• Journal of Environmental Policy
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• v.12 no.3
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• pp.21-47
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• 2013

The aim is to analysis landslide vulnerability in Inje, Korea, using GCI(Geospatial Correlative Integration) and probability rainfalls based on geographic information system (GIS). In order to achieve this goal, identified indicators influencing landslides based on literature review. We include indicators of exposure to climate(rainfall probability), sensitivity(slope, aspect, curvature, geology, topography, soil drainage, soil material, soil thickness and soil texture) and adaptive capacity(timber diameter, timber type, timber density and timber age). All data were collected, processed, and compiled in a spatial database using GIS. Karisan-ri that had experienced 470 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data, while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 3-day cumulative rainfalls of 449 mm. Results show that number of slope has comparatively strong influence on landslide damage. And inclination of $25{\sim}30^{\circ}C$, the highest correlation landslide. Improved previous landslide vulnerability methodology by adopting GCI. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing landslide mitigation policies.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.66-66
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• 2020

최근 기후변화로 인한 전 세계적인 기온상승이 야기되고 있으며, 농업에 직접적인 영향을 주는 기상학적 및 수문학적 변화가 급격하게 진행되고 있다. 우리나라의 경우 최근 7년 동안 지역별로 극심한 가뭄이 매년 발생하고 있고, 가뭄의 발생 빈도와 강도가 증가하는 추세이다. 특히 밭의 경우 농업용 저수지 등 수리시설물로부터 관개용수를 공급받는 논 작물과 달리 자연 강우를 통해 필요한 용수량을 공급받는 천수답이 대부분이고 관개시설이 부족하기 때문에, 기후변화에 의한 가뭄의 취약성이 높다. 밭작물은 작물의 생육 시기와 기후 환경, 수자원 환경에 민감하고 토양수분을 흡수함으로써 생육하기 때문에 이러한 밭작물의 소비수량 및 관개용수량은 증발산량 뿐만 아니라 토양내 수분의 이동을 고려하여 수분 부족량을 산정해야 한다. 본 연구에서는 미래 기후변화에 의한 밭가뭄 평가를 위하여 밭 작물별 소비수량 및 관개용수량을 추정하기 위한 밭 토양수분 물수지 모형 (Soil Moisture Model)을 구성하였다. 또한 대표농도경로 (Representative Concentration Pathway, RCP) 시나리오 기반의 제5차 결합기후모델상호비교사업 (Coupled Model Intercomparison Project Phase 5, CMIP5)에서 제공하는 RCP 시나리오를 기반으로 한 전지구 기후모델 (General Circulation Model, GCM)의 기후예측결과를 적용함으로써 미래 밭 가뭄 평가를 수행하였다. 과거 기상자료 및 미래 대표농도경로 시나리오와 작물 기초자료를 수집하여 과거 및 미래 작물증발산량을 산정하였으며, 토양수분 물수지 모형에 적용하여 밭작물의 토양수분 변화를 모의하고 기후변화에 따른 작물별/생육시기별 소비수량 및 관개용수량을 추정하였다.

• Journal of Soil and Groundwater Environment
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• v.13 no.4
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• pp.40-53
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• 2008

Groundwater pollution prediction methods have been developed to plan the sustainable groundwater usage and protection from potential pollution in many countries. DRASTIC established by US EPA is the most widely used groundwater vulnerability mapping method. However, the DRASTIC showed limitation in predicting the groundwater contamination because the DRASTIC method is designed to embrace only hydrogeologic factors. Therefore, in this study, three different methods were applied to improve a groundwater pollution prediction method: US EPA DRASTIC, Modified-DRASTIC suggested by Panagopoulos et al. (2006), and LSDG (Land use, Soil drainage, Depth to water, Geology) proposed by Rupert (1999). The Modified-DRASTIC is the modified version of the DRASTIC in terms of the rating scales and the weighting coefficients. The rating scales of each factor were calculated by the statistical comparison of nitrate concentrations in each class using the Wilcoxon rank-sum test; while the weighting coefficients were modified by the statistical correlation of each parameter to nitrate concentrations using the Spearman's rho test. The LSDG is a simple rating method using four factors such as Land use, Soil drainage, Depth to water, and Geology. Classes in each factor are compared by the Wilcoxon rank-sum test which gives a different rating to each class if the nitrate concentration in the class is significantly different. A database of nitrate concentrations in groundwaters from 149 wells was built in Keumsan area. Application of three different methods for assessing the groundwater pollution potential resulted that the prediction which was represented by a correlation (r) between each index and nitrate was improved from the EPA DRASTIC (r = 0.058) to the modified rating (r = 0.245), to the modified rating and weights (r = 0.400), and to the LSDG (r = 0.415), respectively. The LSDG seemed appropriate to predict the groundwater pollution in that it contained land use as a factor of the groundwater pollution sources and the rating of each class was defined by a real pollution nitrate concentration.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.408-408
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• 2011

