1986).
    Article  Google Scholar 

    9.
    Wernli, H. & Davies, H. C. A Lagrangian-based analysis of extratropical cyclones. I: the method and some applications. Quart. J. Roy. Meteor. Soc. 123, 467–489 (1997).
    Article  Google Scholar 

    10.
    Madonna, E., Wernli, H., Joos, H. & Martius, O. Warm conveyor belts in the ERA-Interim dataset (1979–2010). Part I: climatology and potential vorticity evolution. J. Climate 27, 3–26 (2014).
    Article  Google Scholar 

    11.
    Sodemann, H. et al. (eds) In Atmospheric Rivers p. 286 (Springer, 2020).

    12.
    Doyle, J. D., Amerault, C., Reynolds, C. A. & Reinecke, P. A. Initial condition sensitivity and predictability of a severe extratropical cyclone using a moist adjoint. Monthly Weather Rev. 142, 320–342 (2014).
    Article  Google Scholar 

    13.
    Schäfler, A. & Harnisch, F. Impact of the inflow moisture on the evolution of a warm conveyor belt. Quart. J. Roy. Meteor. Soc. 141, 299–310 (2015).
    Article  Google Scholar 

    14.
    Rodwell, M. J., Richardson, D. S., Parsons, D. B. & Wernli, H. Flow-dependent reliability: a path to more skillful ensemble forecasts. Bull. Am. Meteor. Soc. 99, 1015–1026 (2018).
    Article  Google Scholar 

    15.
    Lavers, D. A. et al. Winter floods in Britain are connected to atmospheric rivers. Geophys. Res. Lett. 38, L23803 (2011).
    Article  Google Scholar 

    16.
    Lavers, D. A. & Villarini, G. The nexus between atmospheric rivers and extreme precipitation across Europe. Geophys. Res. Lett. 40, 3259–3264 (2013).
    Article  Google Scholar 

    17.
    Ramos, A. M., Trigo, R. M., Liberato, M. L. & Tomé, R. Daily precipitation extreme events in the Iberian Peninsula and its association with atmospheric rivers. J. Hydrometeor. 16, 579–597 (2015).
    Article  Google Scholar 

    18.
    Ralph, F. M. et al. Flooding on California’s Russian River: role of atmospheric rivers. Geophys. Res. Lett. 33, L13801 (2006).
    Article  Google Scholar 

    19.
    Neiman, P. J., Schick, L. J., Ralph, F. M., Hughes, M. & Wick, G. A. Flooding in western Washington: the connection to atmospheric rivers. J. Hydrometeor. 12, 1337–1358 (2011).
    Article  Google Scholar 

    20.
    Viale, M. & Nunez, M. N. Climatology of winter orographic precipitation over the subtropical central Andes and associated synoptic and regional characteristics. J. Hydrometeor. 12, 481–507 (2011).
    Article  Google Scholar 

    21.
    Kingston, D. G., Lavers, D. A. & Hannah, D. M. Floods in the Southern Alps of New Zealand: the importance of atmospheric rivers. Hydrol. Process. 30, 5063–5070 (2016).
    Article  Google Scholar 

    22.
    Pasquier, J. T., Pfahl, S. & Grams, C. M. Modulation of atmospheric river occurrence and associated precipitation extremes in the North Atlantic Region by European weather regimes. Geophys. Res. Lett. 46, 1014–1023 (2019).
    Article  Google Scholar 

    23.
    UK Met Office. Record Breaking Rainfall. https://www.metoffice.gov.uk/weather/warnings-and-advice/uk-storm-centre/storm-dennis (UK Met Office, 2020).

    24.
    Insured losses from Europe’s Storm Victoria (aka Dennis) estimated at €286M: PERILS. Insurance J. https://www.insurancejournal.com/news/international/2020/03/30/562719.htm (2020).

