Global distribution of small reservoirs and their role in surface water storage

Small on-farm reservoirs play a vital role in sustaining irrigation and livestock water demands, particularly in regions facing acute water scarcity (Aminzadeh et al., 2024). However, comprehensive understanding of their global distribution and contribution to local water budgeting and management remains limited. This research leverages high-resolution satellite data from Sentinel 1 and Sentinel 2 to develop a global database of small agricultural reservoirs (<0.1 km2) across geographic and climatic zones. Machine learning algorithms are employed to improve the accuracy of reservoir detection from satellite imagery. In addition to mapping the spatial and temporal distribution of these reservoirs, we estimate their storage capacity by correlating surface area and depth metrics. The study enables monitoring of surface water storages across scales thus offering critical insights into the role of small reservoirs in water budgeting and accounting, particularly in water-stressed regions of the world.

Subjects

Surface Water Storage

water reservoir detection

DDC Class

551: Geology, Hydrology Meteorology

333.7: Natural Resources, Energy and Environment

006.31: Machine Learning

Lizenz

https://creativecommons.org/licenses/by/4.0/

Publication version

publishedVersion

Name

EGU25-1571-print.pdf

Size

284.3 KB

Format

Adobe PDF

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Global distribution of small reservoirs and their role in surface water storage