Research Bulletin No.

65

Groundwater Assessment in Kathajodi-Surua

Inter-Basin for Sustainable Water Resources
Management in Deltaic Aquifers
Dr. Sheelabhadra Mohanty
Senior Scientist (SWCE)
Dr. Madan K. Jha
Professor, IIT, Kharagpur
Dr. Ashwani Kumar
Director, DWM
Dr. S. K. Jena
Principal Scientist (SWCE)

Directorate of Water Management

(Indian Council of Agricultural Research)
Bhubaneswar - 751023, Odisha

2014
Correct citation:

Mohanty, Sheelabhadra; Jha, Madan K.; Kumar Ashwani; Jena, S.K. 2014. Groundwater
Assessment in Kathajodi-Surua Inter-Basin for Sustainable Water Resources
Management in Deltaic Aquifers. Bulletin No.-65. Directorate of Water management,
Indian Council of Agricultural Research, Chandrasekharpur, Bhubaneswar, India, 41p.

© 2014, Directorate of Water Management (ICAR).

Published by:

Director,
Directorate of Water Management,
(Indian Council of Agricultural Research)
Chandrasekharpur, Bhubaneswar, Odisha, 751023, India.
Phone: 91-674-2300060 ; EPBAX: 91-674-2300010, 2300016
Fax: 91-674-2301651; Web site: www.dwm.res.in

Printed at:

S J Technotrade (P) Ltd.

Subarnarekha Chambers,
Plot No : A-9 & 10, Unit – IV,
Bhouma Nagar, Bhubaneswar – 751001
Cell: 9132573795
Email : info.technotrade@gmail.com
 PREFACE

Water is indispensable for virtually all human activities and for sustaining our
ecosystem. Indeed water is the lifeline of the mankind. However, with increase in
population and higher living standards, there will be ever increasing demand for good
quality water. Almost 97% of the earth's water occurs as salt water in the oceans.
About 2% of the water occurs as snow and ice in polar and mountainous regions
leaving only 1% of the global water as liquid freshwater. Almost 98% of this liquid
freshwater occurs as groundwater, and hence it is the most valuable freshwater
resource of the earth.

However, overexploitation and continued mismanagement of groundwater resources

to supply ever increasing demand of water has led to water shortages, increased
pollution and degraded ecosystems worldwide. Hence the key concern is how to
maintain a long term sustainable yield from the aquifer in the face of impending
climate change and socio-economic factors. This requires groundwater assessment
for development of a sustainable groundwater management plan in river basins.
Development of an ef icient groundwater management plan requires detailed
hydrogeologic investigation in the study area which can help in vulnerability
assessment of aquifer system or, assessment of sustainable yield of aquifer.

In the current study, in-depth hydrologic and hydrogeologic investigations were

carried out in Kathajodi-Surua Inter-basin within Mahanadi Delta of Odisha to
explore the possibility of enhanced and sustainable groundwater supply. The detailed
knowledge of hydrology and hydrogeology of the study area is crucial for the ef icient
planning and management of scarce water resources in a basin. The present study is
irst of its kind in the study area. We hope that the results of this study will be helpful
for groundwater modeling of the deltaic groundwater system as well as for
determining optimal pumping rates so as to ensure ef icient groundwater utilization
in the study area. The results of the study will also be useful for other river basins of
India.

Authors
 CONTENTS

Contents Page No.

1. Introduction






1
2. Study Area






3
2.1 Groundwater monitoring



5
3. Hydrologic Analysis





6
3.1 Rainfall characteristics


6
3.2 Stream low characteristics


7
3.3 Land use/land cover variation


8
3.4 Soil map





10
3.5 Runoff potential in study area


11
3.6 Groundwater recharge


13
3.7 Crop water requirement



15
4 Hydrogeologic Analysis




18
4.1 Basin geology




18
4.2 Hydraulic parameters of aquifer system

23
4.3 Rainfall groundwater dynamics


25
4.4 Stream-aquifer interaction


28
4.5 Hydraulic connectivity in study area

33
4.6 Groundwater quality



36
5 Conclusion






39
6 References






40
 1. INTRODUCTION

Groundwater is a very important and invaluable natural resource on the earth. Its
unique qualities that it is easily accessible, generally free from pathogens and
suspended particles, and requires no or little treatment has made it the most
important and preferred source of water for domestic, agricultural and industrial
uses. However, the over-exploitation and the growing pollution of groundwater are
depleting the aquifers worldwide and threatening the sustainability of water supply
and ecosystems on the earth (Shah et al., 2000; Zektser, 2000; Sophocleous, 2005;
Biswas et al., 2009). Hence, the present challenge is how to maintain a long-term
sustainable yield from aquifers (e.g., Hiscock et al., 2002; Alley and Leake, 2004) in the
face of looming climate change and socio-economic changes.

In India, the demand for water has already increased a multiple times over the years
due to increasing population, growing urbanization, agriculture expansion, rapid
industrialization and economic development and the water demand has an increasing
trend in all the sectors (Kumar et al., 2005; Mall et al., 2006). Total water requirement
in India for various activities around the year 2050 has been assessed as 1450
km3/year (Gupta and Deshpande 2004). This is signi icantly more than the current
estimate of utilizable water resource potential (1086 km 3 /year) through
conventional development strategies. Already there are several areas of the country
that face water scarcity due to intensive groundwater exploitation (CGWB, 2006). The
experiences in the ield of water management in India have shown that the
indiscriminate uses of water resources have either lowered groundwater levels or
caused waterlogging and salinity in different parts of the country. In recent studies,
the analysis of GRACE satellite data revealed that the groundwater reserves in the
states of Rajasthan, Punjab and Haryana are being depleted at a rate of 17.7±4.5
3
km /yr (Rodell et al., 2009). Thus, the depletion of groundwater resources has
increased the cost of pumping, caused seawater intrusion in coastal areas and has
raised questions about sustainability of groundwater supply and ecological security.
Therefore, ef icient and judicious utilization of surface and groundwater resources is
very much essential to protect vital groundwater resources as part of sustainable land
and water management strategies.

