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).