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West Africa Dams and Reservoirs Dataset

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Important usage condition: Use and redistribution are governed by CC BY 4.0. Review and comply with the license before using the data.
Persistent identifier
doi:10.60507/FK2/YLDK1Y
Published version
1.0
Publication date
2026-02-26
License
CC BY 4.0

Description

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.

Creators

Keywords

Dams, Reservoirs, Dataset, Water management, West Africa

Files

Before downloading: Use and redistribution are governed by CC BY 4.0. Review and comply with the license before using the data.
FileTypeBytesChecksum
2026-02-19_Kouassi_WA_Dams-Res_Dataset_Readme.txttext/plain20832MD5 87b45832bf5ecdd90e3106ebd6725bed
2026-02-19_Kouassi_WA_Dams.csvtext/csv261071MD5 046b106da1e3a57ec2f1c461fe411b26
2026-02-19_Kouassi_WA_Dams.zipapplication/zipped-shapefile132830MD5 a87f9b4ef2e96625b737ffac8595c138
2026-02-19_Kouassi_WA_Reservoirs.zipapplication/zipped-shapefile2936391MD5 7073b2869c32a095bc8b42db96e05076
2026-02-19_Kouassi_WA_Reservoirs.csvtext/csv233811MD5 6fcf66505d28f2a24a4a20191129d1c4
2026-02-02_Kouassi_WA_Dams-Res-dens_Comp-and-Orig.pngimage/png1527908MD5 ff9b9d472f23ff39cc63ac4ee21fbd9c

Citation

Kouassi, Valery Bessely Stanislas; Yao, Blé Amouna Fhorest; Soro, Gneneyougo Emile; Goula, Bi Tié Albert; Kelome, Nelly Carine; Klaus, Julian, 2026-02-26, West Africa Dams and Reservoirs Dataset, doi:10.60507/FK2/YLDK1Y, V1.0

Additional Dataverse fields

Id571
Dataset Typedataset
Internal Version Number55
Latest Version Publishing StateRELEASED
Release Time2026-02-26T07:06:04Z
Create Time2026-01-22T10:28:12Z
Citation Date2026-02-26
File Access RequestTrue

