Abstract
The aim of this study is to estimate likely changes in flood indices under a future climate and to assess the uncertainty in these estimates for selected catchments in Poland. Precipitation and temperature time series from climate simulations from the EURO-CORDEX initiative for the periods 1971–2000, 2021–2050 and 2071–2100 following the RCP4.5 and RCP8.5 emission scenarios have been used to produce hydrological simulations based on the HBV hydrological model. As the climate model outputs for Poland are highly biased, post processing in the form of bias correction was first performed so that the climate time series could be applied in hydrological simulations at a catchment-scale. The results indicate that bias correction significantly improves flow simulations and estimated flood indices based on comparisons with simulations from observed climate data for the control period. The estimated changes in the mean annual flood and in flood quantiles under a future climate indicate a large spread in the estimates both within and between the catchments. An ANOVA analysis was used to assess the relative contributions of the 2 emission scenarios, the 7 climate models and the 4 bias correction methods to the total spread in the projected changes in extreme river flow indices for each catchment. The analysis indicates that the differences between climate models generally make the largest contribution to the spread in the ensemble of the three factors considered. The results for bias corrected data show small differences between the four bias correction methods considered, and, in contrast with the results for uncorrected simulations, project increases in flood indices for most catchments under a future climate.
Highlights
Future flood hazard projections are essential for flood risk management and adaptation to climate change
The climate projections used for such analyses are obtained from Global Climate Model (GCM) simulations, which are dynamically downscaled to a regional level using regional climate models (RCMs)
In the case of climatic variables, various characteristics that may influence hydrological indices could be selected for validation, and climatic variables which are relevant for flood indices include mean annual and monthly air temperature, annual and monthly sum of precipitation, maximum daily precipitation and 3-day accumulated annual maximum precipitation
Summary
Future flood hazard projections are essential for flood risk management and adaptation to climate change. The climate projections used for such analyses are obtained from Global Climate Model (GCM) simulations, which are dynamically downscaled to a regional level using regional climate models (RCMs). Despite considerable recent progress in global climate modelling, the variability and uncertainty of climate model outputs have not improved substantially (Knutti and Sedlacek 2013). In applying such projections to assess, for example, future changes in flooding, the question arises as to how other sources of uncertainty within the modelling chain add to the intrinsic uncertainty in the climate projections. How are simulations of catchmentscale hydrological processes affected by global- and regional- scale uncertainties when deriving estimates for changes in flood indices?
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