• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.15-22
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• 2000

Long ranged groundwater-level data often have the missing intervals because of the trouble of monitoring systems at the national groundwater monitoring wells. Geostatistical methods are very useful for the supplement of the missing data. Ordinary kriging was applied for the interpolation of the missing groundwater-level data with a smooth sinusoidal variation. Conditional simulation was used for the reproduction of the missing data with high fluctuations. Two geostatistical methods produced the very accurate estimates at the missing intervals and reproduced their original variations. This fact is proved by the cross validation test and graphical method, respectively.

• Journal of Soil and Groundwater Environment
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• v.6 no.1
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• pp.33-43
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• 2001

A calculation technique which estimates natural recharge using groundwater level change was proposed and prepared with the existing techniques using groundwater recession curve during dry days. As a part of estimating natural groundwater recharge nation wide, the reliable data from the national groundwater monitoring network were used and the methodology was applied to the three sites which have enough data (Chungju, Jinju and Kwangju). For this study, seasonal variation of groundwater level change, an analysis of lagging time on groundwater level and cumulative precipitation, and a comparative study for groundwater recharge were conducted.

• Journal of Environmental Science International
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• v.28 no.4
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• pp.423-433
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• 2019

This study was carried out to identify the problems of the underground watersheds on Jeju Island, and to establish the hydraulic groundwater basin to be used as basis for the analysis of the groundwater model. In order to evaluate the adequacy of the groundwater basin on Jeju Island, a correlation analysis between elevation and groundwater level was conducted using data from 125 observation wells. The analysis, conducted with an elevation step of 100 m, exhibited values of R2 in the range 0.1653-0.8011. No clear correlation was observed between elevation and groundwater level. In particular, the eastern and western areas showed an inverse proportionality between elevation and groundwater level. The Kriging technique was used to analyze the underground water level data and to define the equipotential lines for all areas of Jeju Island. Eight groundwater watersheds were delineated by considering the direction of groundwater flow, the positions of the observation wells, and the long and short axes of the watersheds.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.153-167
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• 2024

Recently the ground settlement has been increasing in urban area according to development. And, this may attribute a groundwater level drawdown. This study presents an analysis of groundwater level drawdown for circular vertical shaft excavation of ｢◯◯◯◯ double track railway build transfer operate project｣. And, in-situ monitoring data and numerical analysis were compared. So, if we examine the groundwater level drawdown in design, ground conditions should be applied so that the site situation can be reflected. And, groundwater level should be considered a seasonal measurement in order to apply the appropriate groundwater level. It was confirmed a similar predicted value to groundwater level drawdown of in-situ monitoring data.

• Journal of Soil and Groundwater Environment
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• v.26 no.4
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• pp.27-43
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• 2021

Since climate factors, such as precipitation, temperature, etc., show repeated patterns every year, it can be said that future changes can be predicted by analyzing past climate data. As with groundwater, seasonal variations predominate. Therefore, when a drought occurs, the groundwater level is also lowered. Thus, a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use Standard Groundwater Level Index (SGI) to which the Standard Precipitation Index (SPI) method is applied to evaluate the severity of droughts and predict drought trends. However, due to the strong interferences caused by the recent increase in groundwater use, it is difficult to represent the droughts of regions or entire watersheds by only using groundwater level change data using the SPI or SGI methods, which analyze data from one representative observation station. Therefore, if the long-term groundwater level changes of all the provinces of a watershed are analyzed, the overall trend can be shown even if there is use interference. Thus, future groundwater level changes and droughts can be more accurately predicted. Therefore, in this study, it was confirmed that the groundwater level changes in the last 5 years compared with the monthly average groundwater level changes of the monitoring wells installed before 2015 appeared similar to the drought occurrence pattern. As a result of analyzing the correlation with the water storage yields of 3,423 agricultural reservoirs that do not immediately open their sluice gates in the cases of droughts or floods, it was confirmed that the correlation was higher than 56% in the natural state. Therefore, it was concluded that it is possible to re-evaluate agricultural droughts through long-term groundwater level change analyses.

• 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.16 no.3
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• pp.38-47
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• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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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.

• Environmental Engineering Research
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• v.22 no.4
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• pp.369-376
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• 2017

The trend analysis of the study was acquired by selecting multiyear monthly groundwater table data and monitors the wells in each sub-district under the study area. The intention of this research was to analyze the outcome of the non-parametric Mann-Kendall test at greater than the significance level which is 95% of groundwater level in Sylhet. The aptitude is effective at two conjunctures where the confidence bounds are 95% and it meets the estimate line of Sen's. To calculate and assess the spatial differences in the inanition of groundwater table, geostatistical methods was applied based on data from 27 groundwater wells during the period from January 1975 to December 2011 which were obtained from a secondary source, Bangladesh Water Development Board. The geographic information system was used to assess the spatial change in order to find the level of groundwater. Cross-validation errors were found within an advisable level in estimating the groundwater depth with different interpolation models of ordinary kriging methods. Finally, surface maps were generated with the best-fitted model. The southeast region was found highly vulnerable from groundwater level point of view. Northern region was detected highest hazard prone area for diverge groundwater using kriging method.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.2
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• pp.1-11
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• 2023

This study analyzed the impact of greenhouse cultivation area and groundwater level changes due to the water curtain cultivation in the greenhouse complexes. The groundwater observation data in the Miryang study area were used and classified into greenhouse and field cultivation areas to compare the groundwater impact of water curtain cultivation in the greenhouse complex. We identified the characteristics of the groundwater time series data by the terrain of the study area and selected the optimal model through time series analysis. We analyzed the time series data for each terrain's two representative groundwater observation wells. The Seasonal ARIMA model was chosen as the optimal model for riverside well, and for plain and mountain well, the ARIMA model and Seasonal ARIMA model were selected as the optimal model. A suitable prediction model is not limited to one model due to a change in a groundwater level fluctuation pattern caused by a surrounding environment change but may change over time. Therefore, it is necessary to periodically check and revise the optimal model rather than continuously applying one selected ARIMA model. Groundwater forecasting results through time series analysis can be used for sustainable groundwater resource management.