Pingtung coastal plain, located at the active convergent
boundary between Philippine Sea Plate and Eurasian Plate, is one of the most
active areas regarding tectonic deformation in Taiwan. Groundwater
over-pumping for aquaculture along the coast area of Pingtung plain induced
a serious land subsidence problem for decades. How much land subsidence
contributed by tectonic activity and groundwater pumping is a crucial issue
for tectonic study and groundwater management in this area. This study
collected the data in different fields and proposed a conceptual model to
calculate the quantities of land subsidence caused by natural (tectonic) and
human (pumping) factors. The data from the Global Positioning System (GPS)
are used to illustrate the total subsidence concerning vertical
displacement. A system called the multi-level compaction monitoring well
(MCMW) is able to measure the vertical compaction in different depths from
the earth surface to the depth of 200 m. Two GPS stations, named CLON and
FALI, close to two MCMWs, named Jiadong and Fangliao, are adopted for
analysis The data during 2007 and 2016 taken from MCMWs and groundwater
observation wells indicate that the compaction in the shallow depth should
be mainly caused by groundwater over-pumping due to their high correlation
coefficients (from 0.58–0.95). The difference of the vertical deformation
between GPS and MCMW indicates that there is deformation beyond the depth
within 200 m. From the data and literature, the further vertical deformation
should be due to tectonic activity associated with tectonic escape and
extrusion of the Taiwan orogen with average vertical deformation from
In southwest Taiwan, the Eurasian Plate is subducting with south-east
direction beneath the Philippine Sea Plate at the Manila trench (Wu, 1978).
In the previous studies with the moving speed of the Philippine Sea Plate of
about 8.2 cm yr
Taiwan is ranked 56th in the world regarding population with 667 person km
The distribution of monitoring system in the study area (Modified from Chiang et al., 2004).
The purpose of this research is to summarize information from the aforementioned research papers to propose a conceptual model to estimate how much land subsidence is due to the tectonic activities and non-tectonic activities. In this study, the data from global positioning system (GPS) is used to measure the vertical land deformation and a nearby system called the multi-level compaction monitoring well (MCMW) measures the compaction within 200 m. These two survey data conducted from 2007 to 2016. Moreover, the correlation between the data of compaction monitoring wells, groundwater monitoring wells, and rainfall quantity are compared to realize the seasonal influence. After the data analysis, then knowing the area where the land surface changes occur and strongly affected by the change in the groundwater level, the elemental frequency analysis is proposed. This approach provides additional ideas on geological surveys as well as estimation of subsidence caused by plate tectonics in different sensitive tectonic regions in the world.
Nowadays, the methodology for measuring land subsidence has been upgraded for years, and there are new studies to find out the past and present geological issues. In Taiwan, there are four techniques commonly used to observe land subsidence such as leveling, GPS, MCMW, and differential interferometric synthetic aperture radar (DInSAR). These techniques support each other in spatial and temporal domains. Three of them are used to measure the total subsidence consists of leveling, continuous GPS, and DInSAR. The one left measure compaction in different layers are MCMWs. Following Hung et al. (2010), the advantage of GPS is the daily sampling which provides sufficient data as well as high mobility and a quick survey. The next one is the MCMWs are used to measure the compaction of aquifer systems by anchoring several magnetic rings to aquifer systems at different depths with the advantage is its high accuracy of (about 1–5 mm). The final technique, DInSAR is used to measure landscape changes by using many images at different times to create the interferogram images. The advantage is a spatial resolution, but there are various errors, especially for the atmospheric error which reduces the accuracy up to 2 cm. Therefore, using survey data from continuous GPS and MCMW is proposed which are the powerful technique in this research. The distribution of monitoring system used in this study is shown in Fig. 1.
From the 10-year continuous leveling data, it has been shown that changing land surfaces at CLON station and Jiadong well is similar, so the CLON station is closest to Jiadong well. Besides that, there is a total of five wells for monitoring groundwater levels which were chosen in the study area. We divided into two areas of subsidence measuring in Jiadong township and Fangliao township, so the division of groundwater monitoring wells in two areas is also carried out for easy analysis. In Jiadong township area (Fig. 2), they include three groundwater observation wells named Wenfeng (WF), Dazhuang (DZ), Daxiang (DXi). In the Fangliao township area, the remaining two wells are named Fangliao (FL), and DeXing (DX). The groundwater observation wells have from the first aquifer to third aquifer and its distribution from the depth of 25 to 200 m. In this study, the GPS and groundwater level data are based on the daily solution. However, the MCMW result is based on a monthly solution.
