• 한국지하수토양환경학회지:지하수토양환경
• /
• 제21권4호
• /
• pp.30-41
• /
• 2016

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제20권7호
• /
• pp.112-120
• /
• 2015

Statistical trend analysis using the data from the National Groundwater Quality Monitoring Network (NGQMN) of Korea was conducted to establish a new groundwater quality management framework. Sen’s test, a non-parametric statistical method for trend analysis, was used to determine the linear trend of the groundwater quality data. The analysis was conducted at different confidence levels (i.e., at 70, 80, 90, 95, and 99% confidence levels) for three of groundwater quality parameters, i.e., nitrate-nitrogen, chloride, and pH, which have sufficient time series of the NGQMN data between 2007 and 2013. The results showed that different trends can be determined for different depths even for the same monitoring site and the numbers of wells having significant trends vary with different confidence levels. The wells with increasing or decreasing trends were far less than the wells with no trend. Chloride had more wells with increasing trend than other parameters. On the other hand, nitrate-nitrogen had the most wells with increasing trend and concentration exceeding 75% of the threshold values (TVs). Based on the methodology used for this study, we suggest including groundwater TVs and trend analysis to evaluate groundwater quality and to establish an advanced groundwater quality management framework.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제26권6호
• /
• pp.186-195
• /
• 2021

In Korea, groundwater quality is monitored through National Groundwater Quality Monitoring Network (NGQMN) administered by Ministry of Environment. For a given contaminant, compliance to groundwater quality standards is assessed on a annual basis by monitoring the number of incidents that concentration exceeds the regulatory limit. However, this approach provides only a fractional information about groundwater quality degradation, and more crucial information such as location and severity of the contamination cannot be obtained. For better groundwater quality management on a watershed, a more spatially informative and intuitive method is required. This study presents two statistical methods to convert point-wise monitoring data into information on groundwater quality status of a watershed by using a proposed grading scale. The proposed grading system is based on readily available reference standards that classify the water quality into 4 grades. The methods were evaluated with NO₃^-, Cl^-, and total coliform data in Geum River basin. The analyses revealed that groundwater in most watersheds of Geum River basin is good for domestic or/and drinking with no treatment. But, there was notable quality degradation in Bunam seawall and So-oak downstream standard watersheds contaminated by NO₃^- and Cl^-, respectively.

• 한국농공학회논문집
• /
• 제64권6호
• /
• pp.13-23
• /
• 2022

The purpose of this study was to analyze the impact of greenhouse cultivation area and groundwater level changes due to the water curtain cultivation in the greenhouse complexes, which are mainly situated along rivers where water resources are easy to secure. The groundwater observation network in Miryang, Gyeongsangnam-do, located downstream of the Nakdong River, was selected for the study area. We classified the groundwater monitoring well into the greenhouse (riverside) and field cultivation areas (plain and mountain) to compare the groundwater impact of water curtain cultivation in the greenhouse complex. The characteristics of groundwater level changes classified by terrain type were analyzed using the observed data. Riverside wells have significant permeability coefficients and are close to rivers, so they are greatly affected by river flow and precipitation changes so that water level shows a specific pattern of annual changes. Most plain wells do not show a constant annual change, but observation wells near small rivers and small-scale greenhouse cultivation areas sometimes show annual and daily changes in which the water level drops during winter. Compared to other observation wells, mountain wells do not show significant yearly changes in water level and show general characteristics of bedrock aquifer well with a low permeability coefficient.

• 지질공학
• /
• 제23권2호
• /
• pp.137-147
• /
• 2013

지하수자원의 효율적인 관리를 위해 강우에 대한 지하수위 변화를 예측하는 것은 중요한 문제이다. 본 연구에서는 자료기반 학습 알고리즘인 인공신경망과 지지벡터기계를 이용하여 시계열 예측 모델을 만들고 이를 국가지하수관측망 중 가산, 신광, 청성 관측소 지하수위 변화 예측에 적용하였다. 모델의 입력 성분 구성 방법에 따라 네 가지 모형을 설정하고 각 관측소 및 모델 별 예측 결과를 비교 평가하였다. 강우 입력 모형의 경우 지하수위 감쇠 및 기저 변화 예측을 위해 큰 규모의 입력 성분 구성이 필요하지만 강우 및 지하수위 입력 모형은 보다 작은 규모의 입력 성분으로 효과적으로 지하수위 변화를 예측하는 것으로 나타났다. 강우 및 지하수위 입력 모형의 활용성 증대를 위해 고안된 반복 예측 모형의 경우 관측값과 예측값 사이에 0.75~0.95의 상관계수를 보여 적용 가능성이 큰 것으로 판단된다. 전체적으로 강우-지하수위 교차상관계수가 낮은 신광 관측소의 예측 오차가 크게 나타났고 ANN 모델에 비해 SVM의 예측력이 다소 높은 것으로 조사되었다. 또한 반복 예측 모형의 모델 파라미터 선정 과정에서 보정 단계 오차에 대한 예측 단계 오차의 비의 분포를 조사한 결과 SVM의 경우가 더 작게 나타나 SVM이 본 연구 자료에 대해 보다 안정적이고 효율적인 모델임을 평가하였다.

