Bias correction of climate models for hydrological modelling – are simple methods still useful?

Abstract

ABSTRACTThe spatial climatic characteristics of the Himalayas are complex and a challenge for regional climate models (RCMs). There is no doubt that some form of correction before any application of RCM simulations is a must. In recent years, simple bias correction techniques have been overshadowed by more popular and complex bias correction techniques. In this study an attempt is made to compare the performance of a simple and of a comparatively complex correction technique for hydrological analysis at a monthly resolution in the Kaligandaki River Basin of Nepal. The research workflow consists of bias correction of temperature and precipitation using a simple technique (linear scaling) and a comparatively complex one (quantile mapping). The performance at monthly resolution is evaluated against observed meteorological data while a combined evaluation is made via hydrological model response analysis. The wetter and colder RCM estimates were significantly improved after bias correction. The hydrological modelling response also shows the importance of the bias correction of the RCMs. However, no significant difference was observed between the outputs of linear scaling and quantile mapping which exhibited almost identical performances. Hence, this study has a novel conclusion that a simple method, such as linear scaling, is sufficient for hydrological analysis at monthly resolution.