Reliability of Tropical Rainfall Measuring Mission for Rainfall Estimation in Brantas Sub-Watersheds

Abstract

Rainfall data is pivotal for hydrological studies, water resource management, and climate analysis. However, regions like Indonesia face challenges due to uneven rainfall station distribution. This study explores the potential of Tropical Rainfall Measuring Mission (TRMM) 3B42RT Daily V7 satellite data for rainfall estimation in such areas, focusing on the Brantas sub-watersheds: Kedak, Ngampel, and Kresek. Multiple TRMM scenarios are assessed for reliability and accuracy against ground-based rainfall station data. In monthly rainfall analysis, TRMM exhibits stronger correlations with average ground station data (coefficients of determination ranging from 0.62 to 0.74 for individual stations and 0.76 to 0.79 for averages) with an average PBIAS of 35.07%. The TRMM data exhibited weak performance on daily rainfall records, as evidenced by the low coefficient of determination (R²) values ranging from 0.04 to 0.21. TRMM proves sufficiently reliable for areas with limited rainfall records, particularly for cumulative monthly rainfall assessment. A comparative analysis of rainfall values for different return periods reveals that TRMM tends to provide lower values compared to single-station ground-based estimates. However, nearly similar values were obtained for area-averaged ground-based stations. Combining area-averaged TRMM data with cumulative ground-based rainfall data reduces variability in values for diverse return periods (3-8%), enhancing data accuracy. In conclusion, TRMM 3B42RT Daily V7 data integration enhances rainfall estimation accuracy in regions with limited data availability.