Quantifying the Impacts of Fire-Related Perturbations in WRF-Hydro Terrestrial Water Budget Simulations in California's Feather River Basin

Wildfire activity in the western United States (WUS) is increasingly impacting water supply, and land surface models (LSMs) that do not explicitly account for fire disturbances can have critical uncertainties in burned areas. This study quantified responses from the Weather Research and Forecasting Hydrological modelling system (WRF-Hydro) to a suite of fire-related perturbations to hydrologic soil and runoff parameters, vegetation area, land cover classifications and associated vegetation properties, and snow albedo across the heavily burned Feather River Basin in California. These experiments were used to quantify the impacts of fire-related perturbations in model simulations under the observed meteorological conditions during the 2000–2022 water years and determine whether applying these fire-related perturbations enhanced post-fire model accuracy across the 11–12 post-fire months evaluated herein. The most comprehensive fire-aware simulation consistently modelled enhanced annual catchment streamflow (by 8%–37%), subsurface flow (by 72%–116%), and soil moisture (by 4%–9%), relative to the baseline simulation which neglected fire impacts. Simulated fire-enhanced streamflow was predominately attributable to fire-induced vegetation area reductions that reduced transpiration. Simulated streamflow enhancements occurred throughout the water year, excluding early-summer (e.g., May–June) when the baseline simulation modelled relatively more snowmelt and streamflow because fire perturbations caused earlier model snow depletion. Vegetation area reductions favoured increased model ground snow accumulation and enhanced snow ablation while imposed snow albedo darkening enhanced ablation, ultimately resulting in similar peak SWE and earlier snow disappearance (on average by 8-days) from the most comprehensive fire-aware simulation relative to the baseline simulation. The baseline simulation had large degradations in streamflow accuracy following major fire events that were likely partially attributable to neglecting fire disturbances. Applying fire-related perturbations reduced post-fire streamflow anomaly biases across the three study catchments. However, remaining large post-fire streamflow uncertainties in the fire-perturbed simulation underscores the importance of additional observationally constrained fire-disturbance model developments.