• Journal of Soil and Groundwater Environment
• /
• v.18 no.6
• /
• pp.1-7
• /
• 2013

Groundwater development and use have been increasing in Korea causing frequent occurrences of related hazards such as groundwater level decline, land subsidence, and groundwater contamination. To tackle these groundwater problems, central and local governments have set-up and maintained many groundwater monitoring programs such as the National Groundwater Monitoring Network and the Groundwater Quality Monitoring Network, which collect very valuable data on the overall status of domestic groundwater to aid proper groundwater management. However, several problems mainly related to the remediation of contaminated groundwater remain unresolved. Recently, there have been some incidents related to the contamination of groundwater, and these have drawn the concern of the Korean people. Although groundwater contamination has been investigated in detail, actual groundwater remediation work has not yet been implemented. The remediation of the contaminated groundwater must begin immediately in order to sustain the eco-system service of clean groundwater and enhance the welfare of the Korean people.

• Journal of Soil and Groundwater Environment
• /
• v.12 no.6
• /
• pp.92-99
• /
• 2007

As of 2007, there are 2,499 groundwater quality monitoring stations in total in Korea. Among them,478 are operated by the MOCT (Ministry of Construction and Transportation) for the National Groundwater Network Program, 781 wells by the ME (Ministry of Environment) for monitoring of the area where imminent contamination is expected, and 1240 wells by the local governments for monitoring of other areas. Even though, water quality data obtained from those wells are being provided to the public since 1999, the information for the wells has not been appropriately informed. In this study, we assessed the wells that are being used for the national groundwater quality monitoring from the points of operation, location, and well configuration to provide suggestions for the improvement of the national groundwater quality monitoring.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2003.04a
• /
• pp.259-262
• /
• 2003

In the Republic of Korea, Ministry of Construction & Transportation and Korea Water Resources Corporation manage the national groundwater monitoring network at the 169 stations and will organize the supplementary groundwater monitoring network at the 10,000 stations by 2011 year. The method that organizes the monitoring network was developed using the Analytic Hierarchy Process with pairwise comparison. Several estimation factors for the estimating every district were selected to reflect each district conditions. Their weighting value was decided by pairwise comparison and questions to the experts about groundwater The optimal number of groundwater monitoring well was calculated through the developed method. To verify this method, groundwater was monitored in Jeonju city by way showing the example. The study area In Jeonju city needs 7 stations for the supplementary groundwater monitoring network. The results monitored in 7 stations inferred the groundwater level around the study area by Kriging. The mean of residual between inferred groundwater level value from Kriging and actual groundwater level is rather low. Furthermore, the mean and standard deviation of residual between inferred groundwater level change and actual groundwater change is much lower. The Fact that 7 monitoring stations are sufficient for observing the groundwater condition in the study area makes it possible for suggested monitoring number to be proper.

• Journal of the Korean earth science society
• /
• v.42 no.5
• /
• pp.556-570
• /
• 2021

This study presents the data analysis results of groundwater chemistry and the occurrence of fluoride in groundwater obtained from the groundwater quality monitoring network of Korea. The groundwater data were collected from the National Groundwater Information Center and censored for erratic values and charge balance (±10%). From the geochemical graphs and various ionic ratios, it was observed that the Ca-HCO₃ type was predominant in Korean groundwater. In addition, water-rock interaction was identified as a key chemical process controlling groundwater chemistry, while precipitation and evaporation were found to be less important. According to a non-parametric trend test, at p=0.05, the concentration of fluoride in groundwater did not increase significantly and only 4.3% of the total groundwater exceeded the Korean drinking water standard of 1.5 mg/L. However, student t-tests revealed that the fluoride concentrations were closely associated with the lithologies of tuff, granite porphyry, and metamorphic rocks showing distinctively high levels. This study enhances our understanding of groundwater chemical composition and major controlling factors of fluoride occurrence and distribution in Korean groundwater.

