• Journal of Climate Change Research
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• v.4 no.4
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• pp.331-348
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• 2013

The frequency and intensity of abnormal climate caused by climate change is increasing in Korea. Also, the amount of damage from disaster is increasing rapidly. The research on vulnerability assessment analyzes environmentally, socially and economically vulnerable indicators and is ongoing to reduce the intensity of damage and establish adaptation policies for climate change. Therefore, in this study, we assessed vulnerability using weighting value derived by the regression equation. There are 3 evaluation items : vulnerability assessment for farmland erosion to flood, vulnerability assessment for health to heat wave, vulnerability assessment for forest fire to drought. For this study, indicators for each sectors were selected and spatial data for each sectors were established using GIS program. Results showed that vulnerability to heat wave was more affected by climate factors. On the other hand, vulnerability to flood and drought was more affected by social-economic factors. Then, to analysis efficiency of the regression analysis, vulnerability result was compared between the existing vulnerability research with no weighting applied and the vulnerability research with the influence of weighting value derived by the regression. This study showed that the regression analysis is efficient to provide practical and feasible alternatives in terms of planning climate change adaptation policies and it is expected to be utilized for vulnerability assessment in the future.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1127-1134
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• 2018

According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), climate change increases the frequency of abnormal weather phenomenon. As the frequency of abnormal weather phenomenon increases, frequency of disasters related to water resources such as floods and droughts also increases. Drought is the main factor that directly affects water supply. Recently, the intensity of drought and the frequency of drought occurrence have increased in Korea. So, there is a need for water resource securing technology for stable water supply. Korean Water Plan mentioned that water reserves concept is necessary for stable water supply. Most multi-purpose reservoirs in Korea have emergency storage in addition to conservation storage used for water supply. However, there is no clear use standard for emergency storage. This study investigated the use of reservoir reserves for stable water supply. In order to consider the climate change impact, the AR5-based hydrological scenario was used as inflow data for the reservoir simulation model. Reservoir simulations were carried out in accordance with the utilization conditions of emergency storage and water supply adjustment standard. The optimal reserves for each multi-purpose reservoirs was estimated using simulation results.

• Journal of Wetlands Research
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• v.15 no.4
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• pp.595-607
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• 2013

In this study we estimated ETCCDI and frequency based precipitation using observed precipitation and precipitation from Representative Concentration Pathway(RCP) scenarios for 58 weather stations which have the recorded data more than 30 years. We tried to eliminate the bias by Quantile Mapping and tested for outliers of simulated data under climate change scenario. Then we estimated ETCCDI related to precipitation and frequency based precipitation for the future. In addition to this study examined the changes of frequency based precipitation for the future target periods. According to the result, dry days will be increased in Korean Peninsula in the 2090s. Also it showed that the number of heavy precipitation day more than 80mm/day tends to be increased in 3~7% in the future. The precipitation of 24-hour duration under climate change will be increased by 17.7% for 80-year frequency, 18.2% for 100-year frequency and 19.6% for 200-year frequency in 2090s. In the 21st century, the damage caused by natural disasters is expected to be increased due to increase of precipitation and the change of runoff characteristics under climate change. Therefore, the proposed ETCCDI and precipitation frequency under climate change are expected to be used for the future natural disaster plan.

• Journal of Korea Water Resources Association
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• v.46 no.2
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• pp.195-204
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• 2013

As drought is phenomenon of nature with unavoidability and repeated characteristic, it is necessary to plan to respond to it in advance and construct drought management system to minimize its damage. This study suggested standard for classification of drought, which is appropriate for our nation to respond to drought by assessing drought severity in the regions for this study. For data collection, 61 locations were selected - the locations keep precipitation data over 30 years of observation. And data for monthly precipitation for 37 years from 1973 were used. Based on this, this study classified unified drought interval into four levels using drought situation phases which are used in government. For standard for classification of drought severity fit to our nation, status of main drought was referred and these are classified based on accumulated probability of drought - 98~100% Exceptional Drought, 94~98% Extreme Drought, 90~94% Severe Drought, 86~90% Moderate Drought. Drought index (SPI, PDSI) was made in descending order and quantitative value of drought index fit to standard of classification for drought severity was calculated. To compare classification results of drought severity of SPI and PDSI with actual drought, comparison by year and month unit were analyzed. As a result, in comparison by year and comparison by month unit of SPI, drought index of each location was mostly identical each other between actual records and analyzed value. But in comparison by month unit of PDSI for same period, actual records did not correspond to analyzed values. This means that further study about mutual supplement for these indexes is necessary.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.403-411
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• 2016