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Complete Dataverse metadata

Citation Metadata

Title title
West Africa Dams and Reservoirs Dataset
Author author
  1. Author Name
    Kouassi, Valery Bessely Stanislas
    Author Affiliation
    Department of Geography, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
    Author Identifier Scheme
    ORCID
    Author Identifier
    0009-0005-9360-5280
  2. Author Name
    Yao, Blé Amouna Fhorest
    Author Affiliation
    Unité de Formation et de Recherche Sciences et Gestion de l’Environnement, Université Nangui Abrogoua, Abidjan, Côte d’Ivoire
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0000-0002-3608-5734
    Expandedvalue
    Person Name
    Blé Amouna Fhorest, YAO
    @id
    https://orcid.org/0000-0002-3608-5734
    Scheme
    ORCID
    @type
    https://schema.org/Person
  3. Author Name
    Soro, Gneneyougo Emile
    Author Affiliation
    Unité de Formation et de Recherche Sciences et Gestion de l’Environnement, Université Nangui Abrogoua, Abidjan, Côte d’Ivoire
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0000-0002-1672-4797
    Expandedvalue
    Person Name
    Gneneyougo Emile, SORO
    @id
    https://orcid.org/0000-0002-1672-4797
    Scheme
    ORCID
    @type
    https://schema.org/Person
  4. Author Name
    Goula, Bi Tié Albert
    Author Affiliation
    Unité de Formation et de Recherche Sciences et Gestion de l’Environnement, Université Nangui Abrogoua, Abidjan, Côte d’Ivoire
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0000-0003-2484-0904
    Expandedvalue
    Person Name
    Bi Tié Albert, GOULA
    @id
    https://orcid.org/0000-0003-2484-0904
    Scheme
    ORCID
    @type
    https://schema.org/Person
  5. Author Name
    Kelome, Nelly Carine
    Author Affiliation
    Département des Sciences de la Terre, Université d’Abomey-Calavi, Abomey-Calavi, Benin
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0000-0002-5693-588X
    Expandedvalue
    Person Name
    KELOME, Nelly
    @id
    https://orcid.org/0000-0002-5693-588X
    Scheme
    ORCID
    @type
    https://schema.org/Person
  6. Author Name
    Klaus, Julian
    Author Affiliation
    Department of Geography, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
    Author Identifier Scheme
    ORCID
    Author Identifier
    0000-0002-6301-1634
Dataset Contact datasetContact
  1. Dataset Contact Name
    Kouassi, Valery
    Dataset Contact Affiliation
    University of Bonn
    Dataset Contact Email
    valerykouassi.vk@gmail.com
Ds Description dsDescription
  1. Ds Description Value
    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.
    Ds Description Date
    2025-12-30
Subject subject
  1. Earth and Environmental Sciences
Free Keyword freeKeyword
  1. Free Keyword Value
    Dams
  2. Free Keyword Value
    Reservoirs
  3. Free Keyword Value
    Dataset
  4. Free Keyword Value
    Water management
  5. Free Keyword Value
    West Africa
Language language
  1. English
Producer producer
  1. Producer Name
    West African Science Service Centre on Climate Change and Adapted Land Use
    Producer Affiliation
    Université d'Abomey-Calavi
    Producer Abbreviation
    WASCAL
    Producer URL
    https://wascal.org/fr/
    Producer Logo URL
    https://wascal.org/wp-content/uploads/2025/10/new-wascal-combined-logo2.jpg
  2. Producer Name
    Department of Geography
    Producer Affiliation
    University of Bonn
    Producer URL
    https://www.geographie.uni-bonn.de/en
    Producer Logo URL
    https://www.uni-bonn.de/en/++theme++unibonn.theme/images/logos/logo_desktop.svg
Grant Number grantNumber
  1. Grant Number Agency
    University of Bonn
    Grant Number Value
    Argelander Scholarships for doctoral candidates from universities in Africa, Latin America, and South/East Asia
  2. Grant Number Agency
    West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL)
    Grant Number Value
    WASCAL PhD Scholarship Programme
Depositor depositor
KOUASSI, Valery Bessely Stanislas
Date Of Deposit dateOfDeposit
2026-01-22
Date Of Collection dateOfCollection
  1. Date Of Collection Start
    2025-03-01
    Date Of Collection End
    2025-07-30
Kind Of Data kindOfData
  1. Aggregate Data
Software software
  1. Software Name
    Quantum Geographic Information System (QGIS)
    Software Version
    3.28.3
Related Datasets relatedDatasets
  1. Global Information System on Water and Agriculture of the Food and Agriculture Organization (FAO AQUASTAT). https://www.fao.org/aquastat/en/databases/dams
  2. 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/
  3. HydroLAKES. https://www.hydrosheds.org/products/hydrolakes
  4. GlObal GeOreferenced Database of Dams (GOODD). https://www.globaldamwatch.org/goodd
  5. Future Hydropower Reservoirs and Dams Database (FHReD). https://www.globaldamwatch.org/fhred
  6. Global Reservoirs and Dams version 1.3 (GranD V1.3). https://www.globaldamwatch.org/grand/
  7. Global River Obstruction Database version 1.1 (GROD v1.1). https://zenodo.org/records/5793918
  8. Reservoir and Lake Surface Area Timeseries (ReaLSAT). https://doi.org/10.5281/zenodo.7614815
  9. Georeferenced global Dams And Reservoirs (GeoDAR). https://zenodo.org/records/6163413
  10. Global Dam Tracker (GDAT). https://zenodo.org/records/7616852
  11. Global Dam Watch (GDW database (V1)). https://www.globaldamwatch.org/database
  12. Global Lakes/Reservoirs Surface Extent Dataset (GLRSED). https://zenodo.org/records/14190225
Other References otherReferences
  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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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