Investigating Major Snowmelt and Rain-on-Snow flood Events in the US and Asia and Techniques for Detection

Snowmelt is a primary source of water in many mountainous regions of the world, and has a far-reaching influence in areas that rely upon melt water to replenish reservoirs and aquifers. Melting snow can also produce wide-scale flooding, particularly when combined with rainfall, and techniques to identify rain-on-snow (ROS) events have shown promise for operational applications. In many developing countries and remote regions, snow data are sparse, making these regions particularly susceptible to flooding or drought which can have broad reaching political and economic implications.

In this study a database of snowmelt and rain-on-snow events was developed for the US and southwest Asia. The Flood Observatory archives flooding events dating back to the mid-1980s, however the majority of floods are attributed to heavy rain. Flood Observatory records were augmented with additional events found in news reports and online archives. MODIS satellite imagery was used to identify whether snowmelt was a contributing factor, delineate inundated areas, and to gain an understanding of the regions impacted. Here we report on the frequency and scale of snowmelt flood events, and discuss the resulting damage to property and infrastructure.

A technique to capture the spatial extent and timing of snowmelt floods in near real-time using satellite-borne observations is also evaluated. Passive microwave satellite data has been used to identify snowmelt and ROS events given the sensitivity of the signal to wet snow. For selected high-flow and flood events we compare the diurnal amplitude variation (DAV) signal over the watershed area to streamflow data to assess the capability in predicting the magnitude and timing of flooding. The results show that satellite remote sensing provides tools for detecting and evaluating the occurrence and magnitude of snow-related flood events.