    25.
    Corringham, T. W., Ralph, F. M., Gershunov, A., Cayan, D. R. & Talbot, C. A. Atmospheric rivers drive flood damages in the western United States. Sci. Adv. 5, eaax4631 (2019).
    Article  Google Scholar 

    26.
    Waliser, D. & Guan, B. Extreme winds and precipitation during landfall of atmospheric rivers. Nat. Geosci. 10, 179–183 (2017).
    CAS  Article  Google Scholar 

    27.
    Khouakhi, A. & Villarini, G. On the relationship between atmospheric rivers and high sea water levels along the US West Coast. Geophys. Res. Lett. 43, 8815–8822 (2016).
    Article  Google Scholar 

    28.
    Dettinger, M. D., Ralph, F. M., Das, T., Neiman, P. J. & Cayan, D. Atmospheric rivers, floods, and the water resources of California. Water 3, 445–478 (2011).
    Article  Google Scholar 

    29.
    Baggett, C. F., Barnes, E. A., Maloney, E. D. & Mundhenk, B. D. Advancing atmospheric river forecasts into subseasonal‐to‐seasonal time scales. Geophys. Res. Lett. 44, 7528–7536 (2017).
    Article  Google Scholar 

    30.
    DeFlorio, M. J. et al. Global assessment of atmospheric river prediction skill. J. Hydrometeor. 19, 409–426 (2018).
    Article  Google Scholar 

    31.
    Lavers, D. A., Pappenberger, F., Richardson, D. S. & Zsoter, E. ECMWF Extreme Forecast Index for water vapor transport: a forecast tool for atmospheric rivers and extreme precipitation. Geophys. Res. Lett. 43, 11,852–11,858 (2016).
    Google Scholar 

    32.
    Lavers, D. A., Zsoter, E., Richardson, D. S. & Pappenberger, F. An assessment of the ECMWF extreme forecast index for water vapor transport during boreal winter. Weather Forecast. 32, 1667–1674 (2017). This paper describes the ECMWF Extreme Forecast Index product for integrated vapour transport and highlights the increased possible awareness of atmospheric rivers and extreme precipitation.
    Article  Google Scholar 

    33.
    Nayak, M. A., Villarini, G. & Lavers, D. A. On the skill of numerical weather prediction models to forecast atmospheric rivers over the central United States. Geophys. Res. Lett. 41, 4354–4362 (2014).
    Article  Google Scholar 

    34.
    Wick, G. A., Neiman, P. J., Ralph, F. M. & Hamill, T. M. Evaluation of forecasts of the water vapor signature of atmospheric rivers in operational numerical weather prediction models. Weather Forecast. 28, 1337–1352 (2013).
    Article  Google Scholar 

    35.
    Leutbecher, M. & Palmer, T. N. Ensemble forecasting. J. Comput. Phys. 227, 3515–3539 (2008).
    Article  Google Scholar 

    36.
    Lavers, D. A. et al. The gauging and modeling of rivers in the sky. Geophys. Res. Lett. https://doi.org/10.1029/2018GL079019 (2018).

    37.
    Rutz, J. J. et al. The atmospheric river tracking method intercomparison project (ARTMIP): quantifying uncertainties in atmospheric river climatology. J. Geophys. Res. 2019, 13777–13802 (2019).
    Article  Google Scholar 

    38.
    Martin, A. C., Ralph, F. M., Wilson, A., DeHaan, L. & Kawzenuk, B. Rapid cyclogenesis from a mesoscale frontal wave on an atmospheric river: impacts on forecast skill and predictability during atmospheric river landfall. J. Hydrometeor. 20, 1779–1794 (2019).
    Article  Google Scholar 

    39.
    Bauer, P., Thorpe, A. & Brunet, G. The quiet revolution of numerical weather prediction. Nature 525, 47–55 (2015).
    CAS  Article  Google Scholar 

    40.
    Lavers, D. A. et al. Earlier awareness of extreme winter precipitation across the western Iberian Peninsula. Meteorol. Appl. 25, 622–628 (2018).

    41.
    Lavers, D., Tsonevsky, I., Richardson, D. & Pappenberger, F. The Extreme Forecast Index for water vapour flux, ECMWF Newslett. 160, https://www.ecmwf.int/en/newsletter/160/news/extreme-forecast-index-water-vapour-flux (2019).

