Abstract

Abstract. This paper aims to quantify the uncertainty in projections of future hydrological extremes in the Biala Tarnowska River at Koszyce gauging station, south Poland. The approach followed is based on several climate projections obtained from the EURO-CORDEX initiative, raw and bias-corrected realizations of catchment precipitation, and flow simulations derived using multiple hydrological model parameter sets. The projections cover the 21st century. Three sources of uncertainty are considered: one related to climate projection ensemble spread, the second related to the uncertainty in hydrological model parameters and the third related to the error in fitting theoretical distribution models to annual extreme flow series. The uncertainty of projected extreme indices related to hydrological model parameters was conditioned on flow observations from the reference period using the generalized likelihood uncertainty estimation (GLUE) approach, with separate criteria for high- and low-flow extremes. Extreme (low and high) flow quantiles were estimated using the generalized extreme value (GEV) distribution at different return periods and were based on two different lengths of the flow time series. A sensitivity analysis based on the analysis of variance (ANOVA) shows that the uncertainty introduced by the hydrological model parameters can be larger than the climate model variability and the distribution fit uncertainty for the low-flow extremes whilst for the high-flow extremes higher uncertainty is observed from climate models than from hydrological parameter and distribution fit uncertainties. This implies that ignoring one of the three uncertainty sources may cause great risk to future hydrological extreme adaptations and water resource planning and management.

Highlights

  • Hydrological models are useful in water resource planning and management, flood and drought prediction, assessments of catchment-scale impacts of climate change, and the understanding of system dynamics

  • The standard procedure consists of a chain of consecutive actions, starting from the choice of a general circulation model (GCM) driven by an assumed greenhouse gas emission scenario, through downscaling of climatic forcing to a catchment scale, e.g. using the regional climate model (RCM), hydrological modelling and estimation of hydrological extreme indices using statistical tools

  • Following the results presented by Demirel et al (2013a) the choice of the GCM/RCM has larger influence than the choice of the emission scenario on the projections of low-flow indices

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Summary

Introduction

Hydrological models are useful in water resource planning and management, flood and drought prediction, assessments of catchment-scale impacts of climate change, and the understanding of system dynamics. Research on the impact of climate changes on future hydrological extremes is usually performed by an application of hydrological models to the projected meteorological inputs under assumed future climate scenarios (Wilby and Harris, 2006; Honti et al, 2014). We cannot directly assess the impact of the first three sources of uncertainties on predictions of hydrological extremes in the future due to a lack of observations of future climate realizations. This is one of the reasons why the term projections is used instead of predictions (Honti et al, 2014). The introduction of conditioning based on available past observations of climatic and hydro-

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