• The Journal of Engineering Geology
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• v.32 no.4
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• pp.697-723
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• 2022

Data-driven models to predict groundwater levels 30 days in advance were developed for 12 groundwater monitoring stations in the middle-Jeju watershed, Jeju Island. Stacked long short-term memory (stacked-LSTM), a deep learning technique suitable for time series forecasting, was used for model development. Daily time series data from 2001 to 2022 for precipitation, groundwater usage amount, and groundwater level were considered. Various models were proposed that used different combinations of the input data types and varying lengths of previous time series data for each input variable. A general procedure for deep-learning-based model development is suggested based on consideration of the comparative validation results of the tested models. A model using precipitation, groundwater usage amount, and previous groundwater level data as input variables outperformed any model neglecting one or more of these data categories. Using extended sequences of these past data improved the predictions, possibly owing to the long delay time between precipitation and groundwater recharge, which results from the deep groundwater level in Jeju Island. However, limiting the range of considered groundwater usage data that significantly affected the groundwater level fluctuation (rather than using all the groundwater usage data) improved the performance of the predictive model. The developed models can predict the future groundwater level based on the current amount of precipitation and groundwater use. Therefore, the models provide information on the soundness of the aquifer system, which will help to prepare management plans to maintain appropriate groundwater quantities.

• Journal of Soil and Groundwater Environment
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• v.25 no.1
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• pp.84-94
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• 2020

Jeju Island is seeking reliable ways to secure alternative water resources using rainwater in order to conserve and manage its groundwater as sustainable water resources. The purpose of this study is to investigate the rainwater storage capability of small-size storage facilities installed at farmhouses in Uigwi and Wimi of Namwon-eup region. The rainwater outflows from the storage facilities in rain events were analyzed. The appropriate size of rainwater utilizing facilities are suggested to be about 5,800 ㎥ in Uigwi area and 4,900 ㎥ in Wimi area based on the calculation from the rainfall frequency and runoff amounts. If those facilities are put into operation in Uigwi and Wimi area, it is estimated approximately 32.3 and 11.5% of total agricultural water can be supplied by the facilities. Wimi area showed low rainwater usage because of less number of facilities relative to the size of farm areas and less intensive underground water usage. It is analyzed that more than 55% of agricultural water can be supplied by rainwater if 70 facilities without the rainwater facilities are connected to the rainwater utilizing facilities.

• Journal of Environmental Science International
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• v.18 no.9
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• pp.1017-1026
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• 2009

In Jeju island, the surface runoff characteristics are quite different from those of inland. Most of streams show dried characteristics by means of large portion of recharge which goes to the deep aquifer. For this reason, the accurate estimation of hydrologic components by using watershed model like SWAT is very difficult. On the other hand, the integrated SWAT-MODFLOW model is able to simulate the complex runoff structure including stream-aquifer interaction, spatial-temporal groundwater recharge and so on. The comprehensive results of Pyoseon region in Jeju island show that the amount of groundwater discharge to stream is very small, but it might be added to the discharge into the sea. Statistical analysis shows that SWAT-MODFLOW's results represent better than SWAT's. Also, SWAT-MODFLOW produces a reasonable water budget which shows a quite similar pattern of observed one. This result proves that the integrated SWAT-MODFLOW can be used as a proper tool for hydrologic analysis of entire Jeju island.

• Journal of Korea Water Resources Association
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• v.57 no.10
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• pp.757-767
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• 2024

In the Hankyung-Daejeong watersheds of western Jeju Island, several groundwater wells showed abnormal measurements of high electrical conductivity (EC) and pH. To identify the causes of this abnormal water quality, we conducted borehole imaging, vertical EC logging, groundwater quality analysis, and SEM-EDS analysis of white suspended matter in the well. Most of the wells showing abnormal water quality had well-grouting below the water table, with borehole EC values ranging from 300 to 10,000 μS/cm. The wells exhibited higher ion concentrations compared to nearby wells and had a high pH range of 8.2 to 12.7, indicating a slightly to strong alkalinity. The primary components of the white-colored suspended matter were identified as oxygen and magnesium. These findings suggest that the abnormal water quality of the study wells is caused by the cement mortar used for grouting during well construction rather than by nitrate contamination or seawater intrusion. To prevent the influence of well-grouting on water quality during groundwater well development, an establishment of standards for groundwater development and utilization facilities is needed.

