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Part 1: Document Description
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Citation |
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Title: |
West Africa Dams and Reservoirs Dataset |
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Identification Number: |
doi:10.60507/FK2/YLDK1Y |
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Distributor: |
bonndata |
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Date of Distribution: |
2026-02-26 |
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Version: |
1 |
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Bibliographic Citation: |
Kouassi, 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, V1 |
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Citation |
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Title: |
West Africa Dams and Reservoirs Dataset |
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Identification Number: |
doi:10.60507/FK2/YLDK1Y |
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Authoring Entity: |
Kouassi, Valery Bessely Stanislas (Department of Geography, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany) |
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Yao, Blé Amouna Fhorest (Unité de Formation et de Recherche Sciences et Gestion de l’Environnement, Université Nangui Abrogoua, Abidjan, Côte d’Ivoire) |
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Soro, Gneneyougo Emile (Unité de Formation et de Recherche Sciences et Gestion de l’Environnement, Université Nangui Abrogoua, Abidjan, Côte d’Ivoire) |
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Goula, Bi Tié Albert (Unité de Formation et de Recherche Sciences et Gestion de l’Environnement, Université Nangui Abrogoua, Abidjan, Côte d’Ivoire) |
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Kelome, Nelly Carine (Département des Sciences de la Terre, Université d’Abomey-Calavi, Abomey-Calavi, Benin) |
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Klaus, Julian (Department of Geography, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany) |
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Producer: |
West African Science Service Centre on Climate Change and Adapted Land Use |
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Department of Geography |
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Software used in Production: |
Quantum Geographic Information System (QGIS) |
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Grant Number: |
Argelander Scholarships for doctoral candidates from universities in Africa, Latin America, and South/East Asia |
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Grant Number: |
WASCAL PhD Scholarship Programme |
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Distributor: |
bonndata |
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Access Authority: |
Kouassi, Valery |
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Depositor: |
KOUASSI, Valery Bessely Stanislas |
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Date of Deposit: |
2026-01-22 |
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Holdings Information: |
https://doi.org/10.60507/FK2/YLDK1Y |
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Study Scope |
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Keywords: |
Earth and Environmental Sciences |
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Abstract: |
The 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. |
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Date of Collection: |
2025-03-01-2025-07-30 |
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Kind of Data: |
Aggregate Data |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
<a href="http://creativecommons.org/licenses/by/4.0">CC BY 4.0</a> |
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Other Study Description Materials |
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Related Studies |
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Global Information System on Water and Agriculture of the Food and Agriculture Organization (FAO AQUASTAT). https://www.fao.org/aquastat/en/databases/dams |
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Global Lakes and Wetlands Database (GLWD-1 (Level 1) & GLWD-2 (Level 2)). https://www.worldwildlife.org/our-work/science/global-lakes-and-wetlands-database/ |
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HydroLAKES. https://www.hydrosheds.org/products/hydrolakes |
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GlObal GeOreferenced Database of Dams (GOODD). https://www.globaldamwatch.org/goodd |
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Future Hydropower Reservoirs and Dams Database (FHReD). https://www.globaldamwatch.org/fhred |
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Global Reservoirs and Dams version 1.3 (GranD V1.3). https://www.globaldamwatch.org/grand/ |
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Global River Obstruction Database version 1.1 (GROD v1.1). https://zenodo.org/records/5793918 |
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Reservoir and Lake Surface Area Timeseries (ReaLSAT). https://doi.org/10.5281/zenodo.7614815 |
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Georeferenced global Dams And Reservoirs (GeoDAR). https://zenodo.org/records/6163413 |
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Global Dam Tracker (GDAT). https://zenodo.org/records/7616852 |
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Global Dam Watch (GDW database (V1)). https://www.globaldamwatch.org/database |
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Global Lakes/Reservoirs Surface Extent Dataset (GLRSED). https://zenodo.org/records/14190225 |
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Other Reference Note(s) |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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Label: |
2026-02-02_Kouassi_WA_Dams-Res-dens_Comp-and-Orig.png |
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Text: |
Compared 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. |
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Notes: |
image/png |
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Label: |
2026-02-19_Kouassi_WA_Dams-Res_Dataset_Readme.txt |
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Text: |
Readme file of the West Africa Dams and Reservoirs Dataset providing detailed information on the dataset. |
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Notes: |
text/plain |
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Label: |
2026-02-19_Kouassi_WA_Dams.csv |
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Text: |
CSV file of dam point locations in West Africa and their attributes. |
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Notes: |
text/csv |
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Label: |
2026-02-19_Kouassi_WA_Reservoirs.csv |
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Text: |
CSV file of the reservoir polygon associated with dams in West Africa and their attributes. |
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Notes: |
text/csv |
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Label: |
2026-02-19_Kouassi_WA_Reservoirs.zip |
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Text: |
Shapefile of the reservoir polygon associated with dams in West Africa and their attributes. |
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Notes: |
application/zipped-shapefile |
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Label: |
2026-02-19_Kouassi_WA_Dams.zip |
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Text: |
Shapefile of dam point locations in West Africa and their attributes. |
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Notes: |
application/zipped-shapefile |