• Journal of Soil and Groundwater Environment
• /
• v.17 no.1
• /
• pp.22-32
• /
• 2012

This study suggests a method to grade groundwater quality quantitatively using statistical approaches for evaluating the quality of groundwater in wells included in the Groundwater Quality Monitoring Network (GQMN). The proposed analysis method is applied to GQMN data from 2001 to 2008 for nitrate nitrogen, chloride, trichloroethylene, potential of hydrogen (pH), and electrical conductivity. The analysis results are obtained as groundwater quality grades of the groundwater representing each of the monitoring stations. The degree of groundwater contamination is analysed for water quality parameters, district, and usage. The results show that the degree of groundwater contamination is relatively high by nitrate nitrogen, bacteria and electrical conductivity and at Seoul, Incheon, Gwangju, Gyeonggido and Jeollado. The degree of contamination by nitrate nitrogen and trichloroethylene is especially high when the groundwater is used for agricultural and industrial water, respectively. It is evaluated that potable groudnwater in GQMN is significantly vulnerable to nitrate nitrogen and bacteria contamination.

• The Journal of Engineering Geology
• /
• v.32 no.2
• /
• pp.281-293
• /
• 2022

Time series analysis was performed on data from 2009 to 2018 from the Chuncheon groundwater observation network to understand the characteristics of groundwater level fluctuations in the network. There are five observatories, all of which are installed in rock aquifers, and periodic inspections and management are performed by the relevant operating organization. Auto-correlation, spectral density, and cross-correlation analysis was performed.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2003.09a
• /
• pp.199-201
• /
• 2003

The monitoring effectiveness not only depends on the effectiveness of the network, but also the costs of the network. Generally the costs of the monitoring network are mainly on the equipment and personnel; the implementation and maintenance; the observation and sample connection; the sample analysis; and the data storage and processing. The cost of the monitoring network can be expressed as a function of monitoring frequency because the monitoring method can be an automatic or a manual measurement. To determine the sampling frequency of subsidiary groundwater monitoring stations, time series data of national groundwater monitoring stations were used. The proposed optimal sampling frequency for subsidiary groundwater monitoring station is about 7 to 20 days and the average frequency is about 2 weeks.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2005.10a
• /
• pp.148-149
• /
• 2005

• Journal of Soil and Groundwater Environment
• /
• v.19 no.3
• /
• pp.123-133
• /
• 2014

It is important to predict the groundwater level fluctuation for effective management of groundwater monitoring system and groundwater resources. In the present study, three different time series models for the prediction of groundwater level in response to rainfall were built, those are transfer function noise model (TFNM), artificial neural network (ANN), and adaptive neuro fuzzy interference system (ANFIS). The models were applied to time series data of Boen, Cheolsan, and Hongcheon stations in National Groundwater Monitoring Network. The result shows that the model performance of ANN and ANFIS was higher than that of TFNM for the present case study. As lead time increased, prediction accuracy decreased with underestimation of peak values. The performance of the three models at Boen station was worst especially for TFNM, where the correlation between rainfall and groundwater data was lowest and the groundwater extraction is expected on account of agricultural activities. The sensitivity analysis for the input structure showed that ANFIS was most sensitive to input data combinations. It is expected that the time series model approach and results of the present study are meaningful and useful for the effective management of monitoring stations and groundwater resources.

• Journal of Soil and Groundwater Environment
• /
• v.16 no.3
• /
• pp.38-47
• /
• 2011

Groundwater monitoring data from the National Groundwater Monitoring Stations, a total of 320 stations, were analyzed to identify the response of water level and quality to the Odaesan earthquake (M4.9) occurred in January 2007. Among the total of eight stations responded to the earthquake, five wells showed water-level decline, and in three wells, water level rose. In terms of recovery, water levels in four stations had recovered to the original level in five days, but not in the rest four wells. The magnitude of water-level change shows weak relations to the distance between the earthquake epicenter and the groundwater monitoring station. However, the relations to the transmissivities of monitored aquifer in the station with the groundwater change were not significant. To implement the earthquake monitoring system through the groundwater monitoring network, we still need to accumulate the long-term monitoring data and geostatistically analyze those with hydrogeological and tectonic factors.