    42.
    Ralph, F. M. et al. A scale to characterize the strength and impacts of atmospheric rivers. Bull. Am. Meteor. Soc. 100, 269–289 (2019).
    Article  Google Scholar 

    43.
    Ralph, F. M. et al. West Coast forecast challenges and development of atmospheric river reconnaissance. Bull. Am. Meteor. Soc., 101, E1357–E1377, https://doi.org/10.1175/BAMS-D-19-0183.1 (2020). This paper provides an overview of Atmospheric River Reconnaissance in the northeast Pacific which is key to the ideas proposed for AR Recon Atlantic.

    44.
    Stone, R. E. et al. Atmospheric river reconnaissance observation impact in the navy global forecast system. Monthly Weather Rev. 148, 763–782 (2020).
    Article  Google Scholar 

    45.
    Lavers, D. A. et al. Forecast errors and uncertainties in Atmospheric Rivers. Weather Forecast. https://doi.org/10.1175/WAF-D-20-0049.1 (2020).

    46.
    National Winter Season Operations Plan. Winter Season Reconnaissance https://www.ofcm.gov/publications/nwsop/nwsop2.htm (2019).

    47.
    Schäfler, A. et al. The North Atlantic Waveguide and Downstream Impact Experiment. Bull. Amer. Meteor. Soc. 99, 1607–1637 (2018). This paper describes the NAWDEX observational campaign in the North Atlantic and AR Recon Atlantic would build on these findings.
    Article  Google Scholar 

    48.
    Grams, C. M., Magnusson, L. & Madonna, E. An atmospheric dynamics perspective on the amplification and propagation of forecast error in numerical weather prediction models: a case study. Quart. J. R. Meteor. Soc. 144, 2577–2591 (2018).
    Article  Google Scholar 

    49.
    Schäfler, A. et al. Observation of jet stream winds during NAWDEX and characterization of systematic meteorological analysis errors. Monthly Weather Rev. https://doi.org/10.1175/MWR-D-19-0229.1 (2020).

    50.
    Rennie, M. & Isaksen, L. Use of Aeolus observations at ECMWF. ECMWF Newslett. 163, https://www.ecmwf.int/en/newsletter/163/news/use-aeolus-observations-ecmwf (2020).

    51.
    Guan, B., Waliser, D. E., Molotch, N. P., Fetzer, E. J. & Neiman, P. J. Does the Madden–Julian oscillation influence wintertime atmospheric rivers and snowpack in the Sierra Nevada? Monthly Weather Rev. 140, 325–342 (2012).
    Article  Google Scholar 

    52.
    Ralph, F. M. et al. The impact of a prominent rain shadow on flooding in California’s Santa Cruz mountains: a CALJET case study and sensitivity to the ENSO cycle. J. Hydrometeor. 4, 1243–1264 (2003).
    Article  Google Scholar 

    53.
    Lavers, D. A., Villarini, G., Allan, R. P., Wood, E. F. & Wade, A. J. The detection of atmospheric rivers in atmospheric reanalyses and their links to British winter floods and the large-scale climatic circulation. J. Geophys. Res. 117, D20106 (2012).
    Google Scholar 

    54.
    Jasperse J. et al. Preliminary viability assessment of Lake Mendocino forecast informed reservoir operations. Technical report. http://pubs.er.usgs.gov/publication/70192184 (USGS, 2017). More

  • in

    Moist heat stress extremes in India enhanced by irrigation

    1.
    Im, E. S., Pal, J. S. & Eltahir, E. A. B. Deadly heat waves projected in the densely populated agricultural regions of South Asia. Sci. Adv. 3, e1603322 (2017).
    Article  Google Scholar 
    2.
    Mazdiyasni, O. et al. Increasing probability of mortality during Indian heat waves. Sci. Adv. 3, 1–6 (2017).
    Article  Google Scholar 

    3.
    Mishra, V., Mukherjee, S., Kumar, R. & Stone, D. A. Heat wave exposure in India in current, 1.5 °C, and 2.0 °C worlds. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/aa9388 (2017).

