West Africa Dams and Reservoirs Datasetdoi:10.60507/FK2/YLDK1Ybonndata2026-02-261Kouassi, Valery Bessely Stanislas; Yao, Blé Amouna Fhorest; Soro, Gneneyougo Emile; Goula, Bi Tié Albert; Kelome, Nelly Carine; Klaus, Julian, 2026, "West Africa Dams and Reservoirs Dataset", https://doi.org/10.60507/FK2/YLDK1Y, bonndata, V1West Africa Dams and Reservoirs Datasetdoi:10.60507/FK2/YLDK1YKouassi, Valery Bessely StanislasYao, Blé Amouna FhorestSoro, Gneneyougo EmileGoula, Bi Tié AlbertKelome, Nelly CarineKlaus, JulianWest African Science Service Centre on Climate Change and Adapted Land UseDepartment of GeographyQuantum Geographic Information System (QGIS)Argelander Scholarships for doctoral candidates from universities in Africa, Latin America, and South/East AsiaWASCAL PhD Scholarship ProgrammebonndataKouassi, ValeryKOUASSI, Valery Bessely Stanislas2026-01-22Earth and Environmental SciencesThe West Africa Dams and Reservoirs Dataset, also called Harmonized Dataset for Dams and Reservoirs in West Africa is a West Africa-specific compiled dataset developed through the integration of twelve existing datasets. This harmonized dataset aims to address the heterogeneous data records of West African dams and reservoirs in existing datasets while enhancing the accessibility of dam and reservoir information for policy development, investment planning, and regional-scale analyses. The dataset contains 1,429 georeferenced dams and 1,258 reservoirs (with a minimum surface area of 0.57 × 10⁻³ km²), 38 attributes, and an estimated total reservoir surface area of 14,038 km² and a cumulative storage capacity of 267,369 MCM. The West Africa Dams and Reservoirs Dataset is provided in shapefile and CSV formats for both dam and reservoir entries: WA_Dams (point locations of dams in West Africa) and WA_Reservoirs (polygon representations of reservoirs in West Africa) available for download and future updates.2025-03-012025-07-30Aggregate Data<a href="http://creativecommons.org/licenses/by/4.0">CC BY 4.0</a>Global Information System on Water and Agriculture of the Food and Agriculture Organization (FAO AQUASTAT). https://www.fao.org/aquastat/en/databases/damsGlobal Lakes and Wetlands Database (GLWD-1 (Level 1) & GLWD-2 (Level 2)). https://www.worldwildlife.org/our-work/science/global-lakes-and-wetlands-database/HydroLAKES. https://www.hydrosheds.org/products/hydrolakesGlObal GeOreferenced Database of Dams (GOODD). https://www.globaldamwatch.org/gooddFuture Hydropower Reservoirs and Dams Database (FHReD). https://www.globaldamwatch.org/fhredGlobal Reservoirs and Dams version 1.3 (GranD V1.3). https://www.globaldamwatch.org/grand/Global River Obstruction Database version 1.1 (GROD v1.1). https://zenodo.org/records/5793918Reservoir and Lake Surface Area Timeseries (ReaLSAT). https://doi.org/10.5281/zenodo.7614815Georeferenced global Dams And Reservoirs (GeoDAR). https://zenodo.org/records/6163413Global Dam Tracker (GDAT). https://zenodo.org/records/7616852Global Dam Watch (GDW database (V1)). https://www.globaldamwatch.org/databaseGlobal Lakes/Reservoirs Surface Extent Dataset (GLRSED). https://zenodo.org/records/14190225Bai, 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, 2023.2026-02-02_Kouassi_WA_Dams-Res-dens_Comp-and-Orig.pngCompared to existing datasets, the compiled dataset integrates both large- and small-scale reservoirs. It includes a higher number of small-scale entries while preserving the central latitude mode observed in the selected datasets. This suggests better spatial completeness and scale coverage compared to individual datasets, although residual biases from the sources remain in the compiled dataset.image/png2026-02-19_Kouassi_WA_Dams-Res_Dataset_Readme.txtReadme file of the West Africa Dams and Reservoirs Dataset providing detailed information on the dataset.text/plain2026-02-19_Kouassi_WA_Dams.csvCSV file of dam point locations in West Africa and their attributes.text/csv2026-02-19_Kouassi_WA_Reservoirs.csvCSV file of the reservoir polygon associated with dams in West Africa and their attributes.text/csv2026-02-19_Kouassi_WA_Reservoirs.zipShapefile of the reservoir polygon associated with dams in West Africa and their attributes.application/zipped-shapefile2026-02-19_Kouassi_WA_Dams.zipShapefile of dam point locations in West Africa and their attributes.application/zipped-shapefile