Accurate extreme rainfall representation is critical for resilient hydrological design and sustainable water management in tropical regions. This study evaluates the GPM IMERG product across three diverse watersheds in East Java (Welang, Kedak, and Grindulu) using Extreme Value Theory (EVT). By employing Generalized Extreme Value (GEV) and Peaks Over Threshold (POT) methods, the research assesses the reliability of satellite estimates in characterizing the extreme events that safeguard community security and infrastructure longevity. Results indicate that while GPM IMERG excels at monthly scales, it lacks the daily precision required for effective flash flood mitigation, particularly in small basins. Crucially, GEV analysis reveals a structural mismatch: ground observations exhibit heavy-tailed (Fréchet) distributions, while GPM IMERG follows bounded (Weibull) distributions. Consequently, the satellite product underestimates high-magnitude events at long return periods, the exact events that define the design limits of adaptive hydraulic structures. Complementary POT analysis identifies scale-dependent biases across catchments. These findings suggest that while GPM IMERG is robust for regional monitoring, it requires distribution-specific bias correction to support disaster-resilient engineering. Addressing these gaps is essential for achieving climate-responsive sustainable development in data-scarce regions.
Ansori et al. (2026) studied this question.
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