The Effects of Mitigation Measures on Flood Damage Prevention in Korea

Abstract

This study analyzed the characteristics of flood damages and the effects of structural and non-structural flood damage mitigation measures in Korea. First, a theoretical discussion of the structural and non-structural measures to mitigate flood damages was used to select the variables and devise the hypotheses. An analysis was conducted using the Auto-Regressive Integrated Moving-Average (ARIMA) time series methodology, Korean socioeconomic data, and damage characteristics of major flood events. The effects of flood damage mitigation measures on the extent of flood damages were assessed using an intervention time series model. The major findings were that the intervention effects of structural and non-structural measures were statistically significant from 1958 to 2013 (a period of 55 years) and that while the former were ineffective at mitigating flood damages, the latter were successful in doing so. Based on the above findings, policy suggestions for future flood damage mitigation measures in Korea were offered. For structural measures, the government should manage its existing facilities, recover ecosystems of damaged rivers, and devise mitigation measures for urban areas. For non-structural measures, the government should enhance its flood forecasting capacity, revise laws related to flood control and prevention, and update and rationalize land-use plans.

The Influence of the Middle East Respiratory Syndrome Outbreak on Online and Offline Markets for Retail Sales

“…That is, it is useful for identifying the net impact and its duration after controlling for trends and seasonal factors. This model has been employed to investigate external intervention effects such as flood control policy [74], institutional urban transition [76], stock price change [73], financial crisis [75], and government policy on importing Indian gold [77]. Therefore, we finally employ the ARIMA with intervention model to determine the heterogeneous net impacts and their duration on sales of retail goods in both offline and online markets.…”

“…The last alternative is to employ an ARIMA model with intervention to analyze and determine the changes, variations, and interventions over time [73,74]. It is called the autoregressive integrated moving average with exogenous variables (ARIMAX) model.…”

Flood vulnerability characteristics considering environmental justice and urban disaster prevention plan in Seoul, Korea

“…The average annual precipitation for 30 years from 1981 to 2010 was 1450 mm (KMA 2021). Floods generally occurred in the summer (July-August), and precipitation during this period accounted for twothirds of the annual precipitation (Son et al 2015).…”

Beyond Flood Hazard Maps: Detailed Flood Characterization With Remote Sensing, Gis and 2d Modelling

“…As the most frequently occurring natural disaster impacting more people worldwide than any other natural disasters (Banks et al, 2014), understanding floods and assessing the risks associated to it, including the development of forecasting and warning systems, and preparation and implementation of flood mitigation and adaptation measures, have become more and more important nowadays (Banks et al, 2014;Dale et al, 2012;dos Santos and Tavares, 2015;Son et al, 2015;Adams and Pagano, 2016).…”