Study region: A volcanic island (Jeju Island, South Korea). Study focus: To predict and prepare for a drought, the variables that affect groundwater-level variations are better understood through groundwater monitoring networks. In this study, we analyzed various observational data (including precipitation, evapotranspiration, groundwater usage, tidal levels, and groundwater levels) to investigate the effects of historic droughts on groundwater level in a volcanic island in 2017 by using principal component analysis (PCA) and correlation analysis. New hydrological insights for the region: Based on the results of these analyses, we can select index wells that are vulnerable to droughts. This is demonstrated by the decrease in total water input caused by the low amount of precipitation and the increased groundwater usage to compensate for this water shortage. This study indicated that PCA could be a powerful tool for summarizing large datasets to select index wells that are vulnerable to droughts, which would significantly reduce the expense of monitoring programs. In addition, we investigated whether the observed variables changed with the temporal resolution of the monitoring. When the temporal resolution changed from monthly to daily and hourly groundwater-level data, the main variables that affected the groundwater-level variations at each temporal resolution were different. Therefore, it is helpful to comprehensively develop a groundwater management plan using statistical approaches with proper temporal monitoring resolution during drought.
- Groundwater level
- Multivariate statistical method
- Principal component analysis
- Temporal groundwater monitoring