Development of flood depth-damage curve for urban area in kuantan, pahang - Sumiliana, Sulong (2023)
Flood is a frequent natural hazard worldwide that has significant financial consequences. Therefore, flood damage assessment has become a crucial element to be considered in the implementation of efficient flood risk management. The flood damage curve is a commonly accepted approach for the estimation of flood damages worldwide. However, this method usually considers only the flood depth while the effect of other flooding conditions such as the impact and resistance parameters to the degree of flood damages are normally neglected. In fact, the flood risk assessment should cover all damage dimensions to obtain an extensive description of flood damages. In Malaysia, conducting the assessment of flood damages is challenging due to data scarcity, thus, there are assessments that adopt damage models from other developed countries. Hence, this study provides flood damage estimation framework with limited data focusing on the derivation of a multivariate flood damage model and site-specific flood depth–damage curves for the residential and commercial areas. The empirical dataset collected from the 2013 flood in the Kuantan River Basin (KRB) was used to investigate the influence of impact and resistance variables on the level of flood damages using the multivariate regression approach including Multiple Linear Regression (MLR), Regression Tree (RT) and Random Forest (RF) techniques. The multivariate analysis was utilized to generate synthetic damage data where RF regression model was selected due to its satisfactory results. The damage curve was established by plotting the damage percentages against the observed flood depth using a combination of the synthetic and empirical data. The total direct tangible flood damage for Kuantan during year 2013 flood and various Average Recurrence Intervals (ARIs) was calculated using the combination of hazard, vulnerability, and exposure. The study’s findings revealed that socio-economy and property characteristics have shown a significant correlation to the degree of flood damage. Flood depth was found to have a significant effect in all damages categories followed by flood duration, property value, building type and household/business income. The developed site-specific flood depth–damage curve in this study was acceptable compared with other studies where the correlation coefficient, R2, was greater than 0.8 for residential and commercial categories. The average damage per unit to residential area in Permatang Badak was the highest (RM13,053) and the business premises in Sungai Isap suffered the worst damage (RM37,153). The estimation of flood damage for the return period of 10 years, 20 years, 50 years, and 100 years shows that damage worsens with increasing ARI to residential and commercial categories. The multivariate flood damage model, flood damage curve, as well as estimation of flood damage were tested by comparison to empirical 2013 data and calculation of statistical error indicators. The validations results were good compared to previous studies where the values of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Bias Error (MBE), Coefficient of Variation (CV) obtained were closer to 0 and HR was close to 0.9. Although it is a site-specific study, the framework can be applied to assess the potential flood damages to other data-scarce areas. In addition, this study may serve as guidelines to assist in future damage assessment works in Malaysia, as well as offer decision-makers with an indispensable tool for managing strategies related to flood risk.