Preprints
https://doi.org/10.5194/essd-2024-470
https://doi.org/10.5194/essd-2024-470
27 Nov 2024
 | 27 Nov 2024
Status: this preprint is currently under review for the journal ESSD.

GRILSS: Opening the Gateway to Global Reservoir Sedimentation Data Curation

Sanchit Minocha and Faisal Hossain

Abstract. Reservoir sedimentation poses a significant challenge to freshwater management, leading to declining storage capacity and inefficient reservoir operations for various purposes. However, trustworthy and independently verifiable information on declining storage capacity or sedimentation rates around the world is sparse and suffers from inconsistent metadata and curation to allow global-scale archiving and analyses. The Global Reservoir Inventory of Lost Storage by Sedimentation (GRILSS) dataset addresses this challenge by providing organized, well-curated and open-source data on sedimentation rates and capacity loss for 1,015 reservoirs in 75 major river basins across 54 countries. This publicly accessible dataset captures the complexities of reservoir sedimentation, influenced by regional factors such as climate, topography, and land use. By curating the information from numerous sources with disparate formats in a homogenized data structure, GRILSS serves as an invaluable resource for water managers, policymakers, and researchers for improved sediment management strategies. The open-source nature of GRILLS promotes collaboration and contributions from the global community to grow the dataset. By providing essential reference data on sedimentation to understand the global challenge of reservoir sedimentation, this GRILLS dataset represents a gateway for the global community to share sedimentation and storage loss data for sustainable operation of world’s reservoirs for future generations.

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Sanchit Minocha and Faisal Hossain

Status: open (until 03 Jan 2025)

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Sanchit Minocha and Faisal Hossain
Sanchit Minocha and Faisal Hossain

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Short summary
Trustworthy and independently verifiable information on declining storage capacity or sedimentation rates around the world is sparse and suffers from inconsistent metadata and curation to allow global-scale archiving and analyses. Global Reservoir Inventory of Lost Storage by Sedimentation (GRILSS) dataset addresses this challenge by providing organized, well-curated and open-source data on sedimentation rates and capacity loss for 1,015 reservoirs in 75 major river basins across 54 countries.
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