• Journal of Soil and Groundwater Environment
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• v.15 no.2
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• pp.18-23
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• 2010

Usability of soil quality monitoring network for ascertaining soil quality changes was evaluated by analysing soil quality monitoring results. Tolerance limits of soil quality monitoring results from 1997 to 2007 were calculated and compared with Korean soil quality standards. This study determined that soil quality was changed if the upper 95% tolerance limit value was greater than the soil quality standard. Fluoride most frequently exceeded the soil quality standard and nickel, zinc, arsenic, copper, lead and cadmium were followed. Analysis on land use showed that tolerance limits of industrial land use most frequently exceeded the soil quality standards and residential, road and various land uses then frequently exceeded. Tolerance limits of land uses expecting high contaminant loads frequently exceeded the soil quality standards. This fact imply that the soil quality monitoring network generates reasonable data to represent change in Korean soil quality. This study also suggested that representative sampling from well identified points should be done to improve data reliability and accurately ascertain soil quality changes.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.04a
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• pp.94-96
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• 2003

Since 1995, MOCT(Ministry of Construction and Transportation) and KOWACO(Korea Water Resources Corporation) have established the National Groundwater Monitoring Network in South Korea and also MOE(Ministry of Environment) has operated Groundwater Quality Monitoring network. Until 2001, 202 monitoring stations by MOCT and 780 monitoring wells by MOE have been constructed, measured groundwater level and analyzed water samples. Groundwater quality analysis has been conducted two times a year during last 6 years for all monitoring wells. The quality data has about 15 components including pH, COD, Count of Coliform group, and etc.. Trend analysis has been peformed for 6 components(Coliform, pH, COD, NO$_3$-N, Cl and EC) of water quality which are analyzed more than 7 times for total monitoring wells. Two test methods have been used ; Sen's test and Mann-Kendall test. These trend tests have been done at the 0.05 significance level. By the result of Sen's test, Count of Coliform group has either upward or downward trends at 4.3 percent of the monitoring points. pH does at 5.6 percent, COD does at 8.6 percent, Nitrate-Nitrogen does at 13.2 percent, Chloride does at 13.4 percent, and. EC does at 11.6 percent of the monitoring points. The exact causes of the groundwater quality trends are difficult to specify. Notable downward trends in nitrate at many monitoring points may be the result of reduction on some contamination sources. Potential causes include diminished agricultural areas, improvements in sewage treatment and a decrease in atmospheric deposition. Increase in chloride at many monitoring points may be the result of increased non-point source pollution such as road salting and runoff from sprawling paved developments and suburbs.

• Journal of Soil and Groundwater Environment
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• v.21 no.4
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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.

• Journal of Soil and Groundwater Environment
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• v.20 no.7
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• pp.112-120
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• 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.

• Journal of Soil and Groundwater Environment
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• v.18 no.2
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• pp.19-26
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• 2013

This study developed the classification of National Soil Quality Monitoring Network (NSQM) and its site selection criteria to meet the recently established purposes of the NSQM. The NSQM were suggested by this study to classify into the six-purposes site groups from the current classification of land uses. The six purposes site groups were 1) intensive observation sites, 2) contaminant loading sites, 3) human activity sites, 4) background sites, 5) river soil sites, and 6) sites near the groundwater quality monitoring wells. Furthermore, this study developed the site selection criteria of NSQM utilizing the accumulated NSQM data, road traffic data, chemical emission data, census, soil information, and the literature related to soil quality variation due to contaminant loads. For selecting suitable sites for NSQM, this study used road traffic, chemical emission, the distance from the contaminant sources, and population information as specific criteria. The suggested site classification and criteria were appled for the current 100 NSQM sites for evaluation. Forty sites were met to the criteria suggested by this study, but sixty sites were not met to the criteria. However, some of the sixty sites also included the obscure sites that their addresses were not apparent to find them.

