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Author: Bronstert, A. × End date: 2024 × Start date: 2020 × Start date: 1990 × DDC: 550 ×

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Now showing 1 - 3 of 3
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    The role of spatial variability of soil moisture for modelling surface runoff generation at the small catchment scale
    (Göttingen : Copernicus GmbH, 1999) Bronstert, A.; Bárdossy, A.
    The effects of spatial variability of soil moisture on surface runoff generation at the hillslope and small catchment scale were studied. The model used is physically based accounting for the relevant hydrological processes during storm runoff periods. A case study investigating the effects on runoff generation in a loessy small catchment is presented. In this study the storm rainfall response was modelled using different distribution patterns of the initial soil moisture content, and where different initial soil moisture fields were generated by using both interpolation methods and stochastic simulation methods. It is shown that spatial variability of pre-event soil moisture results in an increase in runoff production compared to averaged values. It is of particular importance to note the combined organised/stochastic variability features, that is, the superposition of systematic and random features of soil moisture dominate local generation of surface runoff. In general one can say that the stronger the organised heterogeneity is, the more important is an adequate and refined interpolation technique which is capable of accounting for complex spatial trends. The effects of soil moisture variations are of particular importance for storms, where the produced runoff volume is just a small fraction of precipitation.
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    Assessment of climate change impacts on water resources in three representative ukrainian catchments using eco-hydrological modelling
    (Basel : MDPI AG, 2017) Didovets, I.; Lobanova, A.; Bronstert, A.; Snizhko, S.; Maule, C.F.; Krysanova, V.
    The information about climate change impact on river discharge is vitally important for planning adaptation measures. The future changes can affect different water-related sectors. The main goal of this study was to investigate the potential water resource changes in Ukraine, focusing on three mesoscale river catchments (Teteriv, UpperWestern Bug, and Samara) characteristic for different geographical zones. The catchment scale watershed model-Soil and Water Integrated Model (SWIM)-was setup, calibrated, and validated for the three catchments under consideration. A set of seven GCM-RCM (General Circulation Model-Regional Climate Model) coupled climate scenarios corresponding to RCPs (Representative Concentration Pathways) 4.5 and 8.5 were used to drive the hydrological catchment model. The climate projections, used in the study, were considered as three combinations of low, intermediate, and high end scenarios. Our results indicate the shifts in the seasonal distribution of runoff in all three catchments. The spring high flow occurs earlier as a result of temperature increases and earlier snowmelt. The fairly robust trend is an increase in river discharge in the winter season, and most of the scenarios show a potential decrease in river discharge in the spring.
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    Three perceptions of the evapotranspiration landscape: Comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances
    (Chichester : John Wiley and Sons Ltd, 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.