Coastal aquifers are always under threat of seawater intrusion due to over-extraction of groundwater. The objective here is to assess aquifer response to variation in pumping and rainfall recharge due to projected climate change by groundwater modelling in a heavily exploited aquifer. Finite element groundwater flow modelling was carried out from March 1988 to December 2030 using FEFLOW software. Steady state calibration was done to match observed and simulated groundwater head by varying aquifer parameters within the allowable range. Transient state calibration was carried out during the period March 1988 to December 2002. The calibrated model was validated by comparing the simulated and observed groundwater head from January 2003 to December 2012. Groundwater head was predicted for a period until 2030 under eight different scenarios of changes in pumping and rainfall recharge. This prediction indicated that 10% increase of recharge and 10% decrease of pumping causes 3 m and 6 m increase in groundwater head in upper and lower aquifers, respectively, by the end of 2030. Groundwater recharge can be increased by rejuvenation of existing surface water bodies, check dams and construction of proposed check dams. Thus, increase of groundwater recharge and decrease in well field pumping is achievable to restore this heavily exploited coastal aquifer in another 20 years.
INTRODUCTION
Large quantities of groundwater are being pumped from coastal aquifers to meet various human needs. These aquifers are sources of fresh water for more than one billion people living in coastal regions (Ferguson & Gleeson 2012). Population growth, over-extraction of groundwater for agricultural and industrial purposes, climate change and sea level rise are the important factors causing seawater intrusion, degradation of chemical quality of groundwater and land subsidence in coastal aquifers (Barazzuoli et al. 2008). Thus, coastal aquifers are always under threat as over-exploitation leads to seawater intrusion and degradation of groundwater quality. Hence, it is very important to utilize coastal groundwater resources with great caution. Sustainable management of coastal groundwater resources is essential in order to prevent seawater intrusion. The projected change in the rainfall due to climate change will play a greater role in seawater intrusion. Groundwater flow modelling can be used as a management tool to assess the sustainability of aquifer systems and to decide on a safe pumping pattern to avoid seawater intrusion. Several studies have been carried out on groundwater flow modelling in order to understand various issues related to sustainable utilization of groundwater. Chao et al. (2010) identified various measures to be taken for achieving sustainable utilization of groundwater resources by numerical modelling. Many researchers have analysed groundwater flow dynamics, the need for the improvement of groundwater level monitoring network and identified areas for groundwater exploitation by numerical modelling using finite difference method (Senthilkumar & Elango 2001, 2004; Elango 2005; Yang et al. 2012; Alam & Umar 2013; Jean et al. 2013; Okocha & Atakpo 2013). However, it is difficult to consider complex aquifers with irregular boundaries by the finite difference method of groundwater modelling. Advancement in computational technology and the complexity of aquifer systems have allowed researchers to start using finite element method for groundwater flow modelling. Lavigne et al. (2010) developed a numerical groundwater flow model using finite element method in a quaternary sedimentary aquifer. Barazzuoli et al. (2008) and Garcia et al. (1998) simulated coastal aquifers to determine the important components of the water budget and to identify river, aquifer and sea relationships by using finite element model. These studies indicate that the complex aquifer system can be discretized effectively by finite element approach. Movement of fresh groundwater and saltwater in a coastal aquifer mainly depends on the density variation and pumping of fresh groundwater. Coastal aquifers are vulnerable to the variations in groundwater recharge and change in seaward pumping of groundwater (Werner et al. 2012). Datta et al. (2009) used the finite element based flow and transport model to evaluate the effectiveness of planned pumping strategies to locally control seawater intrusion. The present study was carried out in the coastal aquifer north of Chennai from where groundwater is extensively pumped for irrigation, industrial purposes and for providing the Chennai municipal water supply for the past four decades. Chennai is the fourth largest metropolitan city, it is located on the Coromandel coast of the Bay of Bengal and has the third largest expatriate population in India. As the aquifer in this region is heavily exploited and seawater has intruded into the aquifers over a distance of 13 km (CGWB 2013) from the sea, it is essential to identify options for sustainable management of groundwater resources. Rao et al. (2004) simulated groundwater flow by conceptualizing the region as a single layer and estimated the volume of seawater intrusion with and without check dam. However, this study has not considered the spatial and temporal dynamics of fresh water and salt water. Charalambous & Garratt (2009) studied the recharge and pumping relationship through finite element model in the Arani-Korttalaiyar (A-K) river basin by considering this region as a confined aquifer, even though it is a two aquifer system. These studies have not considered the presence of two aquifer systems. As there is interaction between the upper and lower aquifer during pumping, it is crucial to consider both aquifers for modelling. Climate change models for the eastern coast of India projected variation in rainfall from a minimum of 858 ± 10 mm to a maximum of 1,280 ± 16 mm (INCCA 2010). The increased rainfall in the 2030s with respect to the 1970s was estimated to be 2 mm–54 mm, an increase of 0.2% to 4.4%, respectively (INCCA 2010). Groundwater modelling studies carried out earlier have not considered the projected change in rainfall due to climate change. The projected change in rainfall has to be accounted for in modelling to assess aquifer response to pumping and recharge. Hence, the present study was carried out with the objective of developing a finite element three-dimensional groundwater flow model to assess the aquifer response to pumping and rainfall recharge due to the projected climate change, which is necessary to identify options for sustainable management of this aquifer system and to mitigate the problem of seawater intrusion.
