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    The importance of user acceptance, support, and behaviour change for the implementation of decentralised water technologies

    Progress Towards the Sustainable Development Goals. Report of the Secretary-General (United Nations, Economic and Social Council, 2022).Sustainable Development Goal 6 Synthesis Report 2018 on Water and Sanitation (United Nations, 2018).Luoto, J. et al. What point-of-use water treatment products do consumers use? Evidence from a randomized controlled trial among the urban poor in Bangladesh. PLoS ONE 6, e26132 (2011).Article 
    CAS 

    Google Scholar 
    Pickering, A. J. et al. Differences in field effectiveness and adoption between a novel automated chlorination system and household manual chlorination of drinking water in Dhaka, Bangladesh: a randomized controlled trial. PLoS ONE 10, e0118397 (2015).Article 

    Google Scholar 
    Oteng-Peprah, M., de Vries, N. & Acheampong, M. A. Households’ willingness to adopt greywater treatment technologies in a developing country—exploring a modified theory of planned behaviour (TPB) model including personal norm. J. Environ. Manag. 254, 109807 (2020).Article 
    CAS 

    Google Scholar 
    Tortajada, C. & van Rensburg, P. Drink more recycled wastewater. Nature 577, 26–28 (2020).Article 
    CAS 

    Google Scholar 
    Tortajada, C. & Nam Ong, C. Reused water policies for potable use. Int. J. Water Resour. D 32, 500–502 (2016).Article 

    Google Scholar 
    Batel, S., Devine-Wright, P. & Tangeland, T. Social acceptance of low carbon energy and associated infrastructures: a critical discussion. Energy Policy 58, 1–5 (2013).Article 

    Google Scholar 
    Hurlimann, A. & Dolnicar, S. When public opposition defeats alternative water projects—the case of Toowoomba Australia. Water Res. 44, 287–297 (2010).Article 
    CAS 

    Google Scholar 
    Kenney, S. Purifying water: responding to public opposition to the implementation of direct potable reuse in California. UCLA J. Environ. Law Policy 37, 85–122 (2019).Article 

    Google Scholar 
    Mosler, H.-J. A systematic approach to behavior change interventions for the water and sanitation sector in developing countries: a conceptual model, a review, and a guideline. Int. J. Environ. Health Res. 22, 431–449 (2012).Article 

    Google Scholar 
    Boisson, S. et al. Effect of household-based drinking water chlorination on diarrhoea among children under five in Orissa, India: a double-blind randomised placebo-controlled trial. PLoS Med. 10, e1001497 (2013).Article 

    Google Scholar 
    Sonego, I. L., Huber, A. C. & Mosler, H.-J. Does the implementation of hardware need software? A longitudinal study on fluoride-removal filter use in Ethiopia. Environ. Sci. Technol. 47, 12661–12668 (2013).Article 
    CAS 

    Google Scholar 
    Stauber, C. E. et al. A cluster randomized trial of the impact of education through listening (a novel behavior change technique) on household water treatment with chlorine in Vihiga District, Kenya, 2010–2011. Am. J. Trop. Med. 104, 382–390 (2021).Article 
    CAS 

    Google Scholar 
    Hoffmann, S. et al. A research agenda for the future of urban water management: exploring the potential of nongrid, small-grid, and hybrid solutions. Environ. Sci. Technol. 54, 5312–5322 (2020).Article 
    CAS 

    Google Scholar 
    Anthonj, C. et al. Do health risk perceptions motivate water- and health-related behaviour? A systematic literature review. Sci. Total Environ. 819, 152902 (2022).Article 
    CAS 

    Google Scholar 
    Huber, A. C., Tobias, R. & Mosler, H.-J. Evidence-based tailoring of behavior-change campaigns: increasing fluoride-free water consumption in rural Ethiopia with persuasion. Appl. Psychol. Health Well Being 6, 96–118 (2014).Article 

    Google Scholar 
    Johnston, M. et al. Development of an online tool for linking behavior change techniques and mechanisms of action based on triangulation of findings from literature synthesis and expert consensus. Transl. Behav. Med. 11, 1049–1065 (2021).Article 

    Google Scholar 
    Belcher, B. M., Davel, R. & Claus, R. A refined method for theory-based evaluation of the societal impacts of research. MethodsX 7, 100788 (2020).Article 

    Google Scholar 
    Deutsch, L., Belcher, B., Claus, R. & Hoffmann, S. Leading inter- and transdisciplinary research: lessons from applying theories of change to a strategic research program. Environ. Sci. Policy 120, 29–41 (2021).Article 

    Google Scholar 
    De Buck, E. et al. Approaches to Promote Handwashing and Sanitation Behaviour Change in Low- and Middle-Income Countries: A Mixed Method Systematic Review (Campbell Systematic Reviews, 2017).Inauen, J. et al. Environmental issues are health issues: making a case and setting an agenda for environmental health psychology. Eur. Psychol. 26, 219–229 (2021).Article 

    Google Scholar 
    Mosler, H.-J. & Contzen, N. Systematic Behavior Change in Water, Sanitation and Hygiene. A Practical Guide Using the RANAS Approach 1.1 edn (Eawag, 2016).Hering, J. G., Waite, T. D., Luthy, R. G., Drewes, J. E. & Sedlak, D. L. A changing framework for urban water systems. Environ. Sci. Technol. 47, 10721–10726 (2013).Article 
    CAS 

    Google Scholar 
    Rabaey, K., Vandekerckhove, T., de Walle, A. V. & Sedlak, D. L. The third route: using extreme decentralization to create resilient urban water systems. Water Res. 185, 116276 (2020).Article 
    CAS 

    Google Scholar 
    Khatri, K., Vairavamoorthy, K. & Porto, M. in Water for a Changing World. Developing Local Knowledge and Capacity (eds Alaerts, G. & Dickinson, N.) 93–112 (CRC Press, 2008).Massoud, M. A., Tarhini, A. & Nasr, J. A. Decentralized approaches to wastewater treatment and management: applicability in developing countries. J. Environ. Manag. 90, 652–659 (2009).Article 

    Google Scholar 
    Noppers, E. H., Keizer, K., Bolderdijk, J. W. & Steg, L. The adoption of sustainable innovations: driven by symbolic and environmental motives. Glob. Environ. Change 25, 52–62 (2014).Article 

    Google Scholar 
    Nolan, J. M., Schultz, P. W., Cialdini, R. B., Goldstein, N. J. & Griskevicius, V. Normative social influence is underdetected. Pers. Soc. Psychol. Bull. 34, 913–923 (2008).Article 

    Google Scholar 
    Huber, A. C. & Mosler, H.-J. Determining behavioral factors for interventions to increase safe water consumption: a cross-sectional field study in rural Ethiopia. Int. J. Environ. Health Res. 23, 96–107 (2013).Article 

    Google Scholar 
    Chesley, N., Meier, H., Luo, J., Apchemengich, I. & Davies, W. H. Social factors shaping the adoption of lead-filtering point-of-use systems: an observational study of an MTurk sample. J. Water Health 18, 505–521 (2020).Article 

    Google Scholar 
    Graf, J., Meierhofer, R., Wegelin, M. & Mosler, H.-J. Water disinfection and hygiene behaviour in an urban slum in Kenya: impact on childhood diarrhoea and influence of beliefs. Int. J. Environ. Health Res. 18, 335–355 (2008).Article 

    Google Scholar 
    Lilje, J. & Mosler, H.-J. Effects of a behavior change campaign on household drinking water disinfection in the Lake Chad Basin using the RANAS approach. Sci. Total Environ. 619–620, 1599–1607 (2018).Article 

    Google Scholar 
    Murray, A. L. et al. Evaluation of consistent use, barriers to use, and microbiological effectiveness of three prototype household water treatment technologies in Haiti, Kenya, and Nicaragua. Sci. Total Environ. 718, 134685 (2020).Article 
    CAS 

    Google Scholar 
    Kraemer, S. M. & Mosler, H.-J. Persuasion factors influencing the decision to use sustainable household water treatment. Int. J. Environ. Health Res. 20, 61–79 (2010).Article 

    Google Scholar 
    Heri, S. & Mosler, H.-J. Factors affecting the diffusion of solar water disinfection: a field study in Bolivia. Health Educ. Behav. 35, 541–560 (2008).Article 

    Google Scholar 
    Daniel, D., Sirait, M. & Pande, S. A hierarchical Bayesian belief network model of household water treatment behaviour in a suburban area: a case study of Palu—Indonesia. PLoS ONE 15, e0241904 (2020).Article 
    CAS 

    Google Scholar 
    Daniel, D. et al. Understanding the effect of socio-economic characteristics and psychosocial factors on household water treatment practices in rural Nepal using Bayesian belief networks. Int. J. Hyg. Environ. Health 222, 847–855 (2019).Article 
    CAS 

    Google Scholar 
    Thaher, R. A., Mahmoud, N., Al-Khatib, I. A. & Hung, Y.-T. Reasons of acceptance and barriers of house onsite greywater treatment and reuse in Palestinian rural areas. Water https://doi.org/10.3390/w12061679 (2020).Gómez-Román, C., Sabucedo, J.-M., Alzate, M. & Medina, B. Environmental concern priming and social acceptance of sustainable technologies: the case of decentralized wastewater treatment systems. Front. Psychol. https://doi.org/10.3389/fpsyg.2021.647406 (2021).Marks, J., Cromar, N., Fallowfield, H. & Oemcke, D. Community experience and perceptions of water reuse. Water Supply 3, 9–16 (2003).Article 
    CAS 

    Google Scholar 
    Domènech, L. & Saurí, D. Socio-technical transitions in water scarcity contexts: public acceptance of greywater reuse technologies in the metropolitan area of Barcelona. Resour. Conserv. Recycl. 55, 53–62 (2010).Article 

    Google Scholar 
    Portman, M. E., Vdov, O., Schuetze, M., Gilboa, Y. & Friedler, E. Public perceptions and perspectives on alternative sources of water for reuse generated at the household level. J. Water Reuse Desalination https://doi.org/10.2166/wrd.2022.002 (2022).Article 

    Google Scholar 
    Nancarrow, B. E., Porter, N. B. & Leviston, Z. Predicting community acceptability of alternative urban water supply systems: a decision making model. Urban Water J. 7, 197–210 (2010).Article 

    Google Scholar 
    Huber, A. C., Bhend, S. & Mosler, H.-J. Determinants of exclusive consumption of fluoride-free water: a cross-sectional household study in rural Ethiopia. J. Public Health 20, 269–278 (2012).Article 

    Google Scholar 
    MacDonald, M. C. et al. Assessing participant compliance with point-of-use water treatment: an exploratory investigation. Public Work. Manag. Policy 23, 150–167 (2018).Article 

    Google Scholar 
    Tobias, R. & Berg, M. Sustainable use of arsenic-removing sand filters in vietnam: psychological and social factors. Environ. Sci. Technol. 45, 3260–3267 (2011).Article 
    CAS 

    Google Scholar 
    Contzen, N. & Marks, S. J. Increasing the regular use of safe water kiosk through collective psychological ownership: a mediation analysis. J. Environ. Psychol. 57, 45–52 (2018).Article 

    Google Scholar 
    Blum, A. G., Null, C. & Hoffmann, V. Marketing household water treatment: willingness to pay results from an experiment in rural Kenya. Water 6, 1873–1886 (2014).Article 

    Google Scholar 
    Brouwer, R., Job, F. C., van der Kroon, B. & Johnston, R. Comparing willingness to pay for improved drinking-water quality using stated preference methods in rural and urban Kenya. Appl. Health Econ. Health Policy 13, 81–94 (2015).Article 

    Google Scholar 
    Amaris, G., Dawson, R., Gironás, J., Hess, S. & Ortúzar, J. D. D. Understanding the preferences for different types of urban greywater uses and the impact of qualitative attributes. Water Res. 184, 116007 (2020).Article 
    CAS 

    Google Scholar 
    Nancarrow, B. E., Leviston, Z. & Tucker, D. I. Measuring the predictors of communities’ behavioural decisions for potable reuse of wastewater. Water Sci. Technol. 60, 3199–3209 (2009).Article 
    CAS 

    Google Scholar 
    Po, M., Nancarrow, B. E. & Kaercher, J. D. Literature Review of Factors Influencing Public Perceptions of Water Reuse Vol. 54 (CSIRO Land and Water, 2003).Rozin, P., Haddad, B., Nemeroff, C. & Slovic, P. Psychological aspects of the rejection of recycled water: contamination, purification and disgust. Judgm. Decis. Mak. 10, 50–63 (2015).Article 

    Google Scholar 
    Wester, J. et al. Psychological and social factors associated with wastewater reuse emotional discomfort. J. Environ. Psychol. 42, 16–23 (2015).Article 

    Google Scholar 
    Jeffrey, P. & Jefferson, B. Public receptivity regarding ‘in-house’ water recycling: results from a UK survey. Water Supply 3, 109–116 (2003).Article 

    Google Scholar 
    Brown, R. R. & Davies, P. Understanding community receptivity to water re-use: Ku-ring-gai Council case study. Water Sci. Technol. 55, 283–290 (2007).Article 
    CAS 

    Google Scholar 
    Mankad, A. Decentralised water systems: emotional influences on resource decision making. Environ. Int. 44, 128–140 (2012).Article 

    Google Scholar 
    Altherr, A.-M., Mosler, H.-J., Tobias, R. & Butera, F. Attitudinal and relational factors predicting the use of solar water disinfection: a field study in Nicaragua. Health Educ. Behav. 35, 207–220 (2008).Article 

    Google Scholar 
    Chen, Z. et al. Analysis of social attitude to the new end use of recycled water for household laundry in Australia by the regression models. J. Environ. Manag. 126, 79–84 (2013).Article 

