Assessment of flood mitigation services in Khon Kaen City through integrated modelling and scenario simulations
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Abstract
This study highlighted the identifying remedial measures for flood mitigation under varying rainfall intensity. The MIKE URBAN was coupled with the MIKE 21 within the MIKE FLOOD URBAN model to simulate flood propagation in Khon Kaen City. The reliability of 1D model was proven through calibration and validation, in which the water level observed in Nong Khot Lake was satisfactorily predicted as the values of coefficients of determination (R2) and Nash-Sutcliffe Efficiency (NSE) are greater than 0.80, Root Mean Square Error (RMSE) is close to zero, and Percent bias (PBIAS) is less than 10%. The MIKE FLOOD URBAN was further calibrated for the rainfall event of 1 September 2019, while the results from a low Relative Error (RE) of 0.14 and a high F-statistics (FS) of 83.72% indicated a high goodness of fit between UAV-based mapping (0.196 km2) and MIKE FLOOD URBAN simulated flood extents (0.169 km2). The MIKE FLOOD URBAN was validated against floodmarks on 25 September 2022, and there was a satisfactory correlation between flood depth reported by news reports and the simulated results. To respond to floods caused by tropical storms Podul and Noru of September 2019 and September 2022, respectively, five flood mitigation scenarios were examined for their effectiveness compared to the baseline. The integration between the drainage improvement project of Maliwan Road and advance depletion of water level in Nong Khot Lake by 3.5 m, was the most promising combination to alleviate flood consequences at repeatedly flooded areas with the maximum decrease in flood depths of 0.77 m. The average flood depth and total flooded areas were decreased by up to 27.66% and 10.66%, respectively, which is an optimistic sign to convince agencies to extend these management actions to include other flood mitigation works for enhancing flood resilience of Khon Kaen City.
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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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