    4.
    Coffel, E. D., Horton, R. M. & de Sherbinin, A. Temperature and humidity based projections of a rapid rise in global heat stress exposure during the 21st century. Environ. Res. Lett. 13, 014001 (2017).
    Article  Google Scholar 

    5.
    King, A. D. et al. Emergence of heat extremes attributable to anthropogenic influences. Geophys. Res. Lett. 43, 3438–3443 (2016).
    Article  Google Scholar 

    6.
    Knutson, T. R. & Ploshay, J. J. Detection of anthropogenic influence on a summertime heat stress index. Clim. Change 138, 25–39 (2016).
    Article  Google Scholar 

    7.
    Matthews, T. K. R., Wilby, R. L. & Murphy, C. Communicating the deadly consequences of global warming for human heat stress. Proc. Natl Acad. Sci. USA 114, 3861–3866 (2017).
    Article  Google Scholar 

    8.
    Kjellstrom, T. et al. Heat, human performance, and occupational health: a key issue for the assessment of global climate change impacts. Annu. Rev. Public Health 37, 97–112 (2016).
    Article  Google Scholar 

    9.
    Sherwood, S. C. How important is humidity in heat stress? J. Geophys. Res. Atmos. 123, 11808–11810 (2018).
    Article  Google Scholar 

    10.
    Horton, R. M., Mankin, J. S., Lesk, C., Coffel, E. & Raymond, C. A review of recent advances in research on extreme heat events. Curr. Clim. Change Rep. 2, 242–259 (2016).
    Article  Google Scholar 

    11.
    Buzan, J. R., Oleson, K. & Huber, M. Implementation and comparison of a suite of heat stress metrics within the Community Land Model version 4.5. Geosci. Model Dev. 8, 151–170 (2015).
    Article  Google Scholar 

    12.
    Kang, S. & Eltahir, E. A. B. North China Plain threatened by deadly heatwaves due to climate change and irrigation. Nat. Commun. 9, 2894 (2018).
    Article  Google Scholar 

    13.
    Shankar, P. V., Kulkarni, H. & Krishnan, S. India’s groundwater challenge and the way forward. Econ. Political Wkly 46, 37–45 (2011).
    Google Scholar 

    14.
    Amarasinghe, U. A., Shah, T. & Anand, B. K. India’s water supply and demand from 2025-2050: business-as-usual scenario and issues. In Proc. Workshop on Analyses of Hydrological, Social and Ecological Issues of the National River Linking Project (eds Amarasinghe, U. A. & Sharma, B. R.) 23–61 (IWMI, 2007).

    15.
    Ambika, A. K., Wardlow, B. & Mishra, V. Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015. Sci. Data 3, 160118 (2016).
    Article  Google Scholar 

    16.
    Cook, B. I., Puma, M. J. & Krakauer, N. Y. Irrigation induced surface cooling in the context of modern and increased greenhouse gas forcing. Clim. Dyn. 37, 1587–1600 (2011).
    Article  Google Scholar 

    17.
    Thiery, W. et al. Present-day irrigation mitigates heat extremes. J. Geophys. Res. Atmos. 122, 1403–1422 (2017).
    Article  Google Scholar 

    18.
    Boucher, O., Myhre, G. & Myhre, A. Direct human influence of irrigation on atmospheric water vapour and climate. Clim. Dyn. 22, 597–603 (2004).
    Article  Google Scholar 

    19.
    Lobell, D. et al. Regional differences in the influence of irrigation on climate. J. Clim. 22, 2248–2255 (2009).
    Article  Google Scholar 

    20.
    Kumar, R. et al. Dominant control of agriculture and irrigation on urban heat island in India. Sci. Rep. 7, 14054 (2017).
    Article  Google Scholar 

    21.
    Mueller, N. D. et al. Cooling of US Midwest summer temperature extremes from cropland intensification. Nat. Clim. Change 6, 317–322 (2015).
    Article  Google Scholar 

    22.
    Asoka, A., Gleeson, T., Wada, Y. & Mishra, V. Relative contribution of monsoon precipitation and pumping to changes in groundwater storage in India. Nat. Geosci. 10, 109–117 (2017).
    Article  Google Scholar 