DESCRIPTION OF THE STUDY AREA
Location of study area with monitoring wells and rain gauge stations.
MATERIALS AND METHODS
Model description
Groundwater modelling was carried out by the finite element approach. For this purpose, FEFLOW code was chosen as this model is flexible and able to consider the complex geometry of the region. This code solves the groundwater flow equations by numerical approximations using finite element method. FEFLOW is an interactive finite element simulation system for two- and three-dimensional, i.e., horizontal, vertical or axi-symmetric, steady or transient state, fluid density, coupled flow and mass in groundwater system (FEFLOW 6.1 2012). The major stages involved in modelling are: (1) discretization of model area; (2) three-dimensional layer configurations to separate the aquifer system into a number of slices; and (3) problem settings to define the model conditions, simulation time and error tolerance values required for simulation.
RESULTS AND DISCUSSION
Geology
Stratigraphic sequence of the study area (after UNDP 1987)
Quaternary | Fine to coarse sand, gravel, laterite, clay and sandy clay |
Tertiary | Clay, shale and sandstone |
Upper Gondwana | Gondwana shale and clay |
Archaean | Granite, gneiss and charnockite |
Quaternary | Fine to coarse sand, gravel, laterite, clay and sandy clay |
Tertiary | Clay, shale and sandstone |
Upper Gondwana | Gondwana shale and clay |
Archaean | Granite, gneiss and charnockite |
Hydrogeology
Subsurface west to east geological cross section along A–A' of the study area.
Model formulation and grid design
Three-dimensional discretization of the area and boundary conditions.
Boundary and initial conditions
As the eastern side of the model area is bounded by the Bay of Bengal, it was considered as a constant head boundary. As the northern and southern boundaries are watershed boundaries, they were considered as no flow boundary. Up to a distance of about 2 km in the north east and south east boundary was considered as constant head boundary as it consists of canals and back water. The two rivers flowing in this region were considered as river head boundary and the time variant river stage was assigned. The rivers up to a distance of about 5 km from the sea were considered as a constant head boundary as they have saline backwaters from the sea throughout the year. As the western boundary was fixed arbitrarily, it was considered as variable head boundary and time varying head was assigned based on the groundwater head observed in the nearby wells. Groundwater head during the month March 1988 was assigned as initial condition.
Aquifer characteristics
Aquifer properties such as hydraulic conductivity and specific yield of the upper and lower aquifers were assigned based on geology and from pumping test results conducted by UNDP (1987). The vertical hydraulic conductivity for semi-confining (aquitard) layer is 0.001 m/day (UNDP 1987).
