Estimation of radar-rainfall and assessment of its uncertainty in upper Yom basin, Thailand

Abstract

Thailand’s mountainous upper Yom basin experiences frequent floods due to high river discharge. However, limited rain gauges restrict hydrological applications and flood risk assessments. Weather radar offers promise for rainfall estimation using reflectivity–rainfall (Z–R) relationships, but associated uncertainties hinder their use. Therefore, this study: i) determined the Z–R relationship for radar-rainfall estimation in the upper Yom basin; and ii) assessed the uncertainty of the determined radar-rainfall. The least-square error (LSE) method and the bias-variance correction (BVC) method were used to determine the Z–R relationships and the 95% prediction intervals (PI) for radar-rainfall estimated by both methods were calculated and compared. This showed that the LSE method tended to underestimate rainfall but gave more certainty (The 95% PI is much narrower), while the BVC gave average rainfall closer to that observed but uncertainty was much higher. Even though the LSE method does not yield an accurate average radar-rainfall, the 95% PI of the radar-rainfall estimated by this method can potentially be used to determine the range of estimated actual rainfall.