Towards running a physically-based snow model for near real time operational water forecasts

English Abstract:

Traditional operational modeling tools for forecasting water inflow to reservoirs are challenged by more frequently occurring uncharacteristic flow patterns caused from climate change. To tackle these uncharacteristic events that do not follow historical patterns, water managers must turn to new models based on the physically based, energy balance modeling techniques. Currently, the USDA-ARS produces near real time snow water equivalent (SWE) maps using Isnobal for two mountain basins, the Boise River Basin in southwest Idaho and the Tuolumne Basin in California that feeds the Hetch Hetchy reservoir. However, both basins have minimal weather data from automatic weather stations, making model input and model validation difficult. This presentation will examine how Isnobal, coupled to a water routing model, has performed over the past three years of near real time water forecasting. Input data to drive the modeling in these data sparse areas will be derived from the sparse weather station network and high resolution weather forecast models, providing new distributed forcing data for modeling.