• Journal of Soil and Groundwater Environment
• /
• v.21 no.6
• /
• pp.80-86
• /
• 2016

Earthquakes of M5.1, M5.8 and M4.5 occurred in September 12 and 19 respectively in Gyeongju, Gyeongbuk Province. Theses earthquakes inflated fears of people and highlighted necessity of detailed countermeasures because we have considered our country is safe to earthquakes. In the meanwhile, earthquake also impacts groundwater and thus it was recently reported that the Gyeongju Earthquakes affected groundwater there. This study evaluates daily groundwater data collected from five national groundwater monitoring stations (Geoncheon, Sannae, Oedong, Yangbuksin, Cheonbuk) in Gyeongju. The analysis revealed that only groundwater level of bedrock monitoring well hosted in andesite exhibited earthquake impact while no wells in the other four stations hosted in sedimentary rocks showed substantial responses to the earthquakes. This may be derived from the difference of seismic velocity of hosting rocks as well as epicenter distance. Special interest on groundwater monitoring is required to predict earthquakes as precursory phenomena.

• Journal of Korea Water Resources Association
• /
• v.51 no.11
• /
• pp.1011-1020
• /
• 2018

This study aims to develop a drought monitoring scheme based on groundwater which can be exploit for water supply under drought stress. In this context, groundwater level can be used as a proxy for better understanding the temporal evolution of drought state. First, kernel density estimator is presented in the monthly groundwater level over the entire national groundwater stations. The estimated cumulative distribution function is then utilized to map the monthly groundwater level into the standardized groundwater level index (SGI). The SGI for each station was eventually converted into the index for major cities through the Thiessen polygon approach. We provide a drought classification for a given SGI to better characterize the degree of drought condition. Ultimately, we conclude that the proposed monitoring framework enables a more reliable estimation of the drought stress, especially for a limited water supply area.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.268-268
• /
• 2021

Groundwater resource is mostly used in Abomey-calavi (southern region of Benin) as main source of water for domestic, industrial, and agricultural activities. Groundwater intake across the region is not perfectly controlled by a network due to the presence of many private boreholes and traditional wells used by the population. After some decades, this important resource is becoming more and more vulnerable and needs more attention. For a better groundwater management in the region of Abomey-calavi, the present study attempts to predict a future probable groundwater drought using Recurrent Neural Network (RNN) for future groundwater level prediction. The RNN model was created in python using jupyter library. Six years monthly groundwater level data was used for the model calibration, two years data for the model test and the model was finaly used to predict two years future groundwater level (years 2020 and 2021). GRI was calculated for 9 wells across the area from 2012 to 2021. The GRI value in dry season (by the end of March) showed groundwater drought for the first time during the study period in 2014 as severe and moderate; from 2015 to 2021 it shows only moderate drought. The rainy season in years 2020 and 2021 is relatively wet and near normal. GRI showed no drought in rainy season during the study period but an important diminution of groundwater level between 2012 and 2021. The Pearson's correlation coefficient calculated between GRI and rainfall from 2005 to 2020 (using only three wells with times series long period data) proved that the groundwater drought mostly observed in dry season is not mainly caused by rainfall scarcity (correlation values between -0.113 and -0.083), but this could be the consequence of an overexploitation of the resource which caused the important spatial and temporal diminution observed from 2012 to 2021.

• Journal of the Korean Society of Groundwater Environment
• /
• v.2 no.2
• /
• pp.58-63
• /
• 1995

Cokriging was applied for the estimation of the water levels of the basal leachate and the surrounding groundwater at the Nanjido waste landfill area. When the groundwater level is estimated at the high relief area, it makes a good result to use the data of groundwater level and elevation simultaneously because groundwater level is correlated with topography. This study determined the best semivariogram model of 87 groundwater levels and 144 elevations through cross validation test, and produced the contour maps of groundwater levels using ordinary kriging and universal kiging. Two contour maps don't make big difference at the waste site because this area has a large number of groundwater level data. However, they show big difference at the upper left part of the study area because this area has high relief and a small number of sample data. Their difference is also found at the south area near the Han river. When the topography is considered for the both areas, the contour map of cokriging is thought to be closer to the real groundwater distribution than that of kriging.