• Journal of Soil and Groundwater Environment
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• v.25 no.4
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• pp.67-76
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• 2020

Polycyclic aromatic hydrocarbons (PAHs) are organic compounds that tend to persist in environmental media for a long period of time. This work presents a 2-year monitoring study of occurrence of three PAHs (benzo(a)pyrene, naphthalene, and fluoranthene) in groundwater. The groundwater samples were collected from 106 sites of nation's groundwater quality monitoring network and analyzed by simultaneous analysis method to quantify the concentrations of the PAHs. Benzo(a)pyrene was not detected in all samples. Naphthalene and fluoranthene concentrations ranged from not detected to 12.8 ng/L and not detected to 10.5 ng/L with their detection frequency being 57.8 and 4.2%, respectively. The concentrations of PAHs in ground- and drinking waters are not currently regulated in Korea, but the concentration levels of naphthalene and fluoranthene found in this work were lower than the regulatory limits of other countries (naphthalene 0.001~0.07 mg/L, fluoranthene 0.001~1.4 mg/L). The monitoring result of this study revealed that PAHs exist as trace amounts in domestic groundwater, however continuos monitoring is necessary to protect groundwater from PAHs contamination with growing industrialization and urbanization.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.13-23
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• 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.

• Clean Technology
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• v.26 no.1
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• pp.39-54
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• 2020

This study analyzed the groundwater quality according to the depth and geological features in Gyeongsangnam-do area using groundwater quality monitoring network data to grasp the groundwater quality characteristics and to provide basic data for policy making on efficient groundwater management. Five hundred and three data sets were acquired from background water quality exclusive monitoring network in soil groundwater information system for five years (2013 ~ 2017). Except for the total coliforms and tracer items such as mercury, phenol, and others, the parameters of water quality were significant or very significant, depending on depth and geological features. As the depth got deeper, the average value of pH and electrical conductivity increased; water temperature, dissolved oxygen, oxide reduction potential, arsenic, total coliforms, and turbidity decreased; and total unfit rate for drinking water standards was lower. It was found that the sum of the positive and negative ions was the highest in the clastic sedimentary rock and the lowest in metamorphic rock. The total unfit rate for drinking water standards was the highest for metamorphic rocks, followed by clastic sedimentary rock and unconsolidated sediments and, finally, intrusive igneous rock with the lowest penetration. The Na-Cl water type, which indicated the possibility of contamination by external pollutants, appeared only at some points in shallow depths and in clastic sedimentary rocks.

• The Journal of Engineering Geology
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• v.23 no.2
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• pp.137-147
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• 2013

For the effective management of groundwater resources, it is necessary to predict groundwater level fluctuations in response to rainfall events. In the present study, time series models using artificial neural networks (ANNs) and support vector machines (SVMs) have been developed and applied to groundwater level data from the Gasan, Shingwang, and Cheongseong stations of the National Groundwater Monitoring Network. We designed four types of model according to input structure and compared their performances. The results show that the rainfall input model is not effective, especially for the prediction of groundwater recession behavior; however, the rainfall-groundwater input model is effective for the entire prediction stage, yielding a high model accuracy. Recursive prediction models were also effective, yielding correlation coefficients of 0.75-0.95 with observed values. The prediction errors were highest for Shingwang station, where the cross-correlation coefficient is lowest among the stations. Overall, the model performance of SVM models was slightly higher than that of ANN models for all cases. Assessment of the model parameter uncertainty of the recursive prediction models, using the ratio of errors in the validation stage to that in the calibration stage, showed that the range of the ratio is much narrower for the SVM models than for the ANN models, which implies that the SVM models are more stable and effective for the present case studies.

• Journal of Soil and Groundwater Environment
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• v.16 no.6
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• pp.113-121
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• 2011

In this study, we suggested the management scheme of analyzing the national and oversea related policy against soil and groundwater contamination by radioactive materials due to nuclear accidents. In Korea, we need to remedy swiftly the contaminated land due to intensive land development demand. So, we need to develop more effective management scheme to recover actively the land contaminated by radioactive materials. We require to improve monitoring network, to expand media-specific monitoring system, to prepare management system for remediation of contaminated land, and to develop flow work for soil and groundwater remediation.