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. Considering rapid increases in the number of climate model simulations beingproduced by modelling centres, it is often infeasible to use all of them inclimate change impact studies. In order to thoughtfully select subsets ofclimate simulations from a large ensemble, several envelope-based methodshave been proposed. The subsets are expected to cover a similar uncertaintyenvelope to the full ensemble in terms of climate variables. However, it isnot a given that the uncertainty in hydrological impacts will be similarlywell represented. Therefore, this study investigates the transferability ofclimate uncertainty related to the choice of climate simulations tohydrological impacts. Two envelope-based selection methods, K meansclustering and the Katsavounidis–Kuo–Zhang (KKZ) method, are used to selectsubsets from an ensemble of 50 climate simulations over two watersheds withvery different climates using 31 precipitation and temperature variables.Transferability is evaluated by comparing uncertainty coverage betweenclimate variables and 17 hydrological variables simulated by a hydrologicalmodel. The importance of choosing climate variables properly when selectingsubsets is investigated by including and excluding temperature variables.Results show that KKZ performs better than K means at selecting subsets ofclimate simulations for hydrological impacts, and the uncertainty coverage ofclimate variables is similar to that of hydrological variables. The subset ofthe first 10 simulations covers over 85 % of total uncertainty. Asexpected, temperature variables are important for the snow-related watershed,but less important for the rainfall-driven watershed. Overall, envelope-basedselection of around 10 climate simulations, based on climate variables thatcharacterize the physical processes controlling the hydrology of thewatershed, is recommended for hydrological impact studies.

Transferability of climate simulation uncertainty to hydrological impacts