Analysis of high streamflow extremes in climate change studies: How do we calibrate hydrological models?

Abstract

Abstract. Climate change impact studies on hydrological extremes often rely on the use of hydrological models with parameters inferred by using observational data of daily streamflow. In this work we show that this is an error prone procedure when the interest is to develop reliable Empirical Cumulative Distribution Function curves of annual streamflow maximum. As an alternative approach we introduce a methodology, coined Hydrological Calibration of eXtremes (HyCoX), in which the calibration of the hydrological model is carried out by directly targeting the probability distribution of high flow extremes. In particular, hydrological simulations conducted during a reference period, as driven by climate models’ outputs, are constrained to maximize the probability that the modeled and observed high flow extremes belong to the same population. The application to the Adige river catchment (southeastern Alps, Italy) by means of HYPERstreamHS, a distributed hydrological model, showed that this procedure preserves statistical coherence and produce reliable quantiles of the annual maximum streamflow to be used in assessment studies.