Spatial Scale Resolution of Prognostic Hydrological Models: Simulation Performance and Application in Climate Change Impact Assessment

In this paper, long-term hydrological response of a watershed to climate change was investigated taking into account the spatial scale effect on the performance of hydrological models. A water balance model was used in which variations of soil moisture, snow budget, deep infiltration and interactions with groundwater resources were modeled. Four various combinations of sub-catchment delineation, altitudinal discretization and division into square-shaped grids were tested for semi-distributed water balance modeling of a basin located in southwest of Iran, namely Roodzard Basin, with arid and semiarid climate based on Köppen-Geiger climate classification. The results showed improvement in the model performances when spatial variations of the meteorological data and topographic characteristics of the basin were incorporated in the modeling process. The effects of spatial scale resolution dependency were evaluated in projecting streamflow for various climate change scenarios. The results showed that finer resolution of grid cells in the semi-distributed model does not necessarily result in more accurate estimation of monthly streamflows and altitudinal discretization provides almost same accuracy as the results of grid-based models. Moreover, probability distribution of projections obtained from water balance models for A2 and B2 of Special Report on Emissions Scenarios (SRES) scenarios presented less coefficient of variation and skewness compared with historical observations.