Recently, the number of occurrences of inundation and the severity of flood damage has increased rapidly as the frequency of localized heavy rainfall and the ratio of impervious area increased in urban areas. Most local governments focus on employing structural measures (e.g., the construction of detention reservoirs/pump stations, rehabilitation of drainage and sewer pipes) to prevent urban inundation. On the other hand, the effectiveness of implementing such structural measures is being dimished because there are already many inundation prevention facilities. The limitation of structural measures can be overcoming by employing non-structure measures, such as flood alerts and the operation of drainage facilities. This study suggests the pump operation rule (i.e., suggesting pump stop level) for a new detention reservoir operating method, which triggers the operation of a pump based on the water level at the monitoring node in urban drainage system. In the new reservoir operation, a total of 48 rainfall events are generated by the Huff distribution for determining the proper pump stop level. First, the generated rainfall events are distributed as frequencies, quartiles, and durations. The averaged system resilience value was determined to range from 1.2 m to 1.5 m is based on the rainfall-runoff simulation with rainfall generated by the Huff distribution. In this range, 1.2 m was identified considering the safety factor of 1.25 by the Standard on sewer facilities in 2011.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.381-381
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• 2017

수자원 분야에 대한 기후변화의 영향은 홍수, 가뭄 등 극치 수문사상의 증가와 변동성 확대를 초래하는 것으로 알려져 있으며, 이에 따라 예년에 비해 발생빈도 및 심도가 증가한 가뭄에 대한 모니터링 및 피해경감을 위해 정부에서는 국민안전처를 비롯한 관계기관 합동으로 생활 공업 농업용수 등 분야별 가뭄정보를 제공하고 있다. 국토교통부와 환경부는 생활 및 공업용수 분야의 가뭄정보 제공을 위해 광역 지방 상수도를 이용하는 급수 지역과 마을상수도, 소규모급수시설 등 미급수지역의 용수수급 정보를 분석하여 가뭄 분석정보를 제공 중에 있다. 하지만, 미급수지역에 대한 가뭄 예?경보는 기준이 되는 수원정보의 부재로 기상 가뭄지수인 SPI6를 이용하여 정보를 생산하고 있다. 기상학적 가뭄 상황과 물부족에 의한 체감 가뭄은 차이가 있으며, 미급수 지역의 경우 지하수를 주 수원으로 사용하는 지역이 대부분으로 기상학적 가뭄지수인 SPI6를 이용한 가뭄정보로 실제 물수급 상황을 반영하기는 부족한 실정이다. 따라서 본 연구에서는 미급수지역의 주요 수원인 지하수의 수위 상황을 반영한 가뭄모니터링 기법을 개발하고자 하였으며, 가용량 분석이 현실적으로 어려운 지하수의 특성을 고려하여 수위 거동의 통계적 분석을 통해 가뭄을 모니터링 할 수 있는 방법으로 접근하였다. 국가지하수관측소 중 관측기간이 10년 이상이고 강우와의 상관성이 높은 관측소들을 선정한 후, 일수위 관측자료를 월별로 분리하여 1월~12월 각 월에 대해 핵밀도 함수 추정기법(kernel densitiy estimation)을 적용하여 월별 지하수위 분포 특성을 도출하였다. 각 관측소별 관측수위 분포에 대해 백분위수(percentile)를 이용하여, 25%~100% 사이는 정상, 10%~25% 사이는 주의단계, 5%~10% 사이는 심한가뭄, 5% 이하는 매우심함으로 가뭄의 단계를 구분하였다. 각 백분위수에 해당하는 수위 값은 추정된 Kernel Density와 Quantile Function을 이용하여 산정하였고, 최근 10일 평균수위를 현재의 수위로 설정하여 가뭄의 정도를 분류하였다. 분석된 결과는 관측소를 기점으로 역거리가중법(inverse distance weighting)을 통해 공간 분포를 시켰으며, 수문학적, 지질학적 동질성을 반영하기 위하여 유역도 및 수문지질도를 중첩한 공간연산을 통해 전국 지하수 가뭄상태를 나타내는 지하수위 등급분포도를 작성하였다. 실제 가뭄상황과의 상관성을 분석하기 위해 언론기사를 통해 확인된 가뭄시기와 백문위수 25%이하로 분석된 지하수 가뭄시기를 ROC(receiver operation characteristics) 분석을 통해 비교 검증하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.545-553
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• 2021