    Google Scholar 
    Friedler, E. & Lahav, O. Centralised urban wastewater reuse: what is the public attitude. Water Sci. Technol. 54, 423–430 (2006).Article 
    CAS 

    Google Scholar 
    Fielding, K. S., Dolnicar, S. & Schultz, T. Public acceptance of recycled water. Int. J. Water Resour. D 35, 551–586 (2019).Article 

    Google Scholar 
    Sutherland, C. et al. Socio-technical analysis of a sanitation innovation in a peri-urban household in Durban, South Africa. Sci. Total Environ. 755, 143284 (2021).Article 
    CAS 

    Google Scholar 
    Tyler, T. R. Social justice: outcome and procedure. Int. J. Psychol. 35, 117–125 (2000).Article 

    Google Scholar 
    Ross, V. L., Fielding, K. S. & Louis, W. R. Social trust, risk perceptions and public acceptance of recycled water: testing a social-psychological model. J. Environ. Manag. 137, 61–68 (2014).Article 

    Google Scholar 
    Siegrist, M., Connor, M. & Keller, C. Trust, confidence, procedural fairness, outcome fairness, moral conviction, and the acceptance of GM field experiments. Risk Anal. 32, 1394–1403 (2012).Article 

    Google Scholar 
    Huijts, N. M. A., Contzen, N. & Roeser, S. Unequal means more unfair means more negative emotions? Ethical concerns and emotions about an unequal distribution of negative outcomes of a local energy project. Energy Policy 165, 112963 (2022).Article 

    Google Scholar 
    Marks, S. J., Onda, K. & Davis, J. Does sense of ownership matter for rural water system sustainability? Evidence from Kenya. J. Water Sanit. Hyg. Dev. 3, 122–133 (2013).Article 

    Google Scholar 
    Mankad, A. & Tapsuwan, S. Review of socio-economic drivers of community acceptance and adoption of decentralised water systems. J. Environ. Manag. 92, 380–391 (2011).Article 

    Google Scholar 
    Choukr-Allah, R. in Arab Environment. Water: Sustainable Management of a Scarce Resource (eds El-Ashry, M. et al.) 107–124 (Arab Forum for Environment and Development, 2010).Greenaway, T. & Fielding, K. S. Positive affective framing of information reduces risk perceptions and increases acceptance of recycled water. Environ. Commun. 14, 391–402 (2020).Article 

    Google Scholar 
    Kraemer, S. M. & Mosler, H.-J. Effectiveness and effects of promotion strategies for behaviour change: solar water disinfection in Zimbabwe. Appl. Psychol. 61, 392–414 (2012).Article 

    Google Scholar 
    Kirby, M. A. et al. Effects of a large-scale distribution of water filters and natural draft rocket-style cookstoves on diarrhea and acute respiratory infection: a cluster-randomized controlled trial in Western Province, Rwanda. PLoS Med. 16, e1002812 (2019).Article 

    Google Scholar 
    Trent, M. et al. Access to household water quality information leads to safer water: a cluster randomized controlled trial in india. Environ. Sci. Technol. 52, 5319–5329 (2018).Article 
    CAS 

    Google Scholar 
    John, A. & Orkin, K. Can simple psychological interventions increase preventive health investment? J. Eur. Econ. Assoc. 20, 1001–1047 (2021).Article 

    Google Scholar 
    Ambuehl, B., Kunwar, B. M., Schertenleib, A., Marks, S. J. & Inauen, J. Can participation promote psychological ownership of a shared resource? An intervention study of community-based safe water infrastructure. J. Environ. Psychol. 81, 101818 (2022).Article 

    Google Scholar 
    Sheeran, P. & Webb, T. L. The intention–behavior gap. Soc. Pers. Psychol. Compass 10, 503–518 (2016).Article 

    Google Scholar 
    Pierce, J. L. & Jussila, I. Collective psychological ownership within the work and organizational context: Construct introduction and elaboration. J. Organ. Behav. 31, 810–834 (2010).Article 

    Google Scholar 
    Pierce, J. L., Kostova, T. & Dirks, K. T. Toward a theory of psychological ownership in organizations. Acad. Manag. Rev. 26, 298–310 (2001).Article 

    Google Scholar 
    Schwarzer, R. Self-regulatory processes in the adoption and maintenance of health behaviors. J. Health Psychol. 4, 115–127 (1999).Article 
    CAS 

    Google Scholar 
    Schwartz, S. H. & Howard, J. A. in Altruism and Helping Behaviour: Social, Personality, and Developmental Perspectives (eds Rushton, J. P. & Sorrentino, R. M.) 189–211 (Lawrence Erlbaum, 1981).Cialdini, R. B., Kallgren, C. A. & Reno, R. R. A focus theory of normative conduct: a theoretical refinement and reevaluation of the role of norms in human behavior. Adv. Exp. Soc. Psychol. 24, 201–234 (1991).Article 

    Google Scholar 
    Dreibelbis, R. et al. The integrated behavioural model for water, sanitation, and hygiene: a systematic review of behavioural models and a framework for designing and evaluating behaviour change interventions in infrastructure-restricted settings. BMC Public Health 13, 1015 (2013).Article 

    Google Scholar 
    Daniel, D., Pande, S. & Rietveld, L. Socio-economic and psychological determinants for household water treatment practices in indigenous–rural Indonesia. Front. Water https://doi.org/10.3389/frwa.2021.649445 (2021).Check, J. & Schutt, R. K. in Research Methods in Education (eds Check, J. & Schutt, R. K.) 141–169 (SAGE Publications, 2012).Reynaert, E., Hess, A. & Morgenroth, E. Making waves: why water reuse frameworks need to co-evolve with emerging small-scale technologies. Water Res. X 11, 100094 (2021).Article 
    CAS 

    Google Scholar 
    Hug, S. J., Winkel, L. H., Voegelin, A., Berg, M. & Johnson, A. C. Arsenic and other geogenic contaminants in groundwater—a global challenge. Chimia 74, 524–524 (2020).Article 
    CAS 

    Google Scholar 
    Safe water enterprises: an entrepreneurial approach to drinking water. Siemens Stiftung https://www.siemens-stiftung.org/en/projects/safe-water-enterprises/ (2023).Lakho, F. H. et al. Decentralized grey and black water reuse by combining a vertical flow constructed wetland and membrane based potable water system: full scale demonstration. J. Environ. Chem. Eng. 9, 104688 (2021).Article 
    CAS 

    Google Scholar 
    Gikas, P. & Tchobanoglous, G. The role of satellite and decentralized strategies in water resources management. J. Environ. Manag. 90, 144–152 (2009).Article 
    CAS 

    Google Scholar 
    Garcia, X. & Pargament, D. Reusing wastewater to cope with water scarcity: economic, social and environmental considerations for decision-making. Resour. Conserv. Recycl. 101, 154–166 (2015).Article 

    Google Scholar 
    Metcalf & Eddy Inc. an AECOM Company et al. Water Reuse: Issues, Technologies, and Applications (McGraw-Hill Education, 2007).Singh, N. K., Kazmi, A. A. & Starkl, M. A review on full-scale decentralized wastewater treatment systems: techno-economical approach. Water Sci. Technol. 71, 468–478 (2014).Article 

    Google Scholar 
    Chen, Z., Wu, Q., Wu, G. & Hu, H.-Y. Centralized water reuse system with multiple applications in urban areas: lessons from China’s experience. Resour. Conserv. Recycl. 117, 125–136 (2017).Article 

    Google Scholar 
    Ambuehl, B. et al. The role of psychological ownership in safe water management: a mixed-methods study in Nepal. Water 13, 589 (2021).Article 

    Google Scholar 
    Sharma, A. K., Tjandraatmadja, G., Cook, S. & Gardner, T. Decentralised systems—definition and drivers in the current context. Water Sci. Technol. 67, 2091–2101 (2013).Article 

    Google Scholar 
    O’Driscoll, M. P., Pierce, J. L. & Coghlan, A.-M. The psychology of ownership: work environment structure, organizational commitment, and citizenship behavior. Group Organ. Manag. 31, 388–416 (2006).Article 

    Google Scholar 
    Marks, S. J. & Davis, J. Does user participation lead to sense of ownership for rural water systems? Evidence from Kenya. World Dev. 40, 1569–1576 (2012).Article 

    Google Scholar  More

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    The accuracy and usability of point-of-use fluoride biosensors in rural Kenya

    Test manufactureThe DNA plasmid encoding the fluoride biosensor used in this study was assembled using Gibson assembly (New England Biolabs, Cat#E2611S) and purified using a Qiagen QIAfilter Midiprep Kit (QIAGEN, Cat#12143). Its coding sequence consists of the crcB fluoride riboswitch from Bacillus cereus regulating the production of the enzyme catechol 2,3-dioxygenase, all expressed under the constitutive E. coli sigma 70 consensus promoter J2311939. A complete sequence of the plasmid used is available on Addgene with accession number 128810 (pJBL7025) [https://www.addgene.org/128810/].Cell-free biosensing reactions used in the tests were set up according to previously established protocols20,40. Briefly, reactions consist of cleared cellular extract, a reagent mix containing amino acids, buffering salts, crowding agents, enzymatic substrate, and an energy source, and a reaction-specific mix of template DNA and sodium fluoride in an approximately 30/30/40 ratio (Supplementary Table 3). Test reactions contained no sodium fluoride, while positive control reactions were supplemented with 1 mM sodium fluoride to induce gene expression. Template DNA concentration for both sets of reactions was 5 nM, determined by the maximal template concentration at which no color change was observed in the absence of fluoride.During reaction setup, master mixes of cellular extract, reagent mix, and template mix were prepared for both test and positive control reactions in 1.7 mL microcentrifuge tubes. Individual reactions were then aliquoted into 20 µL volumes in PCR tube strips for lyophilization. After aliquoting on ice, PCR tube caps were pierced with a pin, strips were wrapped in aluminum foil, then the wrapped strips were immersed in liquid nitrogen for freeze-drying for approximately 3 min. Reactions were immediately transferred to a Labconco FreeZone 2.5 Liter −84 °C Benchtop Freeze-Dryer (Cat# 710201000) with a condenser temperature of −84 °C and pressure of 0.04 mbar and freeze-dried overnight (≥16 h).After freeze-drying, tests were vacuum sealed (KOIOS Vacuum Sealer Machine, Amazon, Amazon Standard Identification Number (ASIN) B07FM3J6JF) in a food saver bag (KOIS Vacuum Sealer Bag, Amazon, ASIN B075KKWFYN), along with a desiccant (Dri-Card Desiccants, Uline, Cat# S-19582) (Supplementary Fig. 3). Vacuum sealed reactions were then paced in a light-protective outer bag (Mylar open-ended food bags, Uline, Cat# S-11661) and impulse heat-sealed (Metronic 8-inch Impulse Bag Sealer, Amazon, ASIN B06XC76JVZ) before shipping. Tests were also shipped with single-use 20 µL micropipettes (MICROSAFE® 20 µL, Safe-Tec LLC, Cat# 1020) for field operation.Test-kit shipment to Nakuru County, KenyaA first shipment of biosensor tests was used to assess 33 water samples from the first 16 households surveyed. All of these tests resulted in a faint yellow color, regardless of water source or fluoride concentration established via fluorimeter. This was likely caused by thermal degradation of the tests during shipment with the commercial shipping agency. While previous studies report shelf stability for up to a year20,41, these figures were derived from storage in temperature-controlled laboratory conditions. Commercial shipment routes from Illinois, USA to Nairobi, Kenya pass through extremely hot regions, e.g., Dubai for this particular shipment. These conditions were much different from those in the previous study usability study in Costa Rica in which tests were transported by commercial air, with gentler shipping and storage conditions20. A laboratory investigation of test temperature stability indicated that elevated storage temperatures can indeed cause test components to degrade, resulting in a faint yellow color upon rehydration consistent with field observations (Supplementary Fig. 2).The next batch of tests was therefore shipped refrigerated on January 25th, 2022, which we hypothesized would extend the tests’ shelf stability to align with earlier findings. After the tests were made and packaged, they were placed in a polystyrene foam-lined container before being covered with a NanoCool refrigeration system (Peli BioThermal). The container was then sealed shut and shipped using a standard commercial shipping service. This batch of tests was held in customs, refrigerated, until release on February 28th, 2022. These tests were used in the field from March 5th to March 14th, 2022 to generate the data on test accuracy reported in this manuscript.As discoloration due to thermal degradation could confound the intended yellow hue in the presence of fluoride (i.e., false positives), we assessed test accuracy using only tests that had been refrigerated during shipping and transport to participants’ houses. The 33 water samples from the first 16 households were therefore excluded from analysis of test accuracy.Participant recruitmentParticipants were recruited from six sublocations (Kelelwet, Kipsimbol, Kigonor, Parkview, Lalwet, and Mwariki) in Barut Ward within Nakuru County (Supplementary Fig. 4, geographic information adapted from OpenStreetMap42). This location was chosen because of high fluoride levels and familiarity with the communities by the study team.Before any data were collected, community meetings were held in each sub-location to discuss study goals and objectives. After obtaining permission from the community and village assistant chiefs to conduct research, local community mobilizers were engaged to assist with identifying households eligible for participation. Individuals who were 18 years or older, had lived in Nakuru country for more than three months, relied on local water sources for drinking, had a child in the household, were willing to discuss their household water situation, and provide a sample of each source of water in the household for fluoride testing were eligible. We sought to recruit 10–12 participants from each of the five sublocations to ensure a range of sociodemographic characteristics and drinking water sources. Having a child resident was a criterion in order to elucidate community understandings about fluorosis in children.Data collectionAfter obtaining informed written consent, participants participated in a 30-min survey (cf. Supplementary Fig. 1 for a graphical overview of data collection). Topics included household sociodemographic information, knowledge, attitudes, and behaviors about fluoride and fluorosis, and household water insecurity using the validated Household Water Insecurity Experiences (HWISE) scale43. The 12 HWISE items query the frequency of experiences with water insecurity in the prior month; “never” is scored 0, “often/always” scored 3, for a range of 0–36. These data were collected to be able to investigate if user experiences or attitudes about testing varied by experiences with fluorosis or water insecurity. Participants were also asked about the number of sources of their water and willingness to provide and test water samples. Survey responses were recorded on tablets using Open Data Kit (ODK)44.After completion of the survey, participants provided 1–3 samples of water from different household sources. They then received a brief (~5 min) explanation of the testing process, and then tested their own household samples using the fluoride biosensor tests. Each test consisted of a microtube that was a positive control, and a second microtube in which the sample of interest was tested. To test their samples, participants first removed the tests from the light-protective foil pouch and vacuum sealed pouch containing desiccant, both of which were then discarded (Supplementary Fig. 3). A micropipette was then filled with 20 µL water by slowly immersing it to the fill line. To dispense the water, the thumb and index finger were used to cover the holes in the micropipette while the bulb was squeezed with the other hand. The reactions were then incubated at ambient temperature for up to six hours, shorter if there was a visible color change. During this incubation time, participants were asked to check hourly for yellow color change and note the time taken for it to occur. Tests were expected to turn yellow if fluoride levels were ≥1.5 ppm, with no color change for tests of water below this level. All positive controls were expected to turn yellow. Color change was read after placing reactions against a white background for visual contrast.The study team returned to conduct a second survey on user experiences with the testing process and to test the water samples using the gold-standard photometer within 6 h. Participants were asked about their experiences with the testing procedure as well as their interpretation of the color of the results of the sample and control tests. Photographs of the completed reactions were also taken at this time. Finally, quantitative fluoride measurements were taken by the field team with a Hanna Instruments Fluoride High Range Photometer Kit (Cat# HI97739C), a gold-standard method used to assess the accuracy of the bioengineered tests. Photometry results on actual measured fluoride concentrations of water samples were shared with and explained to participants. At the conclusion of the second survey, each participant was given KES 500 (USD 4.30) as remuneration for the time and effort spent participating in the research. Each participating household was also given a ceramic drinking water filter.Data were collected from November 16th to November 23rd, 2021 and March 5th to March 14th, 2022. During surveying and water testing, participants and research assistants maintained COVID-19 protocols as per the local area guidelines. Study staff were vaccinated, maintained appropriate social distancing, sanitized hands, and cleaned field tools after each household visit.Data analysisData were exported from ODK into Microsoft Excel for analysis. Basic descriptive statistics were performed to describe participant socio-demographics and experiences with usability, including if participants’ interpretation of color change matched that of study staff. Open-ended items about fluoride and fluorosis knowledge, attitudes, and behavior were grouped thematically and coded independently by two authors. Knowledge-related responses were characterized as “correct” if consistent with conventional biomedical understanding, “incorrect”, or unfamiliar.Tests were classified as ‘ON’ by the Kenya-based field team if they were visibly yellow after six hours, and ‘OFF’ if there was no observable color change by eye. These assessments were independently validated by the US-based team from photographs of the completed tests. Tests classified as ‘ON’ were marked true positive if they corresponded to a photometer measured fluoride concentration ≥1.5 ppm, and false positive if they corresponded to a photometer measured fluoride concentration More

