Analysis and Mathematical Modeling for Flood Surveillance from Rainfall by Extreme Value Theory for Agriculture in Phitsanulok Province, Thailand (European Journal of Pure and Applied Mathematics, 2022)
Attempts to use the generalized extreme value distribution and generalized Pareto distribution with the maximum likelihood estimates on the extreme rainfall data at one weather station over Phitsanulok province. This paper gathered the rainfall data from January 1987 to December 2021. The estimated return level is 10, 20, 50, and 100 years. The result displays the modeling of the generalized extreme value distribution (GEV); the Gumbel distribution was a fitting proposal for extreme annual rainfall in Phitsanulok province, with μ = 24.95(1.39), σ=22.59(1.06), and ξ=0.03(0.05). In addition, the modeling of the generalized Pareto distribution (GPD) with daily rainfall data in Phitsanulok province had to fit on σ=49.08(2.99), and ξ=-0.28(0.03). Moreover, we obtained return levels with an upward trend in the change in return periods.
Keywords: Extremes value theory; Generalized extreme value distribution; Generalized Pareto distribution; Return level; Maximum likelihood estimation