Combining Radar and Rain Gauge Rainfall Estimates for Flood Forecasting Using Conditional Merging Method

Radar rainfall estimates are increasingly applied to flood applications. Early warning with the use of radar rainfall estimates and hydrologic models is crucial for minimizing flood and flash flood-related hazard. The strength of radar rainfall data, the ability to capture spatial rainfall information, is the weakness of rain gauge data and the weakness of radar rainfall data, inability to accurately capture rainfall amounts at a single location, is the strength of rain gauges. Therefore By merging the two datasets, the result is gauge adjusted radar rainfall data, a dataset that maintains volume accuracy at the gauge locations while retaining spatial information from Radar. The main idea of gauge adjustment is combine the individual strengths of the to measurement systems. In this paper describes a short overview over the gauge adjustment methods applied in operational fields. And the technique employed is a conditional merging technique(CM). To evaluate the this method, statistics and hyetograph for rain gauges and radar rainfalls are compared using hourly radar rainfall data from the Imjin-river, Gangwha, rainfall radar site. Results show that rainfall field estimated by Condional Merging method give the best results in a statistics and qualitative way.