Groundwater recharge
Percentage of groundwater recharge from rainfall
Geology . | Percentage of groundwater recharge from rainfall . |
---|---|
Beach sand | 17 |
Silty sand/Clayey sand | 15 |
Laterite | 12 |
Geology . | Percentage of groundwater recharge from rainfall . |
---|---|
Beach sand | 17 |
Silty sand/Clayey sand | 15 |
Laterite | 12 |
Groundwater pumping
Model calibration
Initial and calibrated hydraulic conductivity and storage coefficient values
Geology/Pumping test locations . | Hydraulic conductivity, K (m/d) . | Specific yield/Storage coefficient . | ||
---|---|---|---|---|
Initial . | Calibrated . | Initial . | Calibrated . | |
Upper aquifer (based on the geology) | ||||
Beach sand | 110 | 100 | 0.30 | 0.30 |
Silty sand | 85 | 75 | 0.10 | 0.12 |
Clayey sand | 50 | 65 | 0.06 | 0.08 |
Laterite | 5 | 4 | 0.025 | 0.03 |
Lower aquifer (based on pumping tests (UNDP 1987 )) | ||||
Kattur | 75 | 100 | 8 × 10−3 | 8.5 × 10−3 |
Interface | 118 | 100 | 2.5 × 10−3 | 3 × 10−3 |
NE Minjur | 228 | 250 | 5 × 10−3 | 6 × 10−3 |
Duranallur | 69 | 50 | 1.4 × 10−3 | 2 × 10−3 |
Panjetti | 118 | 85 | 7 × 10−3 | 8 × 10−3 |
Geology/Pumping test locations . | Hydraulic conductivity, K (m/d) . | Specific yield/Storage coefficient . | ||
---|---|---|---|---|
Initial . | Calibrated . | Initial . | Calibrated . | |
Upper aquifer (based on the geology) | ||||
Beach sand | 110 | 100 | 0.30 | 0.30 |
Silty sand | 85 | 75 | 0.10 | 0.12 |
Clayey sand | 50 | 65 | 0.06 | 0.08 |
Laterite | 5 | 4 | 0.025 | 0.03 |
Lower aquifer (based on pumping tests (UNDP 1987 )) | ||||
Kattur | 75 | 100 | 8 × 10−3 | 8.5 × 10−3 |
Interface | 118 | 100 | 2.5 × 10−3 | 3 × 10−3 |
NE Minjur | 228 | 250 | 5 × 10−3 | 6 × 10−3 |
Duranallur | 69 | 50 | 1.4 × 10−3 | 2 × 10−3 |
Panjetti | 118 | 85 | 7 × 10−3 | 8 × 10−3 |
(I) Steady state and (II) transient state calibration for upper and lower aquifers.
(I) Steady state and (II) transient state calibration for upper and lower aquifers.
Simulation of groundwater head
Temporal variation in observed and simulated groundwater head (m msl) for (a) Well no.1 and (b) Well no. 5 in the upper aquifer.
Temporal variation in observed and simulated groundwater head (m msl) for (a) Well no.1 and (b) Well no. 5 in the upper aquifer.
Temporal variation in observed and simulated groundwater head (m msl) for (a) Well no. 8, (b) Well no. 12 and (c) Well no. 19 in the lower aquifer.
Temporal variation in observed and simulated groundwater head (m msl) for (a) Well no. 8, (b) Well no. 12 and (c) Well no. 19 in the lower aquifer.
Spatial variation in observed and simulated groundwater head in the upper aquifer.
Spatial variation in observed and simulated groundwater head in the upper aquifer.
Spatial variation in observed and simulated groundwater head in the lower aquifer.
Spatial variation in observed and simulated groundwater head in the lower aquifer.
Cross section showing simulated groundwater head (a) June and (b) December for the years 1990, 2000, 2010 and 2012.
Cross section showing simulated groundwater head (a) June and (b) December for the years 1990, 2000, 2010 and 2012.
Sensitivity analysis
Sensitivity of the model for the changes in horizontal hydraulic conductivity.
Sensitivity of the model for the changes in vertical hydraulic conductivity.