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    Looking for massive carbon capture

    Smil, V. IEEE Spectrum 55, 72–75 (2018).Ritchie, H., Roser, M. & Rosado, P. CO2 and greenhouse gas emissions. Our World in Data (2020); https://go.nature.com/3iO9QSvHenry, A., Prasher, R. & Majumdar, A. Nat. Energy 5, 635–637 (2020).Article 
    CAS 

    Google Scholar 
    Caldera, U. & Breyer, C. Nat. Sustain. https://doi.org/10.1038/s41893-022-01056-7 (2023).Article 

    Google Scholar 
    Bastin, J.-F. et al. Science 365, 76–79 (2019).Article 
    CAS 

    Google Scholar 
    Child, M. et al. Renew. Energy 139, 80–101 (2019).Article 

    Google Scholar 
    Crippa, M. et al. CO2 emissions of all world countries (Joint Research Centre (European Commission), 2022); https://doi.org/10.2760/730164Urbina, A. in Sustainable Solar Electricity 131–155 (Springer Cham, 2022).Yu, H. F. et al. Sustainability 14, 8567 (2022).Article 

    Google Scholar 
    Caldera, U. & Breyer, C. Energy 200, 117507 (2020).Article 

    Google Scholar  More

  • in

    Afforesting arid land with renewable electricity and desalination to mitigate climate change

    Land area for afforestation with RE-based SWRO desalinationRestoration land37 and bare land areas22 with the following water stress conditions were determined to be areas where forests could grow if irrigated with a secure water supply. The projected water stress, water supply and demand data for the decade 2040 are used. The renewable water resources in these areas were not considered sufficient to sustain forest growth.

    Land nodes that lie in high (40%  More

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    Soil moisture-constrained East Asian Monsoon meridional patterns over China from observations