1
The state of Odisha in eastern India is no exception and it has its own share of water
problem with diverse situation in different parts like the recurrence of drought in
western parts, pockets of saline water in the coastal tract and acute water scarcity in
many other parts. Because of uneven nature of rainfall and its capricious distribution,
there is an increasing dependence on groundwater resources for meeting the growing
water demand of agriculture, industrial and domestic sectors. About 3 million people
in the western part of Odisha are facing acute drinking water crisis due to large-scale
deforestation, unplanned irrigation and poor management of natural resources.
Moreover, the overexploitation of groundwater has resulted in declining groundwater
levels in several areas and seawater intrusion in coastal areas (CGWB, 2006). More
than 80% of the geographical area of Odisha is underlain by hard rocks and the
remaining area by semi-consolidated and unconsolidated subsurface formations. In
hard-rock terrains, groundwater is mainly con ined to weathered residuum and
fractured zones, with limited to moderate groundwater potential. Even though
suf icient water is available in coastal areas in the monsoon season, there is a water
shortage for irrigation in the post-monsoon season. Therefore, there is a need to
develop optimal groundwater management strategies to increase area under post-
monsoon season crops and thereby sustain agricultural productivity and livelihoods.

Development of an ef icient groundwater management plan requires detailed

hydrogeologic investigation in the river basin. The hydrogeologic investigations along
with use of modeling techniques can help in vulnerability assessment of aquifer
system or, assessment of sustainable yield of aquifer. Considering the growing water
problem in Odisha, the Kathajodi-Surua Inter-basin within the Mahanadi deltaic
system of Odisha was selected as a study area for in-depth hydrologic and
hydrogeologic investigations to explore the possibility of enhanced and sustainable
groundwater supply. Needless to mention that detailed knowledge of hydrology and
hydrogeology of the study area is crucial for the ef icient planning and management of
scarce water resources in a basin. The present study is irst of its kind in the study area.
The results of this study will be helpful for groundwater modeling of the deltaic
groundwater system as well as for determining an optimal cropping pattern and
optimal pumping rates so as to ensure ef icient groundwater utilization in the study
area. The results of the study will also be useful for other river basins of India in
general and eastern India in particular.

2
 2. STUDY AREA

Kathajodi-Surua Inter-basin which is locally known as Bayalish Mouza, is located in

the Cuttack district of Odisha, Eastern India. The basin is a part of the Mahanadi Delta
which is located around the con luence of the Mahanadi River with the Bay of Bengal
along the eastern coast of India (Fig. 1). The apex of the Mahanadi delta lies at Naraj
where Mahanadi River divides into two major branches: Mahanadi to the north and
Kathajodi to the south. The Kathajodi River, after the branching out of Kuakhai River, is
further divided into two branches, namely Kathajodi to the north and Surua to the
south. Both the branches of the Kathajodi River later rejoin and is named as the Debi
2
River afterwards. Bayalish Mouza is the entrapped land mass of about 35 km area
surrounded on both sides by the Kathajodi River and its branch Surua.

Agriculture is the major occupation of the inhabitants. Total cultivated area in the
study area is 2445 ha, of which 1365 ha is irrigated land. The area under low land is
408 ha, medium land 1081 ha and high land is 956 ha. Paddy is the major crop in the
monsoon season, whereas crops like vegetables, potato, groundnut, greengram,
blackgram and horsegram are grown in the post-monsoon season. Owing to the lack
of irrigation infrastructure for surface water, all the irrigated lands are irrigated by
groundwater. At present there are 69 functioning government tubewells in the study
area, which are the major sources of groundwater withdrawal. These tubewells were
earlier constructed and managed by Orissa Lift Irrigation Corporation (OLIC),
Cuttack, Orissa, but now they have been handed over to the water users' associations
(WUAs). Although there is no water shortage during the monsoon season (June to
October), in the summer season (March to May), the farm ponds dry up and the
groundwater supply is not suf icient to meet the entire water demand of the farmers.

During the monsoon season, a problem of waterlogging is encountered in the study

area. Embankments have been provided on the banks of the rivers to prevent the entry
of river water into the inhabited area during lood events. Therefore, entire rainwater
of the region is drained through the main drain and discharged at a single outlet into
the river. A sluice gate is provided at the outlet of the area to prevent entry of river
water during lood events. During this time period, waterlogging problem is
encountered in the downstream side of the study area.

3
Fig. 1: Location Map of the Kathajodi-Surua Inter-Basin

4
2.1 Groundwater monitoring

Since no groundwater data were available in the study area, a groundwater

monitoring program was initiated in February 2004. For the monitoring of
groundwater levels, nineteen tubewells were selected in the study area in such a way
that they represent approximately four west-east and four north-south cross-sections
of the study area. The locations of the nineteen monitoring wells are shown as red
circles (A to S) in Fig. 2. Groundwater levels were monitored in the 19 tubewells on a
weekly basis from February 2004 to October 2007. The geographic locations of the
tubewells in the study area were found with the help of a global positioning system
(GPS) and the elevations of the tubewell sites were determined by leveling survey.

Fig. 2: Base Map of the Study Area Showing Drainage Network and Location of Tubewells

5
 3. HYDROLOGIC ANALYSIS
3.1 Rainfall characteristics

Analysis of 20 years (1990-2009) of rainfall data in the study area indicated that the
average annual rainfall is 1649.8 mm with a standard deviation of 375.9 mm. The
variation of mean monthly rainfall over the 20-year period along with standard
deviation bars is shown in Fig. 3. It is apparent from this igure that the highest mean
monthly rainfall (402.8 mm) with a standard deviation of 193.6 mm is observed in the
month of August. Though the rainfall events are distributed throughout the year, the
rainy season usually starts from mid-June and lasts up to mid-October. November
through May is usually characterized as a dry period. The most reliable months for
rainfall are July, August and September.
Thus, the bulk of the rainfall is concentrated
in a relatively short time span, which
increases the potential for both surface
runoff and recharge to the aquifer but limits
them to short periods of a year. As suf icient
rainfall is available during July, August and
September, groundwater withdrawal is
minimum during these months. Relatively
large standard deviations in the months of
May, June, July, August, September and
Fig. 3: Variation of Mean Monthly Rainfall in
October indicate that the magnitude of the Study Area
monthly rainfall varies appreciably from
year to year.

