Cold Climates, Complex Hydrology: Can A Land Surface Model Accurately Simulate Deep Percolation?

Abstract. Cold regions present unique challenges for land surface models simulating deep percolation or potential groundwater recharge. Previous model evaluation efforts often overlooked these regions and did not account for various sources of uncertainties influencing model performance and its evaluation. This work addresses these limitations using high-resolution integrated lysimeter measurements to assess the performance of the SVS land surface model in a cold climate. SVS showed promise in the simulation of snowmelt and rainfall-driven deep percolation events. It also simulated daily snow depth well, with a correlation coefficient (r) greater than 0.94 and a mean-bias-error (MBE) smaller than 3.0 cm for most of the simulation period. The newly implemented soil-freezing scheme reasonably simulated the near-surface soil temperature (r = 0.89) with a slight cold bias (MBE = -0.8 °C). However, the model's inability to represent frozen soil infiltration and preferential flow resulted in a significant underestimation of percolation (r: 0.35, MBE: -0.8 mm·day^-1) and near-surface soil moisture during cold months (MBE: -0.058 m³ ·m^-3). Those findings highlight the importance of a comprehensive model evaluation for improving deep percolation modeling in cold regions. Such improvements can lead to more informed decision-making regarding groundwater resource management in a changing climate.