Large-Scale Hydrological and Sediment Modeling in Nested Domains under Current and Changing Climate

Abstract

Continental and global dynamic hydrological models have emerged recently as tools for large-scale analyses. One such tool is a dynamic process-based rainfall-runoff and water quality model called Hydrological Predictions for Environment (HYPE). This study presents and compares historical simulations of runoff and sediment concentrations for three nested-model domains using global, continental (Europe), and national (Sweden) catchment-based HYPE applications. Future impacts on runoff, soil moisture, and aridity from changing climate were assessed using the global and continental HYPE applications with three coupled model intercomparison project phase 5 (CMIP5) global climate models (GCMs). Simulated sediment concentrations varied considerably among the nested models in spatial patterns due to different data sources, whereas runoff values were more similar. Regardless of the variation, the global model was able to provide information on climate change impacts comparable to those from the continental and national models for hydrological indicators. Global hydrological models are thus valuable tools for, e.g., first screenings of climate change effects and detection of spatial patterns. Comparison across nested domains demonstrates the significance of scale that needs to be considered when interpreting the impacts alongside with model performance.