Estimation of Direct and Indirect Economic Losses Caused by a Flood With Long‐Lasting Inundation: Application to the 2011 Thailand Flood

Abstract

River floods are common natural disasters that cause serious economic damage worldwide. In addition to direct economic damage, such as the destruction of physical assets, floods with long-lasting inundation cause direct and indirect economic losses within and outside the affected area. Direct economic losses include loss of opportunity, due to interruption of business activities, and the costs associated with emergency measures such as cleaning, while indirect economic losses affect sectors within the trade and supply network. Few studies have explicitly estimated direct and indirect economic losses in several sectors, due to the difficulty of modeling inundation depth and period at finer scales. Here we developed a global modeling framework to estimate the direct and indirect economic losses associated with floods using a computable general equilibrium model and a global river and inundation model, which can simulate the flood extent, depth, and period. Application of the method to the 2011 Thailand flood demonstrated that the estimated economic losses due to business interruption in the industry and service sectors totaled $14.7 billion, which was about two thirds of the estimated direct economic damage caused by the flood ($22.0 billion). The estimated indirect economic losses reduced the gross domestic product of Thailand by 4.81% in 2011, without considering transboundary effects, and will cause more than 0.5% reduction in gross domestic product even in 2030, resulting in $55.3 billion of total losses from 2011 to 2030. Comprehensive estimation of direct and indirect economic losses facilitates understanding of various types of flood-related economic risks during and after a flood.

A dynamic disastrous CGE model to optimize resource allocation in post-disaster economic recovery: post-typhoon in an urban agglomeration area, China

“…As tangible assets losses in other industries still lack data, this study did not consider them. Direct business interruption losses refer to the production losses caused by business interruption in secondary and tertiary industries because of the direct impact of typhoons, such as strategic shutdowns before and during disasters [35,42]. In response to Mangkhut, Guangdong Province suspended school, work, business, and production for about one day to reduce the impact of the disaster.…”

“…In terms of social activities, residents' consumption was mainly concentrated in education (SEC37), health, social security and social welfare (SEC38), culture, sports and recreation (SEC39), and public administration and social organizations (SEC40) in the post-disaster stage. But residents' consumption before the disaster was mainly concentrated in farming, forestry, animal husbandry and fishery (SEC1), manufacture of food and tobacco (SEC5), transport, storage and postal services (SEC28), and hotels and catering services (SEC29), indicating that Mangkhut created inconveniences for local people to obtain clothing, food, housing, and transportation and it reduced their quality of life temporarily [35,60]. Therefore, to ensure the normal lives of the affected residents, the local government should carry out post-disaster recovery measures in a timely fashion [3,26,61].…”

“…However, current post-disaster economic recovery analyses are limited to examining DE loss; they do not consider IDE loss or, especially, the cumulative effects of the two [10]. This approach underestimates natural disaster losses and leads to a reduction in the inputs of recovery resources, which is not conducive to the overall recovery and development of socio-economies [13,35,36]. Therefore, it is necessary to consider the DE and IDE losses of natural disasters to determine the necessary recovery resources [37].…”

A quantitative evaluation of flood damage methodology under a portfolio of adaptation scenarios

“…1). This framework was previously successfully used for reproducing observed historical stream ow and inundated area in Thailand (Tanoue et al 2020;Taguchi et al 2022).…”

A numerical approach to understand the responses of passenger vehicles moving through floodwaters

“…Later, a comparison between simulation outcomes and previously published experimental work was performed and a good agreement was observed. In the past decades, flood risks have become a crucial issue in urban areas resulting in serious infrastructure damages, economic losses, fatalities and injuries among people (Ahmadalipour & Moradkhani, 2019;Chou et al, 2019;Hammond et al, 2015;Kreibich et al, 2009;Špitalar et al, 2020;Tanoue et al, 2020;Vojinovic & Tutulic, 2009). Nowadays, flood occurrence probabilities have increased due to the constant increment rate of land urbanization and the effects of climate changes which make flood risk issues more serious (Bahrawi et al, 2020;Chen et al, 2021;Zhou et al, 2019).…”