1. INTRODUCTION
Coastal areas host large populations of people owing to their prosperity. In the 20th century, 21 megalopolises in the coastal areas have grown rapidly to achieve a population of more than eight million, and more than a third of the global population resides within 100 km of the shore (Nicholls, 2008). With the increasing area affected by seawater intrusion (SWI) in coastal areas, the available amount of water resources is decreasing due to the salinization of the aquifer. Furthermore, changes caused by the salinization of coastal aquifers, such as limitations in the cultivation environment of agricultural and marine products, are damaging economic activities (Howard, 2002; Chang, 2010).
The land-use changes due to industrial development increase surface runoff and decrease recharge of the groundwater system. Furthermore, climate change increases rainfall intensity by changing the rainfall pattern. As the number of days without rain rises, the amount of water resources discharged to the surface is increased, while the amount of recharge to the aquifer is decreased. Consequently, groundwater resources are gradually decreasing (Chamine, 2015; Bernard-Jannin et al., 2017; Azimi et al., 2018; Mondal et al., 2018; Ray and Ray, 2019). The continuous rise in sea levels accelerates the increase in the SWI range. According to the analysis method of Ghyben–Herzberg, the effect of a 1 m rise in the sea level on the freshwater aquifer corresponds to 40 m of a freshwater thickness (Todd and Mays, 2005). Sherif and Singh (1999) claimed that when the sea level rises by 0.5 m, the effect of SWI reaches up to 9 km from the shore. The imbalance between the inflow and outflow from the aquifer can cause a faster drop in the freshwater groundwater level in areas with a larger pumping water quantity (Scanlon et al. 2012a). The SWI are accelerating due to the extensive use of groundwater in coastal areas, and the resulting effects by the excessive pumping of groundwater are being actively researched (Bobba, 2002; Loáiciga et al., 2012; Carretero et al., 2013; Langevin and Zygnerski, 2013; Rasmussen et al., 2013; Sefelnasr and Sherif, 2014). To efficiently establish response measures to SWI damage, one must select an area where SWI damage occurs most actively and choose response measures in line with the regional characteristics. One diagnostic method is the SWI assessment for a coastal groundwater aquifer. The general vulnerability assessment method for groundwater resources involves overlaying thematic maps linked with the scored geographic information system (GIS) data using the overlaying technique and assessing vulnerability according to the value (National Research Council, 1993). For the vulnerability assessment, the range of fixed scores is classified and presented under subjective judgment, depending on the values and types of factors associated with groundwater resources (Gogu and Dassargues, 2000; Uricchio et al., 2004). The vulnerability of groundwater resources is defined as their sensitivity to human activities and natural phenomena, and the recharge required to maintain groundwater resources and the possibility of the spread of pollutants by potential pollution sources have likewise been defined (Babiker et al., 2005). Representative vulnerability parameters for the potential pollution of groundwater resources include DRASTIC (Aller et al., 1987; Depth to groundwater, net Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, hydraulic Conductivity), and SINTACS (Civita, 1994; depth to the groundwater table (S), effective infiltration (I), unsaturated zone attenuation capacity (N), soil attenuation capacity (T), hydrogeological characteristics of the aquifer (A), hydraulic conductivity (C), and topographical slope (S)). To consider the effect of coastal aquifers on SWI, GALDIT (Chachadi and Lobo-Ferreira, 2001; groundwater occurrence (G), aquifer hydraulic conductivity (A), height of groundwater level above the sea (L), distance from the shore (D), impact of the existing status of SWI (I) and saturated thickness of the aquifer (T)) has been developed as a representative vulnerability assessment method. Recently, the assessment method of the GALDIT index has been modified for the range of the existing score and weight (Bordbar et al., 2019, 2020). The parameter replacement of GALDIT factors and the improvement of data interpolation methods have been researched as well (Klassen and Allen, 2017; Luoma et al., 2017; Hallal et al., 2019).
Several previous studies on SWI in South Korea addressed the inflow of seawater into the aquifer using the seawater monitoring network (SIMN), which was built at the national level (Lee et al., 2008). Numerous studies on SWI have been conducted on Jeju Island in South Korea (Shin and Hwang, 2020). A vulnerability assessment for SWI using GALDIT for Jeju Island was conducted for the first time in South Korea (Chang et al., 2019). Recently, studies on seawater intrusion in the inland areas of Korea have been incomplete compared with those in the island areas, but studies on the coastal areas of the west coast have begun. For example, Kim and Yang (2018) prioritized three SWI response measures for SWI-vulnerable areas when climate change was applied using the multi-criteria decision-making (MCDM) method. Chun et al. (2018) conducted a two-dimensional numerical analysis of the effects of SWI on coastal areas according to different climate change scenarios.
Studies on SWI can set different time scales according to the objectives of the study. For example, studies on the mid-to-long-term effects of SWI, such as climate change, set time scales of ten to several hundred years (Loáiciga et al., 2012; Langevin and Zygnerski, 2013; Rasmussen et al., 2013; Sefelnasar and Sherif., 2014). In contrast, studies on short repetitive variation characteristics, such as tidal effects, conduct hourly analyses (Kim et al., 2006; Kuan et al., 2012). In the past, techniques such as vulnerability assessments used representative values obtained through statistical tests of 10 years or longer-term data (Recinos et al., 2015; Allouche et al., 2017). To establish response measures to SWI, the flow characteristics according to the periods of salt and freshwater groundwater resources must also be considered. The assessment of flow characteristics for groundwater resources consists of factors for the spatial distribution and temporal changes in the groundwater level recorded in a time series (Gundogdu and Guney, 2007; Sun et al., 2009).
Therefore, to analyze the effect of the temporal characteristics of parameters, such as the groundwater level that changes over time, we developed a monthly SWI assessment method based on the original GLADIT. Data on SWI of coastal aquifers over the last 10 years were collected to analyze the monthly variations. The monthly vulnerability changes of the SWI were analyzed by classifying the collected data into monthly means. The GALDIT method, which is the most representative SWI assessment method, was used. We attempted to indicate spatiotemporally vulnerable areas and periods by classifying the six parameters of GALDIT into parameters that change monthly (L, I, T) and parameters that change little over time (G, A, D).