피해자료 및 현장조사를 통한 공공건물 침수 손상함수 개발

이창희,김상호,황신범 한국방재학회 2019 한국방재학회논문집 Vol.19 No.6

홍수에 대한 피해평가는 홍수 위험 관리를 하는데 있어서 중요한 요소다. 홍수 피해를 추정하기 위해서 일반적으로 침수심별 손상함수가 사용된다. 미국, 유럽, 일본 등 주요 선진국에서는 과거의 홍수피해에 대한 분석과 전문가의 판단에 근거하여 침수심별 손상함수를 이용한 홍수 피해 추정 모형을 개발하였다. 그러나 이러한 손상함수는 개발된 지역 데이터를 기반으로 만들어 졌기 때문에 우리나라에서는 이를 그대로 적용할 수 없다. 이러한 문제를 해결하기 위해 본 연구에서는 공공건물에 대해서 우리나라의 실제 피해 데이터를 활용하여 손상함수를 개발하였다. 공제회로부터 획득한 각종 사고데이터와 현장조사에 의한 침수심 등을 이용하여 공공건물 건물유형별로 손상률을 산정하였다. 손상함수는 침수 피해에 따른 홍수피해액 추정을 가능하게 함으로써, 홍수피해저감 대책에 대한 비용대비 효과분석에 활용될 수 있다. Flood damage assessment is an important factor in flood risk management. Flood depth damage functions are commonly used to estimate flood damage. Major developed countries such as the US, Japan, and those of Europe have developed flood damage estimation models based on damage analyses of past flood cases as well as the judgment of flood experts. However, such damage procedures are not applicable to Korea, because they are based on data from regions in other developed countries. To solve this problem, this study developed damage functions using actual damage data from public buildings in Korea. Damage rates were calculated for each type of public building by utilizing various damage data obtained from the mutual aid association and the building register, and data on the depth of flooding, obtained through field surveys. The damage function can then be used to analyze the cost-effectiveness of flood damage reduction measures.

홍수터 관리를 위한 홍수직접피해 공간분석

김종섭,임광섭,김만식 한밭대학교 2008 한밭대학교 논문집 Vol.25 No.-

The main damages by several recent flood events in Korea are responsible for steep increase of direct flood damage, and the scale and coot of damages. Many studies are actively in progress to evaluate the possible economical damages and long-standing problem Assignment of graphical development has received considerable attention. The integration of topographical, hydrological, hydraulic and economic information in flood damage simulation makes it possible to determine the total impact of floods by means of stage damage curves and Geographic Information Systems (GIS). This methodology is applied to a Yeoju-gun. of Gyeonggi-Do located in South Han River Basin of South Korea. The study describes the procedure to identify, determine and represent direct flood damage caused by various-size of design floods using HEC-RAS and ArcGIS. Especially, ArcGIS is used for mapping and analyzing economic value of damages with 2D and 3D graphic capabilities. Overall, the results of this study indicate that GIS is useful and efficient for the automatic generation of flood maps, and an effective environment for estimating, mapping, and analyzing economic value of direct flood damage.

학교건물에 대한 홍수 침수심별 손상함수 개발에 관한 연구

이창희,김상호,황신범,김길호 한국수자원학회 2017 한국수자원학회논문집 Vol.50 No.8

홍수피해저감효과를 분석하기 위해서는 수리·수문학적 분석을 통한 피해예상지역과 침수심을 분석함과 함께 피해예상지역에 대한 피해액 추정 이 가능해야 한다. 홍수피해액의 추정은 일반적으로 건물의 구조물 및 내용물에 대해서 침수심의 변화에 따라 분석된다. 본 연구에서는 실제 피해 지역의 자료들을 토대로 학교건물에 대한 침수심별 손상함수를 개발하고 적용하였다. 그리고 학교건물에 대한 손상함수의 개발절차, 침수심별 손 상함수의 보완과정을 제시하였고, 그리고 손상함수의 적용결과에 대한 기존 기법과도 비교하여 검증하였다. 본 연구를 통해 손상함수를 개발하는 과정과 개발된 침수심별 손상률 그리고 함수의 적용과정은 향후 피해규모에 따른 홍수피해액 추정을 가능하게 하여 홍수피해저감 대책에 대한 비 용대비 효과분석 수행에 활용될 수 있을 것으로 기대된다. In order to analyze flood damage mitigation effects, it is necessary not only to analyze inundation areas and depth through hydraulic and hydrological analysis but also to estimate flood damages. Flood damages of structure and contents of buildings are generally analyzed according to the flood depth. In this study, we developed and applied flood depth-damage functions for the school buildings based on actual damage data. In addition, the development and modification procedure of flood depth-damage functions for school buildings is presented in this paper, and the developed damage functions are verified by comparing them with the existing method. It is expected that the process of developing and applying flood depth-damage functions presented in this study can be used in the cost benefit analysis of flood damage mitigation measures.

