EXTREME RAIN AND FLOOD RISK: CAN WE SEE IT COMING? - Misshuari, Imas Wihdah; Wulandari, Ratri; Bin Salim, Mohd Razman (INDONESIAN JOURNAL OF CONSTRUCTION ENGINEERING AND SUSTAINABLE DEVELOPMENT (CESD), 2025)
Climate change has significantly altered rainfall patterns, increasing the frequency of extreme rainfall events that have a major impact on infrastructure resilience and water resource management. This study aims to predict the recurrence period of extreme rainfall in Asahan Regency, North Sumatra, using the Gumbel distribution. The data used is annual maximum rainfall. The data was sorted, and its probability was calculated using the Weibull formula, then converted to Gumbel-z values. These values were used in a linear regression model to determine the location (μ) and scale (β) parameters of the distribution. The calculations were performed manually and using Python to ensure accuracy. The analysis results showed a strong negative correlation between maximum rainfall and Gumbel values, with R² = 0.742, indicating the reliability of the model in predicting extreme events. The Gumbel distribution proved to be effective in estimating the recurrence period of extreme rainfall. These findings offer vital perspectives on disaster mitigation, infrastructure planning, and sustainable water management in Asahan Regency. This predictive model plays an important role in hydrological planning and flood risk reduction in the region.