|
Other References
| Bai, B., Mu, L., and Tan, Y.: A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED ): An Integration of Multi‐Source Data, Geoscience Data Journal, 12, https://doi.org/10.1002/gdj3.285, 2025.; FAO: AQUASTAT – FAO’s global information system on water and agriculture: geo-referenced database on dams, FAO, https://www.fao.org/aquastat/en/databases/dams, last access: 11 February 2025, 2021.; Khandelwal, A., Karpatne, A., Ravirathinam, P., Ghosh, R., Wei, Z., Dugan, H. A., Hanson, P. C., and Kumar, V.: ReaLSAT, a global dataset of reservoir and lake surface area variations, Scientific data, 9, https://doi.org/10.1038/s41597-022-01449-5, 2022.; Lehner, B., Beames, P., Mulligan, M., Zarfl, C., Felice, L. de, van Soesbergen, A., Thieme, M., Garcia de Leaniz, C., Anand, M., Belletti, B., Brauman, K. A., Januchowski-Hartley, S. R., Lyon, K., Mandle, L., Mazany-Wright, N., Messager, M. L., Pavelsky, T., Pekel, J.-F., Wang, J., Wen, Q., Wishart, M., Xing, T., Yang, X., and Higgins, J.: The Global Dam Watch database of river barrier and reservoir information for large-scale applications, Scientific data, 11, 1069, https://doi.org/10.1038/s41597-024-03752-9, 2024.; Lehner, B. and Döll, P.: Development and validation of a global database of lakes, reservoirs and wetlands, Journal of Hydrology, 296, 1–22, https://doi.org/10.1016/j.jhydrol.2004.03.028, 2004.; Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J. C., Rödel, R., Sindorf, N., and Wisser, D.: High‐resolution mapping of the world's reservoirs and dams for sustainable river‐flow management, Frontiers in Ecol & Environ, 9, 494–502, https://doi.org/10.1890/100125, 2011.; Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O.: Estimating the volume and age of water stored in global lakes using a geo-statistical approach, Nature communications, 7, 13603, https://doi.org/10.1038/ncomms13603, 2016.; Mulligan, M., van Soesbergen, A., and Sáenz, L.: GOODD, a global dataset of more than 38,000 georeferenced dams, Scientific data, 7, 31, https://doi.org/10.1038/s41597-020-0362-5, 2020.; Wang, J., Walter, B. A., Yao, F., Song, C., Ding, M., Maroof, A. S., Zhu, J., Fan, C., McAlister, J. M., Sikder, S., Sheng, Y., Allen, G. H., Crétaux, J.-F., and Wada, Y.: GeoDAR: georeferenced global dams and reservoirs dataset for bridging attributes and geolocations, Earth Syst. Sci. Data, 14, 1869–1899, https://doi.org/10.5194/essd-14-1869-2022, 2022.; Yang, X., Pavelsky, T. M., Ross, M. R. V., Januchowski‐Hartley, S. R., Dolan, W., Altenau, E. H., Belanger, M., Byron, D., Durand, M., van Dusen, I., Galit, H., Jorissen, M., Langhorst, T., Lawton, E., Lynch, R., Mcquillan, K. A., Pawar, S., and Whittemore, A.: Mapping Flow‐Obstructing Structures on Global Rivers, Water Resources Research, 58, https://doi.org/10.1029/2021WR030386, 2022.; Zarfl, C., Lumsdon, A. E., Berlekamp, J., Tydecks, L., and Tockner, K.: A global boom in hydropower dam construction, Aquat Sci, 77, 161–170, https://doi.org/10.1007/s00027-014-0377-0, 2015.; Zhang, A. T. and Gu, V. X.: Global Dam Tracker: A database of more than 35,000 dams with location, catchment, and attribute information, Scientific data, 10, 111, https://doi.org/10.1038/s41597-023-02008-2, 2023. |
