Remotely Sensed Input Data for Real-Time Flood Forecastingby N. Kouwen, Univ of Waterloo, Waterloo, Canada,
E. D. Soulis, Univ of Waterloo, Waterloo, Canada,
A. Pietroniro, Univ of Waterloo, Waterloo, Canada,
Abstract: The WATFLOOD flood forecasting system has been developed to use a variety of remotely sensed data, namely weather radar for precipitation, Landsat MSS imagery for land cover classification, GOES imagery for snow cover extent, and the future Radarsat for soil moisture data or snow pack water content. The system includes a menu driven, interactive data management system.
Subject Headings: Hydrologic data | Floods | Weather forecasting | Radar | Forecasting | Remote sensing | Snow
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