Global Dam Storage (GDS)

Global Dam Storage (GDS) dataset and derivation code Overview This repository contains the Global Dam Storage (GDS) dataset, a monthly reservoir storage series developed to evaluate and improve the representation of reservoir operations in global hydrological models (GHMs). This dataset was created by synthesising satellite-derived reservoir surface area time series from the Global Reservoir Surface Area Dataset (GRSAD) (Zhao and Gao, 2018) with bathymetric relationships from the Global Reservoir Bathymetry Dataset (GRDL) (Hao et al. 2024). Repository contents and their descriptions GDS.xlsx: The GDS monthly storage time series for some 7,229 dams with a GRanD ID. All storage values are provided in Million Cubic Meters (MCM). GDS.xlsx structure: Each column corresponds to a specific reservoir, with the column header denoting the reservoir's unique GRanD ID. GDS_gen_v1.py: The Python script used to merge the source datasets, optimise reservoir bathymetry, and extract the final GDS dataset. SaGHM_python_setup.yml: A Conda environment configuration file ensuring the exact software dependencies and versions are available for complete reproducibility. Readme.rtf: Detailed instructions on folder structure and script usage. References Hao, Zhen, Fang Chen, Xiaofeng Jia, et al. 2024b. ‘GRDL: A New Global Reservoir Area‐Storage‐Depth Data Set Derived Through Deep Learning‐Based Bathymetry Reconstruction’. Water Resources Research 60 (1): e2023WR035781. https://doi.org/10.1029/2023WR035781. Zhao, Gang, and Huilin Gao. 2018. ‘Automatic Correction of Contaminated Images for Assessment of Reservoir Surface Area Dynamics’. Geophysical Research Letters 45 (12): 6092–99. https://doi.org/10.1029/2018GL078343.