Aquifer response for changes in recharge and pumping
It is observed that groundwater head in the lower aquifer has declined to the maximum during the years 2004 and 2005. The major reason for this is due to over-pumping of wells to meet the huge demand for Chennai city's water supply during the years 2002, 2003 and 2004 when the rainfall was 28%, 34% and 16% below the normal annual rainfall, respectively. Based on the estimate given by Touche & Sivaprakasam (1992), about 35 MCM/y of groundwater was pumped for the city's water supply during the years 1987–1990, which means that the groundwater pumping from this aquifer during the years 2003–2005 would have been definitely greater than 35 MCM/y. On the other hand, the average groundwater pumped by local farmers for agricultural activity is 310 MCM/y (UNDTCD 1980). The above statement proves that this coastal aquifer is affected by over-exploitation. The projected rainfall by climate change models (INCCA 2010) indicates increased rainfall in the 2030s with respect to the 1970s is about 4.4%. Further, the maximum increase in rainfall is projected to occur in March, April and May in the 2030s, with rainfall set to increase by 14 mm on an average with respect to the same period in the 1970s (INCCA 2010). The climate prediction indicates a standard deviation of about 130 mm in the projected rainfall in the year 2030 (INCCA 2010), which is about 10% of the present annual rainfall of 1,200 mm. For the projected climate change in the northern parts of Tamil Nadu where the study area is located, the rainfall is likely to increase and the water yield to rise by 10–40% (INCCA 2010). Therefore, the groundwater model was used to study the impact of the projected changes in rainfall on the coastal aquifer. The expected increase in rainfall will result in a corresponding increase in groundwater recharge by about 10%. On the other hand, demand for water is increasing and there is a huge gap in demand and supply for Chennai city. Owing to this, groundwater pumping from the western part of the study area is likely set to increase by about 10% by the year 2030. Accordingly, the model was used to predict the groundwater flow from the year 2013 to 2030 with the normal recharge and pumping conditions. A total of eight scenarios were considered:
Scenario 1: 10% increase in rainfall recharge and normal pumping
Scenario 2: 10% decrease in rainfall recharge and normal pumping
Scenario 3: 10% increase in pumping
Scenario 4: 10% increase in rainfall recharge with 10% increase in pumping
Scenario 5: 10% decrease in rainfall recharge and 10% increase in pumping
Scenario 6: 10% decrease in pumping
Scenario 7: 10% decrease in rainfall recharge and 10% decrease in pumping
Scenario 8: 10% increase in rainfall recharge and 10% decrease in pumping.
Effect of increase/decrease in rainfall recharge and pumping on groundwater head by the end of year 2030
Scenario number . | Description . | Upper aquifer . | Lower aquifer . | ||
---|---|---|---|---|---|
Eastern side (Well no. 2 . | Western side (Well no. 5) . | Eastern side (Well no. 7) . | Western side (Well no. 20) . | ||
1 | 10% increase in rainfall recharge | Increase by 2 m | Increase by 1.7 m | Increase by 2 m | Increase by 1.5 m |
2 | 10% decrease in rainfall recharge | Decrease by 1 m | Decrease by 0.8 m | Decrease by 1.5 m | Decrease by 1 m |
3 | 10% increase in pumping | Decrease by 1 m | Decrease by 0.8 m | Decrease by 4 m | Decrease by 3 m |
4 | 10% increase in rainfall recharge with 10% increase in pumping | Increase by 1 m | Increase by 0.8 m | Decrease by 2.5 m | Decrease by 1.5 m |
5 | 10% decrease in rainfall recharge and 10% increase in pumping | Decrease by 1.5 m | Increase by 1 m | Decrease by 5 m | Decrease by 3.5 m |
6 | 10% decrease in pumping | Increase by 1 m | Increase by 0.8 m | Increase by 3.5 m | Increase by 2 m |
7 | 10% decrease in rainfall recharge and 10% decrease in pumping | Increase by 1 m | Increase by 0.8 m | Increase by 2 m | Increase by 1 m |
8 | 10% increase in rainfall recharge and 10% decrease in pumping | Increase by 3 m | Increase by 1.8 m | Increase by 6 m | Increase by 4.5 m |
Scenario number . | Description . | Upper aquifer . | Lower aquifer . | ||
---|---|---|---|---|---|
Eastern side (Well no. 2 . | Western side (Well no. 5) . | Eastern side (Well no. 7) . | Western side (Well no. 20) . | ||
1 | 10% increase in rainfall recharge | Increase by 2 m | Increase by 1.7 m | Increase by 2 m | Increase by 1.5 m |
2 | 10% decrease in rainfall recharge | Decrease by 1 m | Decrease by 0.8 m | Decrease by 1.5 m | Decrease by 1 m |
3 | 10% increase in pumping | Decrease by 1 m | Decrease by 0.8 m | Decrease by 4 m | Decrease by 3 m |
4 | 10% increase in rainfall recharge with 10% increase in pumping | Increase by 1 m | Increase by 0.8 m | Decrease by 2.5 m | Decrease by 1.5 m |
5 | 10% decrease in rainfall recharge and 10% increase in pumping | Decrease by 1.5 m | Increase by 1 m | Decrease by 5 m | Decrease by 3.5 m |
6 | 10% decrease in pumping | Increase by 1 m | Increase by 0.8 m | Increase by 3.5 m | Increase by 2 m |
7 | 10% decrease in rainfall recharge and 10% decrease in pumping | Increase by 1 m | Increase by 0.8 m | Increase by 2 m | Increase by 1 m |
8 | 10% increase in rainfall recharge and 10% decrease in pumping | Increase by 3 m | Increase by 1.8 m | Increase by 6 m | Increase by 4.5 m |
Predicted groundwater head by varying rainfall recharge by ±10% in a few wells.
