Quantifying key parameter sensitivities for water table depth in hydrological schemes of CoLM-PSUADE

Abstract. Accurately representing groundwater dynamics in land surface models (LSMs) is crucial for understanding water-energy cycles and assessing water resources. However, most LSMs lack systematic sensitivity analyses of parameters regulating water table depth (WTD). This study couples the Common Land Model (CoLM) with Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE) in a single-point framework to facilitate systematic parameter analysis and calibration aimed at improving WTD simulation. The CoLM-PSUADE framework was then applied to evaluate groundwater-related parameters using WTD observations from the Gongga Mountain site. A comprehensive analysis integrating qualitative sensitivity analysis, quantitative sensitivity analysis, and parameter optimization techniques was conducted to evaluate the sensitivity of 56 parameters associated with key hydrological processes and to determine their optimal ranges. The results indicate that eight parameters can be identified as robustly sensitive, including those controlling unsaturated soil water movement (56-soil_alpha, 53-soil_n), subsurface runoff (40-rsubmax), plant hydraulic processes (49-beta, 45-krmax, 46-ck0), and net surface water infiltration (4-alpha_rain, 10-rhol_nir). Among them, the subsurface runoff parameter r_sub,max exhibits a well-defined optimal range (on the order of 10⁻⁴) and can regulate both the magnitude of subsurface runoff and its decay with increasing WTD when combined with another empirical parameter in the SIMTOP (Simple TOPMODEL-based) scheme, f_drai, thereby exerting strong control on WTD. The soil hydraulic parameter α shows the highest sensitivity. It regulates unsaturated hydraulic conductivity and soil water retention, thereby exerting a dominant influence on the variability and lagged response of WTD. Based on these findings, a stepwise calibration strategy is recommended, in which the subsurface runoff parameters (r_sub,max and f_drai) are first adjusted to constrain the mean WTD, followed by optimization of other key parameters, such as α, to improve the temporal dynamics of WTD. It is demonstrated that CoLM-PSUADE provides a useful tool for sensitivity-guided parameter optimization in high-dimensional LSMs and hydrological models.