• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.101-113
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• 2010

Recently actual rainfall pattern is decreasing rainy days and increasing in rainfall intensity and the frequency of flood occurrence is also increased. To consider recent situation, Engineers use deterministic methods like a PMP(Probable Maximum Precipitation). If design storm wouldn't occur, increasing of design criteria is extravagant. In addition, the biggest structure cause trouble with residents and environmental problem. And then it is necessary to study considering probability of rainfall parameter in each sub-basin for design of water structure. In this study, stochastic rainfall patterns are generated by using log-ratio method, Johnson system and multivariate Monte Carlo simulation. Using the stochastic rainfall patterns, hydrological analysis, hydraulic analysis and 2nd flooding analysis were performed based on GIS for their applicability. The results of simulations are similar to the actual damage area so the methodology of this study should be used about making a flood risk map or regidental shunting rout map against the region.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.54-54
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• 2011

홍수로 인한 인적 물적 피해는 국가 및 지방자치단체의 치수방재노력에도 불구하고 매년 끊이지 않고 발생하고 있다. 다행히 인명피해의 경우 1970, 80년대 연간 300명 규모에서 2000년대에는 150명 가량으로 줄고 있으나, 재산상의 피해는 매년 증가하고 있는 실정이다. 또한 과거 자연재난에 의한 홍수피해에 기후변화라는 외부요인이 추가적으로 발생하고 있는 실정이며, 국가 경제 발전 및 노령화 사회로 인한 홍수취약인구 증가로 좀 더 적극적인 방재대책이 필요할 것으로 판단된다. 이러한 방재대책 등의 국가정책 수립을 위해서는 장래의 홍수피해 예측이 무엇보다 필요하게 되는데, 현재까지는 홍수피해의 빈도분석 등을 통해 이러한 예측이 이루어지고 있다. 그러나 기후변화라는 외생변수는 과거 자료의 확률적 특성을 마비시켜 이러한 방법론들은 효용성을 잃게될 것으로 전망된다. 홍수피해액을 산정하는 방법은 일반적으로 2005년 이후 하천설계기준에서 채택하고 있는 다차원법을 많이 사용하고 있는데, 이 방법은 침수구역의 물리적 피해를 고려할 수 있어 비교적 정확한 홍수피해액을 산정할 수 있는 것으로 알려져 왔다. 그러나 이 방법을 적용하기 위해서는 정확한 침수심 산정이 무엇보다 필요하게 되는데, 이를 위해서는 지리정보체계(GIS)와 수리모형의 연계가 필수적이다. 따라서 이 방법은 주로 중소유역단위의 취수사업에 적용되어 왔다. 그러나 정책결정에 필요한 대규모유역 또는 지자체단위의 피해비용 산정에의 적용은 한계를 갖게 된다. 따라서 본 연구에서는 향후 기후변화 시나리오에 적용이 가능하도록 과거 홍수피해자료와 호우사상의 강우특성을 중심으로 양자간의 히스토그램 분석을 실시하였다. 또한 실제 홍수피해 조사자료는 대부분 지방자치단체별로 조사가 되고 있는 실정이므로 본 연구에서도 행정구역별로 분석을 수행하였다. 분석 결과 지자체별 전체 피해액은 발생횟수가 높은 중규모 호우사상으로 인한 비중이 가장 높게 나타나고 있으며, 국가에서 집중해야할 치수대책 수립 대상 규모도 이를 중점적으로 고려하여야 할 것으로 판단된다.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.1
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• pp.135-144
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• 2009

The objective of this study is to examine the effect of hydrological factors on critical durations, and to analyze the relationship between the watershed characteristics and the critical duration of design rainfall in the medium sized catchments. Hydrological factors are used to return period, probable intensity formula, hydrograph method, effective rainfall and temporal pattern of design rainfall. Hydrologic analysis has done over the 44 medium sized catchments with $50{\sim}5,000{\beta}{\yen}$. Watershed characteristics such as catchment area, channel length, channel slope, catchment slope, time to peak, concentration of time and curve number were used to simulate correlation analysis. All of hydrological factors except return period influence to the critical duration of design rainfall. Also, it is revealed that critical duration is influenced by the watershed characteristics such as area, channel length, channel slope and catchment slope. Multiple regression analysis using watershed characteristics is carried out for the estimation of relationship among these. And the 7 type equations are proposed by the multiple regression using watershed characteristics and critical duration of design rainfall. The determination coefficient of multiple regression equations shows $0.96{\sim}0.97$.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.125-125
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• 2011

