Summary
This study examines parameter sensitivity in the Noah-MP land surface model by identifying 139 hard-coded parameters previously embedded in model code and performing global sensitivity analysis across diverse US catchments. The analysis reveals that whilst two-thirds of applicable standard parameters influence hydrologic fluxes, the most sensitive parameter is a hard-coded soil surface resistance value for direct evaporation. The authors conclude that comprehensive model calibration requires jointly optimising both plant and soil parameters, and incorporating hard-coded parameters as calibration variables, to derive realistic parameter estimates and improve model predictive capacity.
UK applicability
The methodological approach and findings regarding parameter sensitivity in land surface models are applicable to UK hydrological and meteorological modelling, particularly given the UK's diverse hydrometeorological regimes. However, the specific parameter sensitivities identified may differ under UK climatic and soil conditions, requiring similar analysis adapted to regional characteristics.
Key measures
Sobol' sensitivity indices (≥1%) for standard parameters and hard-coded parameters; latent heat flux; total runoff; surface runoff; component fluxes
Outcomes reported
The study identified 139 hard-coded parameters in the Noah-MP land surface model and performed Sobol' global sensitivity analysis to evaluate their impact on hydrologic output fluxes (latent heat and total runoff) across 12 catchments with differing hydrometeorological regimes in the United States.
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