Synthetic flood damage function for direct damage estimation in Loei Town Municipality
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Abstract
The reflection between flood damage phenomena and flood characteristics in the flood-affected areas of Loei Town Municipality where flood damage issue is not deeply examined and documented, is desirable for a more accurate damage estimation. Therefore, based on the available empirical dataset collected during 2021-2023 floods, the site-specific flood damage functions and their curves were developed for assessing direct monetary damage to buildings. The replacement cost for household damaged contents was gathered through survey interview of 637 households, in which 75% and 25% of the entire dataset were randomly split for constructing and validating synthetic functions, respectively. The polynomial function was the best fitting method, rather than the other five damage functions (i.e., exponential, Fourier, Gaussian, Rational, and the Sum of Sines), as characterized by the highest R2 values of 0.73, while relatively low values of MAE (0.17), MBE (-0.17), and RMSE (0.19) clearly indicated the validity of the synthetic damage function. All relevant data were then entered into the HEC-FIA software for damage estimation based on a structure-by-structure basis. The results revealed that the 2002 flood caused 199,330 USD in damage to Loei Town Municipality, which showed a reasonable agreement with the governmental relief budget (accounted for 56% of the 2002 total flood-relief budget of Loei Province). It is noteworthy that the findings gained from this study may be of assistance when assessing flood damage to buildings for the areas with flood-related data scarcity, in which the depth-damage function/curve developed herein could help pave the way towards more accurate flood damage estimation for risk assessment at local scale. Finally, this study could be technically beneficial for government and local authorities of Loei Town Municipality in making decisions in reducing flood damage and for residents living in flood-prone areas to achieve resilience after flood events.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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