Role of Passive Microwave Remote Sensing in Improving Flood Forecasts

Abstract

Accurate information concerning antecedent soil moisture conditions is a key source of hydrologic forecasting skill for regional-scale flooding events occurring over time scales of days to weeks. Remotely sensed surface soil moisture observations are a viable source of such information and can potentially improve flood peak timing and magnitude forecasting in such events. C- and X-band brightness temperature data from the Advanced Microwave Scanning Radiometer (AMSR-E) aboard NASA's Aqua satellite are used here to demonstrate the potential for improving streamflow forecasts by using remotely sensed surface soil moisture during a flooding event in northeastern Australia (Queensland) during January-February 2004. An analysis of AMSR-E brightness temperature imagery reveals a clear anomaly of low AMSR-E brightness temperatures (i.e., high soil moisture conditions) over the affected areas in the four- to five-day period preceding peak streamflow conditions. Land surface conditions are a remotely detectable precursor to subsequent downstream flooding. Use of a simple adaptive model demonstrates that AMSR-E passive microwave observations can add skill to streamflow forecasts during the event.