    23.
    Azhar, G. S. et al. Heat-related mortality in India: excess all-cause mortality associated with the 2010 Ahmedabad heat wave. PLoS ONE 9, e91831 (2014).
    Article  Google Scholar 

    24.
    Marcella, M. P. & Eltahir, E. A. B. Introducing an irrigation scheme to a regional climate model: a case study over West Africa. J. Clim. 27, 5708–5723 (2014).
    Article  Google Scholar 

    25.
    Puma, M. J. & Cook, B. I. Effects of irrigation on global climate during the 20th century. J. Geophys. Res. Atmos. 115, D16120 (2010).
    Article  Google Scholar 

    26.
    Willett, K. M. & Sherwood, S. Exceedance of heat index thresholds for 15 regions under a warming climate using the wet-bulb globe temperature. Int. J. Climatol. https://doi.org/10.1002/joc.2257 (2012).

    27.
    Sherwood, S. C. & Huber, M. An adaptability limit to climate change due to heat stress. Proc. Natl Acad. Sci. USA 107, 9552–9555 (2010).
    Article  Google Scholar 

    28.
    Byrne, M. P. & O’Gorman, P. A. Trends in continental temperature and humidity directly linked to ocean warming. Proc. Natl Acad. Sci. USA 115, 4863–4868 (2018).
    Article  Google Scholar 

    29.
    Willett, K. M., Gillett, N. P., Jones, P. D. & Thorne, P. W. Attribution of observed surface humidity changes to human influence. Nature 449, 710–712 (2007).
    Article  Google Scholar 

    30.
    Bollasina, M. & Nigam, S. The summertime ‘heat’ low over Pakistan/northwestern India: evolution and origin. Clim. Dyn. 37, 957–970 (2011).
    Article  Google Scholar 

    31.
    Gentine, P., Holtslag, A. A. M., D’Andrea, F. & Ek, M. Surface and atmospheric controls on the onset of moist convection over land. J. Hydrometeorol. 14, 1443–1462 (2013).
    Article  Google Scholar 

    32.
    Kang, S. & Eltahir, E. A. B. Impact of irrigation on regional climate over eastern China. Geophys. Res. Lett. 46, 5499–5505 (2019).
    Article  Google Scholar 

    33.
    Kueppers, L. M., Snyder, M. A. & Sloan, L. C. Irrigation cooling effect: regional climate forcing by land-use change. Geophys. Res. Lett. 34, L03703 (2007).
    Article  Google Scholar 

    34.
    Alter, R. E., Im, E. S. & Eltahir, E. A. B. Rainfall consistently enhanced around the Gezira Scheme in East Africa due to irrigation. Nat. Geosci. 8, 763–767 (2015).
    Article  Google Scholar 

    35.
    Im, E. S. & Kang, S. & Eltahir, E. A. B. Projections of rising heat stress over the western Maritime Continent from dynamically downscaled climate simulations. Glob. Planet. Change https://doi.org/10.1016/j.gloplacha.2018.02.01 (2018).

    36.
    Sacks, W. J., Cook, B. I., Buenning, N., Levis, S. & Helkowski, J. H. Effects of global irrigation on the near-surface climate. Clim. Dyn. 33, 159–175 (2009).
    Article  Google Scholar 

    37.
    Dileepkumar, R., Achutarao, K. & Arulalan, T. Human influence on sub-regional surface air temperature change over India. Sci. Rep. 8, 8967 (2018).
    Article  Google Scholar 

    38.
    Seneviratne, S. I. et al. Land radiative management as contributor to regional-scale climate adaptation and mitigation. Nat. Geosci. 11, 88–96 (2018).
    Article  Google Scholar 

    39.
    Sharma, A. et al. Green and cool roofs to mitigate urban heat island effects in the Chicago metropolitan area: evaluation with a regional climate model. Environ. Res. Lett. 11, 064004 (2016).
    Article  Google Scholar 

    40.
    Georgescu, M., Moustaoui, M., Mahalov, A. & Dudhia, J. An alternative explanation of the semiarid urban area ‘oasis effect’. J. Geophys. Res. Atmos. https://doi.org/10.1029/2011JD016720 (2011).