Predicted groundwater head by increasing the groundwater pumping by 10% and changing the rainfall recharge by ±10% in a few wells.
Predicted groundwater head by increasing the groundwater pumping by 10% and changing the rainfall recharge by ±10% in a few wells.
Predicted groundwater head by decreasing the pumping by 10% and varying the rainfall recharge by ±10%.
Predicted groundwater head by decreasing the pumping by 10% and varying the rainfall recharge by ±10%.
Thus, as expected, intervention with pumping and rainfall recharge will help to restore this aquifer and increase the groundwater head (Figure 18). The groundwater recharge in this area can be increased by managed aquifer recharge structures such as construction of check dams across the rivers and construction of percolation ponds as well as by rejuvenation of existing surface water bodies. Parimalarenganayaki & Elango (2015) estimated that about 1.3 MCM of water is recharged from October 2010 to May 2011 through the construction of a single check dam in the Arani river. Percolation pond is another method to increase local groundwater recharge. A preliminary assessment by the interpretation of satellite image indicated the possibility of construction of several percolation ponds. Groundwater pumping for agriculture purposes can be reduced by creating the awareness in farmers for cultivating less water intensive or drought tolerant crops during low rainfall periods. Groundwater pumping by the CMWSSB from Minjur and Panjetty well fields has already been stopped (due to salinization). Thus, the increase of groundwater recharge and decrease of well field pumping is an achievable task to restore this heavily exploited coastal aquifer. The present study shows that this coastal aquifer will replenish in another 20 years if groundwater recharge is increased by 10% and pumping is decreased by 10%.
CONCLUSION
Finite element groundwater flow modelling was carried out for the north of Chennai coastal aquifer for assessment of response of the aquifer system for changes in groundwater recharge due to the projected climate change and groundwater pumping. The model predicts the groundwater head with a reasonable level of accuracy. Further, the model was validated by comparing the monthly simulated and observed groundwater head for a long period, that is from January 2003 to December 2012. The model was then used to assess the response of changes in pumping and the projected changes in climate on rainfall until the year 2030. Groundwater head was predicted until the year 2030 under eight different scenarios to assess the response of groundwater level to the changes due to pumping and rainfall variation due to climate change. It is inferred that a 10% increase in rainfall recharge due to climate change and 10% decrease in groundwater pumping will lead to a 3 m and 6 m increase in groundwater head in upper and lower aquifers, respectively, by the end of year 2030. Thus, as expected, intervention in pumping and rainfall recharge will help to mitigate the problem of seawater intrusion. Groundwater recharge in this area can be increased by managed aquifer recharge structures such as construction of check dams and percolation ponds as well as by rejuvenation of existing surface water bodies. The projected increase in rainfall due to climate change and the recharge structures will help to increase the groundwater recharge by 10%. Groundwater pumping for agriculture can be reduced by providing proper awareness to farmers and suggestions to cultivate drought tolerant crops during low rainfall periods. Groundwater pumping from Minjur and Panjetty well fields has already been stopped due to salinization of groundwater. Thus, the increase of groundwater recharge and decrease of well field pumping is an achievable task to restore this heavily exploited coastal aquifer. Prediction of groundwater head by modelling indicated that this coastal aquifer will replenish in another 20 years if groundwater recharge is increased by 10% and pumping is decreased by 10%. Thus, groundwater modelling was used to assess possible measures to overcome the problem of seawater intrusion in the next 20 years in this aquifer.
ACKNOWLEDGEMENTS
The authors wish to thank the Department of Science and Technology, New Delhi, India, for providing funds to this research (grant no: DST/WAR-W/SWI/05/2010). The authors acknowledge Tamil Nadu Public Works Department and Chennai Metropolitan Water Supply and Sewerage Board, India, for providing the necessary groundwater head and borehole data.