Selection of Bias Correction Methods to Assess the Impact of Climate Change on Flood Frequency Curves

Enrique Soriano,Luis Mediero,Carlos Garijo

doi:10.3390/w11112266

Abstract

Climate projections provided by EURO-CORDEX predict changes in annual maximum series of daily rainfall in the future in some areas of Spain because of climate change. Precipitation and temperature projections supplied by climate models do not usually fit exactly the statistical properties of the observed time series in the control period. Bias correction methods are used to reduce such errors. This paper seeks to find the most adequate bias correction techniques for temperature and precipitation projections that minimizes the errors between observations and climate model simulations in the control period. Errors in flood quantiles are considered to identify the best bias correction techniques, as flood quantiles are used for hydraulic infrastructure design and safety assessment. In addition, this study aims to understand how the expected changes in precipitation extremes and temperature will affect the catchment response in flood events in the future. Hydrological modelling is required to characterize rainfall-runoff processes adequately in a changing climate, in order to estimate flood changes expected in the future. Four catchments located in the central-western part of Spain have been selected as case studies. The HBV hydrological model has been calibrated in the four catchments by using the observed precipitation, temperature and streamflow data available on a daily scale. Rainfall has been identified as the most significant input to the model, in terms of its influence on flood response. The quantile mapping polynomial correction has been found to be the best bias correction method for precipitation. A general reduction in flood quantiles is expected in the future, smoothing the increases identified in precipitation quantiles by the reduction of soil moisture content in catchments, due to the expected increase in temperature and decrease in mean annual precipitations.

Highlights

Climate change projections predict reductions in the availability of water resources, as well as changes in the frequency and severity of extreme hydrological events [1]
The results of this study confirm the need for bias correction in temperature and precipitation projections to improve their fitting to observations
Mean monthly temperatures supplied by climate models in the control period are significantly lower than observed data

Summary

Introduction

Climate change projections predict reductions in the availability of water resources, as well as changes in the frequency and severity of extreme hydrological events [1]. Climate change will affect floods, which are the natural hazard that generates the largest damages in Europe [2]. The impact of climate change on the hydrological cycle can be assessed by using both climatic and hydrological models. Several studies and models have been developed. Most of such studies are focused on either monthly or annual scales [3]. A few studies have studied the impact of climate change on floods [4]

Objectives

Results

Conclusion