• The Journal of Engineering Geology
• /
• v.19 no.3
• /
• pp.313-321
• /
• 2009

The relationship between precipitation and groundwater level and the correlation between the moving average of precipitation and goundwater level were analyzed for the Han river watershed in Korean peninsular. Fourteen regions in the watershed were selected and there were somewhat different patterns of seasonal fluctuation of groundwater level data. The groundwater level data tends to decrease in dry spell and increase in wet spell however the range between maximum and minimum values is quite different for each gauging point. We could have stronger correlation between groundwater level for fractured rock aquifer and the moving average of precipitation than the groundwater level for alluvial aquifer. The critical infiltration, which is the maximum daily infiltration averaged throughout watershed, value is turned out to have the range of 10 to 90 mm. We could have stronger correlation when we consider critical infiltration and modify the original precipitation data than we use original precipitation data. We also could have higher correlation coefficient when we consider snowmelt effect for the watershed that has considerable snow event.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.3B
• /
• pp.265-276
• /
• 2011

Precipitation data and groundwater level data were collected for Korean peninsular and Jeju island. The relationship between precipitation and groundwater level and the correlation between the moving average of precipitation and goundwater level were analyzed. Critical infiltration, which is the spatially averaged maximum daily infiltration depth over interested region, is considered when the precipitation data was modified for moving average process and correlation between the moving average of modified precipitation and groundwater level. High correlation regions, which have greater than 0.6 correlation coefficients, were selected after the analysis with ciritical infiltration. Twenty-six regions were selected for high correlation regions. If we divide the regions by administrative district, there are nine regions for Gyungsang-Do, five regions for Chunchung-Do, four regions for Gyunggi-Do and Gangwon-Do, three regions for Jolla-Do, and one region for Jeju island. The groundwater level data for high correlation regions shows obvious response after precipitation event and there are few cases with abrupt change in groundwater level without precipitation-related event.

• 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.

• The Journal of Engineering Geology
• /
• v.21 no.4
• /
• pp.337-348
• /
• 2011

We examined temporal variations in and relationships among groundwater level, groundwater temperature, and electric conductivity, and estimated groundwater recharge at Jeju Island. The time lag and regulation time of groundwater level data revealed that monitoring well in Ansung (JM-AS) has the highest auto-correlation. The cross-correlations for electric conductivity-water level, precipitation-water level, and air temperature-water temperature revealed that monitoring well in Seogwi-2 (JR-SG2) (electric conductivity-water level), monitoring well in Hamo (JD-HM) (precipitation-water level), and monitoring well in Wonjongjang-2 (JT-WJJ2) (air temperature-water temperature) had the highest cross-correlations. The average groundwater recharge ratio was 39.61%, and the average groundwater recharge amount was 1,153,490,407 $m^3/yr$, which is consistent with the results of previous studies.

• Journal of Soil and Groundwater Environment
• /
• v.16 no.2
• /
• pp.41-51
• /
• 2011

This study was conducted to investigate the relationship between groundwater level change and a large earthquake using the data of groundwater and seawater intrusion monitoring wells in Jeju Island. Groundwater level data from 13 observation wells were analyzed with a large earthquake. The Earthquake occurred at Sumatra, Indonesia (Mw = 7.7) on 13 June 2010, and groundwater level anomalies which seems to be related to the Earthquake were found in 6 monitoring wells. They lasted for approximately 16~27 minutes and the range of groundwater level fluctuations were about 1.4~2.4 cm. Coefficient of determination values for relationship between groundwater level change and transmissivity, and response time were calculated to be $R^2$ = 0.76 and $R^2$ = 0.96, respectively. The study also indicates that the high transmissivity of aquifer showed the high goundwater level changes and longer response time.

• Journal of Korea Water Resources Association
• /
• v.53 no.5
• /
• pp.337-345
• /
• 2020

In order to provide information for proper management of groundwater resources, an analysis of the effects of precipitation and groundwater withdrawal on groundwater levels is needed. In this study, we analyzed the correlation of precipitation-groundwater level and groundwater withdrawal-groundwater level using time series data converted by normalized standard deviation (Nor.St.Dev) and cross correlation coefficient (CCC) for nine groundwater monitoring wells in the middle mountainous area in the southeastern Jeju Island. First, the CCCs of precipitation-groundwater level were estimated using daily time series data, and the low CCCs of up to 0.3 were obtained. However, the result of using the Nor.St.Dev showed a clearer correlation by obtaining a CCC of up to 0.8. In addition, in most cases, precipitation variability and groundwater level variability had positive CCCs, whereas groundwater withdrawal variability and groundwater level variability had negative CCCs. Therefore, the groundwater level in this study area was largely influenced by precipitation with little effect of groundwater withdrawal. Lastly, as a result of analyzing the relative effects of Seongpanak and Gyorae rainfall station on the groundwater level, the rainfall at the relatively downstream Gyorae rainfall station has more influence. The analysis method used in this study can be easily used for analyzing the effects of precipitation and groundwater withdrawal on groundwater level variability in other regions in the future.