Evaluating satellite-based precipitation data for regional IDF development: application of bias-corrected IMERG products in the solo river system

The prediction of extreme precipitation through Intensity-Duration-Frequency (IDF) relationships shapes water resource management strategies, particularly in regions with limited ground monitoring networks. This study presents a comprehensive evaluation of satellite-derived precipitation for developing IDF relationships in the Solo River system by employing data from 25 ground monitoring stations (2001–2020) as the validation points. This study examines three iterations of IMERG satellite products through probability distribution analysis by incorporating Lognormal, Weibull, Gumbel, GEV, Log-Pearson Type 3, and Exponential models. Key findings include: (1) The IMERG final (IMERG-F) product demonstrated superior performance at both station and basin scales, with bias ranges of 12.1–15.6% and 5.6% to -0.6% respectively, outperforming both early (13.6–16.8%) and late (19.3–31.4%) iterations. (2) Geographic analysis revealed distinctive spatial patterns in estimation accuracy, with northern coastal stations showing significant positive bias (Nglirip: +74.5% for 2-year return periods) and high-elevation locations exhibiting systematic underestimation (Tawangmangu: -20.9%). (3) Post-bias correction, IMERG-F estimations achieved substantial improvement, reducing deviation from 43.7% to 6.1% for 2-year return periods and from 9.4% to 5.1% for century-scale events in the Lamong catchment. This study establishes a framework for leveraging satellite precipitation data in hydrological design applications for data-limited watersheds, providing crucial insights for water resource management in regions with sparse monitoring networks.