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Climate change impact studies are associated with error propagation and amplification of uncertainties through model chains from global climate models down to impact (e.g. hydrological) models. The effect of water management, which reduces discharge variability, is often not considered in climate change impact studies. Here, we investigated how water resources management influences discharge variability and uncertainty propagation of climate change scenarios by combining the analyses of observed flow records and model-based climate change impact simulations. Two neighbouring catchments, the Schwarze Elster River (Germany) and the Spree River (Germany and Czech Republic) which are similar in climate, topography and land use, but different in terms of water resources management were chosen as study area. The intense water resources management in the Spree River catchment includes a high reservoir capacity, water use in terms of mining discharges and water withdrawals by power plants as well as water transfers.
The analysis of historical flow records focusses on variability indices (Parde index, Richards-Baker-Flashiness Index, Interquartile Ratio and Baseflow Index). The climate change impact simulations were carried out using a model cascade of (i) the statistical regional model STAR (100 stochastically generated realizations each for 3 scenarios with different prescribed temperature trend), (ii) the hydrological models SWIM and EGMO, and (iii) the water resources management model WBalMo.
The analysis of the observed discharges reveals that the annual discharge variability in the Spree catchment is dominated by mining activities rather than natural rainfall-runoff processes. Due to the high reservoir capacity in the Spree catchment its discharge is characterised by less seasonality and short-term variability compared to the Schwarze Elster. Simulations with climate change scenarios assuming increasing temperature and decreasing precipitation result in pronounced reductions of discharge in both catchments. The differences in potential natural discharges between the Schwarze Elster and the Spree catchments as projected by the hydrological models SWIM and EGMO are marginal. The uncertainties related to the climate projection are propagated through the hydrological models. In the Schwarze Elster catchment, the managed discharges simulated by WBalMo are comparable to the potential natural discharges. In the Spree River however, the short-term variability is moderated by water resources management and managed discharge under climate change is less affected by amplification of uncertainties through model chains.
The results of the study, which combines the analyses of observed flow records and model-based climate change impact simulations, imply that generally, effective water resources management reducing discharge variability hence also reduces uncertainty related to climate change impacts on river discharge. Catchments with a high storage ratio are thus less vulnerable to changing climate conditions. This underlines the role of water resources management in coping with climate change impacts. Yet, due to decreasing reservoir volumes in drought periods, reservoir management alone cannot compensate strong changes in climate conditions over long time periods.
The water balance of the Rivers Spree, Schwarze Elster and Lusatian Neisse is profoundly disturbed due to large-scale open-cast lignite mining activities and water management. Together with continental climate conditions this affects
water resources and water users in the region. Driven by scenarios of the regional climate model STAR which assume increasing temperature and decreasing precipitation, two hydrological models, the Soil and Water Integrated Model
SWIM and the catchment model EGMO simulate declining natural discharges in the region. Thus, decreasing managed discharges are simulated with the long term water management model WBalMo. The refinement of the simulation time step of WBalMo from months to weeks improves the consideration of climate variability and is also associated with higher simulated managed discharges in
early summer. Management scenarios in terms of a reduced outlet capacity of a mining lake reservoir result in higher releases from other reservoirs and slightly
reduced summer discharges in downstream river sections.
The Soil and Water Integrated Model (SWIM) was used to assess potential climate and land-use change impacts in the Central European catchments of Schwarze Elster, Spree and Lusatian Neisse which are heavily influenced by opencast lignite mining. To account for potential climate change, scenarios of two statistical regional climate models, STAR and WettReg, were used. Regional anthropogenic change was considered in terms of increasing cultivation of energy crops (oilseed rape, silage maize, sunflower and sorghum) and decreasing mining activities (decreasing groundwater depression cone). In the climate scenarios, decreased natural discharge, by up to 60% in the long-term average, was simulated. In simulations with climate scenarios and oilseed rape, this effect is halved; the other energy crops have a small additional impact on discharge. The decreasing groundwater depression cone slightly compensates for climate change impacts. Overall, potential impacts of regional anthropogenic activities are secondary to those of climate change.