ANALYSIS OF UNCONFINED AQUIFER RESPONSE TO
DELINEATE POTENTIAL GROUNDWATER RECHARGE ZONE
IN HARD ROCK TERRAIN
N.C. MONDAL
Groundwater Group, National Geophysical Research institute
Hyderabad, Andhra Pradesh-500 007, India
V.S. SINGH
Groundwater Group, National Geophysical Research institute
Hyderabad, Andhra Pradesh-500 007, India
Delineation of potential groundwater recharge zone is of vital importance to augment
groundwater resources. It is particularly significant in hard rock region where
groundwater is primary source of potable water and it continues to diminish due to
indiscriminate exploitation. Conventionally, suitable zone for artificial recharge is
deciphered using hydrogeological, geophysical and geomorphological maps, which is
often time consuming and uneconomical. Therefore, the analysis of unconfined aquifer
response in terms of rise in water level due to precipitation, a rapid and cost-effective
procedure is evolved. Cross-correlation of rise in water level and precipitation is
established. The entire area is classified into various zones depending on variability in
coefficient of correlation. Thus, most favorable zone for artificial recharge is delineated
and subsequent investigations can be taken up in such a focused zones to affirm the
potential zone.
INTRODUCTION
In many Asian countries there has been rapid development in the various fields,
particularly in agriculture and industry, in the last couple of decades. This has lead to
ever increasing demand for groundwater to meet the requirement of domestic, agriculture
and industry. Such demands are met with indiscriminate exploitation of groundwater, in
the absence of any groundwater legislation. The only source of replenishment of this
exploited resource is rainfall, which is limited to few monsoon months in a year,
particularly, in semi arid regions of our country. According to an estimate, there is about
4 to 17 percent of annual rainfall that replenishes groundwater in semi arid regions
Rangarajan and Athavale [1]. The annual rainfall in the semi arid region is often scanty
and recurring drought often prevails. The over exploitation of groundwater in such a
situation leads of progressive depletion of its potential (as a consequence progressive
decline in groundwater level) year after year. In order to arrest the depletion in
groundwater potential and to achieve sustainable development, several measures
including artificial groundwater recharge are suggested by Muralidharan and Shanker [2].
In order to implement artificial groundwater recharge, it is essential to delineate
potential groundwater recharge zones. Conventionally, remote sensing, photogeological,
hydrogeological and geophysical methods are deployed to select favorable sites for
implementation of artificial recharge scheme. These methods are indirect, time
consuming and some times uneconomical , particularly, when one has to deal with large
basin. Instead, one can adopt simple and rapid method to scan the entire area and arrive at
suitable zone where detail study can be taken up.
In semi arid region where groundwater occurs in shallow weathered zones, the rise in
groundwater level is a direct consequence of precipitation, particularly in the monsoon
season, when the groundwater withdrawal is minimum. The rise of water level at a
particular place is characteristic feature of unsaturated zone. Therefore, there exist a
definite relationship between amount of rise in water level and precipitation for a
particular region. In other words each zone is characterized by a parameter that correlates
rise in groundwater level with precipitation. Higher correlation coefficient implies
significant groundwater recharge characteristic or most favorable recharge zone.
Considering this fact, rise in groundwater level and rainfall data from an area in semi arid
region have been analyzed to delineate suitable artificial recharge zone. The monthly
water level data recorded by Public Works Department [3] in 6 monitoring wells in the
study area for 31 years (from March 1971 to February 2002) have been considered for the
analysis. The cross-correlation between rainfall and depth to water level measured in
different months from March 1971 to February 2002 had been determined. The
correlation coefficient of these two parameters varies from place to place and time to
time. It has been found that there has been significant rise in water level due to rain in
the month of October to January. An attempt was therefore made to correlate the water
level variation due to the monsoon rainfall during the months of October to January and
the correlation values have compared with the result of RS and GIS.
STUDY AREA
The area is a hard rock, drought prone region, which is situated in the Dindigul district of
Tamilnadu, India (Figure 1) and lies in between 100 14/ 24// - 100 27/ 00 // N latitude and
770 51/ 00// - 780 01/ 12// E longitude. It is spread over an area of about 240 km2. The basin
is characterized by undulating topography with hills located in the southern parts, sloping
towards north and northwest. The highest elevation (altitude) in the hilly area (Sirumalai
hill) is of order of 1350m (amsl), whereas in the plains its ranges 360m (amsl) in
Southern portions to 240m in the Northern part of the area. No perennial streams exit in
the area, except for short distance streams encompassing 2nd and 3rd order drainage
Mondal and Singh 2003 [4] and [5]. Run off from precipitation within the basin ends in
small streams flowing towards main river Kodaganar. The average annual rainfall is of
the order of 853.0 mm from a period of 1971-2001[3].