    Zhu, S. et al. Distinct impacts of spring soil moisture over the Indo-China Peninsula on summer precipitation in the Yangtze River basin under different SST backgrounds. Clim. Dyn. 56, 1895–1918 (2021).
    Google Scholar 
    Shi, P. et al. Significant land contributions to interannual predictability of East Asian summer monsoon rainfall. Earth’s Futur 9, 1–16 (2021).
    Google Scholar 
    Wu, G. et al. Thermal controls on the Asian summer monsoon. Sci. Rep. 2, 404 (2012).
    Google Scholar 
    Wei, W., Zhang, R., Wen, M., Rong, X. & Li, T. Impact of Indian summer monsoon on the South Asian High and its influence on summer rainfall over China. Clim. Dyn. 43, 1257–1269 (2014).
    Google Scholar 
    Wang, B., Xiang, B. & Lee, J. Y. Subtropical High predictability establishes a promising way for monsoon and tropical storm predictions. Proc. Natl Acad. Sci. USA 110, 2718–2722 (2013).
    Google Scholar 
    Kundzewicz, Z. W. et al. Climate variability and floods in China—a review. Earth-Sci. Rev. 211, 103434 (2020).
    Google Scholar 
    Wang, C., Yang, K., Li, Y., Wu, D. & Bo, Y. Impacts of spatiotemporal anomalies of Tibetan plateau snow cover on summer precipitation in Eastern China. J. Clim. 30, 885–903 (2017).
    Google Scholar 
    Ding, T. & Gao, H. Relationship between winter snow cover days in Northeast China and rainfall near the Yangtze river basin in the following summer. J. Meteorol. Res. 29, 400–411 (2015).
    Google Scholar 
    Kundzewicz, Z. W. et al. Flood risk and its reduction in China. Adv. Water Resour. 130, 37–45 (2019).
    Google Scholar 
    Jiang, T. et al. Each 0.5 °C of warming increases annual flood losses in China by more than US$60 billion. Bull. Am. Meteorol. Soc. 101, E1464–E1474 (2021).
    Google Scholar 
    Su, B. et al. Drought losses in China might double between the 1.5 °C and 2.0 °C warming. Proc. Natl Acad. Sci. USA 115, 10600–10605 (2018).
    Google Scholar 
    Li, Z., Sun, Y., Li, T., Ding, Y. & Hu, T. Future Changes in East Asian Summer Monsoon Circulation and Precipitation Under 1.5 to 5 °C of Warming. Earth’s Futur 7, 1391–1406 (2019).
    Google Scholar 
    Zhang, R. H. Natural and human-induced changes in summer climate over the East Asian Monsoon region in the last half century: a review. Adv. Clim. Chang. Res. 6, 131–140 (2015).
    Google Scholar 
    Almazroui, M. et al. Projected changes in climate extremes using CMIP6 simulations over SREX regions. Earth Syst. Environ. 5, 481–497 (2021).
    Google Scholar 
    Huang, J. J., Zhang, N., Choi, G., McBean, E. A. & Zhang, Q. Spatiotemporal patterns and trends of precipitation and their correlations with related meteorological factors by two sets of reanalysis data in China. Hydrol. Earth Syst. Sci. Discuss 5, 1–35 (2018).
    Google Scholar 
    Ha, K. J., Heo, K. Y., Lee, S. S., Yun, K. S. & Jhun, J. G. Variability in the East Asian Monsoon: a review. Meteorol. Appl. 19, 200–215 (2012).
    Google Scholar 
    Wang, P. X. et al. The global monsoon across time scales: Mechanisms and outstanding issues. Earth-Sci. Rev. 174, 84–121 (2017).
    Google Scholar 
    Wu, G. et al. The influence of mechanical and thermal forcing by the Tibetan Plateau on Asian climate. J. Hydrometeorol. 8, 770–789 (2007).
    Google Scholar 
    Abe, M., Hori, M., Yasunari, T. & Kitoh, A. Effects of the Tibetan Plateau on the onsetof the summer monsoon in South Asia: The role of the air-sea interaction. J. Geophys. Res. Atmos. 118, 1760–1776 (2013).
    Google Scholar 
    Abbas, A., Waseem, M., Ullah, W., Zhao, C. & Zhu, J. Spatiotemporal analysis of meteorological and hydrological droughts and their propagations. Water 13, 2237 (2021).
    Google Scholar 
    Zhu, C., Lee, W. S., Kang, H. & Park, C. K. A proper monsoon index for seasonal and interannual variations of the East Asian Monsoon. Geophys. Res. Lett. 32, 1–5 (2005).
    Google Scholar 
    Wu, L. & Zhang, J. The relationship between spring soil moisture and summer hot extremes over North China. Adv. Atmos. Sci. 32, 1660–1668 (2015).
    Google Scholar 
    Gao, C. et al. Land–atmosphere interaction over the Indo-China Peninsula during spring and its effect on the following summer climate over the Yangtze River basin. Clim. Dyn. 53, 6181–6198 (2019).
    Google Scholar 
    Wang, B. & Fan, Z. Choice of South Asian summer monsoon indices. Bull. Am. Meteorol. Soc. 80, 629–638 (1999).
    Google Scholar 
    Lv, A., Qu, B., Jia, S. & Zhu, W. Influence of three phases of El Niño-Southern Oscillation on daily precipitation regimes in China. Hydrol. Earth Syst. Sci. 23, 883–896 (2019).
    Google Scholar 
    Wu, Z., Li, J., Jiang, Z. & Ma, T. Modulation of the Tibetan Plateau snow cover on the ENSO teleconnections: from the East Asian summer monsoon perspective. J. Clim. 25, 2481–2489 (2012).
    Google Scholar 
    Liu, D., Wang, G., Mei, R., Yu, Z. & Yu, M. Impact of initial soil moisture anomalies on climate mean and extremes over Asia. J. Geophys. Res. 119, 529–545 (2014).
    Google Scholar 
    Ullah, W. et al. Observed linkage between Tibetan plateau soil moisture and South Asian summer precipitation and the possible mechanism. J. Clim. 34, 361–377 (2021).
    Google Scholar 
    Koster, R. D., Chang, Y., Wang, H. & Schubert, S. D. Impacts of local soil moisture anomalies on the atmospheric circulation and on remote surface meteorological fields during boreal summer: a comprehensive analysis over North America. J. Clim. 29, 7345–7364 (2016).
    Google Scholar 
    Seneviratne, S. I. et al. Investigating soil moisture-climate interactions in a changing climate: a review. Earth-Sci. Rev. 99, 125–161 (2010).
    Google Scholar 
    Mei, R. & Wang, G. Impact of sea surface temperature and soil moisture on summer precipitation in the united states based on observational data. J. Hydrometeorol. 12, 1086–1099 (2011).
    Google Scholar 
    Alessandri, A. & Navarra, A. On the coupling between vegetation and rainfall inter-annual anomalies: possible contributions to seasonal rainfall predictability over land areas. Geophys. Res. Lett. 35, 1–6 (2008).
    Google Scholar 
    Dorigo, W. et al. ESA CCI soil moisture for improved Earth system understanding: state-of-the art and future directions. Remote Sens. Environ. 203, 185–215 (2017).
    Google Scholar 
    Santanello, J. A. et al. Land-atmosphere interactions the LoCo perspective. Bull. Am. Meteorol. Soc. 99, 1253–1272 (2018).
    Google Scholar 
    Rasmijn, L. M. et al. Future equivalent of 2010 Russian heatwave intensified by weakening soil moisture constraints. Nat. Clim. Chang. 8, 381–385 (2018).
    Google Scholar 
    Denissen, J. M. C. et al. Soil moisture signature in global weather balloon soundings. npj Clim. Atmos. Sci. 4, 13 (2021).
    Google Scholar 
    Lau, W. K. M. & Kim, K. M. The 2010 Pakistan flood and Russian heat wave: teleconnection of hydrometeorological extremes. J. Hydrometeorol. 13, 392–403 (2012).
    Google Scholar 
    Mann, M. E. et al. Influence of anthropogenic climate change on planetary wave resonance and extreme weather events. Sci. Rep. 7, 12 (2017).
    Google Scholar 
    Miralles, D. G., Teuling, A. J., Van Heerwaarden, C. C. & De Arellano, J. V. G. Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nat. Geosci. 7, 345–349 (2014).
    Google Scholar 
    Dong, X., Zhou, Y., Chen, H., Zhou, B. & Sun, S. Lag impacts of the anomalous July soil moisture over Southern China on the August rainfall over the Huang–Huai River Basin. Clim. Dyn. 58, 1737–1754 (2022).
    Google Scholar 
    Bao, Q., Liu, Y., Shi, J. & Wu, G. Comparisons of soil moisture datasets over the Tibetan Plateau and application to the simulation of Asia summer monsoon onset. Adv. Atmos. Sci. 27, 303–314 (2010).
    Google Scholar 
    Meng, X. et al. Detecting hydrological consistency between soil moisture and precipitation and changes of soil moisture in summer over the Tibetan Plateau. Clim. Dyn. 51, 4157–4168 (2018).
    Google Scholar 
    Wei, J. & Dirmeyer, P. A. Sensitivity of land precipitation to surface evapotranspiration: a nonlocal perspective based on water vapor transport. Geophys. Res. Lett. 46, 12588–12597 (2019).
    Google Scholar 
    Wei, J. & Dirmeyer, P. A. Dissecting soil moisture-precipitation coupling. Geophys. Res. Lett. 39, 1–6 (2012).
    Google Scholar 
    Kim, Y. & Wang, G. Soil moisture-vegetation-precipitation feedback over North America: its sensitivity to soil moisture climatology. J. Geophys. Res. Atmos. 117, 1–18 (2012).
    Google Scholar 
    Ullah, W., Wang, G., Gao, Z., Hagan, D. F. T. & Lou, D. Comparisons of remote sensing and reanalysis soil moisture products over the Tibetan Plateau, China. Cold Reg. Sci. Technol. 146, 110–121 (2018).
    Google Scholar 
    Samuel, J., Coulibaly, P., Dumedah, G. & Moradkhani, H. Assessing model state and forecasts variation in hydrologic data assimilation. J. Hydrol. 513, 127–141 (2014).
    Google Scholar 
    Koster, R. D. et al. Regions of strong coupling between soil moisture and precipitation. Science 305, 1138–1140 (2004).
    Google Scholar 
    Navarra, A. & Tribbia, J. The coupled manifold. J. Atmos. Sci. 62, 310–330 (2005).
    Google Scholar 
    Kottek, M., Grieser, J., Beck, C., Rudolf, B. & Rubel, F. World map of the Köppen–Geiger climate classification updated. Meteorol. Z. 15, 259–263 (2006).
    Google Scholar 
    Liu, B. et al. Asian summer monsoon onset barrier and its formation mechanism. Clim. Dyn. 45, 711–726 (2015).
    Google Scholar 
    Liu, B., Wu, G., Mao, J. & He, J. Genesis of the South Asian high and its impact on the Asian summer monsoon onset. J. Clim. 26, 2976–2991 (2013).
    Google Scholar 
    Li, J. et al. How to measure the strength of the East Asian Summer monsoon. J. Clim. 21, 4449–4463 (2008).
    Google Scholar 
    Wang, B., LinHo, Zhang, Y. & Lu, M. M. Definition of South China Sea monsoon onset and commencement of the East Asian summer monsoon. J. Clim. 17, 699–710 (2004).
    Google Scholar 
    Xing, N., Li, J. & Wang, L. Effect of the early and late onset of summer monsoon over the Bay of Bengal on Asian precipitation in May. Clim. Dyn. 47, 1961–1970 (2016).
    Google Scholar 
    Khan, A. A. et al. Spatial and temporal analysis of rainfall and drought condition in Southwest Xinjiang in Northwest China, using various climate indices. Earth Syst. Environ. 5, 201–216 (2021).
    Google Scholar 
    Zhang, Z., Sun, X. & Yang, X.-Q. Understanding the interdecadal variability of East Asian summer monsoon precipitation: joint influence of three oceanic signals. J. Clim. 31, 5485–5506 (2018).
    Google Scholar 
    Liu, L., Zhang, R. & Zuo, Z. Effect of spring precipitation on summer precipitation in Eastern China: role of soil moisture. J. Clim. 30, 9183–9194 (2017).
    Google Scholar 
    Chahine, M. T. The hydrological cycle and its influence on climate. Nature 359, 373–380 (1992).
    Google Scholar 
    Zhang, R. & Zuo, Z. Impact of spring soil moisture on surface energy balance and summer monsoon circulation over East Asia and precipitation in East China. J. Clim. 24, 3309–3322 (2011).
    Google Scholar 
    Berg, A., Lintner, B., Findell, K. & Giannini, A. Soil moisture influence on seasonality and large-scale circulation in simulations of the West African monsoon. J. Clim. 30, 2295–2317 (2017).
    Google Scholar 
    Taylor, C. M. et al. New perspectives on land-atmosphere feedbacks from the African monsoon multidisciplinary analysis. Atmos. Sci. Lett. 12, 38–44 (2011).
    Google Scholar 
    Zuo, Z. & Zhang, R. Influence of soil moisture in eastern China on the East Asian summer monsoon. Adv. Atmos. Sci. 33, 151–163 (2016).
    Google Scholar 
    Yang, K., Wang, C. & Bao, H. Contribution of soil moisture variability to summer precipitation in the northern hemisphere. J. Geophys. Res. 121, 12,108–12,214 (2016).
    Google Scholar 
    Min, J., Guo, Y. & Wang, G. Impacts of soil moisture on typical frontal rainstorm in Yangtze River Basin. Atmosphere 7, 0–24 (2016).
    Google Scholar 
    Zhu, B., Xie, X., Meng, S., Lu, C. & Yao, Y. Sensitivity of soil moisture to precipitation and temperature over China: present state and future projection. Sci. Total Environ. 705, 135774 (2020).
    Google Scholar 
    Cheng, S., Guan, X., Huang, J., Ji, F. & Guo, R. Long-term trend and variability of soil moisture over East Asia. J. Geophys. Res. 120, 8658–8670 (2015).
    Google Scholar 
    AbdelRahman, M. A. E. & Arafat, S. M. An approach of agricultural courses for soil conservation based on crop soil suitability using geomatics. Earth Syst. Environ. 4, 273–285 (2020).
    Google Scholar 
    Liu, Y. et al. Agriculture intensifies soil moisture decline in Northern China. Sci. Rep. 5, 11261 (2015).
    Google Scholar 
    Yuan, Q. et al. Coupling of soil moisture and air temperature from multiyear data during 1980–2013 over china. Atmosphere 11, 0–14 (2020).
    Google Scholar 
    Xu, Z., Chen, H., Guo, J. & Zhang, W. Contrasting effect of soil moisture on the daytime boundary layer under different thermodynamic conditions in summer over China. Geophys. Res. Lett. 48, 1–11 (2021).
    Google Scholar 
    Xia, K., Li, L., Tang, Y. & Wang, B. Impact of soil freezing-thawing processes on August rainfall over Southern China. J. Geophys. Res. Atmos. 127, 1–16 (2022).
    Google Scholar 
    Gu, X. et al. Extreme precipitation in China: a review on statistical methods and applications. Adv. Water Resour. 163, 104144 (2022).
    Google Scholar 
    Karthikeyan, L., Pan, M., Wanders, N., Kumar, D. N. & Wood, E. F. Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons. Adv. Water Resour. 109, 236–252 (2017).
    Google Scholar 
    Yuan, Z., Yang, Z., Yan, D. & Yin, J. Historical changes and future projection of extreme precipitation in China. Theor. Appl. Climatol. 127, 393–407 (2017).
    Google Scholar 
    Ren, Z. et al. Changes in daily extreme precipitation events in South China from 1961 to 2011. J. Geogr. Sci. 25, 58–68 (2015).
    Google Scholar 
    Dorigo, W. A. et al. Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sens. Environ. 162, 380–395 (2015).
    Google Scholar 
    Wang, G., Garcia, D., Liu, Y., de Jeu, R. & Dolman, A. J. A three-dimensional gap filling method for large geophysical datasets: application to global satellite soil moisture observations. Environ. Model. Softw. 30, 139–142 (2012).
    Google Scholar 
    Hersbach, H. et al. Global reanalysis: goodbye ERA-Interim, hello ERA5. ECMWF Newsl. 17–24 (2019).Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).
    Google Scholar 
    Hagan, D. F. T., Parinussa, R. M., Wang, G. & Draper, C. S. An evaluation of soil moisture anomalies from global model-based datasets over the People’s Republic of China. Water 12, 1–15 (2020).
    Google Scholar 
    Richman, M. B. & Vermette, S. J. The use of procrustes target analysis to discriminate dominant source regions of fine sulfur in the western USA. Atmos. Environ. Part A. Gen. Top. 27, 475–481 (1993).
    Google Scholar 
    Wang, G., Dolman, A. J. & Alessandri, A. A summer climate regime over Europe modulated by the North Atlantic Oscillation. Hydrol. Earth Syst. Sci. 15, 57–64 (2011).
    Google Scholar 
    Catalano, F., Alessandri, A., De Felice, M., Zhu, Z. & Myneni, R. B. Observationally based analysis of land-atmosphere coupling. Earth Syst. Dyn. 7, 251–266 (2016).
    Google Scholar 
    Hannachi, A. A primer for EOF analysis of climate data. (United Kingdom: Department of Meteorology, University of Reading, 2004).Lund, R. B., von Storch, H. & Zwiers, F. W. Statistical analysis in climate research. J. Am. Stat. Assoc. 95, 1375 (2000).
    Google Scholar 
    Preisendorfer, R. W. Principal Component Analysis in Meteorology and Oceanography XVIII, 425 (Elsevier; Distributors for the U.S. and Canada, Elsevier Science Pub. Co., 1988).Krishnamurti, T. N. Tropical East-West circulations during the Northern summer. J. Atmos. Sci. 28, 1342–1347 (1971).
    Google Scholar 
    Mancuso, R. L. A numerical procedure for computing fields of stream function and velocity potential. J. Appl. Meteorol. 6, 994–1001 (1967).
    Google Scholar 
    Kulkarni, P. L., Mitra, A. K., Narkhedkar, S. G., Bohra, A. K. & Rajamani, S. On the impact of divergent part of the wind computed from INSAT OLR data on global analysis and forecast fields. Meteorol. Atmos. Phys. 64, 61–82 (1997).
    Google Scholar 
    Wei, J., Su, H. & Yang, Z. L. Impact of moisture flux convergence and soil moisture on precipitation: a case study for the southern United States with implications for the globe. Clim. Dyn. 46, 467–481 (2016).
    Google Scholar 
    Pal, J. S. et al. Regional Climate Modeling for the Developing World: The ICTP RegCM3 and RegCNET. Bull. Am. Meteorol. Soc. 88, 1395–1410 (2007).
    Google Scholar 
    Dickinson, R. E., Henderson-Sellers, A. & Kennedy, P. J. Biosphere-atmosphere Transfer Scheme (BATS) Version 1e as Coupled to the NCAR Community Climate Model (No. NCAR/TN-387+STR). (University Corporation for Atmospheric Research, 1993). https://doi.org/10.5065/D67W6959.Emanuel, K. A. A scheme for representing cumulus convection in large-scale models. J. Atmos. Sci. 48, 2313–2329 (1991).
    Google Scholar 
    Pal, J. S., Small, E. E. & Eltahir, E. A. B. Simulation of regional-scale water and energy budgets: representation of subgrid cloud and precipitation processes within RegCM. J. Geophys. Res. Atmos. 105, 29579–29594 (2000).
    Google Scholar 
    Dirmeyer, P. A., Zeng, F. J., Ducharne, A., Morrill, J. C. & Koster, R. D. The sensitivity of surface fluxes to soil water content in three land surface schemes. J. Hydrometeorol. 1, 121–134 (2000).
    Google Scholar 
    Wei, J., Dickinson, R. E. & Chen, H. A negative soil moisture–precipitation relationship and its causes. J. Hydrometeorol. 9, 1364–1376 (2008).
    Google Scholar 
    Bisselink, B., van Meijgaard, E., Dolman, A. J. & de Jeu, R. A. M. Initializing a regional climate model with satellite-derived soil moisture. J. Geophys. Res. Atmos. 116, 1–13 (2011).Yang, K. & Wang, C. Seasonal persistence of soil moisture anomalies related to freeze–thaw over the Tibetan Plateau and prediction signal of summer precipitation in eastern China. Clim. Dyn. 53, 2411–2424 (2019).
    Google Scholar 
    Dickinson, R. E., Errico, R. M., Giorgi, F. & Bates, G. T. A regional climate model for the western United States. Clim. Change 15, 383–422 (1989).
    Google Scholar 
    Taylor, K. E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. Atmos. 106, 7183–7192 (2001).
    Google Scholar  More

  • in

    Caravan – A global community dataset for large-sample hydrology

    Goodrich, D. et al. The usda-ars experimental watershed network: Evolution, lessons learned, societal benefits, and moving forward. Water Resources Research 57, e2019WR026473 (2021).Article 
    ADS 

    Google Scholar 
    Likens, G. E. The watershed-ecosystem approach. Hydrological Processes 35, e13977, https://doi.org/10.1002/hyp.13977 (2021).Article 

    Google Scholar 
    Goodman, K. J., Parker, S. M., Edmonds, J. W. & Zeglin, L. H. Expanding the scale of aquatic sciences: the role of the national ecological observatory network (neon). Freshwater Science 34, 377–385 (2015).Article 

    Google Scholar 
    Kovács, G. Proposal to construct a coordinating matrix for comparative hydrology. Hydrological Sciences Journal 29, 435–443 (1984).Article 

