Marc Scheibel (Germany) 1; Paula Lorza (Germany) 1; Eleni Teneketzi (Germany) 1; Tim Aus Der Beek (Germany) 2; Rike Becker (Germany) 2; Corinna Wilmers (Germany) 2
1 - Wupperverband; 2 - IWW
The occurrence of flooding and dry periods on the Wupper catchment has increased in the last decades together with the precipitation regime shifting. In the frame of the Horizon 2020 project BINGO (Bringing INnovation to onGOing water management), the effects of climate change in combination with land and water use scenarios on the water cycle in the Wupper River Basin are investigated. Special focus is given to identifying historical and future trends and extreme events.
Past hydro-meteorological extreme dry periods are evaluated based on historical meteorological data. Indices like SPI and SPEI are estimated for different time scales to determine if they were abnormally dry or wet. These indices are also estimated for medium-term climate predictions (MiKlip, time frame 2015-2024) and long-term climate projections (RCPs scenarios, time-frame 2006-2100). Thus, future abnormal dry periods can be identified, and results from MiKlip and RCPs scenarios can be compared within the next decade. Simulations of storage volume at GDT are performed for past and future conditions, using the water-balance, reservoir-oriented hydrological model. For past conditions, the model is driven with ground data and different water use scenarios. For future conditions, simulations are carried out with different climate change and predicted land and water use scenarios. The resulting simulated storage is correlated with the calculated indices (for past and future conditions). Estimation of different indices have proven to be a robust method for comparison between different data sets. This approach can be applied to other research sites worldwide, serving as a tool which supports decision making processes for reservoir management.
The methodology is validated based on observed volume. For validation and uncertainty assessment of future climate scenarios, the Soil & Water Assessment Tool (SWAT) was setup to simulate inflow rates to GDT. The results are compared with TALSIM simulations at the reservoir inlet. Thus, potential model uncertainties can be identified and more reliable predictions can be made.
Results indicate an increment in variability of annual inflow rates. A shift of dry summer months from early to late summer with decreasing inflow rates is expected; winter months in turn are likely to show increased inflow. Consequently, effectively managing the GDT will become more complex.
Uncertainties in climate data predictions are one of the greatest challenges. The strength of this study is the comparison of different data sets with statistical methods to test the significance of predicted climate change impacts and likelihood of occurrence of extreme events.