InVEST 모형을 이용한 도시 생태계의 홍수 조절서비스 평가

이태호,천금성,권혁수 한국환경복원기술학회 2022 한국환경복원기술학회지 Vol.25 No.6

Along with the urbanization, the risk of urban flooding due to climate change is increasing. Flood regulation, one of the ecosystem services, is implemented in the different level of function of flood risk mitigation by the type of ecosystem such as forests, arable land, wetlands etc. Land use changes due to development pressures have become an important factor in increasing the vulnerability by flash flood. This study has conducted evaluating the urban flood regulation service using InVEST UFRM(Urban Flood Risk Model). As a result of the simulation, the potential water retention by ecosystem type in the event of a flash flood according to RCP 4.5(10 year frequency) scenario was 1,569,611 tons in urbanized/dried areas, 907,706 tons in agricultural areas, 1,496,105 tons in forested areas, 831,705 tons in grasslands, 1,021,742 tons in wetlands, and 206,709 tons in bare areas, the water bodies was estimated to be 38,087 tons. In the case of more severe 100-year rainfall, 1,808,376 tons in urbanized/dried areas, 1,172,505 tons in agricultural areas, 2,076,019 tons in forests, 1,021,742 tons in grasslands, 47,603 tons in wetlands, 238,363 tons in bare lands, and 52,985 tons in water bodies. The potential economic damage from flood runoff(100 years frequency) is 122,512,524 thousand won in residential areas, 512,382,410 thousand won in commercial areas, 50,414,646 thousand won in industrial areas, 2,927,508 thousand won in Infrastructure(road), 8,907 thousand won in agriculture, Total of assuming a runoff of 50 mm(100 year frequency) was estimated at 688,245,997 thousand won. In a conclusion. these results provided an overview of ecosystem functions and services in terms of flood control, and indirectly demonstrated the possibility of using the model as a tool for policy decision-making. Nevertheless, in future research, related issues such as application of models according to various spatial scales, verification of difference in result values due to differences in spatial resolution, improvement of CN(Curved Number) suitable for the research site conditions based on actual data, and development of flood damage factors suitable for domestic condition for the calculation of economic loss.

국가재난 및 수자원관리시스템을 활용한 하천시설물에 대한 홍수피해 함수 개발에 관한 연구

김상호,이창희,김연수,황신범 한국방재학회 2016 한국방재학회논문집 Vol.16 No.4

It is necessary to estimate the flood damage of public facilities in order to establish the measures against flood, because the damage to public facilities is the most damaged item among the total damages during flood. So far, the study for flood damage estimation has been conducted about the depth-damage functions of buildings and their contents of private facilities. Two method has been used: the first is the method of multiplying the factor to the specific asset damages, and the second is the method of using regression equation of inundation area as an independent variable for public facilities. However, this has a limitation that they have been calculated without consideration of public facilities status and hydrometeorological data. This study aims to develop the flood estimation function of the river infra structure, the most damaged item among public facilities due to heavy rains and typhoons. In this study, the data of National Disaster Management System(NDMS) and Water Resources Management Information System(WAMIS) were used, and the developed function was verified by applying the test bed area. The function for river infra structure developed in this study will provide very useful information for disaster reduction measures. 홍수시 공공시설물에 대한 피해가 전체 피해액 중 대부분을 차지하고 있으므로, 홍수피해에 대비한 대책마련을 위하여 공공시설물에 대한 피해액 예측이 필요하다. 지금까지 홍수 피해액 산정 연구는 주로 사유시설에 대한 건물과 건물의 내용물에 대해서 침수심별 피해 함수를 이용하는 연구가 많이 이루어졌다. 공공시설물에 대해서는 두 가지 방법이 이용 되어 왔는데, 하나는 특정자산 피해를 기준으로 계수를 곱하는 방법이고, 다른 하나는 침수면적항을 독립변수로 이용한 피해추정 회귀식에 의한 방법이 이용되었으나, 이는 공공시설물의 현황 및 수문기상데이터와는 관계없이 적용되는 한계점이 있다. 본 연구의 목적은 공공시설물 중 가장 많은 피해액이 발생하고 있는 하천시설에 대해서 호우 태풍으로 인한 홍수피해규모 예측을 위한 함수를 개발하고자 함이다. 함수개발에 국가재난 및 수자원관리시스템의 데이터를 활용하였으며, 개발된 함수는 대상유역에 적용하여 검증하였다. 본 연구에서 개발한 하천시설에 대한 피해함수는 재해저감대책을 마련하는데 필요한 매우 유용한 정보를 제공할 수 있을 것이다.