Cumulative subsidence of GPS data, MCMW data are in the
left
A new idea with a simple equation to estimate subsidence in depths of below
200 m. We rather suspect that the deep subsidence part is caused by natural
impact. There are two main factors of the natural impact such as natural
compaction and plate tectonics. Following the rock cycle, there are three
main types of rocks: sedimentary, metamorphic, and igneous. Under the
influence of nature, each type of rock when altered or destroyed will create
loose materials or unconsolidated soil. That material would be sedimented
respect to the time-consuming transitions through geologic time is called
natural compaction. Tectonic subsidence commonly occurs at a subduction
zone, especially in Pingtung plain that is very active so it can easily lead
to land subsidence. In the conceptual model, we separated into two main
causes likely human and natural impact. Where a GPS station and MCMW device
were established to measure the total subsidence and the changing of
stratigraphic column within 200 m. Thus, the equation to estimate land
subsidence due to tectonic activities is proposed:
Correlation coefficient matrix between subsidence and groundwater level.
Note: DZ1, DZ2, WF, DXi1, DXi2, FL1, FL2, DX1, DX2, DX3 are the abbreviated name of groundwater observation wells.
Figure 2 shows a variation of the time series under the seasonal effect. The
most subsidence often falls during the dry season, so that the annual
compactions in the dry season which calculated from the data of MCMW at both
areas that range from
Monthly tectonic subsidence in
The correlation coefficients among the data from MCMWs and groundwater monitoring wells are high with the values from 0.58 to 0.95, as listed in Table 1. That illustrated that MCMW can measure the land subsidence due to groundwater pumping from the Earth's surface to a depth of 200 m. As mentioned previously, GPS station is established at the ground surface to measure the total subsidence that means that GPS system observes the whole vertical deformation including a movement of tectonic activity.
The measurement period of MCMW device is one-month interval, while that of GPS system is daily interval. However, GPS system is very susceptible to atmospheric, so we used resampling and average method to analyze the data to avoid the errors. Therefore, subsidence data from GPS are processed by using the weekly mean value cooperated with the resampling point. The calculation concept is that based on the date when MCMW data are collected, resample the point of GPS at the same date and averaged the seven values from before three days to after three days. This method is called the mid-point weekly sampling in this study.
After the pre-processes, Eq. (2) is adopted to calculate the tectonic
subsidence, the results are shown in Fig. 3. The average deformation in
Jiadong area and Fangliao area are
MCMW is a system to monitor land subsidence due to groundwater over-pumping.
The data collected from the groundwater monitoring wells and MCMW in
Pingtung plain have the correlation coefficients varied from 0.58–0.95,
which express that the subsidence within 200 m is highly correlative to
groundwater level variations and could be due to groundwater over pumping.
Under the assumption of small influence of natural compaction, the vertical
deformation induced by tectonic activity can be obtained using total
subsidence minus subsidence within 200 m. Then, both the vertical
deformation contributed by natural factor of tectonic activity and human
factor of groundwater over pumping can be estimated. For nature factor, the
tectonic activity causes an average vertical deformation of
The GPS data used in this study was obtained from the website of Academia Sinica, Taiwan, through
The reference review, data analyses, figure and table preparations, and manuscript writing are done by DHT. SJW is the advisor, who provides the idea, data, comments, and suggestions for this research and revises the manuscript.
The authors declare that they have no conflict of interest.
This article is part of the special issue “TISOLS: the Tenth International Symposium On Land Subsidence – living with subsidence”. It is a result of the Tenth International Symposium on Land Subsidence, Delft, the Netherlands, 17–21 May 2021.
The authors would like to thank Professor Jyr-Ching Hu in National Taiwan University, Wei-Chia Hung in Green Environmental Engineering Consultant Co. LTD, and an anonymous reviewer for providing the valuable comments and suggestions to improve this research. The data provided by Academia Sinica, Taiwan, and Water Resources Agency, Taiwan, are much appreciated.
This research has been supported by the Ministry of Science and Technology, Taiwan (grant no. MOST 106-2116-M-008-023-MY3).