Moreover, Fig. 4 shows the variation of annual rainfall over the basin along with the
20-year mean annual rainfall and 75% of
mean annual rainfall lines. It is obvious from
this igure that years 1990, 1993, 1995,
1997, 1999, 2001, 2003, 2005, 2006, 2007
and 2008 have received more than the mean
annual rainfall and rest of the years have
received less than the mean annual rainfall.
According to India Meteorological
Department (IMD), the meteorological
drought year is de ined as a year in which
less than 75% of the average annual rainfall
is received. Based upon this criteria, the Fig. 4: Variation of Annual Rainfall
ye a r s 1 9 9 6 , 2 0 0 0 a n d 2 0 0 2 c a n b e during the 1990-2009 Period

6
characterized as drought years, with the year 1996 being the most severe drought
year wherein only an annual rainfall of 797 mm was received (Fig. 4). The probability
analysis of the monthly rainfall data indicated that Two-Parameter Log Normal
distribution was found to be best it to the rainfall data of January, February, March
and December; Pearson Type III distribution for April and November; Log Pearson
Type III distribution for May, June, August and October; Gumbel Type 1 Extremal
distribution for the month of July and Normal distribution for the month of
September. Using the best- it probability
distribution functions for different months,
the probabilities of monthly rainfalls at 20%,
50% and 80% exceedence of rainfall were
found out which are represented as monthly
rainfall under wet , normal and dry
scenarios, respectively. Fig. 5 shows the
temporal variation of monthly rainfall
during wet, normal and dry scenarios which
indicates considerable variation in the
amount of monthly rainfall during wet and Fig. 5: Monthly Variation of Rainfall during
dry scenarios. Wet, Normal and Dry Scenarios

3.2 Stream low characteristics

The daily variation of stream low in the Kathajodi River for six years (2001-2006) at
the highway bridge gauging station is shown in Fig. 6. It is clear from this igure that
the stream low reaches the peak value during the period July to September when
most of the rainfall occurs. It starts decreasing from the month of October and
becomes very low (<50 m3/s) from December onwards when rainfall events are very
less. The stream low reduces further and varies from 10 to 20 m3/s during February to
May. The stream low varies appreciably over the six year period, with the minimum
stream low (mean low = 283 m3/s) in 2002, which was a meteorological drought year
(Fig. 2). In 2002, 2004 and 2005, the mean stream low was lower than the 6-year
average stream low, whereas it was higher in the remaining years.

The stream low data of the Kathajodi River were analyzed to calculate annual
maximum discharge, minimum discharge, 95-day discharge, ordinary discharge, low
discharge, droughty discharge and mean discharge using the method reported by Jha
et al. (1999). After arranging the daily stream low data of a given year in a descending
th th th th
order, the 95/96 day (96 day for a leap year), the 185/186 day, the 275/276 day,
th
and the 355/356 day discharges are respectively known as 95-day, ordinary, low, and
droughty discharges. Table 1 summarizes the low characteristics for the 6 year
3
period. Lowest maximum stream low (7557 m /s) is observed in 2002, which is

7
signi icantly less than the six-year mean. Maximum stream low is observed in 2001
3 3
(18380 m /s) followed by 2003 (16530 m /s). Although the years 2001, 2003 and
2006 experienced relatively high stream lows, minimum lows were lower. The 95-
day low in 2002 is signi icantly less than the
6-year mean, whereas the ordinary low, low
low and droughty low are comparable over
different years. The minimum low is zero in
three years (2001, 2002 and 2004), while it
is quite low in the remaining three years.
This suggests the unavailability of surface
water resources in the study area for a
considerable time period. Zero stream low
is also detrimental to the river ecosystem.
Therefore, a comprehensive investigation is
necessary in this direction to ind out a Fig. 6: Annual Discharge Hydrograph of the
Kathajodi River at Highway Bridge Gauging
suitable low low in the river during dry Station for the 2001-2006 Period
seasons in order to protect river ecosystems.

Table 1: Stream low Characteristics of the Kathajodi River for 2001-2006 Period

Flow Streamflow (m 3/s)

2001 2002 2003 2004 2005 2006 6-yr Mean
Maximum Flow 18380.0 7557.0 16530.0 9727.0 11184.0 15719.0 13182.8
95-day Flow 643.7 59.0 959.1 431.9 410.5 467.9 495.3
Ordinary Flow 33.3 20.7 24.9 20.9 35.4 25.0 26.7
Low Flow 17.1 13.2 17.5 3.4 17.2 6.7 12.5
Droughty Flow 0.0 0.0 17.0 0.0 2.4 3.0 3.7
Minimum Flow 0.0 0.0 12.1 0.0 1.2 0.9 2.4
Mean Flow 1345.2 283.0 1338.1 587.9 712.5 873.6 856.7

3.3 Land use/land cover variation

Land use/land cover map of the study area for the wet (Kharif) and dry (Rabi) seasons
were generated using remote sensing imagery. One pre-monsoon IRS P6 MX image
(path-101, row-095, LISS-4, and date of pass = 20.03.2004) and another post-
monsoon IRS P6 MX image (path-102, row-073, LISS-4, and date of pass = 20.11.2004)
of the study area were procured from National Remote Sensing Agency (NRSA),
Hyderabad, Andhra Pradesh, India. Both the images were recti ied and geometrically
corrected with respect to the Survey of India toposheets of the study area namely 73
h/15 and 73 l/3 using ERDAS IMAGINE 8.7 software. The classi ication of the FCC map
of the study area was accomplished by supervised classi ication method. A number of

8
 ield visits were made to verify the accuracy of land use classi ications obtained from
th
satellite imagery. The, image of 20 March 2004 was used for generation of land
use/land cover map of the dry season (Rabi season) whereas, the image of 20th
November 2004 was used for the land use/land cover map of the wet season (Kharif
season).

Based on the remote sensing image analysis, land use of the study area was classi ied
into 7 categories, namely settlement, orchard/plantations, water body, wetland,
fallow land, paddy area and vegetables/pulses/oilseed area. The land use/land cover
maps of the wet season (Kharif season) and the dry season (Rabi season) are shown in
Figs. 7 and 8, respectively. The areas under different land uses/land covers in both the
seasons are summarized in Table 2. About 816.42 ha of the study area are covered
under settlements or built up lands, whereas 318.33 ha are covered under
orchard/plantation crops. Paddy is the most dominant crop in the Kharif season
covering an area of 1140.57 ha. In the Rabi season, vegetables, pulses and oilseeds
covering an area of 563.32 ha are grown along with paddy cultivation in an area of
377.42 ha. Clearly, larger area (1307.04 ha) remains fallow during the Rabi season as
compared to the Kharif season (945.25 ha), which necessitates ef icient irrigation
water management in the study area.

