Is hillslope-based catchment decomposition approach superior to hydrologic response unit (HRU) for stream-aquifer interaction modelling: Inference from two process-based coupled models

Abstract

To quantify the surface water-groundwater (SW-GW) exchange flux in a river basin, the inclusion of SW-GW interaction (SGI) process in the next generation earth system models is of growing concern among the hydrologic community that requires a trade-off among model complexity linking streamflow and groundwater flow domains, spatial heterogeneity, and computational demand. Although semi-distributed SGI models seem to be a plausible solution, the question is ‘what could be the effective way to decompose a river basin to assess the sub-surface flux’? Therefore, this study intends to search for a better alternative approach for catchment decomposition between the hillslope- and hydrologic response unit (HRU)-based SGI models; the inherent relationship between the decomposition level and model efficiency; and the appropriate spatial scale of decomposition for hillslopes and HRUs. The typical hydrological models chosen for this study are: the hillslope-based coupled Variable Parameter McCarthy-Muskingum–enhanced hillslope storage Boussinesq (VPMM-ehsB), and the HRU-based coupled Soil and Water Assessment Tool–MODular three-dimensional groundwater FLOW (SWAT-MODFLOW). These semi-distributed models are field-tested to model the streamflow accounting for lateral contributions along the river reach, baseflow, depth to water table, and the SGI flux. The results reveal that the VPMM-ehsB model with hillslope-grid based decomposition outperformed the SWAT-MODFLOW with the HRU-grid based hybrid decomposition in explaining the variance of the entire annual and low (non-monsoon) streamflow time series by 12% and 25%, respectively. The VPMM-ehsB approach has a faster (36%) simulation time than that of the SWAT-MODFLOW showing the potential of the hillslope decomposition approach in the VPMM-ehsB model over the HRU-based approach in the SWAT-MODFLOW for large-scale application in future earth system models.