Vörösmarty, C. J. et al. Global threats to human water security and river biodiversity. Nature 467, 555–561 (2010).
Google Scholar
Ruhi, A., Messager, M. L. & Olden, J. D. Tracking the pulse of the Earth’s fresh waters. Nat. Sustain. 1, 198–203 (2018).
Google Scholar
Pearson, C. Short- and medium-term climate information for water management. World Meteorol. Organ. Bull. 57, 173–177 (2008).
Tetzlaff, D., Carey, S. K., McNamara, J. P., Laudon, H. & Soulsby, C. The essential value of long-term experimental data for hydrology and water management. Water Resour. Res. 53, 2598–2604 (2017).
Google Scholar
Carlisle, D. M., Wolock, D. M. & Meador, M. R. Alteration of streamflow magnitudes and potential ecological consequences: a multiregional assessment. Front. Ecol. Environ. 9, 264–270 (2011).
Google Scholar
Shrestha, S., Kazama, F. & Newham, L. T. H. A framework for estimating pollutant export coefficients from long-term in-stream water quality monitoring data. Environ. Model. Softw. 23, 182–194 (2008).
Google Scholar
Lepistö, A., Futter, M. N. & Kortelainen, P. Almost 50 years of monitoring shows that climate, not forestry, controls long-term organic carbon fluxes in a large boreal watershed. Glob. Change Biol. 20, 1225–1237 (2014).
Google Scholar
Hester, G., Ford, D., Carsell, K., Vertucci, C. & Stallings, E. A. Flood Management Benefits of USGS Streamgaging Program (National Hydrologic Warning Council, 2006).
Xu, H., Xu, C.-Y., Chen, H., Zhang, Z. & Li, L. Assessing the influence of rain gauge density and distribution on hydrological model performance in a humid region of China. J. Hydrol. 505, 1–12 (2013).
Google Scholar
Kiang, J. E., Stewart, D. W., Archfield, S. A., Osborne, E. B. & Eng, K. A National Streamflow Network Gap Analysis (USGS, 2013).
Deweber, J. T. et al. Importance of understanding landscape biases in USGS gage locations: implications and solutions for managers. Fisheries 39, 155–163 (2014).
Google Scholar
Tickner, D. et al. Bending the curve of global freshwater biodiversity loss: an emergency recovery plan. BioScience 70, 330–342 (2020).
Google Scholar
Grill, G. et al. Mapping the world’s free-flowing rivers. Nature 569, 215–221 (2019).
Google Scholar
Olden, J. D. et al. Hydrologic classification of Tanzanian rivers to support national water resource policy. Ecohydrology. https://doi.org/10.1002/eco.2282 (2021).
Lin, P. et al. Global reconstruction of naturalized river flows at 2.94 million reaches. Water Resour. Res. 55, 6499–6516 (2019).
Google Scholar
Yamazaki, D. et al. MERIT Hydro: a high-resolution global hydrography map based on latest topography dataset. Water Resour. Res. 55, 5053–5073 (2019).
Google Scholar
Beck, H. E. et al. Bias correction of global high-resolution precipitation climatologies using streamflow observations from 9,372 catchments. J. Clim. 33, 1299–1315 (2020).
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 Syst. Sci. Data 10, 765–785 (2018).
Google Scholar
Linke, S. et al. Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution. Sci. Data 6, 283 (2019).
Google Scholar
Dobrushin, R. L. Prescribing a system of random variables by conditional distributions. Theory Probab. Appl. 15, 458–486 (1970).
Google Scholar
Schefzik, R., Flesch, J. & Goncalves, A. Fast identification of differential distributions in single-cell RNA-sequencing data with waddR. Bioinformatics 37, 3204–3211 (2021).
Google Scholar
Reid, A. J. et al. Emerging threats and persistent conservation challenges for freshwater biodiversity. Biol. Rev. 94, 849–873 (2019).
Google Scholar
Wittemyer, G., Elsen, P., Bean, W. T., Burton, A. C. O. & Brashares, J. S. Accelerated human population growth at protected area edges. Science 321, 123–126 (2008).
Google Scholar
Colvin, S. A. R. et al. Headwater streams and wetlands are critical for sustaining fish, fisheries, and ecosystem Services. Fisheries 44, 73–91 (2019).
Google Scholar
Chen, K. & Olden, J. D. Threshold responses of riverine fish communities to land use conversion across regions of the world. Glob. Change Biol. 26, 4952–4965 (2020).
Google Scholar
Pardo, I. et al. The European reference condition concept: a scientific and technical approach to identify minimally-impacted river ecosystems. Sci. Total Environ. 420, 33–42 (2012).
Google Scholar
Sauquet, E. et al. Classification and trends in intermittent river flow regimes in Australia, northwestern Europe and USA: a global perspective. J. Hydrol. 597, 126170 (2021).