Fig. 7: Land Use/Land Cover Map of Kathajodi-Surua Inter-basin in the Kharif Season

9
 Fig. 8: Land Use/Land Cover Map of Kathajodi-Surua Inter-basin in the Rabi Season

Table 2 Land Use/Land Cover in the Study Area during Kharif and Rabi Seasons

Sl. No. Land Use Area (ha)

Kharif Season Rabi Season
1 Built-up Land 816.42 816.42
2 Orchard/ Plantations 318.33 318.33
3 Water Body 21.09 21.09
4 Wetland 260.48 98.55
5 Fallow Land 945.25 1307.04
6 Paddy Cultivated Land 1140.57 377.42
7 Land under Vegetables, Pulses or Oilseed - 563.32
in Rabi Season
Total 3502.14 3502.17

3.4 Soil map

The soil map of the study area was prepared in GIS environment with reference to the
soil map of the region prepared by Orissa Space Application Centre (ORSAC),
Bhubaneswar, India. The soil map was recti ied and geometrically corrected as
explained above in case of land use/land cover map. The different soil polygons

10
representing different soil taxonomy were delineated using ArcGIS software. The soil
map shows that the study area comprises three major soil types, namely (i) Fine
loamy, Udic Ustochrepts, (ii) Coarse loamy, Typic Udipsamments and (iii) Fine, Typic
Endoaquepts with a majority of the area belonging to type 1 category (Fig. 9).

The soil groups were characterized in different hydrologic soil groups for
development of hydrologic soil cover complex of the study area. Based on the
characteristics of the soil types present in the study area, the soil types Fine loamy,
Udic Ustochrepts and Fine, Typic Endoaquepts were grouped under hydrologic soil
group C (moderately high runoff potential) and the soil type Coarse loamy, Typic
Udipsamments was grouped under hydrologic soil group B (moderately low runoff
potential) according to the guidelines of USDA Soil Conservation Service (SCS, 1985).

Fig. 9: Soil Map of the Study Area

3.5 Runoff potential in the study area

The curve number technique (SCS, 1985) was used for runoff estimation in the study
area. According to characteristics of the soil types in the study area, soils were
classi ied into different hydrologic soil groups. The land use/land cover coverage of
the wet season and the soil coverage were merged using ArcGIS software to delineate
the curve number coverage of the study area (Subramanya, 2008). All the polygons

11
having a particular land use and a hydrologic soil group were selected and then curve
numbers for Antecedent Moisture Condition (AMC) II condition were assigned to
these polygons with the help of standard table (SCS, 1985). AMC conditions were
determined based on the cumulative previous 5 days rainfall for a particular rainfall
event and using standard guidelines. Based on the AMC conditions, i.e., AMC I, AMC II
or AMC III, curve numbers were assigned to the polygons using the AMC conversion
table (Subramanya, 2008). Composite curve number method was used for runoff
estimation.

The curve number (AMC II) map obtained by overlaying the land use map of the wet
season and the soil map of the study area in GIS environment is shown in Fig. 10. The
areas under different curve numbers are shown in Table 3. It is evident from this table
that a majority of the study area (1081.20 ha) falls under paddy on hydrologic soil
group C, i.e., curve number equal to 82, while only 41.72 ha falls under
orchard/plantation crops in hydrologic soil group B, i.e., curve number 55.

Fig. 10: Spatial Distribution of Curve Number over Kathajodi-Surua Inter-basin

12
The estimated runoff obtained by composite curve number method along with the
total monsoon rainfall for the 1990-2009 period is shown in Fig. 11. The estimated
runoffs for the twenty years period (1990-2009) vary from a minimum of 76.15 mm in
the year 1996 to a maximum of 935.29 mm in the year 2003. Further, the runoff as
percentage of total monsoon rainfall varies from a minimum of 10.19% in the year
1995 to a maximum of 43.3% in the year 2003. Incidentally, more of high rainfall
events occurred in the years 1993, 1997, 1999, 2001, 2003, 2006 and 2007, and hence
more runoffs were generated in these years. It is worth mentioning that this estimated
runoff is not included in the above mentioned stream low which is measured at an
upstream location of the basin, whereas the runoff is discharged at the downstream
end of the basin.

Table 3 Curve Number Distribution (AMC II) in the Study Area during Wet Season

Hydrologic Soil Cover Complex Curve Number Area (ha) Area (%)
(AMC II)
Settlement on Hydrologic Soil Group B 69 235.82 6.73
Settlement on Hydrologic Soil Group C 79 580.64 16.58
Orchard/Plantation on Hydrologic Soil Group B 55 41.72 1.19
Orchard/Plantation on Hydrologic Soil Group C 70 276.66 7.90
Paddy on Hydrologic Soil Group B 74 59.39 1.70
Paddy on Hydrologic Soil Group C 82 1081.20 30.87
Fallow Land on Hydrologic Soil Group B 86 45.65 1.30
Fallow Land on Hydrologic Soil Group C 91 899.61 25.69
Water Body/Wetland 85 281.60 8.04
Total 3502.29 100.00

Based on the above discussion, it can be inferred that the study area has suf icient
runoff potential which can be stored through water harvesting structures such as
farm ponds at suitable locations and check dams across the main drain (Fig. 2). These
water harvesting structures will ensure
increased and dependable water supply for
monsoon and post-monsoon crops as well as
will facilitate augmentation of groundwater
resources in the study area.
3.6 Groundwater recharge
The recharge from rainfall in the study area
was estimated using the rainfall-recharge
relationship in alluvial geological provinces
of India, which is given as (Rangarajan and Fig. 11: Total Monsoon Rainfall, Runoff
Athavale, 2000): and Percent Runoff during 1990-2009

13
 R=0-147(P) - 6


… (1)

Where, P = annual rainfall (mm) and R = annual recharge from rainfall (mm). The
formula gives the total annual recharge from rainfall. The monthly recharge from
rainfall was estimated by dividing the total annual recharge from rainfall into
different monsoon months in proportion to the monthly rainfall.

The total groundwater recharge was

estimated by adding the recharge from
different sources such as rainfall, return low
from irrigation and water bodies. The
recharge from the return low from
irrigation was estimated according to the
guidelines of Central Ground Water Board,
New Delhi, India (CGWB, 1997). Further, the
recharge from water bodies was considered
as 1.4 mm/day for the period during which Fig. 12: Total Rainfall and Recharge
water is present in the water bodies (CGWB, from Rainfall during 1990-2009
1997).

Fig. 12 shows the variation of recharge from rainfall along with the total rainfall
during 1990-2009 period. Recharge from rainfall varies from a minimum of 111.2 mm
in the year 1996 to a maximum of 328 mm in the year 2003. The recharge as
percentage of total rainfall is about 14%, with negligible variation from year to year.
Table 4 shows the monthly total groundwater recharge during 2004-2007, which
reveals that the recharge is mostly concentrated during monsoon months (June to
October). Total groundwater recharge in the years 2004 to 2007 varied from about
288 mm in the year 2004 to 385 mm in the year 2006.

