Global REservoir Inventory (GREI) and Reservoir Sedimentation Database

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Authors: Kai Liu, Chenyu Fan, Chunqiao Song
Cited by: 2

Abstract

This dataset includes the Global REservoir Inventory (GREI_v1), a comprehensive spatial database documenting the locations and attributes of over 550,000 global reservoirs (>0.001 km²), and the GREI_Sed_v1, which provides high-resolution estimates of reservoir sedimentation rates and storage loss. GREI_v1 includes core attributes such as reservoir surface area, location, and storage capacity, while GREI_sed_v1 estimates annual sedimentation rate using a machine-learning framework informed by 6,133 field-surveyed samples. This dual dataset fills a critical gap in global reservoir data, particularly for small and under-monitored reservoirs. It is designed to support research and management in water resources, hydrology, climate adaptation, and sustainability planning.The dataset package contains the following files:Spatial DatabasesGREI_v1.gdb: Global reservoir inventory containing the spatial distribution and associated attributes of reservoirs worldwide.GREI_Sed_v1.gdb: Global reservoir sedimentation database containing sedimentation estimates and associated attributes for reservoirs included in the GREI inventory.Supplementary TablesSedimentation_sample_sources.xlsx: Source information for the 6,133 field-surveyed sedimentation samples used for model development and validation.GREI_data_sources.xlsx: Summary of the datasets used to construct the GREI inventory and sedimentation database.GREI_data_dictionary.xlsx: Descriptions of variables, data types, units, and attribute definitions included in the dataset.

Publication details

Journal / source
Figshare
Publication date
14 January 2026
Document type
Dataset