• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2002년도 추계학술발표회
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• pp.277-279
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• 2002

In late of the 1980's, dramatic increase in water use caused over-exploitation of groundwater and deterioration of water quality in urban areas. To monitor quantity of groundwater resources and their qualities, local groundwater monitoring networks were established. Groundwater resources in urban areas are affected by various human activities including underground building construction (subway), pumping for water use, and pavements. Detailed analysis of the monitored groundwater data would provide some good implications for optimal and efficient management for groundwater resources in the urban area.

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

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2005년도 총회 및 춘계학술발표회
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• pp.296-299
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• 2005

Time series of spring discharge data in Jeju island can provide abundant information on the spatial groundwater system. In this study, the classification based on time series of spring discharge was performed with clustering analysis: discharge rate and EC. Peak discharges are mainly observed in august or september. However, double peaks and late peaks of discharge are also observed at a plenty of springs. Based on results of clustering analysis, it can be deduced that GH model is not appropriate for the conceptual model of Groundwater system in Jeju island. EC distributions in dry season are also support the conclusion.

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

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2002년도 총회 및 춘계학술발표회
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• pp.110-113
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• 2002

Statistical- based, principal component analysis (PCA) was applied to chemical data from two underground storage systems containing LPG to assess the usefulness of such technique at the initial stage (Pyeongtaek) or middle stage (Ulsan) of hydrochemical studies. For the first case, both natural and anthropogenic contamination characterize regional groundwater. Saline water buffered by Namyang lake affects as a natural factor, whereas cement grouting influence as an artificial factor. For the second study area, contaminations due to operation of LPG caverns, such as disinfection activity and cement grouting effect, deteriorate groundwater quality. This study indicates that principal component analysis would be particularly useful for summarizing large data set for the purpose of subsurface characterization, assessing their vulnerability to contamination and protecting recharge zones.

• 한국농공학회논문집
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• 제53권6호
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• pp.51-58
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• 2011

The objective of this study is to identify whether or not the ground water level is decreasing. We suggest a method of estimating the change in groundwater level using newly developed groundwater pumping station data. The Goseong area located in Gyeongnam province was selected considering three factors. First, this area demands relatively large amount of irrigation water because most of the land is used as a paddy field and the proportion of the paddy field within total arable land is increasing. Second, groundwater level data in nearby area are available since these are monitored by Water Management Information System (WAMIS). Third, many groundwater pumping stations have been developed in this area in order to overcome droughts thus detail information for pumping stations are available. Regression results indicate groundwater level has been decreased for over 20 years. This decreasing trend is due to the shortage of surface irrigation water which was caused by the decrease in rainfall.

• 한국지하수토양환경학회지:지하수토양환경
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• 제21권6호
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• pp.67-79
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• 2016

Gaussian process regression (GPR) is proposed as a tool of long-term groundwater quality predictions. The major advantage of GPR is that both prediction and the prediction related uncertainty are provided simultaneously. To demonstrate the applicability of the proposed tool, GPR and a conventional non-parametric trend analysis tool are comparatively applied to synthetic examples. From the application, it has been found that GPR shows better performance compared to the conventional method, especially when the groundwater quality data shows typical non-linear trend. The GPR model is further employed to the long-term groundwater quality predictions based on the data from two domestically operated groundwater monitoring stations. From the applications, it has been shown that the model can make reasonable predictions for the majority of the linear trend cases with a few exceptions of severely non-Gaussian data. Furthermore, for the data shows non-linear trend, GPR with mean of second order equation is successfully applied.

• 한국환경과학회지
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• 제17권2호
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• pp.257-267
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• 2008

Groundwater recharge characteristics in a fractured granite area, Mt. Geumjeong, Korea. was interpreted using bedrock groundwater and wet-land water data. Time series analysis using autocorreclation, cross-correlation and spectral density was conducted for characterizing water level variation and recharge rate in low water and high water seasons. Autocorrelation analysis using water levels resulted in short delay time with weak linearity and memory. Cross-correlation function from cross-correlation analysis was lower in the low water season than the high water season for the bedrock groundwater. The result of water level decline analysis identified groundwater recharge rate of about 11% in the study area.

• 지질공학
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• 제19권2호
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• pp.227-233
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• 2009

우리나라는 수자원 특성상 강우의 시간적, 공간적 불균형이 심하여 수자원 개발과 관리여건이 대단히 열악하다. 이에 따라 현시점에서 향후 물 부족에 대처할 신규 수자원의 안정적 확보방안의 하나인 지하댐의 건설 예정지를 파악하고 지표수와 지하수를 연계하여 효과적으로 개발 이용 가능한 지하댐 개발의 국내 적용을 검토 할 필요가 있다. 이번 연구는 지하댐 건설 예정지인 경남 하동군 횡천강 일대의 지질조사, 수리 수문학 분석 등을 통해 프로그램 입력 자료를 산정하였다. 또한 입력자료를 바탕으로 SWAT-MODFLOW를 통해 지표수 및 지하수의 연계 해석을 실시하였으며 지하댐 건설전과 후의 지하수위 변화를 예측하였다.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2001년도 추계학술발표회
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• pp.148-150
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• 2001

Solid-phase microextraction (SPME) was investigated to understand the BTEX extraction behavior of SPME in groundwater. Analytical procedure was conducted In both conventional and headspace mode. And the conventional direct extraction method and the headspace analysis method were compared. Data obtained with direct and headspace SPME were very similar and showed successful results. In headspace analysis, the linearity was better and RSD (relative standard deviation, %) was smaller than direct extraction.