Table 4 Estimated Monthly Groundwater Recharge in the Period 2004-2007

Month Total Recharge (mm)
2004 2005 2006 2007
January 10.4 10.4 10.4 10.4
February 12.5 12.5 12.5 12.5
March 15.6 15.6 15.6 15.6
April 16.9 16.9 16.9 16.9
May 12.5 26.6 12.5 12.5
June 21.4 27.5 29.0 35.2
July 58.1 88.9 57.8 37.5
August 55.6 43.6 156.2 109.5
September 30.0 67.4 52.0 92.3

14
 Month Total Recharge (mm)
2004 2005 2006 2007
October 42.0 50.1 9.8 16.7
November 5.0 9.9 5.0 5.0
December 8.0 8.0 8.0 8.0
Total 288.1 377.4 385.7 372.1

3.7 Crop water requirement

The irrigation requirement of the crops in the study area is mostly in the post-
monsoon (Rabi) season. Paddy, sugarcane, potato, onion, groundnut, vegetables,
greengram, blackgram, horsegram and mustard are major crops in the study area
during this season. The Department of Agriculture, Government of Orissa has ixed
target areas of coverage under these Rabi crops, which are summarized in Table 5.

Table 5 Targeted Area of Coverage under Different Post-monsoon Crops

Sl. No. Crop Area (ha)

1 Paddy 710
2 Sugarcane 130
3 Potato 200
4 Onion 20
5 Groundnut 82
6 Winter Vegetables 400
8 Summer vegetables 165
8 Greengram 210
9 Blackgram 320
10 Horsegram 150
11 Mustard 36

The water requirements of these crops were computed by the pan evaporation
method. The effective rainfall was estimated by the USDA-SCS method (Doorenbos
and Pruit, 1977). The total crop water requirements in the months of November,
December, January, February, March, April and May were computed as 4.76 x 105, 9.01
5 5 5 5 5 5 3
x 10 , 26.47 x 10 , 22.65 x 10 , 24.69 x 10 , 22.16 x 10 and 8.13 x 10 m ,respectively.
Similarly, the total water requirements for the rabi paddy, sugarcane, potato, onion,
groundnut, winter vegetables, summer vegetables, greengram, blackgram,
horsegram and mustard were computed as 73.85 x 105, 7.47 x 105, 5.78 x 105, 0.59 x
5 5 5 5 5 5 5 5 3
10 , 2.21 x 10 , 10.65 x 10 , 5.03 x 10 , 3.27 x 10 , 5.24 x 10 , 3.0 x 10 and 0.8 x 10 m ,
respectively.

15
The net irrigation requirements of different crops for the wet, normal and dry
scenarios are shown in Table 6(a to c), respectively. The net irrigation requirements of
paddy in the wet, normal and dry scenarios are 875.2, 938.2 and 999.2 mm,
respectively. It is apparent from Tables 6(a,b) that the values of the difference between
the net irrigation requirement in the wet scenario and that in the normal scenario in
the months of November and May is more (28 and 62 mm respectively) because
effective rainfall in the wet scenario is more in these two months. Similarly, the
difference between the net irrigation requirements in the wet scenario and that in the
normal scenario is low (3 mm) in the month of December because the effective rainfall
in the wet scenario is quite low in this month. Interestingly, the net irrigation
requirement in December during normal scenario is the same as that during dry
scenario [Tables 6(b,c)], which is due to the fact that the effective rainfall in the normal
scenario is zero in December.

Table 6(a): Net Irrigation Requirements of the Crops in the Wet Scenario

Net Irrigation Requirement (mm)

Crop
November December January February March April May Total
Paddy - 22.0 231.4 181.9 223.5 216.4 0 875.2
Sugarcane 26.5 0 15.4 37.1 64.8 109.6 54.9 308.3
Potato - 33.7 45.1 64.2 75.9 - - 218.9
Onion - 48.4 48.7 56.5 70.4 - - 224.0
Groundnut - 26.4 41.6 64.2 67.0 - - 199.2
Winter
11.5 58.0 60.7 54.1 - - - 184.3
Vegetables
Summer
- - - - 33.9 75.9 8.1 117.9
Vegetables
Greengram 0 58.0 51.5 - - - - 109.5
Blackgram 0 66.8 48.0 - - - - 114.8
Horsegram - - 18.2 48.7 65.9 - - 132.8
Mustard 0 52.1 68.5 33.2 - - - 153.8

16
Table 6(b) Net Irrigation Requirements of the Crops in the Normal Scenario

Net Irrigation Requirement (mm)

Crop
November December January February March April May Total
Paddy - 25.0 239.4 195.9 240.5 237.4 0 938.2
Sugarcane 54.5 0 23.4 51.1 81.8 130.6 116.9 458.3
Potato - 36.7 53.1 78.2 92.9 - - 260.9
Onion - 51.4 56.7 70.5 87.4 - - 266.0
Groundnut - 29.4 49.6 78.2 84.0 - - 241.2
Winter
39.5 61.0 68.7 68.1 - - - 237.3
Vegetables
Summer
- - - - 50.9 96.9 70.1 217.9
Vegetables
Greengram 17.0 61.0 59.5 - - - - 137.5
Blackgram 20.0 69.8 56.0 - - - - 145.8
Horsegram - - 26.2 62.7 82.9 - - 171.8
Mustard 13.2 55.1 76.5 47.2 - - - 192.0

Table 6(c) Net Irrigation Requirements of the Crops in the Dry Scenario

Net Irrigation Requirement (mm)

Crop
November December January February March April May Total
Paddy - 25.0 242.4 201.9 247.5 252.4 30.0 999.2
Sugarcane 63.5 0 26.4 57.1 88.8 145.6 147.9 529.3
Potato - 36.7 56.1 84.2 99.9 - - 276.9
Onion - 51.4 59.7 76.5 94.4 - - 282.0
Groundnut - 29.4 52.6 84.2 91.0 - - 257.2
Winter
48.5 61.0 71.7 74.1 - - - 255.3
Vegetables
Summer
- - - - 57.9 111.9 101.1 270.9
Vegetables
Greengram 26.0 61.0 62.5 - - - - 149.5
Blackgram 29.0 69.8 59.0 - - - - 157.8
Horsegram - - 29.2 68.7 89.9 - - 187.8
Mustard 22.2 55.1 79.5 53.2 - - - 210.0

17
 4. HYDROGEOLOGIC ANALYSIS

4.1 Basin geology

The lithologic data offer unique opportunities to gather information about type, depth
and areal extent of subsurface formations (aquifer and con ining layers) and
groundwater condition in a basin. These information are of immense importance for
the design and analysis of pumping tests as well as for the numerical modeling of
groundwater systems (Anderson and Woessner, 1992; Fetter, 2000). Using the
lithologic data, geologic pro iles along four west-east sections (Sections A-A', B-B', C-C'
and D-D'), four north-south sections (Sections E-E', F-F', G-G' and H-H') and one
central section (Section I-I') as shown in Fig. 2 were prepared. Thereafter,
stratigraphic analysis was performed to characterize aquifers and con ining layers
present in the study area.

