Preprints
https://doi.org/10.5194/nhess-2020-429
https://doi.org/10.5194/nhess-2020-429

  20 Jan 2021

20 Jan 2021

Review status: this preprint is currently under review for the journal NHESS.

Assessing short-term climate change impacts on water supply at the Wupper catchment area, Germany

Maria Paula Lorza-Villegas1, Rike Becker2, Marc Scheibel1, Tim aus der Beek3, and Jackson Roehrig4 Maria Paula Lorza-Villegas et al.
  • 1Department for Water Resources & Flood Risk Management, Wupper Association (Wupperverband), Wuppertal, Germany
  • 2Department for Hydrometeorology & Flood Risk Management, EGLV (Emschergenossenschaft und Lippeverband), Essen, Germany
  • 3IWW Water Centre, University of Duisburg-Essen, Duisburg, Germany
  • 4Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), Cologne University of Applied Sciences, Cologne, Germany

Abstract. The occurrence of dry periods on the Wupper catchment has increased in the last decades in conjunction with the shifting of the precipitation regime. In the frame of the Horizon 2020 project BINGO (Bringing INnovation to onGOing water management), the effects of climate change scenarios on the water cycle in the Wupper catchment area were investigated. To quantify these effects, a set of hydrological models (NASIM and SWAT) has been set-up, calibrated, and validated for the upper part of the Dhünn River catchment area – Wupper River's main tributary. This sub-catchment corresponds to one of the inflows to the Große Dhünn Reservoir (GDR), the second largest drinking water reservoir in Germany. Both models were driven with climate data from decadal predictions, which have been selected instead of IPCC-RCP scenarios, as they provide a more realistic assumption of climate variability for the next 10 years. Ten decadal members based on the MiKlip (Mittelfristige Klimaprognose – medium-term climate prediction) framework have been prepared for the time span of 2015 to 2024. Additionally, a simulation with TALSIM-NG (a reservoir-oriented hydrological model) was carried out to obtain future reservoir storage. Special focus was given to identify observed trends and compare them to future trends. Past hydro-meteorological extreme dry periods were evaluated based on observed data. Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), and Standardized Runoff Index (SRI) were estimated for different seasons to determine if they were abnormally dry or wet. SPI, SPEI, and SRI were also calculated with decadal predictions to evaluate future extreme dry periods. Uncertainties in climate data predictions are one of the greatest challenges. Observed and forecast time series were compared by means of statistical tests in order to assess uncertainties in climate data predictions. Also, the application of two hydrological models aims to determine potential uncertainties, so that predictions are more reliable. Results indicate that SRI might be more appropriate to estimate drought periods for the study area in the frame of reservoir management – where inflow rates are of crucial importance – as this index quantifies losses in runoff formation processes. In terms of inflow rates to GDR, future changes indicate a reduction in runoff for the spring season, while an increment during winter. On the other hand, a clear change in pattern for fall and summer seasons remains uncertain. Simulations of GDR reservoir volume with different climate scenarios show that water stress by the end of 2024 is not unlikely, so sustainable adaptation measures should be further considered. Effectively managing the GDR will become consequently more complex.

Maria Paula Lorza-Villegas et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Maria Paula Lorza-Villegas et al.

Maria Paula Lorza-Villegas et al.

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Short summary
This study presents an example of a small-scale climate change analysis for a local water association, and how these results can provide valuable information for improved reservoir management. Results indicate a reduction in runoff for the spring season, while an increment during winter. Simulations of reservoir volume show that water stress by the end of 2024 is not unlikely, so sustainable adaptation measures should be considered. This approach can be applied to other reservoirs in the region.
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