Moving land models toward more actionable science: A novel application of the Community Terrestrial Systems Model across Alaska and the Yukon River Basin

Four representative river basins across our study domain were selected for optimization based on observed streamflow and snow water equivalent observations at 10 SNOTEL sites. Fourteen sensitive parameters were identified for optimization with half of them not directly related to hydrology or snow processes. Across fifteen out-of-sample river basins, 13 had improved flow simulations after optimization and the mean Kling-Gupta Efficiency of daily flow increased from 0.43 to 0.63 in a 30-year evaluation.

In addition, we adapted the Shapley Decomposition to disentangle each parameter's contribution to streamflow performance changes, with the seven non-hydrological parameters providing a non-negligible contribution to performance gains. The snow simulation had limited improvement, likely because snow simulation is influenced more by meteorological forcing than model parameter choices.