Published December 8, 2025
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Global dataset of sand dam features and geographical distribution across drylands.

Creators

  • 1. Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Florence, Italy. luigi.piemontese@unifi.it.
  • 2. University of Florence
  • 3. Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Florence, Italy.
  • 4. Department of Water and Climate (HYDR), Vrije Universiteit Brussels, Brussels, Belgium.
  • 5. Department of Physical Geography and Regional Geographical Analysis, University of Seville, Seville, Spain.
  • 6. University of Seville
  • 7. Institute for Environmental Studies (IVM), VU University Amsterdam, Deltares Institute, Delft, Netherlands.
  • 8. VU University Amsterdam
  • 9. UNESCO Chair in Hydropolitics, University of Geneva, Geneva, Switzerland.
  • 10. University of Geneva
  • 11. Institute for Environmental Sciences (ISE), University of Geneva, Geneva, Switzerland.
  • 12. Department of Civil Engineering, University of Texas at Arlington, Arlington, Texas, USA.
  • 13. Dabane Water Workshops, Bulawayo, Zimbabwe.
  • 14. Department of Biology, Eastern Mennonite University, Harrisonburg, Virginia, USA.
  • 15. School of Water, Energy and Environment, Cranfield University, Cranfield, UK.
  • 16. Department of Environmental Science, Auckland University of Technology, Aotearoa, New Zealand.
  • 17. Department of Civil Engineering and Construction Studies, Atlantic Technological University Sligo, Sligo, Ireland.
  • 18. Sand Dams Worldwide, London, UK.

Description

Sand dams are water infrastructure, built across ephemeral sandy rivers, that increase water supply by creating an artificial sandy aquifer upstream of the dam. Despite their effectiveness and recent traction in the research and development arena, empirical data on their distribution and characteristics are scattered and largely unreported. This gap represents a major barrier for understanding the large-scale potential of such a Nature-based Solution and for planning new installations. This paper presents a global dataset of sand dam locations and dimensions, developed collaboratively by research and development experts. We collected sand dam information from several sources, including local sand dam organizations. The data was reviewed and integrated through visual inspection in Google Earth. Although most georeferenced sand dams are from Eastern and Southern Africa, this dataset is a first global inventory and represents an invitation for others working in sand dams around the world to contribute their data. The dataset supports research on the effectiveness of sand dams and can aid practitioners with science-based criteria for sand dam development.
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Open Access

Licence Attribution (CC BY)
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