The analysis of lithologic data along the four west-east, four north-south and one
central cross-sections of the study area [Fig. 13(a to i)] indicated that a con ined or
leaky con ined aquifer exists in the study area, which contributes a major source of
groundwater. This aquifer consists of coarse sand, medium to coarse sand and coarse
sand with gravel; the coarse sand being the dominant formation. The thickness of the
aquifer varies from 20 to 55 m over the basin. The top con ining layer comprises clay
or sandy clay with isolated patches of coarse sand or medium sand, whereas the
bottom con ining layer consists of clay. Wherever the con ining layer consists of sandy

(a)

Fig. 13 (a to i): Geologic Pro iles along Four West-East, Four North-South and a Central Sections

18
(b)

(c)

19
(d)

(e)

20
(f)

(g)

21
(h)

(i)

22
clay or has patches of coarse sand or medium sand, it can contribute leakage into or
from the aquifer depending on hydraulic conditions. The thickness of the top
con ining layer varies from 15 to 50 m, except at Site C where the aquifer is available at
a shallower depth and at Site H where the clay layer is extended up to a depth of 66 m
[Fig. 13(e)]. The depth of the impermeable layer below the aquifer (i.e., bottom
con ining layer) ranges between 47 m and 88 m.

The geologic pro ile along the section D-D' [Fig. 13(d)] shows the presence of multiple
aquifers towards the downstream side of the basin. At Site M, irst aquifer is available
at a depth of 21-30 m and second aquifer at a depth of 40-82 m below the ground level.
Similarly, at Site O, the aquifers are available at depths of 3-12 m, 30-42 m and 49-66.5
m below the ground level and at Site 31, the aquifers are available at depths of 20-40
and 49-82 m. However, as the lithology of many nearby sites do not show a multi-
aquifer system, the patches of coarse sand or medium sand to coarse sand can be
considered as isolated patches within the clay bed. The geologic pro ile along the
section I-I' [Fig. 13(i)] shows the presence of aquifer at a deeper depth towards the
south-east side of the basin. Based on this discussion, it can be concluded that a
con ined or leaky con ined aquifer of 20-55 m thickness exists at depths of 15 to 50 m
in the study area. The aquifer slopes from north-west to south-east direction in the
basin

4.2 Hydraulic parameters of aquifer system

In order to measure the hydraulic parameters like transmissivity and storage

coef icient of the aquifer system, time-drawdown pumping tests were conducted at 9
sites, i.e., B, C, H, I, J, K, O, S and 42 (Fig. 2) in the study area during January to April 2006
using existing infrastructure in the area. Drawdowns in the observation wells were
measured with time during pumping. Wherever observation wells were not available,
single-well pumping test was conducted by measuring the water level in the pumped
well itself during pumping as well as recovery. These ield measured time-drawdown
data of 7 sites (B, C, H, I, K, O, and 42) were analyzed to determine aquifer parameters
transmissivity (T) and storage coef icient (S) by the graphical method using widely
used Aquifer-Test software (WHI, 2002).

The hydraulic parameters of the aquifer system, viz., transmissivity, hydraulic

conductivity and storage coef icient at 9 sites were determined by pumping tests and
are presented in Table 7. The analysis of time-drawdown pumping test data at sites B
and H by Aquifer-Test Software is illustrated in Figs. 14(a) and 14(b), respectively as
an example. The hydraulic conductivity values were obtained by dividing
transmissivity values with corresponding aquifer thickness values obtained from the
lithologic data. It should be noted that, storage coef icient values could not be

23
obtained at sites J and S because of single-well pumping tests at these two sites. Table
7 reveals that the aquifer hydraulic conductivity (K) varies from site to site with a
maximum value of 96.8 m/day at Site O and a minimum value of 11.3 m/day at Site B,
indicating a large spatial variation of K over the basin (i.e., strong heterogeneity of the
aquifer system). This inding is reasonable as the hydraulic properties of alluvial
formations can change within short distances (Anderson and Woessner, 1992).
Further, it can be seen that the downstream region of the study area usually has a
higher hydraulic conductivity than the upstream region. Qualitatively, the hydraulic
conductivity of the basin could be classi ied as 'high' (Todd, 1980), suggesting fast
groundwater movement in the study area. On the other hand, the aquifer
2 2
transmissivity varies from about 3485 m /day (Site O) to 529 m /day (Site B) with an
2
average value of 1779 m /day. The values of storage coef icient range between 1.43 ×
10-4 (Site H) and 9.9 × 10-4 (Site O), which also suggest a signi icant variation of storage
coef icient over the basin.

Table 7: Hydraulic Parameters of the Aquifer System

Site Transmissivity Storage Aquifer Thickness Hydraulic

(m2/day) Coefficient (m) Conductivity (m/day)
Site B 528.5 2.04  10-4 47 11.3
-4
Site C 1521.2 2.34  10 44 34.6
Site H 833.8 1.43  10-4 22 37.9
-4
Site I 1071.4 9.30  10 40 26.8
Site J 3212.0 - 40 80.3
Site K 2463.0 3.24  10-4 28 88.0
-4
Site O 3484.8 9.9  10 36 96.8
Site S 3148.4 - 54 58.3
-4
Site 42 2861.0 4.02  10 48 59.6

Fig. 14(a): Pumping Test Analysis at Fig. 14(b): Pumping Test Analysis at
Site B by Aquifer-Test Software Site H by Aquifer-Test Software

24
4.3 Rainfall-groundwater dynamics

Well hydrographs of different tubewells were plotted along with the bar graphs of
rainfall to study rainfall-groundwater dynamics in the study area. Weekly variation of
groundwater levels at sites A to S during the period February 2004 to October 2007
are shown in Figs. 15(a to d), respectively along with the weekly rainfalls. The
groundwater-level luctuation at Site N has not been shown because the monitoring of
groundwater at this site was discontinued after 7th May 2006. These igures suggest
that groundwater levels at all the sites are generally higher in the rainy season (July to
September). Groundwater level rises in the month of June (week no. 22 to 25) with the
onset of monsoon and reaches its peak during August to September (week no. 33 to
38). From October onwards, it starts declining with the minimum groundwater
level in the months of April/May. The difference in the minimum and maximum
groundwater level varies from 3 to 6.5 m. In the year 2005, there was a delay in
monsoon and hence the minimum groundwater level was observed in the month of
June instead of April/May. The higher groundwater level in the rainy season can be
attributed to either direct recharge from rainfall and/or in low from the river as the
river water level is also maintained at a higher level during the rainy season.