• Nuclear Engineering and Technology
• /
• 제44권6호
• /
• pp.639-652
• /
• 2012

A three-dimensional discrete fracture network model was developed in order to simulate the hydraulic characteristics of a granitic rock mass at Korea Atomic Energy Research Institute (KAERI) Underground Research Tunnel (KURT). The model used a three-dimensional discrete fracture network (DFN), assuming a correlation between the length and aperture of the fractures, and a trapezoid flow path in the fractures. These assumptions that previous studies have not considered could make the developed model more practical and reasonable. The geologic and hydraulic data of the fractures were obtained in the rock mass at the KURT. Then, these data were applied to the developed fracture discrete network model. The model was applied in estimating the representative elementary volume (REV), the equivalent hydraulic conductivity tensors, and the amount of groundwater inflow into the tunnel. The developed discrete fracture network model can determine the REV size for the rock mass with respect to the hydraulic behavior and estimate the groundwater flow into the tunnel at the KURT. Therefore, the assumptions that the fracture length is correlated to the fracture aperture and the flow in a fracture occurs in a trapezoid shape appear to be effective in the DFN analysis used to estimate the hydraulic behavior of the fractured rock mass.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제6권1호
• /
• pp.33-43
• /
• 2001

본 연구에서는 지하수위 변동 곡선을 이용하여 지하수 함양률을 추정하는 기법을 제안하였으며 무강우 기간 지하수위 감수곡선을 이용한 기존의 방법과 비교하였다. 본 연구는 전국 지하수 함양률을 추정하기 위한 연구의 일환으로서 국가 지하수 관측망의 신뢰성 높은 지하수위 자료를 이용하였고 자료가 충실한 세 지역(충주, 진주, 광주)에 대하여 본 방법론을 적용하였다. 이를 위하여 각 지역의 지하수위에 대한 계절적 변동 분석, 지하 수위와 누적 강수량에 대한 시차분석, 지하수 함양률 비교 연구 분석 등을 실시하였다.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제13권1호
• /
• pp.67-76
• /
• 2008

본 연구에서는 지하수위 변동모델과 비포화대 함수모델을 적용한 지하수 함양율 산정 기법을 제안하였다. 기법의 적용성을 살펴보기 위하여 연구지역인 국내 4개 국가지하수 관측소를 선정하였으며 1996년부터 2005년에 이르는 국가 지하수 관측망(포항 연일, 기북, 순천 외서, 홍천 홍천) 수위자료와 포항, 순천, 홍천의 기상청 강우자료가 이용되었다. 각 관측소 주변 토양형에 따른 지하수 함양율은 홍천 관측소가 최소 0.5%에서 최대 61.4%, 포항 연일 관측소는 1.1%에서 27.4%, 포항 기북 관측소는 5.1%에서 41.4%, 및 순천 외서 관측소는 1.1%에서 8.3%의 분포를 보였다. 본 연구에서 이용된 지하수위 변동예측 모델은 지하수위 변동이 강우에 의해서만 발생하는 것으로 가정하였으며 향후 보다 정확한 지하수위 예측을 위해서 지하수 채수나 증발산의 영향을 추가 고려할 필요가 있을 것이라 판단된다. 또한 제안된 기법의 보다 넓은 범위의 적용을 위해서는 비포화 암반의 함수 모델을 도입할 필요가 있을 것이라 판단된다. 현재 본 연구를 공간적으로 확장하여 지역화 하기 위한 연구가 진행 중이다. 본 연구에서 제안하는 지하수 함양율 산정 기법은 가정을 최소화함으로써 방법론적으로 합리적이며 실제 지하수 시스템을 잘 반영하는 과학적인 모델로 기존 지하수 함양율 산정 기법을 충분히 대체할 수 있을 것이라 판단된다.

• 한국지하수토양환경학회:학술대회논문집
• /
• 한국지하수토양환경학회 2004년도 임시총회 및 추계학술발표회
• /
• pp.307-311
• /
• 2004

The unsaturated zone is a significant pathway of the surface contaminant movement and is a highly heterogeneous medium. Therefore, there are limitations in applying conventional convection-dispersion equation(CDE). Artificial neural network(ANN) is considered to be a versatile tool for approximating complex functions. For evaluating the applicability of ANN, numerical tests using ANN were conducted with training set generated by HYDRUS-2D which is based on CDE. The results represent that ANN can estimate the solute transport and the choice of network parameters and generation of training set patterns are important for efficient estimation.

• 한국지하수토양환경학회:학술대회논문집
• /
• 한국지하수토양환경학회 2005년도 총회 및 춘계학술발표회
• /
• pp.348-351
• /
• 2005

In this study, solute breakthrough curves through the unsaturated zone were predicted using artificial neural network (ANN) by numerical tests and laboratory experiments. In the numerical tests, applicability of ANN model to prediction of breakthrough curves was evaluated using synthetic data generated by HYDRUS-2D. An appropriate strategy of ANN application and input data form were recommended. The ANN model was validated by laboratory experiments comparing with HYDRUS-2D simulations. The results show that the ANN model can be an effective method for forecasting solute breakthrough curves through the unsaturated zone when hydraulic data are available.