본 연구에서는 기후변화에 의한 자연재해 취약성을 정량적으로 분석하기 위하여 기상인자와 재해발생으로 인한 피해액의 상관관계를 이용하였다. 재해로 인한 피해액은 1994년부터 2008년까지 15년간 전국 시군별로 피해액을 집계한 자료를 이용하였으며, 우리나라 58개 강우관측소의 일강수량 자료를 이용하여 재해에 영향을 줄 수 있는 네 가지 인자를 추출하였고, 연도별 태풍 발생 횟수도 하나의 기상인자로 고려하였다. 피해액의 규모는 가뭄, 화재, 태풍 및 해일 등 재해발생 유형에 따라서도 영향을 받겠지만, 기후변화 시나리오에 의해 예측할 수 있는 대표적인 미래 추정값은 강수량과 온도 등이며, 결국 재해발생 유형별 시나리오에 의한 재해규모 예측이 아닌 기후변화 시나리오에 의한 미래 재해발생 규모 모형을 구축하기 위해서는 관련 인자로서 강수량으로부터 추출한 인자들을 고려할 수밖에 없을 것이다. 일강수량으로부터 추출한 네 가지 영향인자들은 80mm이상 일강수량 발생일수, 80mm이상 일강수량의 합, 80mm이상 강우의 발생 간격이 30일 이하인 횟수 및 연최대강수량이다. 우선 광역시와 도별로 전국 58개 관측소를 분류하고, 해당 관측소들로부터 추출된 인자들의 평균값을 이용하여 연구를 진행하였다. 미래 강수량 자료는 국립기상연구소의 A2시나리오를 통계학적 Downscaling을 통해 재생산한 자료를 이용하였다. 예측모형은 Bayesian 모형을 기반으로 DEXP(double exponential distribution) 확률분포를 이용하였다. 재해피해액 를 아래와 같이 비정상성 모형으로 구성하였으며, 위치매개 변수의 확률분포를 네 가지 기상인자에 의한 회귀식으로 구성하였다. Y damage costs) = dexp(${\mu}(t),\tau(t)$) $p({\mu}(t))\sim(abs({\alpha}+{\alpha}_1X_1+{\alpha}_2X_2+{\alpha}_3X_3+{\alpha}_4X_4,\;\sigma_{\alpha}^2)$ $p(\tau){\sim}G(k,s)$.

• Journal of the Society of Disaster Information
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• v.12 no.1
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• pp.74-88
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• 2016

Predicting and estimating the disaster characteristics are very important for disaster planning such as prevention, preparedness, response, and recovery. Especially, if we can predict the flood damage before flooding, the predicted or estimated damage will be a very good information to the decision maker for the response and recovery. However, most of the researches, have been performed for calculating disaster damages only after disasters had already happened and there are few studies that are related to the prediction of the damages before disaster. Therefore, the objective of this study was to predict and estimate the flood damages rapidly considering the damage scale and effect before the flood disaster, For this the relationship of rainfall and damage had been suggested using nonlinear regression equation so that it is able to predict the damages according to rainfall. We compared the estimated damages and the actual ones. As a result, the damages were underestimated in 14.16% for Suwon-city and 15.81% for Yangpyeong-town but the damage was overestimated in 37.33% for Icheon-city. The underestimated and overestimated results could be occurred due to the uncertainties involved in natural phenomenon and no considerations of the 4 disaster steps such as prevention, preparedness, response, and recovery which were already performed.. Therefore, we may need the continuous study in this area for reducing various uncertainties and considering various factors related to disasters.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.613-621
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• 2022

Due to the global climate change, the rainfall volume and frequency on the Korean Peninsula are predicted to increase at the end of the 21st century. In addition, impervious surface areas have increased due to rapid urbanization which has caused the urban water cycle to deteriorate. Green Infrastructure (GI) researches have been conducted to improve the water cycle soundness; the efficiency of this technique has been verified through various studies. However, there are still no suitable GI design guidelines for this aspect. Therefore, the rainfall scenarios are set up for each percentile (60, 70, 80, 90) based on the volume and frequency analysis using 10-year rainfall data (Busan Meteorological Station). After determining the GI areas for each scenario, the runoff reduction characteristics are analyzed based on Storm Water Management Model (SWMM) 10-year rainfall-runoff-simulations. The total runoff reduction efficiency for each GI areas are computed to have a range of 13.1~52.1%. As a results of the quantitative analysis, the design rainfall for GI is classified into the 80~85 percentile in the study site.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.383-392
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• 2008

It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established. Therefore, uncertainty analysis are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an unexpected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.290-290
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• 2022