Semi-parametric Geographically Weighted Regression Modelling for Flood Damage Assessment in Gunsan City, Korea

Imee V. Necesito,Tae Sung Cheong,Insang Yu,Sangman Jeong 한국방재학회 2015 한국방재학회 학술발표대회논문집 Vol.14 No.-

Climate change has been a global issue since the 19th century. The increase in rainfall variability, which covers the increase in the earth’s total precipitation, will definitely lead to frequent and more severe flood disasters. As the damage increases year after year with floods as the most chronic and costly disaster among these hazards, Korea has to improve its technological responses and countermeasures to better visualize the hazards brought about by such disasters. Gunsan City ranked number eight in the country’s most susceptible region to floods. From 2004 to 2013, Korea has experienced a total of 174 flood disasters which were estimated to cost USD 7.32 billion. But reports showed that the total expenditure of the government amounted to 1.4 times the estimated losses and damages and the private companies have spent twice the said estimated amount. To summarize, the post-disaster loss and damage reports showed underestimated values. This study aims to develop a semi-parametric geographically weighted regression which can implement a flood damage estimation model of Gunsan City. The model building process include parameters like flood depth, flood duration, inundated area, family income and land price. The datasets are composed of both untransformed and transformed data (using Box-Cox Method). Both Ordinary Least Squares (OLS) Regression and Geographically Weighted Regression (GWR) were evaluated in this study, but the search for best fit resulted to the use of GWR.

단독주택 홍수피해액 평가를 위한 손상함수 개발

최천규(Choi Cheon kyu),김경탁(Kim Kyung tak),김길호(Kim Gil ho),김형수(Kim Hung soo) 한국방재학회 2017 한국방재학회논문집 Vol.17 No.6

본 연구는 홍수피해 평가에서 중요한 요소인 손상함수를 경험적 방법으로 개발하고자 과거 9개 피해지역에서 397개의 단독주택에 대한 홍수피해 정보를 1:1 면담 방식으로 조사하였다. 수집한 자료를 이용하여 3가지 형태의 손상함수를 단순회귀모델로부터 분석하였고, 적합한 함수형태를 결정하였다. 손상함수 형태에 따른 피해액 추정결과의 차이를 확인하기 위해 2011년 동두천시 피해사례에 적용하였고, MD-FDA에 의한 결과와 비교할 때 건물구조물, 건물내용물 피해액 모두 상당한 차이를 보였다. 한국형 홍수피해평가 모델을 위해서는 향후 본 연구에서 다룬 단독주택 외 다양한 용도의 손상함수 개발이 추가적으로 필요하다. In this study, we developed damage functions, which is an important factor in flood loss assessment, by empirical method. For this purpose, we collected field data on the flood damage of 397 single family houses in 9 affected disaster areas through one-on-one interviews. Using the collected data, three types of damage functions were analyzed in a simple regression model and the appropriate functional form was selected. In order to confirm the differences in the estimated damage by each damage function, we applied to the flood damage case of Dongducheon City in 2011. Compared to the assessment results based on MD-FDA, there were significant differences in the amounts of damage of both the building structure and building contents. In order to develop a flood loss assessment model suitable for the situation in Korea, it is necessary to further develop the damage function for buildings with the occupancy other than single-family housing discussed in this study.

Semi-parametric Geographically Weighted Regression Modelling for Flood Damage Assessment

Imee V. Necesito,Tae Sung Cheong,Insang Yu,Sangman Jeong 한국방재학회 2016 Journal of Disaster Management Vol.1 No.3

Climate change has been a global issue since the 19th century. The increase in rainfall variability, which covers the increase in the earth’s total precipitation, will definitely lead to frequent and more severe flood disasters. As the damage increases year after year with floods as the most costly disaster among these hazards, Korea has to improve its technological responses and countermeasures. This study aims to develop a semi-parametric geographically weighted regression which can estimate a flood damage of Gunsan City. The model include parameters like flood depth, flood damage, flood duration, inundated area, family income and land price. This study collects flood depths, flood duration from GIS based flood inundation map and flood damages of local buildings from damages report collected by local government after flooding on August, 2012 in Gunsan City. Flood damage estimation of residential, commercial and agricultural facilities was done by Ordinary Least Squares and Geographically Weighted Regression using collected data. Considering the building and GIS-based spatial information, flood damage by GWR is more appropriate than OLS.

