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- W4387247744 abstract "<strong class=journal-contentHeaderColor>Abstract.</strong> Extreme rainfall events in the Chi watershed of Thailand have significant implications for the safe and economic design of engineered structures and effective reservoir management. This study investigates the characteristics of extreme rainfall events in the Chi watershed, Northeast Thailand, and their implications for flood risk management. We apply extreme value theory to historical maximum cumulative rainfall data for consecutive rainy days from 1984 to 2018. The Generalized Pareto Distribution (GPD) was used to model the extreme rainfall data, with the parameters estimated using Maximum Likelihood Estimator (MLE) and Linear Moment Estimator (L-ME) methods based on specific conditions. The goodness-of-fit tests confirm the suitability of the GPD for the data, with p-values exceeding 0.05. Our findings reveal that certain regions, notably Udon Thani, Chaiyaphum, Maha Sarakham, Tha Phra Agromet, Roi Et, and Sisaket provinces, show the highest return levels for consecutive 2-day (CONS-2) and 3-day (CONS-3) rainfall. These results underscore the heightened risk of flash flooding in these regions, even with short periods of continuous rainfall. Based on our findings, we developed 2D return level maps using the Q-geographic information system (Q-GIS) program, providing a visual tool to assist with flood risk management. The study offers valuable insights for designing effective flood management strategies and highlights the need for considering extreme rainfall events in water management and planning. Future research could extend our findings through spatial correlation analysis and the use of copula functions. Overall, this study emphasizes the importance of preparing for extreme rainfall events, particularly in the era of climate change, to mitigate potential flood-related damage." @default.
- W4387247744 created "2023-10-03" @default.
- W4387247744 date "2023-10-02" @default.
- W4387247744 modified "2023-10-03" @default.
- W4387247744 title "Comment on hess-2023-167" @default.
- W4387247744 doi "https://doi.org/10.5194/hess-2023-167-rc2" @default.
- W4387247744 hasPublicationYear "2023" @default.
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