Streamflow from Snowmelt Runoff using Satellite-borne Microwave Observations

The magnitude and travel time of snowmelt runoff is difficult to accurately model. Snowpack characteristics such as depth, cold content, and density dictate how much snowmelt water will contribute to streamflow during melt events. Flood forecasting of basins with seasonal snowpacks requires the capacity to effectively estimate the magnitude and timing of snowmelt runoff. Satellite-born microwave remote sensing provides snowpack state observations that can be used by flood forecasters to better predict the travel time of snowmelt runoff.

Here we use the Calibrated Enhanced-Resolution Passive Microwave (CETB) dataset to monitor the timing and duration of snowmelt induced high river flows throughout the Central Great Plains. Snowmelt is identified using the Diurnal Amplitude Variation (DAV) snowmelt detection algorithm in conjunction with the CETB dataset. Delineated snowmelt areas are then compared to observed river flows.