Mapping snow water equivalent by combining a spatially distributed snow hydrology model with passive microwave remote-sensing data

An algorithm to incorporate passive microwave remote-sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of snow water equivalent (SWE) as a function of time is implemented. A priori information provided by the snow hydrology model is used to provide initial estimates of snow parameters from brightness temperature measurements. The algorithm is illustrated by applying it to a mountainous region. The passive microwave remote-sensing measurements are 25-km resolution (grid). However, in mountain regions, the spatial variability of SWE over a 25-km grid is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1-km resolution. In their work, the snow hydrology SWE estimates are updated and corrected using Special Sensor Microwave/Imager (SSM/I) passive microwave remote-sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOwpack TELemetry (SNOTEL) sites in and near the basin. The results indicate that the method incorporating the remote-sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time