Engineering Commons^™

A Machine Learning Approach For Improving Near-Real-Time Satellite-Based Rainfall Estimates By Integrating Soil Moisture, Ashish Kumar, Raaj Ramsankaran, Luca Brocca, Francisco Munoz-Arriola

Biological Systems Engineering: Papers and Publications

Near-real-time (NRT) satellite-based rainfall estimates (SREs) are a viable option for flood/drought monitoring. However, SREs have often been associated with complex and nonlinear errors. One way to enhance the quality of SREs is to use soil moisture information. Few studies have indicated that soil moisture information can be used to improve the quality of SREs. Nowadays, satellite-based soil moisture products are becoming available at desired spatial and temporal resolutions on an NRT basis. Hence, this study proposes an integrated approach to improve NRT SRE accuracy by combining it with NRT soil moisture through a nonlinear support vector machine-based regression (SVR) …