    41.
    Zipper, S. C., Schatz, J., Kucharik, C. J. & Loheide, S. P. Urban heat island-induced increases in evapotranspirative demand. Geophys. Res. Lett. https://doi.org/10.1002/2016GL072190 (2017).

    42.
    Siebert, S., Henrich, V., Frenken, K. & Burke, J. Update of the Digital Global Map of Irrigation Areas to Version 5 (FAO, 2013); https://doi.org/10.13140/2.1.2660.6728

    43.
    Mann, H. B. Nonparametric tests against trend. Econometrica 13, 245–259 (1945).
    Article  Google Scholar 

    44.
    Sen, P. K. Estimates of the regression coefficient based on Kendall’s Tau. J. Am. Stat. Assoc. 63, 1379–1389 (1968).
    Article  Google Scholar 

    45.
    Srivastava, A. K., Rajeevan, M. & Kshirsagar, S. R. Development of a high resolution daily gridded temperature data set (1969–2005) for the Indian region. Atmos. Sci. Lett. 10, 249–254.

    46.
    Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).
    Article  Google Scholar 

    47.
    Haldane, J. S. The influence of high air temperatures No. I. J. Hyg. (Lond.) 5, 494–513 (1905).
    Google Scholar 

    48.
    Davies-Jones, R. An efficient and accurate method for computing the wet-bulb temperature along pseudoadiabats. Mon. Weather Rev. 136, 2764–2785 (2008).
    Article  Google Scholar 

    49.
    Steadman, R. G. The assessment of sultriness. Part I. A temperature–humidity index based on human physiology and clothing science. J. Appl. Meteorol. 18, 861–873 (1979).
    Article  Google Scholar 

    50.
    Brooke Anderson, G., Bell, M. L. & Peng, R. D. Methods to calculate the heat index as an exposure metric in environmental health research. Environ. Health Perspect. 121, 1111–1119 (2013).
    Article  Google Scholar 

    51.
    Skamarock, C. et al. A Description of the Advanced Research WRF Model Version 4 (NCAR, 2019); https://doi.org/10.5065/1DFH-6P97

    52.
    Mitchell, K. et al. Noah Land Surface Model (LSM) User’s Guide (NCAR, 2005).

    53.
    Iacono, M. J. Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J. Geophys. Res. Atmos. https://doi.org/10.1029/2008JD009944 (2008).

    54.
    Janzic, Z. I. The step-mountain eta coordinate model: further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Weather Rev. 122, 927–945 (1994).
    Article  Google Scholar 

    55.
    Kain, J. S. & Kain, J. The Kain–Fritsch convective parameterization: an update. J. Appl. Meteorol. 43, 170–181 (2004).
    Article  Google Scholar 

    56.
    Qian, Y., Huang, M., Yang, B. & Berg, L. K. A modeling study of irrigation effects on surface fluxes and land–air–cloud interactions in the Southern Great Plains. J. Hydrometeorol. 14, 700–721 (2013).
    Article  Google Scholar 

    57.
    Siebert, S. et al. Development and validation of the global map of irrigation areas. Hydrol. Earth Syst. Sci. 9, 535–547 (2005).
    Article  Google Scholar 

    58.
    Rienecker, M. M. et al. MERRA: NASA’s modern-era retrospective analysis for research and applications. J. Clim. 24, 3624–3648 (2011).
    Article  Google Scholar 

    59.
    Durre, I. & Yin, X. Enhanced radiosonde data for studies of vertical structure. Bull. Am. Meteorol. Soc. 89, 1257–1262 (2008).
    Article  Google Scholar 

    60.
    Seidel, D. J., Ao, C. O. & Li, K. Estimating climatological planetary boundary layer heights from radiosonde observations: comparison of methods and uncertainty analysis. J. Geophys. Res. Atmos. 115, D16113 (2010).
    Article  Google Scholar 

    61.
    Basha, G. & Ratnam, M. V. Identification of atmospheric boundary layer height over a tropical station using high-resolution radiosonde refractivity profiles: comparison with GPS radio occupation measurements. J. Geophys. Res. Atmos. 114, D161010 (2009).
    Article  Google Scholar  More