Understanding Spatial Heterogeneity of Subsurface Flow using Physically based Hydrologic Connectivity

Hydrologic connectivity has been proposed as an important concept for understanding local processes in the context of catchment hydrology and can be defined as flow path continuity in surface and subsurface flow. It can also provide a missing linkage for preferential flow inferred from unexpected water and chemical migration, which cannot be accounted for completely through the current process-based hydrological models. Thus, we developed a hydrologic connectivity algorithm based on various physical controls to understand better spatially distributed subsurface flow and improve the parameterization scheme in hydrological modeling. The hydrologic connectivity is often dynamic because subsurface flow patterns across a domain could be connected or disconnected seasonally or depending on rainfall event or duration. In this study, we derived the dynamic connectivity using various physical controls (e.g., rainfall intensity and duration, surface and bedrock topography, soil, vegetation, and soil wetness patterns) through a multivariate linear function. The physically based hydrologic connectivity was also applied in model parameterization schemes to improve the prediction of subsurface flow in modeling. This proposed approach was tested at a watershed scale (Little Washita watershed) and showed better results to predict spatially distributed subsurface flow with an improvement of modeling capability.