Generating probabilistic estimates of hydrological response for Irish catchments using a weather generator and probabilistic climate change scenarios

摘要

In accounting for uncertainties in future simulations of hydrological response of a catchment, two approaches have come to the\udfore: deterministic scenario-based approaches and stochastic probabilistic approaches. As scenario-based approaches result in a\udwide range of outcomes, the role of probabilistic-based estimates of climate change impacts for policy formulation has been\udincreasingly advocated by researchers and policy makers. This study evaluates the impact of climate change on seasonal river\udflows by propagating daily climate time series, derived from probabilistic-based climate scenarios using a weather generator\ud(WGEN), through a set of conceptual hydrological models. Probabilistic scenarios are generated using two different techniques.\udThe first technique used probabilistic climate scenarios developed from statistically downscaled scenarios for Ireland, hereafter\udcalled SDprob. The second technique used output from 17 global climate models (GCMs), all of which participated in CMIP3, to\udgenerate change factors (hereafter called CF). Outputs from both the SDprob and the CF approach were then used in combination\udwith WGEN to generate daily climate scenarios for use in the hydrological models. The range of simulated flow derived with the\udCF method is in general larger than those estimated with the SDprob method in winter and vice versa because of the strong\udseasonality in the precipitation signal for the 17 GCMs. Despite this, the simulated probability density function of seasonal mean\udstreamflow estimated with both methods is similar. This indicates the usefulness of the SDprob or probabilistic approach derived\udfrom regional scenarios compared with the CF method that relies on sampling a diversity of response from the GCMs.\udIrrespective of technique used, the probability density functions of seasonal mean flow produced for four selected basins is wide\udindicating considerable modelling uncertainties. Such a finding has important implications for developing adaptation strategies at\udthe catchment level in Ireland