The frequency by water disaster in urban areas are increasing continuously due to climate change and urbanization. Countermeasures are being conducted to reduce the damage caused by water disasters. An analysis based on permeability, one of the parameters that affect runoff, is needed to predict quantitative runoff in urban watersheds and study runoff reduction. In this study, the SWAT model was simulated for the oncheon stream basin, a representative urban stream in Busan. The permeability map was prepared by calculating the CN values for each hydrologic response unit. Based on the permeability map prepared, EPA SWMM analyzed the effect of LID technology application on the water cycle in the basin for short-term rainfall events. The LID element technology applied to the oncheon stream basin was rooftop greening in the residential complex, and waterproof packaging was installed on the road. The land cover status of the land selected based on the permeability map and the application of LID technology reduced the outflow rate, peak flow rate, and outflow rate and increased the infiltration. Hence, LID technology has a positive effect on the water cycle in an urban basin.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.9-15
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• 2021

The frequency of flash floods in mountainous areas is increasing due to the abnormal weather that occurs increasingly in the recent, and it causes human and material damages is increasing. Various plans for disaster mitigation have been established, but artificial plans such as raising embankment and dredging operation are inappropriate for valleys and rivers in national parks that prioritize nature protection. In this study, flood risk assessment was conducted for Gyeryongsan National Park in Korea using the WMS (Watershed Modeling System)which is rainfall runoff model for valleys and rivers in the catchment. As the result, it was simulated that it is flooding in three sub-catchments (Jusukgol, Sutonggol, Dinghaksa) of a total in Gyeryongsan National Park when rainfall over the 50 years return period occurs, and it was confirmed that the risk of trails and facilities what visitors are using was high. The risk of trails in national parks was quantitatively presented through the results of this study, and we intend to present the safe management guidelines of national parks in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.487-487
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• 2021

탁수는 유기물 또는 무기물이 유입되면서 빛의 투과성이 낮아진 수체를 의미한다. 탁수가 발생하게 되면 어류의 폐사, 정수처리 비용의 증가 및 경관의 변화로 인한 피해가 발생하게 된다. 국내에서는 홍수기 또는 태풍 시 유역의 토사가 저수지 상류에서 유입하여 호내의 탁수를 발생시키는 경우가 있는데, 특히 낙동강 유역의 임하호에서 빈번하게 고탁수가 발생하여 왔다. 본 연구에서는 임하호에서 탁수 발생 시 신속 배제를 위한 수치적인 예측 시스템을 소개하고자 한다. 저수지 탁수관리의 기본개념은 용수공급능력을 고려한 고탁수의 신속한 배제이다. 이는 선제적 의사결정을 요구하므로, 지류에서 탁수가 발생한 즉시 향후 상황에 대한 예측이 필요하다. 이러한 예측을 위해 유역관리처는 3단계의 수치해석을 수행한다. 첫 번째는 유역 상류에서 탁수가 감지되었을 때, 호 내 탁수의 분포를 예측하는 것이다. 수심 및 수평방향의 탁수 분포에 대한 상세한 결과가 도출되어야 하기에, 3차원 수치해석 프로그램인 AEM3D를 이용한다. 이때, 과거 고탁수 유입에 대한 자료를 기반으로 산정된 매개변수가 적용된다. 두 번째는 예측된 호내 분포를 초기조건으로 댐 방류량 및 취수탑 위치(선택배제)에 따른 탁수 배제 수치해석을 수행하게 된다. 다양하고 많은 case에 대한 신속한 모의 및 3달 이상의 장기간 예측을 요구하므로, 2차원 수치모델인 CE-QUAL-W2를 활용한다. 이 단계에서 수자원의 안정적 공급이 가능한 범위 내에서 효과적인 탁수 배제 방류 방법 등이 결정되며, 방류 탁도가 예측된다. 세 번째 단계는 방류탁도를 경계조건으로 하여 하류 하천(반변천~내성천 합류 전)의 탁도를 예측하는 것이다. 하천의 탁도 예측은 국내뿐만 아니라 국외에서도 그 사례를 찾아보기가 쉽지 않은데, 이는 중소형의 지류에 대한 입력자료가 충분하지 않고 불확실성이 높기 때문이다. 이에 과거 10여 년의 data를 이용한 회귀분석을 통해 탁수 발생물질(SS)-부유사-유량과의 관계를 도출하고, 2차원 하천모델(EFDC)을 이용하여 수심 평균 탁도를 예측하게 된다. 이러한 세 단계의 예측은 탁수가 호내로 유입됨에 따라 반복되고, 점차 예측 정확도가 향상되게 된다. 세 단계의 과정을 통한 임하호 탁수의 조기 배제는 현재 적지 않은 효과를 거두고 있다고 판단된다. 그러나 탁수를 발생시키는 현탁물질의 종류는 매번 일정하지 않기 때문에, 이러한 예측 시스템에 정확도에 영향을 줄 수 있으므로, 여러 상황을 고려한 딥러닝을 도입하여 탁수 물질에 대한 정보를 예측한다면 보다 합리적인 의사결정 지원 도구가 될 수 있을 것이다.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.