Quantifying key parameter sensitivities for water table depth in hydrological schemes of CoLM-PSUADE at a mountain forest site
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 evaluations of parameter sensitivities governing water table depth (WTD) simulations. This study coupled 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 optimization for 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 screening, quantitative validation, and parameter optimization techniques was conducted to evaluate the sensitivities of 56 parameters associated with key hydrological processes and identify their optimal ranges. The results identified eight sensitive parameters in the initial screening, 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). Additional experiments with independent random seeds revealed varying sensitivity rankings. In particular, the subsurface runoff parameter r sub,max exhibited sampling-dependent sensitivity but showed relatively high importance in the analysis. It exhibited a well-defined optimal range (on the order of 10 ⁻⁴ ) and regulated 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 showed the highest sensitivity. It regulated 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 was 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. This study demonstrated that CoLM-PSUADE provides a useful tool for sensitivity-guided parameter optimization in high-dimensional LSMs and hydrological models.
Versions
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BibTeX
@article{wu2026quantifying,
title = {{Quantifying key parameter sensitivities for water table depth in hydrological schemes of CoLM-PSUADE at a mountain forest site}},
author = {Tingting Wu and Shupeng Zhang and Xiaofan Yang and Yongjiu Dai},
journal = {Hydrology and Earth System Sciences},
year = {2026},
month = nov,
doi = {10.5194/hess-30-6867-2026},
url = {https://doi.org/10.5194/hess-30-6867-2026},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Quantifying key parameter sensitivities for water table depth in hydrological schemes of CoLM-PSUADE at a mountain forest site
AU - Tingting Wu
AU - Shupeng Zhang
AU - Xiaofan Yang
AU - Yongjiu Dai
PY - 2026
DA - 2026/11/09
JO - Hydrology and Earth System Sciences
DO - 10.5194/hess-30-6867-2026
UR - https://doi.org/10.5194/hess-30-6867-2026
AB - 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 evaluations of parameter sensitivities governing water table depth (WTD) simulations. This study coupled 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 optimization for 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 screening, quantitative validation, and parameter optimization techniques was conducted to evaluate the sensitivities of 56 parameters associated with key hydrological processes and identify their optimal ranges. The results identified eight sensitive parameters in the initial screening, 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). Additional experiments with independent random seeds revealed varying sensitivity rankings. In particular, the subsurface runoff parameter r sub,max exhibited sampling-dependent sensitivity but showed relatively high importance in the analysis. It exhibited a well-defined optimal range (on the order of 10 ⁻⁴ ) and regulated 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 showed the highest sensitivity. It regulated 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 was 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. This study demonstrated that CoLM-PSUADE provides a useful tool for sensitivity-guided parameter optimization in high-dimensional LSMs and hydrological models.
SN - 1607-7938
ER -