Abstract
Reservoirs play an important role in relation to water security, flood risk, hydropower and natural flow regime. This study derives a novel dataset with a long-term daily water-balance (reservoir volume, inflow, outflow, evaporation and precipitation) of headwater reservoirs and storage dynamics across the globe. The data is generated using cloud computing infrastructure and a high resolution distributed hydrological model wflow_sbm. Model results are validated against earth observed surface water area and in-situ measured reservoir volume and show an overall good model performance. Simulated headwater reservoir storage indicate that 19.4–24.4 % of the reservoirs had a significant decrease in storage. This change is mainly driven by a decrease in reservoir inflow and increase in evaporation. Deployment on a kubernetes cloud environment and using reproducible workflows shows that these kind of simulations and analyses can be conducted in less than a day.
| Original language | English |
|---|---|
| Article number | 172678 |
| Number of pages | 18 |
| Journal | Science of the Total Environment |
| Volume | 931 |
| DOIs | |
| Publication status | Published - 25 Jun 2024 |
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Wflow_sbm simulation results underlying the publication: Simulation of long-term dynamics of headwater reservoirs across the globe using public cloud computing infrastructure
Weerts, A. H. (Creator), van der Laan, E. (Creator) & Hazenberg, P. (Creator), Wageningen University & Research, 31 Jan 2024
DOI: 10.4121/6f7fa018-5498-4e44-be71-2878214695ca
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