수자원관리와 수문모형에 있어 강수, 증발산, 침투, 침루 등의 물 순환과정에 대한 실질적인 이해와 분석연구의 중요도가 높아지고 있는 실정이며, 그중에서도 토양수분은 강수의 침투, 유출 등의 지표면과 대기사이의 질량 및 에너지이동에 관여하는 중요한 요소로서 수자원 및 수문현상에 직접적인 영향을 미친다. 이를 위해 강수, 증발산, 토양수분과 같은 수문변수에 대한 다양한 관측이 실시되어야 하지만 국내에서는 지속적이고 안정적으로 지상관측을 할 수 없는 실정이며 관련 기반기술도 매우 취약하다. 따라서 이를 극복하기 위해서는 위성영상자료를 이용함으로써 한반도 전체에 대한 광역적인 토양수분자료의 획득을 용이하게 한다. 본 연구의 연구유역은 수자원 연구를 위해서 지정된 용담댐 시험유역으로 하였으며, 토양수분 관측지점의 지상관측 수문자료인 각 지점별 강수량, 지면온도, 인공위성자료인 MODIS 정규식생지수 등의 가용자료를 수집하고 신경망모형을 활용한 토양수분자료 생산 모형을 개발하여, 개선된 시공간 분해능과 공간정보 대표성을 가진 광역 토양수분자료를 생산하고 적용타당성을 분석하였다. 산정된 토양수분모형의 적용가능성을 파악하고자 용담댐 유역의 각 지점별 토양수분 관측데이터와 추정데이터를 비교한 결과 추천, 부귀, 상정 지점의 경우 평균 약 0.9257의 상관계수와 약 1.2917의 평균제곱근오차를 보였고, 검증지점인 천천2의 경우 약 0.8982의 상관계수와 약 5.1361의 평균제곱근오차의 결과를 보여주었으며 토양수분 추정모형의 적용가능성이 높음을 확인할 수 있었다.

• Journal of Soil and Groundwater Environment
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• v.15 no.5
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• pp.32-39
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• 2010

In this study, we applied DRASTIC and SINTACS models for the assessment of groundwater vulnerability to Buyeo-eup area in Buyeo-gun, Chungcheongnam-do, Korea. Currently, DRASTIC model is a main tool for the assessment of groundwater vulnerability, which has been widely applied for the multiple purposes related to local developments, construction projects, groundwater investigations, etc. since 1980s. Because DRASTIC model has been the sole tool used for the domestic environment, there has been doubt about the degree of reliability of the model, and a benchmark model has been sought by the many practitioners. The objective of this study is to check the applicability of SINTACS model to domestic environment, which is the first attempt in Korea as far as authors understand. The comparative results show that the DRASTIC assessment underestimates groundwater vulnerability of the aquifers composed of fractured bedrocks while that from the SINTACS model is relatively higher. Through this study, it is expected that SINTACS model serves as a reasonable alternative of DRASTIC model where the subsurface is composed of more than two different media such as fractured rocks and alluvium.