    Google Scholar 
    Falkenmark, M. & Chapman, T. Comparative hydrology: An ecological approach to land and water resources (Unesco, 1989).Andreassian, V., Hall, A., Chahinian, N. & Schaake, J. Introduction and synthesis: Why should hydrologists work on a large number of basin data sets? In Andreassian, V., Hall, A., Chahinian, N. & Schaake, J. (eds.) Large sample basin experiments for hydrological model parameterization: results of the model parameter experiment–MOPEX, vol. IAHS Publ. 307, 1–5 (Wallingford: IAHS Press, 2006).Blöschl, G. et al. Twenty-three unsolved problems in hydrology (uph)–a community perspective. Hydrological sciences journal 64, 1141–1158 (2019).Article 

    Google Scholar 
    Gupta, H. V. et al. Large-sample hydrology: a need to balance depth with breadth. Hydrology and Earth System Sciences 18, 463–477 (2014).Article 
    ADS 

    Google Scholar 
    Stahl, K. et al. Streamflow trends in europe: evidence from a dataset of near-natural catchments. Hydrology and Earth System Sciences 14, 2367–2382, https://doi.org/10.5194/hess-14-2367-2010 (2010).Article 
    ADS 

    Google Scholar 
    Gudmundsson, L., Seneviratne, S. I. & Zhang, X. Anthropogenic climate change detected in european renewable freshwater resources. Nature Climate Change 7, 813–816 (2017).Article 
    ADS 

    Google Scholar 
    Gudmundsson, L., Leonard, M., Do, H. X., Westra, S. & Seneviratne, S. I. Observed trends in global indicators of mean and extreme streamflow. Geophysical Research Letters 46, 756–766, https://doi.org/10.1029/2018GL079725 (2019).Article 
    ADS 

    Google Scholar 
    Gudmundsson, L. et al. Globally observed trends in mean and extreme river flow attributed to climate change. Science 371, 1159–1162, https://doi.org/10.1126/science.aba3996 (2021).Article 
    ADS 
    CAS 

    Google Scholar 
    Kratzert, F. et al. Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets. Hydrology and Earth System Sciences 23, 5089–5110, https://doi.org/10.5194/hess-23-5089-2019 (2019).Article 
    ADS 

    Google Scholar 
    Kratzert, F. et al. Toward improved predictions in ungauged basins: Exploiting the power of machine learning. Water Resources Research 55, 11344–11354, https://doi.org/10.1029/2019WR026065 (2019).Article 
    ADS 

    Google Scholar 
    Ghiggi, G., Humphrey, V., Seneviratne, S. I. & Gudmundsson, L. Grun: an observation-based global gridded runoff dataset from 1902 to 2014. Earth System Science Data 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019 (2019).Article 
    ADS 

    Google Scholar 
    Ghiggi, G., Humphrey, V., Seneviratne, S. I. & Gudmundsson, L. G-run ensemble: A multi-forcing observation-based global runoff reanalysis. Water Resources Research 57, e2020WR028787, https://doi.org/10.1029/2020WR028787 (2021).Article 
    ADS 

    Google Scholar 
    Addor, N. et al. Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges. Hydrological Sciences Journal 65, 712–725 (2020).Article 
    CAS 

    Google Scholar 
    Schaake, J., Cong, S. & Duan, Q. The US MOPEX data set. In Andreassian, V., Hall, A., Chahinian, N. & Schaake, J. (eds.) Large sample basin experiments for hydrological model parameterization: results of the model parameter experiment–MOPEX, vol. IAHS Publ. 307, 9–28 (Wallingford: IAHS Press, 2006).Fowler, K. J., Acharya, S. C., Addor, N., Chou, C. & Peel, M. C. CAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in australia. Earth System Science Data 13, 3847–3867 (2021).Article 
    ADS 

    Google Scholar 
    Klingler, C., Schulz, K. & Herrnegger, M. LamaH-CE: Large-sample data for hydrology and environmental sciences for central europe. Earth System Science Data 13, 4529–4565 (2021).Article 
    ADS 

    Google Scholar 
    Chagas, V. B. et al. CAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in brazil. Earth System Science Data 12, 2075–2096 (2020).Article 
    ADS 

    Google Scholar 
    Arsenault, R. et al. A comprehensive, multisource database for hydrometeorological modeling of 14,425 north american watersheds. Scientific Data 7, 1–12 (2020).Article 

    Google Scholar 
    Hao, Z. et al. CCAM: China catchment attributes and meteorology dataset. Earth System Science Data 13, 5591–5616 (2021).Article 
    ADS 

    Google Scholar 
    Alvarez-Garreton, C. et al. The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies–chile dataset. Hydrology and Earth System Sciences 22, 5817–5846 (2018).Article 
    ADS 

    Google Scholar 
    Kuentz, A., Arheimer, B., Hundecha, Y. & Wagener, T. Understanding hydrologic variability across europe through catchment classification. Hydrology and Earth System Sciences 21, 2863–2879 (2017).Article 
    ADS 

    Google Scholar 
    Coxon, G. et al. CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in great britain. Earth System Science Data 12, 2459–2483 (2020).Article 
    ADS 

    Google Scholar 
    Newman, A. et al. Development of a large-sample watershed-scale hydrometeorological data set for the contiguous usa: data set characteristics and assessment of regional variability in hydrologic model performance. Hydrology and Earth System Sciences 19, 209–223 (2015).Article 
    ADS 

    Google Scholar 
    Addor, N., Newman, A. J., Mizukami, N. & Clark, M. P. The CAMELS data set: catchment attributes and meteorology for large-sample studies. Hydrology and Earth System Sciences 21, 5293–5313 (2017).Article 
    ADS 

    Google Scholar 
    Do, H. X., Gudmundsson, L., Leonard, M. & Westra, S. The global streamflow indices and metadata archive (gsim)–part 1: The production of a daily streamflow archive and metadata. Earth System Science Data 10, 765–785 (2018).Article 
    ADS 

    Google Scholar 
    Gudmundsson, L., Do, H. X., Leonard, M. & Westra, S. The global streamflow indices and metadata archive (GSIM)–part 2: Quality control, time-series indices and homogeneity assessment. Earth System Science Data 10, 787–804 (2018).Article 
    ADS 

    Google Scholar 
    Linke, S. et al. Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution. Scientific data 6, 1–15, https://doi.org/10.1038/s41597-019-0300-6 (2019).Article 
    ADS 

    Google Scholar 
    Beck, H. E. et al. Global-scale regionalization of hydrologic model parameters. Water Resources Research 52, 3599–3622 (2016).Article 
    ADS 

    Google Scholar 
    Beck, H. E. et al. Global fully distributed parameter regionalization based on observed streamflow from 4,229 headwater catchments. Journal of Geophysical Research: Atmospheres 125, e2019JD031485 (2020).ADS 

    Google Scholar 
    Blöschl, G. et al. Changing climate both increases and decreases european river floods. Nature 573, 108–111 (2019).Article 
    ADS 

    Google Scholar 
    Wilkinson, M. D. et al. The fair guiding principles for scientific data management and stewardship. Scientific data 3, 1–9 (2016).Article 

    Google Scholar 
    Metzger, M. J. et al. A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring. Global Ecology and Biogeography 22, 630–638 (2013).Article 

    Google Scholar 
    Muñoz-Sabater, J. et al. Era5-land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data 13, 4349–4383 (2021).Article 
    ADS 

    Google Scholar 
    Lehner, B. Hydroatlas version 1.0 data download. Figshare https://doi.org/10.6084/m9.figshare.9890531.v1 (2022).Gorelick, N. et al. Google earth engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment https://doi.org/10.1016/j.rse.2017.06.031 (2017).Article 

    Google Scholar 
    Kratzert, F. et al. Caravan – A global community dataset for large-sample hydrology (Version 1.0), Zenodo, https://doi.org/10.5281/ZENODO.7540792 (2022).Muñoz Sabater, J. et al. Era5-land hourly data from 1981 to present. ECMWF https://doi.org/10.24381/cds.e2161bac (2021).Lehner, B., Linke, S. & Thieme, M. Hydroatlas version 1.0. Figshare https://doi.org/10.6084/m9.figshare.9890531.v1 (2019).Fowler, K., Acharya, S. C., Addor, N., Chou, C. & Peel, M. CAMELS-AUS v1: Hydrometeorological time series and landscape attributes for 222 catchments in australia. PANGAEA https://doi.org/10.1594/PANGAEA.921850 (2020).Chagas, V. B. P. et al. CAMELS-BR: Hydrometeorological time series and landscape attributes for 897 catchments in brazil. Zenodo https://doi.org/10.5281/zenodo.3964745 (2020).Alvarez-Garreton, C. et al. The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – chile dataset. PANGAEA https://doi.org/10.1594/PANGAEA.894885 (2018).Coxon, G. et al. Catchment attributes and hydro-meteorological timeseries for 671 catchments across great britain (CAMELS-GB). NERC Environmental Information Data Centre https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9 (2020).Klingler, C., Kratzert, F., Schulz, K. & Herrnegger, M. LamaH-CE: Large-sample data for hydrology and environmental sciences for central europe. Zenodo https://doi.org/10.5281/zenodo.5153305 (2021).Newman, A. et al. A large-sample watershed-scale hydrometeorological dataset for the contiguous usa. UCAR/NCAR – GDEX https://doi.org/10.5065/D6MW2F4D (2014).McMillan, H. K., Westerberg, I. K. & Krueger, T. Hydrological data uncertainty and its implications. Wiley Interdisciplinary Reviews: Water 5, e1319 (2018).
    Google Scholar 
    Beven, K. Facets of uncertainty: epistemic uncertainty, non-stationarity, likelihood, hypothesis testing, and communication. Hydrological Sciences Journal 61, 1652–1665 (2016).Article 

    Google Scholar 
    Colliander, A. et al. Validation of smap surface soil moisture products with core validation sites. Remote Sensing of Environment 191, 215–231 (2017).Article 
    ADS 

    Google Scholar 
    Habib, E. & Krajewski, W. F. Uncertainty analysis of the trmm ground-validation radar-rainfall products: Application to the teflun-b field campaign. Journal of applied meteorology 41, 558–572 (2002).Article 
    ADS 

    Google Scholar 
    Kumar, S. V., Dirmeyer, P. A., Peters-Lidard, C. D., Bindlish, R. & Bolten, J. Information theoretic evaluation of satellite soil moisture retrievals. Remote Sensing of Environment 204, 392–400 (2018).Article 
    ADS 

    Google Scholar 
    Nearing, G. S. et al. Nonparametric triple collocation. Water Resources Research 53, 5516–5530 (2017).Article 
    ADS 

    Google Scholar 
    Alemohammad, S. H., McColl, K. A., Konings, A. G., Entekhabi, D. & Stoffelen, A. Characterization of precipitation product errors across the united states using multiplicative triple collocation. Hydrology and Earth System Sciences 19, 3489–3503 (2015).Article 
    ADS 

    Google Scholar 
    McMillan, H., Jackson, B., Clark, M., Kavetski, D. & Woods, R. Rainfall uncertainty in hydrological modelling: An evaluation of multiplicative error models. Journal of Hydrology 400, 83–94 (2011).Article 
    ADS 

    Google Scholar 
    Domeneghetti, A., Castellarin, A. & Brath, A. Assessing rating-curve uncertainty and its effects on hydraulic model calibration. Hydrology and Earth System Sciences 16, 1191–1202 (2012).Article 
    ADS 

    Google Scholar 
    Koch, J. Caravan extension Denmark – Danish dataset for large-sample hydrology. Zenodo https://doi.org/10.5281/zenodo.6762361 (2022).Knoben, W. J. M., Woods, R. A. & Freer, J. E. A quantitative hydrological climate classification evaluated with independent streamflow data. Water Resources Research 54, 5088–5109, https://doi.org/10.1029/2018WR022913 (2018).Article 
    ADS 

    Google Scholar  More

  • in

    Global water resources and the role of groundwater in a resilient water future

    Vorosmarty, C. J. et al. Global threats to human water security and river biodiversity. Nature 467, 555–561 (2010).Article 

    Google Scholar 
    Doell, P., Mueller Schmied, H., Schuh, C., Portmann, F. T. & Eicker, A. Global-scale assessment of groundwater depletion and related groundwater abstractions: combining hydrological modeling with information from well observations and GRACE satellites. Water Resour. Res. 50, 5698–5720 (2014).Article 

    Google Scholar 
    Wada, Y. et al. Global depletion of groundwater resources. Geophys. Res. Lett. 37, L20402 (2010).Article 

    Google Scholar 
    Douville, H. et al. in Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) 1055–1210 (IPCC, Cambridge Univ. Press, 2021).Olivier, D. W. & Xu, Y. X. Making effective use of groundwater to avoid another water supply crisis in Cape Town, South Africa. Hydrogeol. J. 27, 823–826 (2019).Article 

    Google Scholar 
    Ozment, S. et al. Natural infrastructure in Sao Paulo’s water system. World Resources Institute Report 2013–2014: Interim Findings (2018).Pascale, S., Kapnick, S. B., Delworth, T. L. & Cooke, W. F. Increasing risk of another Cape Town ‘Day Zero’ drought in the 21st century. Proc. Natl Acad. Sci. USA 117, 29495 (2020).Article 

    Google Scholar 
    Alley, W. M., Reilly, T. E. & Franke, O. L. Sustainability of ground-water resources. US Geological Survey Circular 1186 (1999).Wada, Y. & Bierkens, M. F. P. Sustainability of global water use: past reconstruction and future projections. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/9/10/104003 (2014).Article 

