Assessing robustness of large-scale hydrological and sediment modeling using nested domains under current and changing climate

Continental and global dynamic hydrological models have emerged recently as tools for e.g. flood forecasting, large-scale climate impact analyses, and estimation of time-dynamic water fluxes into sea basins. One such tool is a dynamic process-based rainfall-runoff and water quality model, Hydrological Predictions for Environment (HYPE, see https://hypeweb.smhi.se/). We present and compare historical simulations of runoff, soil moisture, aridity, and sediment concentrations for three nested model domains using global (WWH), continental (Europe, E-HYPE), and national (Sweden, S-HYPE) catchment-based HYPE applications (Table 1). Future impacts on hydrological variables from changing climate were then assessed using the global and continental HYPE applications with ensembles based on three Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs). The comparison was carried out for ensemble averages as well as for individual GCMs to illustrate the variability and the need for robust assessments.

We illustrate how modeling across nested domains enables additional assessments of robustness in terms of projected impacts, modelling setups, and model performance criteria. After accounting for the spatial resolution, simulated historical runoff values were quite similar among the nested models while sediment concentrations varied considerably in spatial patterns. 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 shown to be valuable tools for e.g. first screenings of climate change effects and detection of spatial patterns and can be useful to provide information on current and future hydrological states at various domains. The challenges are (1) in deciding when we should use the large-scale models and (2) in interpreting the results, considering the uncertainty of the model results and quality of data especially at the global scale. Comparison across nested domains demonstrates the significance of scale and model performance and supports the need to use model ensembles for large-scale analyses instead of a single model.

Bartosova et al, 2021. Large-Scale Hydrological and Sediment Modeling in Nested Domains under Current and Changing Climate. Journal of Hydrologic Engineering 26, 05021009. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002078