Modelling water availability and water allocation strategies in the Scheldt basin: sub report 4-6. Evaluation of 4 hydrological rainfall-runoff models under climate change conditions
Velez, C.; Maroy, E.; Rocabado, I.; Pereira, F.; Nossent, J.; Mostaert, F. (2021). Modelling water availability and water allocation strategies in the Scheldt basin: sub report 4-6. Evaluation of 4 hydrological rainfall-runoff models under climate change conditions. Version 2.0. FHR reports, 00_162_4-6. Flanders Hydraulics Research: Antwerp. IX, 29 + 63 p. app. pp. https://dx.doi.org/10.48607/33
Part of: FHR reports. Flanders Hydraulics Research: Antwerp, more
In the framework of the water allocation projects there are four hydrological models (NAM, PDM,VHM and WETSPA) calibrated for the region of Flanders. The aim of the models is to generate the flows needed as input in the basin model in other to analyze water allocation problems and generate strategies. It is also expected to use the hydrological models to analyze possible impacts of climate variability in the context of water allocation. To realize that, the models are forced with projected climate variables that are frequently out of the range of the data used in the calibration process. Thus models are force to extrapolate conditions for which the parameterization is or may not be optimal. This may bring errors in the projection of climate effects. The problem assessing the performance of the models is that there is not data available in the future to compare with. The aim of this document is to present the proposed approach for testing the capacity of the calibrated hydrological models to project the climate change effects in the context of water allocation for Flanders. The proposed testing framework combine the use of historical data through an adapted form of Differential Split Sample test (Refsgaard et al., 2014) with and approach that use the relative change of statistical properties of flows between historical data and the projected data (van Steenbergen and Willems, 2012). To assess the model we use a robustness criteria based on a Log Nash-Sutcliffe, BIAS on cumulative volumes and relative changes based on Q50/Q90 estimated from the duration curve.
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