The Use of Satellite Rainfall Estimates with Real-Time Flow Prediction Models for Large Catchments

主要研究目标是将从卫星可见光和红外数据获得平均面雨量估计的气象程序与水文程序和实时流量模型相结合预测。特别是，我们的目标是在使用卫星降雨估计实时预测大型集水区的流量时，描述流量预测的误差。由于降雨估计误差引起的不确定性被明确地考虑在内，并通过气象和水文模型和程序传播，成为实时流量中的不确定性预测。这是一个联合项目，其中卫星数据分析将在威斯康星-密尔沃基大学进行，水文部分将在爱荷华大学进行。​这项研究的结果将使专家、管理人员和其他用户受益，因为将降雨卫星数据和水文数据结合起来的方法将用于实时预测流量，因此，提高实时洪水预报的质量。

The main research objective is to integrate meteorological procedures for obtaining estimates of mean areal rainfall from satellite Visible and InfraRed data with hydrological procedures and models for real-time flow prediction. In particular our objective is to characterize flow-prediction errors when using satellite rainfall estimates in the real-time prediction of streamflows from large catchments. Uncertainty due to rainfall estimation errors is explicitly taken into account and is propagated through the meteorological and hydrological models and procedures to become uncertainty in the real-time flow predictions. This a joint project in which the satellite data analysis will be performed at the University of Wisconsin-Milwaukee and the hydrological part will be performed at the University of Iowa. The results of this research will benefit experts, administrators and other users because the developed methods for integrating rainfall satellite data and hydrologic data will be used in predicting flows in real-time and thus, the quality of real-time flood prediction will be enhanced.