2
35
0
30
4.4 km
2.2
25
INDIA
10.44
N
20
15
PWD Wells
10
70
80
85
Rain gauge
90
Study area
83520
10.36
83514
10.32
Ko
da
ga
na
rR
ive
r
Latitude (in degree)
10.4
75
83515A
Dindigul town
83029A
83029
10.28
83503
la i
ma
Si ru
10.24
77.9
77.94
77.98
Hill
78.02
Longitude (in degree)
Figure 1. Location map
HYDROGEOLOGICAL SETTING
Geologically the area is occupied with Achaean granites and gneisses, intruded by dykes
Balasubramanian [6] and Chakrapani & Manickyan [7]. These are actually a very
heterogeneous mixture of different types of granites intruding into schistose rocks after
the latter where folds and metamorphosed. This mixture includes granite, grandiosities,
gneissic granite and gneisses Krishnan [8]. They are mainly composed of gray and pick
feldspar with quartz grains, biotite and hornblende Thangarajan and Singh [9]. These
formations are crossed by sets of joints and fractures, which have also caused weathering
of the coarser of the rocks. Weathering occurs due to mechanical and mostly chemical
processes that take place while water in the fractures interacts with the formation Larsson
[10]. Black cotton soil and red sandy soil predominate in the area. The thickness of soil
varies from 0.52m to 5.35m but thickness of weather varies from 3.1 to 26.6m Mondal
and Singh [5]. The distribution of the weathered zone is varying from place to place
within the basin, and as such this shallow zone may not be a stable source for large
3
demands of groundwater. There is a major fault running in NE-SW direction for several
kilometers situated North-West of Dindigul town (Figure 2). The weathered zone
2.2
10.44 0
N
Ko
da
ga
na
rR
.
10.32
Dindigul
dP
adim
en t
Bur
ie
Latitude ( in degree)
10.4
10.36
LEGEND
P Pediment
SH Structural Hill
Tannery
River & Drains
Granite
Charnokite
Buried Padiment
Lineament
4.4Km.
P
10.28
SH
um
Sir
10.24
77.9
ll
i Hi
a la
77.98
77.94
78.02
Longitude (in degree)
Figure 2. Geology map
facilitates the movement and storage of groundwater and through a network of joints,
faults and lineaments, which form conspicuous structural features. Apart from the
structural controls on the groundwater movement, the terrain is covered with pediment
and buried pediment at southern and western sides of the study area. Another most
dominant formation is the charnokite, which is found in the extreme southern and
southeastern part of the Sirumalai hill. The term charnokite is used to describe a group of
igneous rocks, varying in composition from acid to ultramafic, characterized by the
presence of orhtopyroxene Krishnan [8]. This formation is less weathered, jointed or
fractured compared to the previous one and could therefore be considered as
impermeable.
RAINFALL AND WATER TABLE
The analysis of monthly rainfall data from Dindigul rain gauge station located at
Dindigul town was collected for the period of March 1971 to February 2002. The
analysis of monthly water level data was also collected from 6 monitoring wells for the
cross- correlation studies. The rainfall distribution in the study area is no uniform due to
4
the presence of hills in the study area and the changes in the topography and ground
surface elevation Athavale et al. [11], Rangarajan et al. [12] and Rangarajan[13]. But in
the study area only one rain gauge station. It is considered that the whole area is affected
by same rainfall, which is monitored in the Dindigul rain gauge station shown in Figure
1. The average monthly rainfall values from the rain gauge station are plotted and it
indicates that the average monthly rainfall is in four different stresses. But it is more
rainfall occurred in the last stress of the each year.
The water level hydrographs with rainfall data is plotted and it can be seen that there
is approximately time lag of one/two months in the response of the water table to the
rainfall events. Therefore, it shows that the aquifer system, spreaded whole the study
area, responding within one/two months lag of rainfall. It can be also observed that the
aquifer response is maximum particularly to the rainfall that occurs from October to
January (when most of the rainfall occurs and withdrawal could be minimum).
UNCONFINED AQUIFER RESPONSE
The water level of unconfined aquifer in the study area with rainfall data response after
one/two months of rainfall. The cross correlation co-efficient were determined in between
depth of water table and corresponding rainfall. The result of correlation coefficients is
shown in Table-1. It clearly indicates that the wells nos. 83029 and 93029A are
responding with two months lag after the rainfall with values of 0.16 and 0.25, but well
nos. 83503, 83514, 83514A and 83520 are in one-month lag of the rainfall with values of
0.14, 0.20, 0.04 and 0.24 respectively. The correlation coefficient values are plotted
corresponding lag of water table rises. This plot indicates that wells 83503, 83514,
83514A and 83520 are responding after one month rainfall whereas wells 83029 and
93029A are in two month lag.
Table 1. Cross correlation matrix in between depth of water table and rainfall in different
lags.
Well no.