    Google Scholar 
    Breslin, S. COP26 has 4 goals. Water is central to all of them. SIWI News https://siwi.org/latest/cop26-has-4-goals-water-is-central-to-all-of-them/ (2021).Global Risks 2021 16th edition (World Economic Forum, 2021); https://www.weforum.org/reports/the-global-risks-report-2021/The Water Challenge: The Roundtable on Water Financing (OECD, 2022); https://www.oecd.org/water/roundtable-on-financing-water.htmThe United Nations World Water Development Report 2018: Nature-Based Solutions for Water (United Nations World Water Assessment Program/UNESCO, 2018).Browder, G., Ozment, S., Rehberger-Bescos, I., Gartner, T. & Lange, G. M. Integrating Green and Gray: Creating Next Generation Infrastructure (World Bank and World Resources Institute, 2019); https://openknowledge.worldbank.org/handle/10986/31430Making Every Drop Count: Agenda for Water Action (High Level Panel on Water, United Nations and World Bank, 2018).Lederer, E. M. Next UN assembly president warns world in dangerous crisis. Washington Post https://www.washingtonpost.com/world/next-un-assembly-president-warns-world-in-dangerous-crisis/2022/06/07/55075dce-e6b6-11ec-a422-11bbb91db30b_story.html (7 June 2022).Tapley, B. D. et al. Contributions of GRACE to understanding climate change. Nat. Clim. Change 9, 358–369 (2019).Article 

    Google Scholar 
    Mekonnen, M. M. & Hoekstra, A. Y. Blue water footprint linked to national consumption and international trade is unsustainable. Nat. Food 1, 792–800 (2020).Article 

    Google Scholar 
    Rodell, M. et al. Emerging trends in global freshwater availability. Nature 557, 651–659 (2018).Article 

    Google Scholar 
    Save, H., Bettadpur, S. & Tapley, B. D. High-resolution CSR GRACE RL05 mascons. J. Geophys. Res. Solid Earth 121, 7547–7569 (2016).Article 

    Google Scholar 
    Tapley, B. D., Bettadpur, S., Watkins, M. & Reigber, C. The Gravity Recovery And Climate Experiment: mission overview and early results. Geophys. Res. Lett. https://doi.org/10.1029/2004gl019920 (2004).Article 

    Google Scholar 
    Richey, A. S. et al. Quantifying renewable groundwater stress with GRACE. Water Resour. Res. 51, 5217–5238 (2015).Article 

    Google Scholar 
    Shamsudduha, M. & Taylor, R. G. Groundwater storage dynamics in the world’s large aquifer systems from GRACE: uncertainty and role of extreme precipitation. Earth Syst. Dyn. 11, 755–774 (2020).Article 

    Google Scholar 
    Vishwakarma, B. D., Bates, P., Sneeuw, N., Westaway, R. M. & Bamber, J. L. Re-assessing global water storage trends from GRACE time series. Environ. Res. Lett. 16, 034005 (2021).Article 

    Google Scholar 
    Pekel, J. F., Cottam, A., Gorelick, N. & Belward, A. S. High-resolution mapping of global surface water and its long-term changes. Nature 540, 418–436 (2016).Article 

    Google Scholar 
    Lehner, B. et al. High-resolution mapping of the world’s reservoirs and dams for sustainable river-flow management. Front. Ecol. Environ. 9, 494–502 (2011).Article 

    Google Scholar 
    Scanlon, B. R. et al. Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data. Proc. Natl Acad. Sci. USA 115, E1080–E1089 (2018).Article 

    Google Scholar 
    MacDonald, A. M. et al. Mapping groundwater recharge in Africa from ground observations and implications for water security. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/abd661 (2021).Article 

    Google Scholar 
    Konikow, L. F. Overestimated water storage. Nat. Geosci. 6, 3 (2013).Article 

    Google Scholar 
    Konikow, L. F. Contribution of global groundwater depletion since 1900 to sea-level rise. Geophys. Res. Lett. https://doi.org/10.1029/2011gl048604 (2011).Article 

    Google Scholar 
    Pokhrel, Y. N. et al. Model estimates of sea-level change due to anthropogenic impacts on terrestrial water storage. Nat. Geosci. 5, 389–392 (2012).Article 

    Google Scholar 
    de Graaf, I. E. M. et al. A global-scale two-layer transient groundwater model: development and application to groundwater depletion. Adv. Water Resour. 102, 53–67 (2017).Article 

    Google Scholar 
    Rateb, A. et al. Comparison of groundwater storage changes from GRACE satellites with monitoring and modeling of major U.S. aquifers. Water Resour. Res. https://doi.org/10.1029/2020WR027556 (2020).Article 

    Google Scholar 
    de Graaf, I. E. M., Gleeson, T., van Beek, L. P. H., Sutanudjaja, E. H. & Bierkens, M. F. P. Environmental flow limits to global groundwater pumping. Nature 574, 90–94 (2019).Article 

    Google Scholar 
    Sophocleous, M. From safe yield to sustainable development of water resources — the Kansas experience. J. Hydrol. 235, 27–43 (2000).Article 

    Google Scholar 
    Konikow, L. F. & Bredehoeft, J. D. Groundwater Resource Development: Effects and Sustainability (USGS Groundwater Project, 2020).MacAllister, D. J., Krishan, G., Basharat, M., Cuba, D. & MacDonald, A. M. A century of groundwater accumulation in Pakistan and northwest India. Nat. Geosci. https://doi.org/10.1038/s41561-022-00926-1 (2022).Article 

    Google Scholar 
    Scanlon, B. R. et al. Effects of climate and irrigation on GRACE-based estimates of water storage changes in major US aquifers. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/ac16ff (2021).Article 

    Google Scholar 
    McGuire, V. L. Water-Level and Recoverable Water In Storage Changes, High Plains Aquifer, Predevelopment to 2015 and 2013–15. US Geological Survey Scientific Investigations Report 2017–5040 (2017); https://doi.org/10.3133/sir20175040Faunt, C. C. Groundwater availability of the Central Valley Aquifer, California. US Geol. Surv. Prof. Pap. 1766 (2009).Vorosmarty, C. J., Green, P., Salisbury, J. & Lammers, R. B. Global water resources: vulnerability from climate change and population growth. Science 289, 284–288 (2000).Article 

    Google Scholar 
    Mekonnen, M. M. & Hoekstra, A. Y. Four billion people facing severe water scarcity. Sci. Adv. https://doi.org/10.1126/sciadv.1500323 (2016).Article 

    Google Scholar 
    Vorosmarty, C. J. & Sahagian, D. Anthropogenic disturbance of the terrestrial water cycle. Bioscience 50, 753–765 (2000).Article 

    Google Scholar 
    Gronwall, J. & Danert, K. Regarding groundwater and drinking water access through a human rights lens: self-supply as a norm. Water https://doi.org/10.3390/w12020419 (2020).Article 

    Google Scholar 
    van Vliet, M. T. H. et al. Global water scarcity including surface water quality and expansions of clean water technologies. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/abbfc3 (2021).Article 

    Google Scholar 
    Podgorski, J. & Berg, M. Global threat of arsenic in groundwater. Science 368, 845–850 (2020).Article 

    Google Scholar 
    Yapiyev, V., Sagintayev, Z., Inglezakis, V. J., Samarkhanov, K. & Verhoef, A. Essentials of endorheic basins and lakes: a review in the context of current and future water resource management and mitigation activities in Central Asia. Water https://doi.org/10.3390/w9100798 (2017).Article 

    Google Scholar 
    Pauloo, R. A., Fogg, G. E., Guo, Z. L. & Harter, T. Anthropogenic basin closure and groundwater salinization (ABCSAL). J. Hydrol. https://doi.org/10.1016/j.jhydrol.2020.125787 (2021).Article 

    Google Scholar 
    Cao, T. Z., Han, D. M. & Song, X. F. Past, present, and future of global seawater intrusion research: a bibliometric analysis. J. Hydrol. https://doi.org/10.1016/j.jhydrol.2021.126844 (2021).Article 

    Google Scholar 
    Werner, A. D. et al. Seawater intrusion processes, investigation and management: recent advances and future challenges. Adv. Water Resour. 51, 3–26 (2013).Article 

    Google Scholar 
    Scanlon, B. R. et al. Linkages between GRACE water storage, hydrologic extremes, and climate teleconnections in major African aquifers. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/ac3bfc (2022).Article 

    Google Scholar 
    Held, I. M. & Soden, B. J. Robust responses of the hydrological cycle to global warming. J. Clim. 19, 5686–5699 (2006).Article 

    Google Scholar 
    Fan, X., Duan, Q. Y., Shen, C. P., Wu, Y. & Xing, C. Global surface air temperatures in CMIP6: historical performance and future changes. Environ. Res. Lett. 15, 104056 (2020).Article 

    Google Scholar 
    Tabari, H. Climate change impact on flood and extreme precipitation increases with water availability. Sci. Rep. https://doi.org/10.1038/s41598-020-70816-2 (2020).Article 

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

    Google Scholar 
    Arias, P. A. et al. in Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) 33−144 (IPCC, Cambridge Univ. Press, 2021).van Dijk, A. et al. The Millennium Drought in southeast Australia (2001–2009): natural and human causes and implications for water resources, ecosystems, economy, and society. Water Resour. Res. 49, 1040–1057 (2013).Article 

    Google Scholar 
    Scanlon, B. R. et al. Hydrologic implications of GRACE satellite data in the Colorado River Basin. Water Resour. Res. 51, 9891–9903 (2015).Article 

    Google Scholar 
    Rateb, A., Scanlon, B. R. & Kuo, C. Y. Multi-decadal assessment of water budget and hydrological extremes in the Tigris-Euphrates Basin using satellites, modeling, and in-situ data. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2020.144337 (2021).Article 

    Google Scholar 
    Anyamba, A., Glennie, E. & Small, J. Teleconnections and interannual transitions as observed in African vegetation: 2015–2017. Remote Sens. https://doi.org/10.3390/rs10071038 (2018).Article 

    Google Scholar 
    Ul Hassan, W. & Nayak, M. A. Global teleconnections in droughts caused by oceanic and atmospheric circulation patterns. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/abc9e2 (2021).Article 

    Google Scholar 
    Shen, Z. X. et al. Drying in the low-latitude Atlantic Ocean contributed to terrestrial water storage depletion across Eurasia. Nat. Commun. 13, 1849 (2022).Article 

    Google Scholar 
    Dettinger, M. D. Atmospheric rivers as drought busters on the US West Coast. J. Hydrometeorol. 14, 1721–1732 (2013).Article 

    Google Scholar 
    Taylor, R. G. et al. Ground water and climate change. Nat. Clim. Change 3, 322–329 (2013).Article 

    Google Scholar 
    Cuthbert, M. O. et al. Observed controls on resilience of groundwater to climate variability in sub-Saharan Africa. Nature 572, 230 (2019).Article 

    Google Scholar 
    Hugonnet, R. et al. Accelerated global glacier mass loss in the early twenty-first century. Nature 592, 726 (2021).Article 

    Google Scholar 
    Zhao, F., Long, D., Li, X., Huang, Q. & Han, P. Rapid glacier mass loss in the Southeastern Tibetan Plateau since the year 2000 from satellite observations. Remote. Sens. Environ. 270, 112853 (2022).Article 

    Google Scholar 
    Li, X. Y. et al. Climate change threatens terrestrial water storage over the Tibetan Plateau. Nat. Clim. Change https://doi.org/10.1038/s41558-022-01443-0 (2022).Article 

    Google Scholar 
    Yao, T. D. et al. The imbalance of the Asian water tower. Nat. Rev. Earth Environ. https://doi.org/10.1038/s43017-022-00299-4 (2022).Article 

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

    Google Scholar 
    Immerzeel, W. W. et al. Importance and vulnerability of the world’s water towers. Nature 577, 364 (2020).Article 

    Google Scholar 
    Dery, S. J. et al. Detection of runoff timing changes in pluvial, nival, and glacial rivers of western Canada. Water Resour. Res. https://doi.org/10.1029/2008wr006975 (2009).Article 

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

    Google Scholar 
    Dahlke, H. E. et al. in Advanced Tools for Integrated Water Resources Management Vol. 3 (eds Friesen, J. & Rodriguez-Sinobas, L.) 215–275 (Elsevier, 2018).Reddy, V. R., Pavelic, P. & Hanjra, M. A. Underground taming of floods for irrigation (UTFI) in the river basins of South Asia: institutionalising approaches and policies for sustainable water management and livelihood enhancement. Water Policy 20, 369–387 (2018).Article 

    Google Scholar 
    McDonald, R. I., Weber, K. F., Padowski, J., Boucher, T. & Shemie, D. Estimating watershed degradation over the last century and its impact on water-treatment costs for the world’s large cities. Proc. Natl Acad. Sci. USA 113, 9117–9122 (2016).Article 

    Google Scholar 
    The State of the World’s Forests 2020. Forests, Biodiversity, and People (FAO/UNEP, 2020).Convention on Wetlands. Global Wetland Outlook: Special Edition 2021 (Secretariat of the Convention on Wetlands, 2021).Scanlon, B. R., Jolly, I., Sophocleous, M. & Zhang, L. Global impacts of conversions from natural to agricultural ecosystems on water resources: quantity versus quality. Water Resour. Res. https://doi.org/10.1029/2006WR005486 (2007).Article 

    Google Scholar 
    Nosetto, M. D., Paez, R. A., Ballesteros, S. I. & Jobbagy, E. G. Higher water-table levels and flooding risk under grain vs. livestock production systems in the subhumid plains of the Pampas. Agric. Ecosyst. Environ. 206, 60–70 (2015).Article 

    Google Scholar 
    Favreau, G. et al. Land clearing, climate variability, and water resources increase in semiarid southwest Niger: a review. Water Resour. Res. https://doi.org/10.1029/2007wr006785 (2009).Article 

    Google Scholar 
    Walker, C. D., Zhang, l, Ellis, T. W., Hatton, T. J. & Petheram, C. Estimating impacts of changed land use on recharge: review of modelling and other approaches appropriate for management of dryland salinity. Hydrogeol. J. 10, 68–90 (2002).Article 