• Journal of Soil and Groundwater Environment
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• v.18 no.3
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• pp.119-133
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• 2013

In the present study, several groundwater vulnerability assessment methods were applied to an agricultural area of Gumma in Korea. For the groundwater intrinsic vulnerability assessment, the performance of DRASTIC, SINTACS and GOD models was compared and an ensemble approach was suggested. M-DRASTIC and multi-linear regression (MLR) models were applied for the groundwater specific vulnerability assessment to nitrate of the study site. The correlation coefficient between the nitrate concentration and M-DRASTIC index was as low as 0.24. The result of the MLR model showed that the correlation coefficient is 0.62 and the areal extents of livestock farming and upland field are most influential factors for the nitrate contamination of groundwater in the study site.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.280-280
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• 2017

국내의 사면안정평가는 국토교통부, 국민안전처, 산림청 등의 주요 기관에서 사면을 구성하고 있는 토양특성과 사면경사 등을 평가할 수 있는 기준을 마련하고 있다. 대부분 경우 이 기준을 가지고 자연사면의 안정성에 대한 전반적인 평가가 이루어지고 있다. 하천관리에서는 다양한 요소들을 고려하여 계획이 수립되고 실행되고 있으며 이 중 산지와 기타 지역에서 유입유사는 그 정도에 따라 하천의 통수능력 감소와 하천생태계 교란 등의 많은 영향을 미치고 있다. 이러한 이유에서 유사는 하천관리에 있어 매우 중요한 관리 대상이다. 그러나 현재 평가기준을 이용하여 사면의 붕괴 및 취약정도를 판단할 수 있으나 유역의 유사발생여부를 평가하기에는 상당한 오류를 가지게 된다. 본 연구에서는 사면평가기준을 통한 1차적인 평가와 강우로부터 발생하는 토양침식과 퇴적을 분석 결과를 적용한 종합적인 2차적인 평가를 수행하였다. (1)기존에 사용하고 있는 사면안정평가기준을 가지고 대상유역인 금호강유역의 토양특성에 대한 등급을 분류한다. (2)토층, 토지이용, 빈도별 강우자료 등 다양한 인자를 고려할 수 있는 C-SEM(Cell-based Sediment Erosion Model)을 이용하여 침식 및 퇴적 깊이를 계산한다. (3)사용하고 있는 평가기준과 침식 및 퇴적깊이에 대한 분석결과를 조합하여 금호강유역에서의 유사발생 평가를 위한 지도를 작성한다. 이 연구는 국가에서 제공하고 있는 유역관련 자료를 이용하여 대상유역에서 유사발생을 평가하고 유사발생 관련인자를 대상으로 평가기준을 제안하였다.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.95-105
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• 2021

Extensive groundwater abstraction has been recognized as one of the major challenges in management of coastal groundwater. The purpose of this study was to assess potential changes of groundwater distribution of northeastern Jeju Island over 10-year duration, where brackish water have been actively developed. To quantitatively estimate the coastal groundwater resources, numerical simulations using three-dimensional finite-difference density-dependent flow models were performed to describe spatial distribution of the groundwater in the aquifer under various pumping and recharge scenarios. The simulation results showed different spatial distribution of freshwater, brackish, and saline groundwater at varying seawater concentration from 10 to 90%. Volumetric analysis was also performed using three-dimensional concentration distribution of groundwater to calculate the volume of fresh, brackish, and saline groundwater below sea level. Based on the volumetric analysis, a quantitative analysis of future seawater intrusion vulnerability was performed using the volume-based vulnerability index adopted from the existing analytical approaches. The result showed that decrease in recharge can exacerbate vulnerability of coastal groundwater resources by inducing broader saline area as well as increasing brackish water volume of unconfined aquifers.

• Journal of Korean Society of Disaster and Security
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• v.12 no.2
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• pp.65-72
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• 2019

More than 64% of Korea's land is occupied by mountain regions, which have terrain characteristics that make it vulnerable to mountain disasters. The trails of Taebaeksan Mountain National Park-the region considered in this study-are located in the vicinity of steep slopes, and therefore, the region is vulnerable to landslides and debris flow during heavy storms. In this study, a slope stability model, which is a deterministic analysis method, was used to examine the potential occurrence of landslides. According to the soil classification of the detailed soil map, the specific weight of soil, effective cohesion, internal friction angle of soil, effective soil depth, and ground slope were used as the parameters of the model, and slope stability was evaluated based on the DEM of a 1 m grid. The results of the slope stability analysis showed that the more hazardous the area was, the closer the ratio of groundwater/effective soil depth is to 1.0. Further, many of the private houses and commercial facilities in the lower part of the national park were shown to be exposed to danger.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.47-57
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• 2010

The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.