PASSIVE MICROWAVE SATELLITE SNOW OBSERVATIONS FOR HYDROLOGIC APPLICATIONS
Melting snow provides an essential source of water in many regions of the world and can also contribute to devastating, wide-scale flooding. The objective of this research was to investigate the potential for passive microwave remotely sensed data to characterize snow water equivalent (SWE) and snowmelt across diverse regions and snow regimes to improve snowmelt runoff estimation. The first step was to evaluate the current, empirically-based passive microwave SWE products compared to NOAA’s operational SWE estimates from SNODAS across 2100 watersheds over eight years. The best agreement was found within basins in which maximum annual SWE is less than 200 mm, and forest fraction is less than 20%. Next, a sensitivity analysis was conducted to evaluate the microwave signal response to spatially distributed wet snow using a loosely-coupled snow-emission model. The results over an area approximately the size of a microwave pixel found a near-linear relationship between the microwave signal response and the percent area with wet snow present. These results were confirmed by evaluating actual wet snow events over a nine year period, and suggest that the microwave response provides the potential basis for disaggregating melting snow within a microwave pixel. Finally, a similar sensitivity analysis conducted in six watersheds with diverse landscapes and snow conditions confirmed the relationship holds at a basin scale. The magnitude of the microwave response to wet snow was compared to the magnitude of subsequent discharge events to determine if an empirical relation exists. While positive increases in brightness temperature (TB) correspond to positive increases in discharge, the magnitude of those changes is poorly correlated in most basins. The exception is in basins where snowmelt runoff typically occurs in one event each spring. In similar basins, the microwave response may provide information on the magnitude of spring runoff. Methods to use these findings to improve current snow and snow melt estimation as well as future research direction are discussed.
flooding, melt, passive microwave, remote sensing, Snow, water, Civil engineering
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