    Google Scholar 
    Nosetto, M. D., Jobbagy, E. G., Jackson, R. B. & Sznaider, G. A. Reciprocal influence of crops and shallow ground water in sandy landscapes of the Inland Pampas. Field Crops Res. 113, 138–148 (2009).Article 

    Google Scholar 
    Gimenez, R., Mercau, J., Nosetto, M., Paez, R. & Jobbagy, E. The ecohydrological imprint of deforestation in the semiarid Chaco: insights from the last forest remnants of a highly cultivated landscape. Hydrol. Process. 30, 2603–2616 (2016).Article 

    Google Scholar 
    Eilers, R. G., Eilers, W. D. & Fitzgerald, M. M. A salinity risk index for soils of the Canadian prairies. Hydrogeol. J. 5, 68–79 (1997).Article 

    Google Scholar 
    Progress on Household Drinking Water, Sanitation and Hygiene 2000–2020: Five Years into the SDGs (WHO/UNICEF, 2021).Cobbing, J. & Hiller, B. Waking a sleeping giant: realizing the potential of groundwater in sub-Saharan Africa. World Dev. 122, 597–613 (2019).Article 

    Google Scholar 
    Rockström, J. & Falkenmark, M. Agriculture: increase water harvesting in Africa. Nature 519, 283–285 (2015).Article 

    Google Scholar 
    MacAllister, D. J., MacDonald, A. M., Kebede, S., Godfrey, S. & Calow, R. Comparative performance of rural water supplies during drought. Nat. Commun. 11, 1099 (2020).Article 

    Google Scholar 
    Aboah, M. & Miyittah, M. K. Estimating global water, sanitation, and hygiene levels and related risks on human health, using global indicators data from 1990 to 2020. J. Water Health 20, 1091–1101 (2022).Article 

    Google Scholar 
    Abell, R. et al. Beyond the Source: The Environmental, Economic and Community Benefits of Source Water Protection (The Nature Conservancy, 2017).Herrera-Garcia, G. et al. Mapping the global threat of land subsidence. Science 371, 34–36 (2021).Article 

    Google Scholar 
    Scanlon, B. R., Reedy, R. C., Faunt, C. C., Pool, D. & Uhlman, K. Can we mitigate climate extremes using managed aquifer recharge: case studies California Central Valley and South-Central Arizona, USA. AGU Fall Meeting Abstract H12G-02, Invited (2015).Qadir, M. et al. Global and regional potential of wastewater as a water, nutrient and energy source. Nat. Resour. Forum 44, 40–51 (2020).Article 

    Google Scholar 
    Water Reuse within a Circular Economy Context. Global Water Security Issues Series 2 (UNESCO, 2020).Jones, E. R., van Vliet, M. T. H., Qadir, M. & Bierkens, M. F. P. Country-level and gridded estimates of wastewater production, collection, treatment and reuse. Earth Syst. Sci. Data 13, 237–254 (2021).Article 

    Google Scholar 
    Jeuland, M. Challenges to wastewater reuse in the Middle East and North Africa. Middle East. Dev. J. 7, 1–25 (2015).Article 

    Google Scholar 
    Zhang, Y. & Shen, Y. Wastewater irrigation: past, present, and future. WIREs Water 6, e1234 (2019).Article 

    Google Scholar 
    Fito, J. & Van Hulle, S. W. H. Wastewater reclamation and reuse potentials in agriculture: towards environmental sustainability. Environ. Dev. Sust. 23, 2949–2972 (2021).Article 

    Google Scholar 
    Gao, L., Yoshikawa, S., Iseri, Y., Fujimori, S. & Kanae, S. An economic assessment of the global potential for seawater desalination to 2050. Water https://doi.org/10.3390/w9100763 (2017).Article 

    Google Scholar 
    Ahdab, Y. D., Thiel, G. P., Bohlke, J. K., Stanton, J. & Lienhard, J. H. Minimum energy requirements for desalination of brackish groundwater in the United States with comparison to international datasets. Water Res. 141, 387–404 (2018).Article 

    Google Scholar 
    Jones, E., Qadir, M., van Vliet, M. T. H., Smakhtin, V. & Kang, S. M. The state of desalination and brine production: a global outlook. Sci. Total Environ. 657, 1343–1356 (2019).Article 

    Google Scholar 
    Lin, S. S. et al. Seawater desalination technology and engineering in China: a review. Desalination https://doi.org/10.1016/j.desal.2020.114728 (2021).Article 

    Google Scholar 
    Martinez-Alvarez, V., Martin-Gorriz, B. & Soto-Garcia, M. Seawater desalination for crop irrigation — a review of current experiences and revealed key issues. Desalination 381, 58–70 (2016).Article 

    Google Scholar 
    Smith, K., Liu, S. M., Hu, H. Y., Dong, X. & Wen, X. H. Water and energy recovery: the future of wastewater in China. Sci. Total Environ. 637, 1466–1470 (2018).Article 

    Google Scholar 
    Pulido-Bosch, A. et al. Impacts of agricultural irrigation on groundwater salinity. Environ/ Earth Sci. https://doi.org/10.1007/s12665-018-7386-6 (2018).Article 

    Google Scholar 
    Kurnik, J. The Next California: Phase 1: Investigating Potential in the Mid-Mississippi Delta River Region (The Markets Institute at WWF, 2020); https://www.worldwildlife.org/publications/the-next-california-phase-1-investigating-potential-in-the-mid-mississippi-delta-river-regionSenay, G. B., Schauer, M., Friedrichs, M., Velpuri, N. M. & Singh, R. K. Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States. Remote Sens. Environ. 202, 98–112 (2017).Article 

    Google Scholar 
    Gebremichael, M., Krishnamurthy, P. K., Ghebremichael, L. T. & Alam, S. What drives crop land use change during multi-year droughts in California’s Central Valley? Prices or concern for water? Remote Sens. https://doi.org/10.3390/rs13040650 (2021).Article 

    Google Scholar 
    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).Article 

    Google Scholar 
    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. https://doi.org/10.1016/j.agwat.2020.106122 (2020).Article 

    Google Scholar 
    Colaizzi, P. D., Gowda, P. H., Marek, T. H. & Porter, D. O. Irrigation in the Texas High Plains: a brief history and potential reductions in demand. Irrig. Drain. 58, 257–274 (2008).Article 

    Google Scholar 
    Scanlon, B. R., Gates, J. B., Reedy, R. C., Jackson, A. & Bordovsky, J. Effects of irrigated agroecosystems: (2). Quality of soil water and groundwater in the southern High Plains, Texas. Water Resour. Res. 46, W09538 (2010).
    Google Scholar 
    Ward, F. A. & Pulido-Velazquez, M. Water conservation in irrigation can increase water use. Proc. Natl Acad. Sci. USA 105, 18215–18220 (2008).Article 

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

    Google Scholar 
    Alcott, B. in The Jevons Paradox and the Myth of Resource Efficiency Improvements (eds Polimeni, J. M., Mayumi, K., & Giampetro, M.) 7–78 (Earthscan, 2008).MacAllister, D. J., Krishan, G., Basharat, M., Cuba, D. & MacDonald, A. M. A century of groundwater accumulation in Pakistan and northwest India. Nat. Geosci. 15, 390–396 (2022).Article 

    Google Scholar 
    Aarnoudse, E. & Bluemling, B. Controlling Groundwater Through Smart Card Machines: The Case of Water Quotas and Pricing Mechanisms in Gansu Province, China. Groundwater Solutions Initiative for Policy and Practice (GRIPP) Case Profile Series 02 (International Water Management Institute, 2017); https://doi.org/10.5337/2016.224Kinzelbach, W., Wang, H., Li, Y., Wang, L. & Li, N. Groundwater Overexploitation in the North China Plain: A Path to Sustainability (Springer, 2021).McDougall, R., Kristiansen, P. & Rader, R. Small-scale urban agriculture results in high yields but requires judicious management of inputs to achieve sustainability. Proc. Natl Acad. Sci. USA 116, 129–134 (2019).Article 

    Google Scholar 
    Langemeyer, J., Madrid-Lopez, C., Mendoza Beltran, A. & Villalba Mendez, G. Urban agriculture — a necessary pathway towards urban resilience and global sustainability? Landsc. Urban Plan. 210, 104055 (2021).Article 

    Google Scholar 
    Palmer, L. Urban agriculture growth in US cities. Nat. Sust. 1, 5–7 (2018).Article 

    Google Scholar 
    Grafius, D. R. et al. Estimating food production in an urban landscape. Sci. Rep. 10, 5141 (2020).Article 

    Google Scholar 
    The State of Food Insecurity in the World 2015 (FAO/IFAD/WFP, 2015).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).Article 

    Google Scholar 
    Gleick, P. H. Global freshwater resources: soft-path solutions for the 21st century. Science 302, 1524–1528 (2003).Article 

    Google Scholar 
    Miralles-Wilhelm, F. Nature-Based Solutions in Agriculture — Sustainable Management and Conservation of Land, Water, and Biodiversity (FAO/The Nature Conservancy, 2021).McDonald, R. I. & Shemie, D. Urban Water Blueprint: Mapping Conservation Solutions to the Global Water Challenge (The Nature Conservancy, 2014); http://water.nature.org/waterblueprintKane, M. & Erickson, J. D. Urban metabolism and payment for ecosystem services: history and policy analysis of the New York city water supply. Adv. Econ. Environ. Resour. 7, 307–328 (2007).Article 

    Google Scholar 
    Greater Cape Town Water Fund: Business Case: Assessing the Return on Investment for Ecological Infrastructure Restoration (The Nature Conservancy, 2019).Hu, J., Lu, Y. H., Fu, B. J., Comber, A. J. & Harris, P. Quantifying the effect of ecological restoration on runoff and sediment yields: a meta-analysis for the Loess Plateau of China. Prog. Phys. Geogr. Earth Environ. 41, 753–774 (2017).Article 

    Google Scholar 
    Liu, W. W. et al. Improving wetland ecosystem health in China. Ecol. Indic. https://doi.org/10.1016/j.ecolind.2020.106184 (2020).Article 

    Google Scholar 
    Cities100: Chennai Is Restoring Waterbodies to Protect Against Flooding and Drought. C40 Knowledge Hub: Nordic Sustainability, South and West Asia, Chennai, Case Studies and Best Practice Examples https://www.c40knowledgehub.org/s/article/Cities100-Chennai-is-restoring-waterbodies-to-protect-against-flooding-and-drought?language=en_US (2019).Chung, M. G., Frank, K. A., Pokhrel, Y., Dietz, T. & Liu, J. G. Natural infrastructure in sustaining global urban freshwater ecosystem services. Nat. Sust. 4, 1068 (2021).Article 

    Google Scholar 
    Qi, Y. F. et al. Addressing challenges of urban water management in Chinese sponge cities via nature-based solutions. Water https://doi.org/10.3390/w12102788 (2020).Article 

    Google Scholar 
    Acreman, M. et al. Evidence for the effectiveness of nature-based solutions to water issues in Africa. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/ac0210 (2021).Article 

    Google Scholar 
    Livneh, B. & Badger, A. M. Drought less predictable under declining future snowpack. Nat. Clim. Change 10, 452–458 (2020).Article 

    Google Scholar 
    Mulligan, M., van Soesbergen, A. & Sáenz, L. GOODD, a global dataset of more than 38,000 georeferenced dams. Sci. Data 7, 31 (2020).Article 

    Google Scholar 
    International Commission on Large Dams https://www.icold-cigb.org/ (2022).Yang, G., Guo, S., Liu, P. & Block, P. Integration and evaluation of forecast-informed multiobjective reservoir operations. J. Water Resour. Plan. Manag. 146, 04020038 (2020).Article 

    Google Scholar 
    Delaney, C. J. et al. Forecast informed reservoir operations using ensemble streamflow predictions for a multipurpose reservoir in northern California. Water Resour. Res. https://doi.org/10.1029/2019wr026604 (2020).Amarasinghe, U. A., Muthuwatta, L., Surinaidu, L., Anand, S. & Jain, S. K. Reviving the Ganges water machine: potential. Hydrol. Earth Syst. Sci. 20, 1085–1101 (2016).Article 

    Google Scholar 
    Shamsudduha, M. et al. The Bengal water machine: quantified freshwater capture in Bangladesh. Science 377, 1315–1319 (2022).Article 

    Google Scholar 
    Chao, B. F., Wu, Y. H. & Li, Y. S. Impact of artificial reservoir water impoundment on global sea level. Science 320, 212–214 (2008).Article 

    Google Scholar 
    Zarfl, C., Lumsdon, A. E., Berlekamp, J., Tydecks, L. & Tockner, K. A global boom in hydropower dam construction. Aquat. Sci. 77, 161–170 (2015).Article 

    Google Scholar 
    Zarfl, C. et al. Future large hydropower dams impact global freshwater megafauna. Sci. Rep. https://doi.org/10.1038/s41598-019-54980-8 (2019).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).Article 

    Google Scholar 
    Di Baldassarre, G. et al. Water shortages worsened by reservoir effects. Nat. Sust. 1, 617–622 (2018).Article 

    Google Scholar 
    Dahlke, H. E., Brown, A. G., Orloff, S., Putnam, D. & O’Geen, T. Managed winter flooding of alfalfa recharges groundwater with minimal crop damage. Calif. Agric. 72, 65–75 (2018).Article 

    Google Scholar 
    Yang, Q. & Scanlon, B. R. How much water can be captured from flood flows to store in depleted aquifers for mitigating floods and droughts? A case study from Texas, US. Environ. Res. Lett. 14, 054011 (2019).Article 

