An Mw 5.5 earthquake occurred in Pohang, South Korea on November 15, 2017, resulting in a great impact on society. Despite a lot of controversy about the cause of the earthquake in relation to the enhanced geothermal system (EGS), the location of earthquake-related active faults is poorly known. Here, we first report the results of the geochemical and isotopic analyses of dissolved gases in groundwater in the Heunghae, Yeonil, and Sinkwang areas. According to the N2-Ar-He relationship, samples from the Heunghae and Yeonil areas are contributed to the mantle, except for the Sinkwang area, where all samples are atmospheric. The Pohang samples consist mainly of N2 and CO2, and some samples of the Heunghae and Yeonil areas contain substantial CH4. Stable isotope compositions of N2 (δ15N=0.2 to 3.6‰), CO2 (δ13C=−27.3 to−16.0‰), and CH4 (δ13C=−76.1 to−70.0‰) indicate that these components are derived from organic substances in sedimentary layer of Pohang Basin. On the other hand, helium isotope ratios (3He/4He, up to 3.83 Ra) represent the significant mantle contribution in the Heunghae and Yeonil areas. Through the distribution of high 3He/4He ratios, we propose that the Heunghae, Namsong, and Jamyeong faults are the passage of mantle-derived fluids. Computed 3He fluxes of the Heunghae (120 to 3,000 atoms cm-2 sec-1), Namsong (52 to 1,300 atoms cm-2 sec-1), and Jamyeong (83 to 2,100 atoms cm-2 sec-1) faults are comparable to other major active faults around the world, reflecting either high porosity or high helium flow rates. Therefore, our results demonstrate that there are active faults near the EGS facilities, which can provide the basis for future studies.
Although there is skepticism about the likelihood of predictive success, research on the prediction of an earthquake through precursory changes in natural parameters, including groundwater, has continued for decades. One of the promising precursors is the changes in groundwater, i.e., the level and composition of groundwater, and the monitoring networks are currently operated to observe earthquake-related changes in several countries situated at the seismically active zone. In Korea, the seismic hazards had not been significantly considered for decades since the seismic activity was relatively low; however, the public demands on the management and prediction of earthquakes were raised by two moderate-size earthquakes which occurred in 2016 and 2017. Since then, a number of studies that were initiated in Korea, including this study to establish a pilot-scale groundwater-monitoring network, consisted of seven stations. The network is aimed at studying earthquake-related groundwater changes in the areas with relatively high potentials for earthquakes. Our study identified a potential precursory change in water levels at one particular station between 2018 and 2019. The observed data showed that most monitoring stations are sufficiently isolated from the diurnal natural/artificial activities and a potential precursory change of water level was observed at one station in 2018. However, to relate these abnormal changes to the earthquake, continuous monitoring and analysis are required as well as the aid of other precursors including seismicity and geodetic data.
Significant variation in the precipitation events caused by global climate change has made it difficult to manage water resources due to the increased frequency of unexpected droughts and floods. Under these conditions, groundwater is needed to ensure a sustainable water supply; thus, estimates of precipitation recharge are essential. In this study, we derived an apparent recharge coefficient (ARC) from a modified water table fluctuation equation to predict groundwater storage changes due to precipitation events. The ARC is calculated as the ratio of the recharge rate over the specific yield (R/Sy); therefore, it implicitly expresses variation in Sy. The ARC varies spatially and temporally, corresponding to the precipitation events and hydrogeological characteristics of unsaturated materials. ARCs for five monitoring wells from two basins in Korea in different seasons were calculated using a 10-year groundwater level and weather dataset for 2005–2014. Then, the reliability of the ARCs was tested by the comparison of the predicted groundwater level changes for 2015 and 2016 with observed data. The root mean square error ranged from 0.03 to 0.09 m, indicating that the predictions were acceptable, except for one well, which had thick clay layers atop the soil layer; the low permeability of the clay slowed the precipitation recharge, interfering with groundwater level responses. We performed a back-calculation of R from the Sy values of the study areas; the results were similar to those obtained via other methods, confirming the practical applicability of the ARC. In conclusion, the ARC is a viable method for predicting groundwater storage changes for regions where long-term monitoring data are available, and subsequently will facilitate advanced decision making for allocating and developing water resources for residents, industry, and groundwater-dependent ecosystems.
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