본 연구는 대규모 기후 앙상블 모의 결과를 이용하여 산정된 극한 강우량을 최근 발생한 극한 호우사상의 규모 평가에 적용하는 것을 목적으로 수행되었다. 2018 년 히로시마 호우사상은 지속시간 24 시간에서 재현기간 1,000 년에 상응하는 극한 규모를 나타냈기 때문에 짧은 기간동안 수집된 관측자료만으로 규모를 평가하기 어렵다. 따라서 이를 평가하고자 대규모 기후 앙상블 모의결과 기반의 d4PDF 자료를 이용하였다. 이 자료는 3,000 개의 연 최대 강우자료를 제공하고, 이를 토대로 통계적 모형 및 가정 없이 비모수적으로 10 년부터 1,000 년의 재현기간을 나타내는 지속시간 24 시간의 확률강우량을 산정했다. 산정된 d4PDF 의 확률강우량은 관측강우량의 확률강우량과 비교하였으며, 관측기간에 가까운 50 년의 재현기간에서는 두 확률강우량의 차이가 3.53%였지만 관측기간 (33 년)과 재현기간 (100 년 이상)의 차이가 증가할수록 오차가 10% 이상으로 증가하는 양상을 나타냈다. 이는 장기간 재현기간에서 관측강우량의 확률강우량은 불확실성을 내포하는 것을 의미한다. d4PDF 의 확률강우량에 대해서 2018 년 히로시마 호우사상은 300 년에 가까운 재현기간을 나타냈다. 미래 기후조건에서의 d4PDF 자료를 이용해 확률강우량을산정했으며, 현재 기후조건대비 미래 기후조건에서 10 년부터 1000 년의 재현기간을 나타내는 확률강우량은 모두 20% 이상으로 증가했다. 미래 기후조건의 확률강우량에 대해 2018 년 히로시마 호우사상은 100 년에 가까운 재현기간을 나타냈으며, 이는 미래 기후조건에서 히로시마 호우사상의 발생 확률이 0.33% (현재 기후)에서 1% (미래 기후)로 증가하는 것을 의미한다. 결과적으로, 대규모 기후 앙상블 모의결과 기반의 d4PDF 는 현재 기후조건과 미래 기후조건하에서 극한 규모의 호우사상의 정량적인 평가에 유용하게 활용될 수 있다.

• Journal of Korea Water Resources Association
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• v.41 no.4
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• pp.379-394
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• 2008

Recently, extreme precipitation events beyond design capacity of hydraulic system have been occurred and this is the causes of failure of hydraulic structure for flood prevention and of severe flood damage. Therefore it is very important to understand temporal and spatial characteristics of extreme precipitation events as well as expected changes in extreme precipitation events and distributional characteristics during design period under future climate change. In this paper, climate change scenarios were used to assess the impacts of future climate change on extreme precipitation. Furthermore, analysis of future extreme precipitation characteristics and I-D-F analysis were carried out. This study used SRES B2 greenhouse gas scenario and YONU CGCM to simulate climatic conditions from 2031 to 2050 and statistical downscaling method was applied to establish weather data from each of observation sites operated by the Korean Meteorological Administration. Then quantile mapping of bias correction methods was carried out by comparing the simulated data with observations for bias correction. In addition Modified Bartlett Lewis Rectangular Pulse(MBLRP) model (Onof and Wheater, 1993; Onof 2000) and adjust method were applied to transform daily precipitation time series data into hourly time series data. Finally, rainfall intensity, duration, and frequency were calculated to draw I-D-F curve. Although there are 66 observation sites in Korea, we consider here the results from only Seoul, Daegu, Jeonju, and Gwangju sites in this paper. From the results we found that the rainfall intensity will be increased and the bigger intensity will be occurred for longer rainfall duration when we compare the climate conditions of 2030s with present conditions.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.267-278
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• 2022

Recently Flood damage volume has increased as heavy rain has frequently occurred. Especially urban areas are a vulnerability to flooding damage because of densely concentrated population and property. A local government is preparing to mitigate flood damage through the heavy rain warning issued by Korea Meteorological Administration. This warning classification is identical for a national scale. However, Seoul has 25 administrative districts with different regional characteristics such as climate, topography, disaster prevention state, and flood damage severity. This study considered the regional characteristics of 25 administrative districts to analyze the flood vulnerability using entropy weight and Euclidean distance. The rainfall classification was derived based on probability rainfall and flood damage rainfall that occurred in the past. The result shows the step 2 and step 4 of rainfall classification was not significantly different from the heavy rain classification of the Korea Meteorological Administration. The flood vulnerability is high with high climate exposure and low adaptability to climate change, and the rainfall classification is low in the northern region of Seoul. It is possible to preemptively respond to floods in the northern region of Seoul based on relatively low rainfall classification. In the future, we plan to review the applicability of rainfall forecast data using the rainfall classification of results from this study. These results will contribute to research for preemptive flood response measures.