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/S_y); therefore, it implicitly expresses variation in S_y. 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 S_y 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.