The in luence of rainfall and river stage on groundwater is evident from the results of
correlation analysis (Table 8). Clearly, the correlation between the weekly rainfall and
weekly groundwater level in the upstream portion of the study area is 'poor' (r =0.333
to 0.398), while it is 'fair' (r = 0.562 to 0.659) in the downstream portion of the study

Fig. 15(a): Groundwater-Level Fluctuations at Sites A to D with Bar Graphs of Rainfall

25
Fig. 15(b): Groundwater-Level Fluctuations at Sites E to I with Bar Graphs of Rainfall

Fig. 15(c): Groundwater-Level Fluctuations at Sites J to M with Bar Graphs of Rainfall

26
 Fig. 15(d): Groundwater-Level Fluctuations at Sites O to S with Bar Graphs of Rainfall

area. However, 'good' (r > 0.8) correlation exists between groundwater level and river
stage at sites G, K, L, M, N, O, P, Q, R and S. It is apparent from Table 8 that the river stage
has a greater in luence on groundwater levels than the direct rainfall; this inding
suggests that the aquifer is not a perfectly con ined aquifer, rather it is a semi-con ined
(leaky) aquifer. It con irms the inding of lithologic investigation.

Table 8 Correlation of Weekly Groundwater Levels with Weekly Rainfall and Weekly
River Stage

Site Correlation Coefficient Remarks Correlation Coefficient (r) Remarks

(r) for Groundwater for Groundwater Level
Level versus Rainfall versus River Stage
Site A 0.382 Poor 0.728 Fair
Site B 0.381 Poor 0.729 Fair
Site C 0.375 Poor 0.720 Fair
Site D 0.376 Poor 0.737 Fair
Site E 0.358 Poor 0.703 Fair
Site F 0.379 Poor 0.722 Fair
Site G 0.589 Fair 0.886 Good
Site H 0.380 Poor 0.725 Fair
Site I 0.398 Poor 0.741 Fair
Site J 0.333 Poor 0.686 Fair

27
 Site Correlation Coefficient Remarks Correlation Coefficient (r) Remarks
(r) for Groundwater for Groundwater Level
Level versus Rainfall versus River Stage
Site K 0.578 Fair 0.857 Good
Site L 0.581 Fair 0.867 Good
Site M 0.585 Fair 0.860 Good
Site N 0.659 Fair 0.812 Good
Site O 0.627 Fair 0.878 Good
Site P 0.582 Fair 0.891 Good
Site Q 0.586 Fair 0.887 Good
Site R 0.562 Fair 0.844 Good
Site S 0.581 Fair 0.879 Good

Note: Poor: r < 0.50, Fair: r = 0.50-0.80, Good: r > 0.80.

In order to assess the extent and frequency of water level luctuations at a particular
site during a month, the mean groundwater level and range of groundwater level
luctuation in that particular month along with their standard deviations were
calculated. Tables 9(a) and 9(b) show the mean groundwater level and its range along
with their standard deviation values at sites A to S for all the months. In the upstream
portion of the study area, highest mean monthly groundwater level is observed in the
month of September, whereas it is observed in the month of August in the downstream
portion. This variation can be attributed to difference in recharge potential, cropping
preferences, pumping schedule and extent of stream-aquifer interaction. Higher
variation of water level is discernable in the monsoon season than in the dry season.
This can be due to recharge from direct rainfall and increased river stage during the
monsoon season. Maximum range (1.25±1.25 m at Site C to 2.88±2.05 m at Site S) of
groundwater level luctuation is observed in the month of July at almost all the sites,
except for sites A, D, F, H where the range of groundwater luctuation is maximum
(1.40±0.98 m at Site A to 1.63±0.71 m at Site D) in the month of August and Site L
where the range was maximum (2.68±2.07 m) in the month of September. As the
groundwater level suddenly increases from a minimum in the month of June due to
increase in river water levels and signi icant rainfalls, a higher deviation of
groundwater level data is observed in July.

4.4 Stream-aquifer interaction

As the underlying aquifer in the study area is alluvial, it is likely that there will be
hydraulic connection between the Kathajodi River and the aquifer. However, no
information was available about the stream-aquifer interaction in the study area,
though it plays an important role in the integrated management of surface water and
groundwater resources. To study stream-aquifer interaction based on available ield
data, well hydrographs at 18 sites were plotted along with the river stage hydrograph

28
 Table 9(a): Monthly Groundwater Level and Range of Fluctuation at Sites A to J
Statistic Groundwater Level (m MSL) and Range of Fluctuation (m) at Different Sites
Month
(m) A B C D E F G H I J
Range±S.D. 0.29±0.07 0.24±0.12 0.35±0.14 0.37±0.14 0.33±0.24 0.26±0.12 0.12±0.07 0.52±0.33 0.42±0.30 0.49±0.19
January
Mean±S.D. 14.88±0.53 16.49±0.43 15.65±0.41 15.10±0.56 15.18±0.27 14.86±0.34 15.61±0.18 15.11±0.19 14.77±0.30 14.45±0.63
Range±S.D. 0.67±0.47 0.38±0.13 0.24±0.19 0.40±0.19 0.45±0.40 0.32±0.19 0.24±0.16 0.45±0.27 0.36±0.25 0.56±0.56
February
Mean±S.D. 14.57±0.35 15.91±0.14 15.59±0.19 14.84±0.31 14.90±0.10 14.45±0.20 15.45±0.09 14.46±0.13 14.43±0.20 13.85±0.33
Range±S.D. 0.49±0.21 0.30±0.16 0.35±0.22 0.57±0.47 0.48±0.27 0.41±0.32 0.27±0.14 0.58±0.51 0.29±0.09 0.27±0.21
March
Mean±S.D. 14.17±0.12 15.55±0.12 15.34±0.09 14.63±0.27 14.49±0.14 14.14±0.24 15.13±0.19 14.32±0.15 14.02±0.08 13.34±0.36
Range±S.D. 0.17±0.10 0.12±0.09 0.12±0.03 0.16±0.08 0.17±0.09 0.16±0.14 0.21±0.21 0.17±0.08 0.11±0.09 0.17±0.09
April
Mean±S.D. 14.17±0.54 15.44±0.20 15.11±0.18 14.43±0.46 14.17±0.16 13.79±0.24 14.96±0.23 14.01±0.17 13.81±0.11 13.16±0.28
Range±S.D. 0.27±0.27 0.18±0.18 0.24±0.24 0.39±0.33 0.28±0.28 0.30±0.29 0.35±0.29 0.33±0.33 0.22±0.22 0.16±0.15
May
Mean±S.D. 14.13±0.37 15.44±0.17 15.09±0.12 14.39±0.29 14.18±0.25 13.83±0.08 15.30±0.21 14.10±0.29 13.78±0.21 13.14±0.17
Range±S.D. 0.51±0.34 0.28±0.28 0.26±0.24 0.37±0.37 0.30±0.30 0.43±0.46 0.31±0.23 0.33±0.26 0.20±0.11 0.42±0.42

