A Deterministic Combinatorial Approach to Investigate Interactions of Soil Hydraulic Parameters on River Flow Modelling

Hydrological modeling is essential for the sustainable management of watershed systems. Physically based models like MOHID-Land simulate soil water dynamics using Richards’ equation, parameterized through the van Genuchten–Mualem (VGM) model. Although the sensitivity of individual VGM parameters—residual water content (θr), saturated water content (θs), pore size distribution (n), inverse of air entry pressure (α), and saturated hydraulic conductivity (Ksat)—is well documented, their combined effects remain underexplored. This study assessed both isolated and joint impacts of these parameters through a deterministic ±10% perturbation scheme, resulting in 31 unique parameter combinations. Model performance was evaluated using the Nash–Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS). Full-parameter interaction achieved the best results (NSE = 0.50, PBIAS = 25.32), compared to the uncalibrated baseline (NSE = 0.01, PBIAS = 34.06). The pair θs and n emerged as the most influential. Adding secondary parameters to this core pair yielded only marginal performance gains, while removing them from the full set caused similarly marginal declines. These findings reveal a hierarchical sensitivity structure, emphasizing θs and n as key targets for calibration. Prioritizing this pair enables a more efficient soil calibration process, preserving model accuracy while reducing computational cost by limiting parameter space exploration.