Google Scholar
Creed, I. F. et al. Enhancing protection for vulnerable waters. Nat. Geosci. 10, 809–815 (2017).
Google Scholar
Abell, R. et al. Freshwater ecoregions of the world: a new map of biogeographic units for freshwater biodiversity conservation. BioScience 58, 403–414 (2008).
Google Scholar
Wilhite, D. A. in Coping with Drought Risk in Agriculture and Water Supply Systems: Drought Management and Policy Development in the Mediterranean, Vol. 26 (eds. Iglesias, A. et al.) 3–19 (Springer Science and Business Media, 2009).
Winemiller, K. O. et al. Balancing hydropower and biodiversity in the Amazon, Congo, and Mekong. Science 351, 128–129 (2016).
Google Scholar
Seyfried, M. S. & Wilcox, B. P. Scale and the nature of spatial variability: field examples having implications for hydrologic modeling. Water Resour. Res. 31, 173–184 (1995).
Google Scholar
Hammond, J. C. et al. Spatial patterns and drivers of nonperennial flow regimes in the contiguous United States. Geophys. Res. Lett. 48, e2020GL090794 (2021).
Google Scholar
Messager, M. L. et al. Global prevalence of non-perennial rivers and streams. Nature 594, 391–397 (2021).
Google Scholar
Busch, M. H. et al. What’s in a name? Patterns, trends, and suggestions for defining non-perennial rivers and streams. Water 12, 1980 (2020).
Google Scholar
Zipper, S. C. et al. Pervasive changes in stream intermittency across the United States. Environ. Res. Lett. 16, 084033 (2021).
Google Scholar
Jaeger, K. L., Olden, J. D. & Pelland, N. A. Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams. Proc. Natl Acad. Sci. USA 111, 13894–13899 (2014).
Google Scholar
Beaufort, A., Lamouroux, N., Pella, H., Datry, T. & Sauquet, E. Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks. Hydrol. Earth Syst. Sci. 22, 3033–3051 (2018).
Google Scholar
Argerich, A. et al. Comprehensive multiyear carbon budget of a temperate headwater stream: carbon budget of a headwater stream. J. Geophys. Res. Biogeosci. 121, 1306–1315 (2016).
Google Scholar
Molden, D. J., Shrestha, A. B., Nepal, S. & Immerzeel, W. W. in Water Security, Climate Change and Sustainable Development (eds. Biswas, A. K. & Tortajada, C.) 65–82 (Springer, 2016).
Kaletová, T. et al. Relevance of intermittent rivers and streams in agricultural landscape and their impact on provided ecosystem services—a Mediterranean case study. Int. J. Environ. Res. Public Health 16, 2693 (2019).
Google Scholar
Zimmer, M. A. et al. Zero or not? Causes and consequences of zero-flow stream gage readings. WIREs Water 7, e1436 (2020).
Google Scholar
Wine, M. L. Toward strong science to support equitable water sharing in securitized transboundary watersheds. Biologia 9, 907–915 (2020).
Google Scholar
Alsdorf, D. E. GEOPHYSICS: tracking fresh water from space. Science 301, 1491–1494 (2003).
Google Scholar
Benstead, J. P. & Leigh, D. S. An expanded role for river networks. Nat. Geosci. 5, 678–679 (2012).
Google Scholar
Allen, D. C. et al. Citizen scientists document long-term streamflow declines in intermittent rivers of the desert southwest, USA. Freshw. Sci. https://doi.org/10.1086/701483 (2019).
Joo, H. et al. Optimal stream gauge network design using entropy theory and importance of stream gauge stations. Entropy 21, 991 (2019).
Google Scholar
Vörösmarty, C. et al. Global water data: a newly endangered species. Eos 82, 54–58 (2001).
Google Scholar
Jordahl, K. et al. Geopandas/geopandas. Zenodo https://doi.org/10.5281/zenodo.3946761 (2020).
Lin, P., Pan, M., Wood, E. F., Yamazaki, D. & Allen, G. H. A new vector-based global river network dataset accounting for variable drainage density. Sci. Data 8, 28 (2021).
Google Scholar
Yu, S. et al. Evaluating a landscape-scale daily water balance model to support spatially continuous representation of flow intermittency throughout stream networks. Hydrol. Earth Syst. Sci. 24, 5279–5295 (2020).
Google Scholar
Kennard, M. J. et al. Classification of natural flow regimes in Australia to support environmental flow management. Freshw. Biol. 55, 171–193 (2010).
Google Scholar
Flow/No Flow Observations with Discharge Data from Probabilistic Stream Surveys (US EPA Office of Research and Development, 2021).
Rosenbaum, P. R. & Rubin, D. B. The bias due to incomplete matching. Biometrics 41, 103–116 (1985).
Google Scholar
Source: Ecology - nature.com