Impacts of climate change on the water regime of the Inn River basin – extracting adaptation-relevant information from climate model ensembles and impact modelling

Korck, J.; Danneberg, J.; Willems, W.

The Inn River basin is a highly relevant study region in terms of potential hydrological impacts of climate change and cross boundary water management tasks in the Alpine Space. Regional analyses in this catchment were performed within the EU co-funded project AdaptAlp. Objective of the study was to gain scientifically based knowledge about impacts of climate change on the water balance and runoff regime for the Inn River basin, this being fundamental for the derivation of adaptation measures.

An ensemble of regional climate projections is formed by combinations of global and regional climate models on the basis of both statistical and bias-corrected dynamical downscaling procedures. Several available reference climate datasets for the study region are taken into account. As impact model, the process-oriented hydrological model WaSiM-ETH is set up.

As expected, regional climate projections indicate temperature increases for the future in the study area. Projections of precipitation change are less homogenous, especially regarding winter months, though most indicate a decrease in the summer. Hydrological simulation results point towards climate induced changes in the water regime of the study region. The analysis of hydrological projections at both ends of the ensemble bandwidth is a source of adaptation relevant information regarding low-flow and high-flow conditions. According to a "drought-prone scenario", mean monthly low flow could decrease up to −40% in the time frame of 2071–2100. A "high-flow-increase-scenario" points towards an increase in mean monthly high flow in the order of +50% in the winter, whilst showing a decrease in autumn.

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Zitierform:

Korck, J. / Danneberg, J. / Willems, W.: Impacts of climate change on the water regime of the Inn River basin – extracting adaptation-relevant information from climate model ensembles and impact modelling. 2012. Copernicus Publications.

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