    Google Scholar 
    Dillon, P. et al. Sixty years of global progress in managed aquifer recharge. Hydrogeol. J. https://doi.org/10.1007/s10040-018-1841-z. (2018).Article 

    Google Scholar 
    Groundwater Replenishment System Technical Brochure, https://www.ocwd.com/media/10443/gwrs-technical-brochure-2021.pdf (2021).Konikow, L. F. Groundwater Depletion in the United States (1900–2008). US Geological Survey Scientific Investigation Report 2013–5079, http://pubs.usgs.gov/sir/2013/5079 (2013).Hartog, N. & Stuyfzand, P. J. Water quality donsiderations on the rise as the use of managed aquifer recharge systems widens. Water 9, 808 (2017).Article 

    Google Scholar 
    Shumilova, O., Tockner, K., Thieme, M., Koska, A. & Zarfl, C. Global water transfer megaprojects: a potential solution for the water–food–energy nexus? Front. Environ. Sci. https://doi.org/10.3389/fenvs.2018.00150 (2018).Article 

    Google Scholar 
    Long, D. et al. South-to-north water diversion stabilizing Beijing’s groundwater levels. Nat. Commun. https://doi.org/10.1038/s41467-020-17428-6 (2020).Article 

    Google Scholar 
    Zhuang, W. Eco-environmental impact of inter-basin water transfer projects: a review. Environ. Sci. Pollut. Res. 23, 12867–12879 (2016).Article 

    Google Scholar 
    Hoekstra, A. Y. Virtual Water Trade: Proceedings of the International Expert Meeting on Virtual Water Trade (UNESCO-IHE, 2003).Oki, T. & Kanae, S. Virtual water trade and world water resources. Water Sci. Technol. 49, 203–209 (2004).Article 

    Google Scholar 
    Dolan, F. et al. Evaluating the economic impact of water scarcity in a changing world. Nat. Commun. https://doi.org/10.1038/s41467-021-22194-0 (2021).Article 

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

    Google Scholar 
    Dalin, C., Wada, Y., Kastner, T. & Puma, M. J. Groundwater depletion embedded in international food trade. Nature 543, 700–704 (2017).Hanasaki, N., Inuzuka, T., Kanae, S. & Oki, T. An estimation of global virtual water flow and sources of water withdrawal for major crops and livestock products using a global hydrological model. J. Hydrol. 384, 232–244 (2010).Article 

    Google Scholar 
    Mekonnen, M. M. & Gerbens-Leenes, W. The water footprint of global food production. Water https://doi.org/10.3390/w12102696 (2020).Article 

    Google Scholar 
    Australian Water Markets Report: 2019-20 Review and 2020-21 Outlook (Aither, 2020); https://aither.com.au/wp-content/uploads/2020/08/2020-Water-Markets-Report.pdfGrafton, R. Q. & Wheeler, S. A. Economics of water recovery in the Murray–Darling Basin, Australia. Annu. Rev. Resour. Econ. 10, 487–510 (2018).Article 

    Google Scholar 
    Moench, M. Water and the potential for social instability: livelihoods, migration and the building of society. Nat. Resour. Forum 26, 195–204 (2002).Article 

    Google Scholar 
    Water Markets in Australia: A Short History (National Water Commission, 2011).Kundzewicz, Z. W. & Döll, P. Will groundwater ease freshwater stress under climate change? Hydrol. Sci. J. 54, 665–675 (2009).Article 

    Google Scholar 
    A Snapshot of the World’s Water Quality: Towards a Global Assessment (UNEP, 2016).Summary Progress Update 2021: SDG 6 — Water and Sanitation for All (UN-Water, 2021).GEMStat: Global Environmental Monitoring System, https://gemstat.org/ (UNEP, 2022).Akhmouch, A. & Correia, F. N. The 12 OECD principles on water governance — when science meets policy. Util. Policy 43, 14–20 (2016).Article 

    Google Scholar 
    Lankford, B., Bakker, K., Zeitoun, M. & Conway, B. D. Water Security: Principles, Perspectives, and Practices (Routledge, 2013).Potapov, P. et al. Global maps of cropland extent and change show accelerated cropland expansion in the twenty-first century. Nat. Food 3, 19 (2022).Article 

    Google Scholar 
    Fan, Y., Li, H. & Miguez-Macho, G. Global patterns of groundwater table depth. Science 339, 940–943 (2013).Article 

    Google Scholar  More

  • in

    Polydimethylsiloxane-coated textiles with minimized microplastic pollution

    Guha Roy, A. Detailing plastic pollution. Nat. Sustain. 2, 654 (2019).Article 

    Google Scholar 
    Lau, W. W. Y. et al. Evaluating scenarios toward zero plastic pollution. Science 369, 1455–1461 (2020).Article 
    CAS 

    Google Scholar 
    Koelmans, A. A. et al. Risk assessment of microplastic particles. Nat. Rev. Mater. 7, 138–152 (2022).Article 

    Google Scholar 
    Rochman, C. M. Microplastics research—from sink to source. Science 360, 28–29 (2018).Article 
    CAS 

    Google Scholar 
    Zhang, Y. et al. Atmospheric microplastics: a review on current status and perspectives. Earth Sci. Rev. 203, 103118 (2020).Article 
    CAS 

    Google Scholar 
    Nowack, B., Cai, Y., Mitrano, D. M. & Hufenus, R. Formation of fiber fragments during abrasion of polyester textiles. Environ. Sci. Technol. 55, 8001–8009 (2021).Article 

    Google Scholar 
    Henry, B., Laitala, K. & Klepp, I. G. Microfibres from apparel and home textiles: prospects for including microplastics in environmental sustainability assessment. Sci. Total Environ. 652, 483–494 (2019).Article 

    Google Scholar 
    Boucher, J. & Friot, D. Primary Microplastics in the Oceans: A Global Evaluation of Sources (IUCN, 2017).Evangeliou, N. et al. Atmospheric transport is a major pathway of microplastics to remote regions. Nat. Commun. 11, 3381 (2020).Article 
    CAS 

    Google Scholar 
    Bergmann, M. et al. White and wonderful? Microplastics prevail in snow from the Alps to the Arctic. Sci. Adv. 5, 1157 (2019).Article 

    Google Scholar 
    Brahney, J., Hallerud, M., Heim, E., Hahnenberger, M. & Sukumaran, S. Plastic rain in protected areas of the United States. Science 368, 1257–1260 (2020).Article 
    CAS 

    Google Scholar 
    Jenner, L. C. et al. Detection of microplastics in human lung tissue using μFTIR spectroscopy. Sci. Total Environ. 831, 154907 (2022).Article 
    CAS 

    Google Scholar 
    Leslie, H. A. et al. Discovery and quantification of plastic particle pollution in human blood. Environ. Int. 163, 107199 (2022).Article 
    CAS 

    Google Scholar 
    Zabala, A. Ocean microfibre contamination. Nat. Sustain. 1, 213 (2018).Article 

    Google Scholar 
    De Falco, F. et al. Evaluation of microplastic release caused by textile washing processes of synthetic fabrics. Environ. Pollut. 236, 916–925 (2018).Article 

    Google Scholar 
    De Falco, F. et al. Novel finishing treatments of polyamide fabrics by electrofluidodynamic process to reduce microplastic release during washings. Polym. Degrad. Stab. 165, 110–116 (2019).Article 

    Google Scholar 
    Suaria, G. et al. Microfibers in oceanic surface waters: a global characterization. Sci. Adv. 6, 8493 (2020).Article 

    Google Scholar 
    Woodward, J., Li, J., Rothwell, J. & Hurley, R. Acute riverine microplastic contamination due to avoidable releases of untreated wastewater. Nat. Sustain. 4, 793–802 (2021).Article 

    Google Scholar 
    De Falco, F. et al. Pectin based finishing to mitigate the impact of microplastics released by polyamide fabrics. Carbohydr. Polym. 198, 175–180 (2018).Article 

    Google Scholar 
    Zhao, X. et al. Macroscopic evidence of the liquidlike nature of nanoscale polydimethylsiloxane brushes. ACS Nano 15, 13559–13567 (2021).Article 
    CAS 

    Google Scholar 
    Shabanian, S., Khatir, B., Nisar, A. & Golovin, K. Rational design of perfluorocarbon-free oleophobic textiles. Nat. Sustain. 3, 1059–1066 (2020).Article 

    Google Scholar 
    Khatir, B., Shabanian, S. & Golovin, K. Design and high-resolution characterization of silicon wafer-like omniphobic liquid layers applicable to any substrate. ACS Appl. Mater. Interfaces 12, 31933–31939 (2020).Article 
    CAS 

    Google Scholar 
    Soltani, M. & Golovin, K. Lossless, passive transportation of low surface tension liquids induced by patterned omniphobic liquidlike polymer brushes. Adv. Funct. Mater. 32, 2107465 (2022).Article 
    CAS 

    Google Scholar 
    Wang, L. & McCarthy, T. J. Covalently attached liquids: instant omniphobic surfaces with unprecedented repellency. Angew. Chem. Int. Ed. 55, 244–248 (2016).Article 
    CAS 

    Google Scholar 
    Liu, J. et al. One-step synthesis of a durable and liquid-repellent poly(dimethylsiloxane) coating. Adv. Mater. 33, 2100237 (2021).Article 
    CAS 

    Google Scholar 
    Özek, H. Z. Silicone-based water repellents. in Waterproof and Water Repellent Textiles and Clothing (ed. Williams, J. T.) 153–189 (Woodhead Publishing, 2018).Cao, C. et al. Robust fluorine-free superhydrophobic PDMS-ormosil@fabrics for highly effective self-cleaning and efficient oil-water separation. J. Mater. Chem. A 4, 12179–12187 (2016).Article 
    CAS 

    Google Scholar 
    Dong, K. et al. Shape adaptable and highly resilient 3D braided triboelectric nanogenerators as e-textiles for power and sensing. Nat. Commun. 11, 2868 (2020).Article 
    CAS 

    Google Scholar 
    Jiang, L., Cheng, Y., Wang, S., Xu, Z. & Zhao, Y. Non-fluorine oil repellency: how low the intrinsic wetting threshold can be for roughness-induced contact angle amplification? Langmuir 38, 5857–5864 (2022).Article 
    CAS 

    Google Scholar 
    Ge, M. et al. A ‘PDMS-in-water’ emulsion enables mechanochemically robust superhydrophobic surfaces with self-healing nature. Nanoscale Horiz. 5, 65–73 (2020).Article 
    CAS 

    Google Scholar 
    Chauvin, J. P. R. & Pratt, D. A. On the reactions of thiols, sulfenic acids, and sulfinic acids with hydrogen peroxide. Angew. Chem. Int. Ed. 56, 6255–6259 (2017).Article 
    CAS 

    Google Scholar 
    Gunji, T., Shigematsu, Y., Kajiwara, T. & Abe, Y. Preparation of free-standing films with sulfonyl group from 3-mercaptopropyl(trimethoxy)silane/1,2-bis(triethoxysilyl)ethane copolymer. Polym. J. 42, 684–688 (2010).Article 
    CAS 

    Google Scholar 
    Remington, W. R. & Gladding, E. K. Equilibria in the dyeing of nylon with acid dyes. J. Am. Chem. Soc. 72, 2553–2559 (1950).Article 
    CAS 

    Google Scholar 
    Herzberg, W. J. & Erwin, W. R. Gas-chromatographic study of the reaction of glass surfaces with dichlorodimethylsilane and chlorotrimethylsilane. J. Colloid Interface Sci. 33, 172–177 (1970).Article 
    CAS 

    Google Scholar 
    Bielecki, R. M., Crobu, M. & Spencer, N. D. Polymer-brush lubrication in oil: sliding beyond the Stribeck curve. Tribol. Lett. 49, 263–272 (2013).Article 
    CAS 

    Google Scholar 
    Zhou, S. M., Tashiro, K. & Ii, T. Moisture effect on structure and mechanical property of nylon 6 as studied by the time-resolved and simultaneous measurements of FT-IR and dynamic viscoelasticity under the controlled humidity at constant scanning rate. Polym. J. 33, 344–355 (2001).Article 
    CAS 

    Google Scholar 
    Venoor, V., Park, J. H., Kazmer, D. O. & Sobkowicz, M. J. Understanding the effect of water in polyamides: a review. Polym. Rev. 61, 598–645 (2021).Article 
    CAS 

    Google Scholar 
    Napper, I. E. & Thompson, R. C. Release of synthetic microplastic plastic fibres from domestic washing machines: effects of fabric type and washing conditions. Mar. Pollut. Bull. 112, 39–45 (2016).Article 
    CAS 

    Google Scholar 
    Napper, I. E., Barrett, A. C. & Thompson, R. C. The efficiency of devices intended to reduce microfibre release during clothes washing. Sci. Total Environ. 738, 140412 (2020).Article 
    CAS 

    Google Scholar 
    Chiong, J. A., Tran, H., Lin, Y., Zheng, Y. & Bao, Z. Integrating emerging polymer chemistries for the advancement of recyclable, biodegradable, and biocompatible electronics. Adv. Sci. 8, 2101233 (2021).Article 
    CAS 

    Google Scholar 
    Ceseracciu, L., Heredia-Guerrero, J. A., Dante, S., Athanassiou, A. & Bayer, I. S. Robust and biodegradable elastomers based on corn starch and polydimethylsiloxane (PDMS). ACS Appl. Mater. Interfaces 7, 3742–3753 (2015).Article 
    CAS 

    Google Scholar 
    De Falco, F., Gentile, G., Di Pace, E., Avella, M. & Cocca, M. Quantification of microfibres released during washing of synthetic clothes in real conditions and at lab scale. Eur. Phys. J. 133, 257 (2018).
    Google Scholar  More