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Integrated hydrodynamic and socio-economic damage modelling for assessment of flood risk in large-scale basin : The case study of Lower Chao Phraya River Basin in Thailand

Thailand has been often affected by severe flood events over the past century. The 2011’s Thailand Flood Catastrophe was the costliest in country’s history, and it was ranked to be the second most damaging natural hazard in the world in terms of economic losses. The Chao Phraya River Basin was noted to be the most vulnerable area prone to flooding in Thailand. The dynamics of flood risk in the river basin have changed drastically over the past fifty years. In particular, flood exposure increased due to rapid urbanization and population growth. Since 2012, integrated flood risk management has been addressed to be the major framework of water-related disasters with the goal of losses and damage reductions. However, there is currently little research in Thailand on how to quantify flood risks and mitigate flood inundation damage on the relation between the occurrence of flood events and their consequential socio-economic implications. In this study, a tradition method in flood risk assessment is implemented by integrating 2D hydrodynamic modelling and the assessment of socio-economic impact of floods into the Chao Phraya River Basin. More specifically, the fully 2D version of the LISFLOOD-FP model code was used to model flood inundation processes. The output of the model was then used to map inundation depth and assess the levels of physical/environmental risk associated to flood hazards on multiple receptors/elements at risk. The European Flood Directive and the KULTURisk methodology were applied to quantify flood risks in monetary terms for residential, industrial, and agricultural sectors. The 2011 flood event was used for model calibration, while a hypothetical flood event with a return period of 100 years was simulated to identify the potential flood losses. Depth-damage functions comprising of JRC-ASIA, the Flemish, and JICA models were used to estimate potential damage for residential and industrial structures. The results showed that LISFLOOD-FP could satisfactorily reproduce the flood inundation extent obtained from satellite imagery in 2011. The model performance (Critical Success Index or F1) was of 56%, with a Bias of 112%. The latter meant the total inundated area was 12% larger than flood extent’s observation. Moreover, the model could simulate flood levels with overall Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of 2.03 m a.s.l. and 1.78 m a.s.l., respectively. For the estimation of flood damage and losses, the Flemish model showed the strongest agreement with the reported flood damage in the residential sector, while JICA-ASIA model underestimated flood damage for industrial sector by just 1%. The KULTURisk methodology also well-estimated crop losses in the 2011 event which an overestimation about 21% from the reported value. Apart from that, fully 2D numerical method could not perfectly represent 1-in-100 year flood inundation due to non-consideration of important features such as the precise river channel topography, hydraulic infrastructures, and flood protection schemes in the river basin. Lack of such features results in an overestimation of flood damage and losses for 1-in-100 year flood comparing to the national flood hazard map and damage assessment which are simulated and estimated by JICA’s study. Such features can be better handled by using a coupled 1D/2D numerical method in order to simulate flood inundation extent more realistically and estimate flood losses. This could help the Thai government to better prepare a budget for flood risk prevention. In addition, even if the Flemish model indicates a good representation of relative flood damage to housing structures, the government should establish depth-damage curves specific for Thailand.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-157381
Date January 2018
CreatorsPumchawsaun, Phat
PublisherStockholms universitet, Institutionen för naturgeografi
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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