Abstract
Abstract. To precisely map the changes in hydrologic response of catchments (e.g. water balance, reactivity or extremes), we need sensitive and interpretable indicators. In this study we defined nine hydrologically meaningful signature indices: five indices were sampled on the flow duration curve, four indices were closely linked to the distribution of event runoff coefficients. We applied these signature indices to the output from a hydrologic catchment model for three different catchments located in the Nahe basin (Western Germany) to detect differences in runoff behavior resulting from different meteorological input data. The models were driven by measured and simulated (COSMO-CLM) meteorological data. It could be shown that the application of signature indices is a very sensitive tool to assess differences in simulated runoff behavior resulting from climatic data sets of different sources. Specifically, the selected signature indices allow assessing changes in water balance, vertical water distribution, reactivity, seasonality and runoff generation. These indices showed that the hydrological model is very sensitive to biases in mean and spatio-temporal distribution of precipitation and temperature because it acts as a filter for the meteorological input. Besides model calibration and model structural deficits, we found that bias correction of temperature fields and further adjustment of bias correction of precipitation fields is absolutely essential. We conclude that signature indices can act as indirect "efficiency measures" or "similarity measures" for output from regional or local climate models.
Highlights
The world is presently facing rapid changes to the climate
To demonstrate the discriminating power of the nine signature indices, we apply the methodology for four different cases: (1) Assessment of model error, (2) Assessment of bias correction, (3) Assessment of CCLM control run and (4) Detection of climate change signal in the CCLM data set
Simulated runoff for Gensingen is much higher than the measured one resulting in a large positive bias for 8 of the 9 indices. This can be explained by incorrect model calibration as well as by incorrect runoff measurements at the gaging station Gensingen
Summary
The world is presently facing rapid changes to the climate. The understanding and prediction of related hydrologic changes is one main question that hydrologists face today (Bloschl and Montanari, 2010; Schaefli et al, 2011). It is essential that we precisely map the changes in hydrologic response of catchments (e.g. water balance, reactivity or extremes). In this context, hydrological models are applied to detect the impact of a changing climate on the hydrology of large basins (Mahmoud et al, 2009). Sangati et al (2009) evaluated the effects of different spatial resolutions in meteorological forcing on modelling of flash floods. They concluded that in their study a correct estimate of rainfall volume is not sufficient for accurate reproduction of flash flood events characterised by large spatial rainfall variability. Piani et al (2010) conclude that precipitation and temperature fields simulated by regional climate models are defective and introduce significant
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