RIBASIM-Simulated Danube River Discharge under Reference and "What-If" Scenarios
Authors/Creators
- 1. Department of Landscape, Water, Infrastructure, Institute of Hydraulic Engineering and River Research, BOKU University Vienna, Austria
- 2. Deltares, Delft, The Netherlands
- 3. Department of Landscape, Water, Infrastructure; Institute of Hydraulic Engineering and River Research; BOKU University Vienna, Austria
- 4. National Institute for Research and Development on Marine Geology and Geo-Ecology (GeoEcoMar), Bucharest, Romania
Description
This dataset provides simulated discharge data for the Danube River generated with the RIBASIM water allocation model. The hydrological input to RIBASIM was derived from simulations with the hydrological model wflow_sbm, performed in the framework of the DOORS Black Sea project (https://www.doorsblacksea.eu/) and combined with water allocation data (e.g., water demands) within RIBASIM. Simulated discharge values are provided for selected nodes along the Danube system for a reference period and for a set of future “what-if” scenarios. The reference simulation covers the period 2010–2020 and is denoted as REF. Future “what-if” scenarios represent a future horizon around 2050 and were produced by applying relative discharge changes, derived from existing literature, to the 2010–2020 reference time series. The RIBASIM model was run at a decadal time step, corresponding to approximately 10-day intervals. Data are provided for the 1st, 11th, and 21st day of each month. Discharge values are reported in m³/s. All worksheets contain the same set of model nodes, with separate worksheets for the reference simulation and each future scenario simulations. The dataset includes discharge values for sites and sectors, including low-flow nodes, critical sections, hydropower plants, nuclear power plants, and public water supply locations. Site identifiers have been anonymized. Dataset associated with manuscript currently under review at International Journal of River Basin Management.
Files
Files
(1.2 MB)
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md5:74ed03b6df4d4829b7caf01b28e7cf9a
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Additional details
Funding
Dates
- Submitted
-
2026