83029
83029A
83503
83514
83515A
83520
Without lag
0.09
0.16
0.05
0.1269
0.03
0.12
1-month lag
0.15
0.23
0.14
0.20
0.04
0.24
2-month lag
0.16
0.25
0.12
0.17
0.01
0.24
3-month lag
0.12
0.20
0.11
0.09
0.001
0.21
4-month lag
0.10
0.18
0.11
0.04
0.01
0.17
RESULTS AND DISCUSSIONS
By applying the cross-correlation analysis to water tables variation in response to rainfall
the following observations have been made.
 The time lags of 1-month and 2-month for the maximum response of the aquifer
after rainfall.
 The amplitude of correlation decreases when lag increases/decreases in
systematic manner.
5
 The depth of the aquifer also governs the delay.
The qualitative estimation of recharge zone is made on the basis of cross correlation
coefficient values. The cross correlation coefficient values from September to March (wet
period) with corresponding response lags are represented in the Table-2 and taking the
maximum recharge coefficients , plotted in Figure 3.
Table 2. Correlation Matrix corresponding lags in PDW wells.
Months
83029
83029A
83503
83514
2-month
2-month
1-month
1-month
lag
lag
lag
lag
September -0.09
-0.12
-0.14
-0.19
October
-0.23
-0.53
-0.41
-0.29
November -0.32
-0.48
-0.53
-0.48
December -0.35
-0.41
-0.36
-0.11
January
-0.34
-0.40
-0.19
-0.31
February
-0.30
-0.37
-0.24
-0.24
March
-0.03
-0.03
-0.19
-0.14
10.44
0
83515A
1-month
lag
-0.14
-0.12
-0.24
-0.35
-0.37
-0.16
-0.06
83520
1-month
lag
-0.09
-0.26
-0.80
-0.37
-0.24
-0.15
-0.15
2.2 Km 4.4 Km
PWD well
83520
10.4
Scale:
-0.35
83515A
Latitude (in degree)
83514
Poor
10.36
-0.40
Less
83029A
10.32
-0.50
83029
Moderate
10.28
-0.60
83503
S
a
i rum
i ll
lai H
High
-0.80
10.24
77.9
77.94
77.98
78.02
Longitude (in degree)
Figure 3. Qualitative Recharge zone through Correlation Coefficient
6
High value of correlation coefficient indicates that the region gets more recharge and low
value indicates that recharge is poor. Due to the rainfall in the month of October PWD
well 83029A is getting response on December. The value of correlation coefficient is –
0.53. The PDW wells 83503, 83514 and 83520 are responding on December due to the
rainfall on November. The correlation values of these wells are –0.53, -0.48 and –0.80
respectively. But in the well 83029 depths of water levels is getting low in February due
to December rainfall. –0.35 is the maximum correlation value in this well. Otherside, the
well 83515A is giving good response due to the rainfall on January. The value is –0.37.
Above these correlation values indicating the behavior of the recharge response of the
unconfined aquifer in the study area.
Institute of Remote Sensing, Anna University, Chennai-600 025 [14], has divided the
study area into four recharge areas using Remote Sensing (data) and GIS. They are (I)
High, (II) Moderate, (III) Less and (IV) Poor zones for recharge. On the base of high
correlation coefficient the entire region is also divided into four recharge zones
(qualitatively) as shown in Figure 3, which is giving the good agreement with the result
of GIS and Remote Sensing technique. These are
 Zones of highly recharge for value of (r>0.60)
 Moderate zone for recharge (0.50 ≤ r ≥ 0.60)
 Zones of less recharge (0.40 ≤ r ≥ 0.50) and
 Zones of poor recharge (r < 0.40).
It is difficult to identify response behavior of the aquifer system with the finite number of
correlation coefficient, because it depends upon different factors, so it has some range
value. The highly favorable zones for recharge are the areas around village of
Sellamanthadu. This area is characterized by bajada, shallow pediment with high
weathered thickness (> 10m), hydrological soil group ‘A’ with moderate infiltration
characteristics as well as runoff (50-130 mm) with slope of 3-to10 %.
Moderate
recharge zones are around Annamaliar Mills and Ambaurai villages. These zones are
characterized by pediment, moderated weathered zone of thickness (15-20m),
hydrological soil group ‘B’ with moderate infiltration rate and runoff (65-80mm) with a
slope of 5-10%. The less favorable condition for recharge is the areas around
Sindalakundu and 50% of the study area. These areas are characterized by hydrological
soil ‘C’ with less runoff (75- 95mm) and slope of (<3%). The poor condition for
recharge is existing only for hills and PI complex having less thickness (<20m) of
weathered chances zones with in hydrological soil group ‘D’ having poor infiltration rate
and runoff (>130 mm) with a slope of > 15 % in the village of A. Vellodu and Dindigul
town.
ACKNOWLEDGEMENTS
Thanks to Director, Dr. V.P. Dimri, NGRI, for permitting to publish this paper and also
thanks to PWD and IRS, Anna University, Chennai for providing the suitable data. N.C.
Mondal is also grateful to CSIR, New Delhi for their partial financial support.
7
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