• Journal of Soil and Groundwater Environment
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• v.10 no.2
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• pp.12-19
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• 2005

Jeju island is one of the highest rainfall areas in the Korean peninsular. However, variation in rainfall amount is much great with years, which resulted in substantial variation in annual groundwater recharge and sustainable yield. Therefore, to cope with groundwater hazard including sea water intrusion and water level decline in accordance with successive extreme drought, Jeju province established a stepwise action system, in which management of representative monitoring wells and corresponding actions to water level conditions was enforced. In this study, rainfall and groundwater monitoring data were analyzed to determine management groundwater level on Jeju island. First, rainfall data for last 30 years were analyzed, which yielded a lower limit of rainfall at a confidence level of 99% as a basis rainfall. Only when the rainfall less than the basis rainfall was sustained over 3 months, the water levels were targeted for the analysis. For the water level data selected using the above criteria, the lower limit of 99% confidence interval was determined as a reference groundwater level. Finally, some ratios of reference groundwater level was determined as stepwise management groundwater level on Jeju island.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.515-522
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• 2013

To investigate groundwater variation characteristics in the Hancheon watershed, Jeju Island, an integrated hydrologic component analysis was carried out. For this purpose, SWAT-MODFLOW which is an integrated surface-groundwater model was applied to the watershed for continuous watershed hydrologic analysis as well as groundwater modeling. First, ephemeral stream characteristics of Hancheon watershed can be clearly simulated which is unlikely to be shown by a general watershed hydrologic model. Second, the temporally varied groundwater recharge can be properly obtained from SWAT and then spatially distributed groundwater recharge can be made by MODFLOW. Finally, the groundwater level variation was simulated with distributed groundwater pumping data. Since accurate recharge as well as abstraction can be reflected into the groundwater modeling, more realistic hydrologic component analysis and groundwater modeling could be possible.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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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.

• Journal of Environmental Science International
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• v.20 no.10
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• pp.1297-1308
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• 2011

This study is to analyze the characteristics of golf course water usage using groundwater and rainwater data obtained from 17 golf courses in Jeju Island during 2007~2009. The groundwater usages were 246,275 $m^3/year$, 213,062 $m^3/year$, 155,235 $m^3/year$, and 126,666 $m^3/year$ in the west, south, east, and north regions, respectively. Monthly rate of the amount of groundwater usage to the amount of permission was 29.5%. The rainfall usages were 386,591 $m^3/year$, 326,464 $m^3/year$, 251,248 $m^3/year$, and 232,061 $m^3/year$ in the south, west, east, and north regions, respectively. Monthly rate of rainwater usage to the amount of water retention of golf courses was 19.6%. The average annual water usage in the 17 golf courses was 499,377 $m^3/year$. From the average usage, it was found that the rainwater usage (305,126 $m^3/year$ ) was 1.6 times higher than that of groundwater (194,251 $m^3/year$ ). That means the annual average rainwater usage to the entire water usage was 61.1%, which was above the criteria of 40%.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.485-493
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• 2021

Groundwater is an important water resource that can be used along with surface water. In particular, in the case of island regions, research on groundwater level variability is essential for stable groundwater use because the ratio of groundwater use is relatively high. Researches using artificial intelligence models (AIs) for the prediction and analysis of groundwater level variability are continuously increasing. However, there are insufficient studies presenting evaluation criteria to judge the appropriateness of groundwater level prediction. This study comprehensively analyzed the research results that predicted the groundwater level using AIs for various regions around the world over the past 20 years to present the range of allowable groundwater level prediction errors. As a result, the groundwater level prediction error increased as the observed groundwater level variability increased. Therefore, the criteria for evaluating the adequacy of the groundwater level prediction by an AI is presented as follows: less than or equal to the root mean square error or maximum error calculated using the linear regression equations presented in this study, or NSE ≥ 0.849 or R² ≥ 0.880. This allowable prediction error range can be used as a reference for determining the appropriateness of the groundwater level prediction using an AI.

• Journal of Soil and Groundwater Environment
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• v.26 no.3
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• pp.1-13
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• 2021

Groundwater monitoring is commonly practiced with real-time sensors placed in several depth spots in aquifer. However, this method only provides monitoring data at the point where the sensors are installed. In this study, we developed a vertical line monitoring system (VLMS) that can provide continuous data of groundwater parameters along the vertical depth. The device was installed in a well located on the coast of the eastern part of Jeju island to monitor electrical conductivity, temperature, salinity, pH, dissolved oxygen, and oxidation-reduction potential over approximately 3 months from September 11 to December 3, 2020. The results indicated that the groundwater levels fluctuated with the tidal change of seawater level, and the upper and lower boundaries of the freshwater and saltwater zone in the groundwater were located at below 16 m and 36 m of mean sea level, respectively. There was a large variation in EC values during the high tide and temperature change was the greatest during flow tide. Although further investigation is needed for improvement of the device to obtain more accurate and reliable data, the device has a potential utility to provide fundamental data to understand the seawater intrusion and transport mechanisms in coastal aquifers.