Abstract

Bias-correction methods are commonly applied to climate model data in hydrological climate impact studies. This is due to the often large deviations between simulated and observed climate variables. These biases may cause unrealistic simulation results when directly using the climate model data as input for hydrological models. Our analysis of the EURO-CORDEX (Coordinated Downscaling Experiment for Europe) data for the Northwestern part of Germany showed substantial biases for all climatological input variables needed by the hydrological model PANTA RHEI. The sensitivity for climatological input data demonstrated that changes in only one climate variable significantly affect the simulated average discharge and mean annual peak flow. The application of bias correction methods of different complexity on the climate model data improved the plausibility of hydrological modeling results for the historical period 1971–2000. The projections for the future period 2069–2099 for high flows indicate on average small changes for representative concentration pathway (RCP) 4.5 and an increase of approximately 10% for RCP8.5 when applying non-bias corrected climate model data. These values significantly differed when applying bias correction. The bias correction methods were evaluated in terms of their ability to (a) maintain the change signal for precipitation and (b) the goodness of fit for hydrological parameters for the historical period. Our results for this evaluation indicated that no bias correction method can explicitly be preferred over the others.

Highlights

  • An intensification of the hydrological cycle due to climate change is likely, but varies in dependence of the geographic region and spatial scale [1]

  • The performance of the approach and linear scaling is significantly better than the applying bias-correction climate model data prior to the use as input data for other methods, whereas delta change shows a on much lower performance

  • Hydrological models seems necessary as it leads to simulations of hydrological processes that

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Summary

Introduction

An intensification of the hydrological cycle due to climate change is likely, but varies in dependence of the geographic region and spatial scale [1]. Changes in intensities and frequencies of precipitation related to global warming investigated both on the global [2] and regional scale [3,4,5] compared climate impact projections of river floods in Europe under climate change. In addition to this, investigations on smaller spatial scales are needed to identify flood endangered areas due to regional varying effects of climate change [6] These studies are necessary in order to develop specific adaptation measures of public authorities and local governments [7]. Huang et al [15] investigated the performance and impacts of BC on flood projections in Germany They applied the distribution mapping method on two different RCMs. In their study, 75% of the change directions (positive/negative) of flood discharge were not influenced by BC.

Observational Data
Study Area
General Procedure
Hydrological Model PANTA RHEI
Sensitivity Analysis for Climate Variables
Bias Correction for Hydrological Modeling
Linear Scaling
Power Transformation
Distribution Mapping
Delta Change
Evaluation of Bias-Correction Methods
X 1 X abs ng
Climatological and Hydrological Bias in the Historical Period
Result represent thethe deviations
Discussion and better
Full Text
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