2007, Conradt, T., Kaltofen, M., Hentschel, M., Hattermann, F.F., Wechsung, F.

This second part of the paper presents the details of the eco-hydrological model SWIM simulating the natural water supply and its coupling to WBalMo, a water management model. Based on the climate scenarios of the STAR model, SWIM simulates the natural water and matter fluxes for the entire Elbe River area. All relevant processes are modelled for hydrotopes and the resulting discharges are accumulated in subbasins. The output data are input for the water management model WBalMo and the quality models Moneris and QSim. WBalMo takes storage management, inputs and withdrawals into account and analyses how demands by industry, power plants and households will be met at changing natural supply conditions. Some of the first results shall be presented here.

2020, Lehmann, J., Kretschmer, M., Schauberger, B., Wechsung, F.

Wheat production plays an important role in Morocco. Current wheat forecast systems use weather and vegetation data during the crop growing phase, thus limiting the earliest possible release date to early spring. However, Morocco's wheat production is mostly rainfed and thus strongly tied to fluctuations in rainfall, which in turn depend on slowly evolving climate dynamics. This offers a source of predictability at longer time scales. Using physically guided causal discovery algorithms, we extract climate precursors for wheat yield variability from gridded fields of geopotential height and sea surface temperatures which show potential for accurate yield forecasts already in December, with around 50% explained variance in an out-of-sample cross validation. The detected interactions are physically meaningful and consistent with documented ocean-atmosphere feedbacks. Reliable yield forecasts at such long lead times could provide farmers and policy makers with necessary information for early action and strategic adaptation measurements to support food security. ©2020. The Authors.

2007, Hattermann, F.F., Gömann, H., Conradt, T., Kaltofen, M., Kreins, P., Wechsung, F.

Central Europe, the focus region of this study, is a region in transition, climatically from maritime to continental and politically from formerly more planning-oriented to more market-oriented management regimes, and in terms of climate change from regions of increasing precipitation in the west and north of Europe to regions of decreasing precipitation in central and southern Europe. The Elbe basin, a trans-boundary catchment flowing from the Czech Republic through Germany into the North Sea, was selected to investigate the possible impacts of global change on crop yields and water resources in this region. For technical reasons, the paper has been split into two parts, the first showing the overall model concept, the model set-up for the agricultural sector, and first results linking eco-hydrological and agro-economic tools for the German part of the basin. The second part describes the model set-up for simulating water supply and demand linking eco-hydrological and water management tools for the entire basin including the Czech part.

2011, Otto-Banaszak, I., Matczak, P., Wesseler, J., Wechsung, F.

We argue that differences in the perception and governance of adaptation to climate change and extreme weather events are related to sets of beliefs and concepts through which people understand the environment and which are used to solve the problems they face (mental models). Using data gathered in 31 in-depth interviews with adaptation experts in Europe, we identify five basic stakeholder groups whose divergent aims and logic can be related to different mental models they use: advocacy groups, administration, politicians, researchers, and media and the public. Each of these groups uses specific interpretations of climate change and specifies how to deal with climate change impacts. We suggest that a deeper understanding and follow-up of the identified mental models might be useful for the design of any stakeholder involvement in future climate impact research processes. It might also foster consensus building about adequate adaptation measures against climate threats in a society.

2013, Conradt, T., Wechsung, F., Bronstert, A.

A problem encountered by many distributed hydrological modelling studies is high simulation errors at interior gauges when the model is only globally calibrated at the outlet. We simulated river runoff in the Elbe River basin in central Europe (148 268 km2) with the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model). While global parameter optimisation led to Nash-Sutcliffe efficiencies of 0.9 at the main outlet gauge, comparisons with measured runoff series at interior points revealed large deviations. Therefore, we compared three different strategies for deriving sub-basin evapotranspiration: (1) modelled by SWIM without any spatial calibration, (2) derived from remotely sensed surface temperatures, and (3) calculated from long-term precipitation and discharge data. The results show certain consistencies between the modelled and the remote sensing based evapotranspiration rates, but there seems to be no correlation between remote sensing and water balance based estimations. Subsequent analyses for single sub-basins identify amongst others input weather data and systematic error amplification in inter-gauge discharge calculations as sources of uncertainty. The results encourage careful utilisation of different data sources for enhancements in distributed hydrological modelling.

2011, Wechsung, F., Gerstengarbe, F.W., Conradt, T., Gräfe, P., Hattermann, F., Hauf, Y., Lüttger, A., Werner, P.C., Walter, C.

[no abstract available]