지리적가중회귀분석 적용을 통한 변이공간지역에서의 손실함수 결정

정태성,lmee. V. Necesito,유인상,정상만 한국방재학회 2014 한국방재학회논문집 Vol.14 No.5

Flood damage estimated by loss function is main factor to assess flood risk for local disaster prevention and response or project forsustainable development. The loss function as an empirical flood depth-damage curve is generally established by Ordinary LeastSquares (OLS) as a Global Regression Model (GRM). This study collects flood depths from GIS based flood inundation map anddamages of local buildings from damages report collected by local government after flooding on August, 2012 in Gunsan City. TheOLS is used to estimate damages of residential, commercial and agricultural buildings and then estimates are assessed quantitativelywith coefficient of determination and spatial autocorrelation. The assessment results show that the Local Regression Model (LRM) ismore adaptive than the GRM to estimate damages because the spatial patterns of residuals exhibit spatial autocorrelation. The GeographicallyWeighted Regression (GWR) developed here as one of the local regression model to establish the loss function not onlycapturing the spatial variations of the affecting factors but also modifying the OLS is proposed for future applications. This methodhave loss functions at each spatial locations which can estimates optimum damages with flood depths at each buildings defined byGIS information. 홍수피해액 추정은 지역별 재해예방 및 대응을 위한 홍수위험도평가나 지속가능개발을 위한 사업타당성 평가를 위한 핵심요인으로 주로 손실함수(Loss Function)를 이용하여 추정한다. 손실함수는 홍수심-피해액 관계를 함수화한 것으로써 대부분 단순회귀분석(OLS)과같은 전역회귀모형(GRM)을 이용하여 결정한다. 본 연구에서는 2012년 8월 홍수 직후 군산시 지역에서 구축된 GIS기반 피해흔적지도로부터 홍수심 자료를 수집하고 주민들의 신고에 기반하여 지자체에서 구축한 건물 위치별 피해액자료를 수집하였다. 수집된 자료를이용하여 OLS로 수심에 대한 주거건물, 상업건물, 농업시설 피해액을 추정한 후 결정계수와 공간적 상관성 등 정량적 검토를 통해 모형의 적정성을 검토하였다. 공간적 자기상관과 정확도를 분석한 결과, 잔차의 공간적 상관성 때문에 GRM보다는 지역회귀모형(LRM)이 홍수피해를 추정하는데 더 적합한 것으로 나타났다. 본 연구에서는 지역회귀모형 중 지리적가중회귀모형(GWR)을 선정하고 손실함수를 개발하였으며, 그 결과 추정치는 공간적 변이를 잘 재현하며 단순회귀분석에 비해 정확도 높은 결과를 보이는 것으로 나타나개발된 방법론은 충분히 활용가치가 있는 것으로 나타났다. 더불어 본 방법은 공간적 변이를 고려하여 지점별 손실함수를 개발하므로GIS정보를 활용한다면 각 건물 위치에서 보다 정확한 홍수심별 피해액을 추정하는 것이 가능하다.

Development of Multivariate Flood Damage Function for Flood Damage Assessment in Gunsan City, Korea

Imee V. Necesito,Tae Sung Cheong,Insang Yu,Sangman Jeong 한국방재학회 2015 한국방재학회 학술발표대회논문집 Vol.14 No.-

From 2004 to 2013, Korea has experienced a total of 174 flood disasters and has a total estimated cost of USD 7.32 billion. However, reports showed that the total expenditure of the government amounted to 1.4 times the estimated losses and damages and the private companies have spent twice the said estimated amount. To summarize, the post-disaster loss and damage reports showed underestimated values. In this regard, the National Emergency Management Agency (NEMA), the government institution designated to assess and analyze the damages and losses as well as evaluate the disaster risks of the said areas in accordance to their disaster risk management plans, are now developing a new estimating method for damages and losses. This study aims to develop flood damage functions that will estimate the flood damages of Gunsan City based on the building type: residential, commercial and agricultural facilities, by utilizing the Ordinary Least Squares Regression and later on, the Geographically Weighted Regression. The model building process includes flood depth, flood duration, inundated area, family income and land price as the parameter variables. Due to normality issue, the datasets were transformed through Box-Cox Method. Both Ordinary Least Squares (OLS) Regression and Geographically Weighted Regression (GWR) were evaluated in this study, but the search for ‘best fit’ resulted to the use of GWR.