29
June
Mean±S.D. 14.33±0.51 15.56±0.26 15.20±0.25 14.65±0.43 14.28±0.36 14.03±0.34 15.61±0.50 14.27±0.47 13.85±0.36 13.35±0.30
Range±S.D. 1.16±1.16 1.43±1.43 1.25±1.25 1.13±1.13 1.49±1.49 1.37±1.37 1.94±1.69 1.34±1.30 1.78±1.78 1.58±1.58
July
Mean±S.D. 15.38±0.62 16.39±0.41 15.96±0.23 15.64±0.48 15.22±0.32 14.93±0.38 16.75±0.40 15.41±0.58 14.99±0.43 14.42±0.55
Range±S.D. 1.40±0.98 1.34±0.75 1.11±0.92 1.63±0.71 1.41±0.83 1.46±0.73 1.18±0.70 1.43±0.58 1.33±0.78 1.53±1.11
August
Mean±S.D. 17.57±0.26 18.35±0.22 17.71±0.31 17.73±0.31 6117±.0.19 17.11±0.30 18.65±0.61 17.66±0.13 17.39±0.11 16.96±0.35
Range±S.D. 0.78±0.50 0.89±0.60 0.76±0.68 0.90±0.61 0.95±0.67 1.25±1.03 2.04±1.21 0.79±0.61 1.12±0.73 0.73±0.46
September
Mean±S.D. 17.81±0.73 18.42±0.67 17.84±0.72 18.02±0.71 17.90±0.59 17.52±0.89 18.46±0.76 17.96±0.60 17.60±0.72 17.30±0.62
Range±S.D. 0.86±0.60 0.72±0.30 0.48±0.25 0.96±0.34 0.72±0.16 1.04±0.59 1.57±0.57 0.68±0.24 1.23±0.31 0.81±0.25
October
Mean±S.D. 17.43±0.37 18.10±0.43 17.60±0.47 17.60±0.48 17.56±0.35 16.96±0.64 17.31±0.35 17.72±0.40 17.07±0.38 17.01±0.41
Range±S.D. 0.62±0.31 0.38±0.15 0.65±0.31 0.91±0.51 0.79±0.58 0.53±0.05 0.59±0.13 0.52±0.36 0.78±0.21 0.72±0.65
November
Mean±S.D. 16.59±0.60 17.31±0.62 16.80±0.82 16.73±0.54 16.67±0.56 15.98±0.75 16.21±0.27 16.58±0.63 16.02±0.45 16.19±0.48
Range±S.D. 0.79±0.41 0.33±0.09 0.36±0.35 0.61±0.33 0.36±0.25 0.66±0.40 0.17±0.14 0.58±0.37 0.31±0.17 0.47±0.33
December
Mean±S.D. 15.48±0.53 16.81±0.48 16.30±0.82 15.71±0.67 15.89±0.71 15.38±0.52 15.79±0.20 15.70±0.18 15.36±0.42 15.18±0.59
 Table 9(b): Monthly Groundwater Level and Range of Fluctuation at Sites K to S

Statistic Groundwater Level (m MSL) and Range of Fluctuation (m) at Different Sites
Month
(m) K L M N O P Q R S
Range±S.D. 0.24±0.16 0.45±0.38 0.18±0.05 0.25±0.10 0.12±0.07 0.30±0.30 0.30±0.30 0.15±0.10 0.17±0.05
January
Mean±S.D. 12.95±0.25 12.95±0.36 12.04±0.26 11.63±0.16 12.07±0.23 12.19±0.18 11.45±0.08 12.01±0.28 11.05±0.09
Range±S.D. 0.29±0.17 0.46±0.14 0.39±0.27 0.47±0.30 0.43±0.33 0.33±0.26 0.26±0.26 0.68±0.60 0.21±0.17
February
Mean±S.D. 12.79±0.28 12.52±0.14 11.86±0.37 11.19±0.27 11.75±0.11 11.84±0.16 11.15±0.28 11.44±0.41 10.75±0.17
Range±S.D. 0.38±0.24 0.24±0.17 0.29±0.19 0.18±0.10 0.11±0.10 0.12±0.04 0.11±0.10 0.30±0.29 0.10±0.06
March
Mean±S.D. 12.47±0.16 12.23±0.25 11.49±0.23 10.87±0.19 11.51±0.17 11.62±0.19 11.01±0.27 10.92±0.52 10.60±0.16
Range±S.D. 0.15±0.10 0.05±0.03 0.23±0.14 0.10±0.05 0.22±0.13 0.14±0.07 0.24±0.30 0.13±0.13 0.06±0.02
April
Mean±S.D. 12.25±0.14 11.97±0.25 11.22±0.26 10.79±0.11 11.28±0.04 11.43±0.12 10.88±0.21 10.72±0.55 10.44±0.03
Range±S.D. 0.40±0.37 0.79±0.79 0.36±0.36 0.72±0.72 0.50±0.47 0.38±0.29 0.37±0.23 0.50±0.49 0.27±0.24
May
Mean±S.D. 12.49±0.25 12.29±0.16 11.42±0.28 11.13±0.03 11.69±0.30 11.72±0.24 11.08±0.26 11.05±0.33 10.60±0.09

30
Range±S.D. 0.49±0.39 0.36±0.24 0.43±0.28 0.32±0.13 0.46±0.37 0.34±0.22 0.32±0.24 0.51±0.33 0.28±0.17
June
Mean±S.D. 12.92±0.79 12.97±0.79 11.82±0.49 11.92±1.00 12.22±0.92 12.06±0.28 11.46±0.26 11.53±0.51 10.90±0.25
Range±S.D. 2.54±1.79 2.65±1.69 2.60±1.59 2.55±2.55 2.56±1.63 2.51±1.57 2.66±1.70 2.77±2.22 2.88±2.05
July
Mean±S.D. 14.20±0.49 14.13±0.29 13.89±0.77 12.98±0.36 13.58±0.47 13.47±0.65 12.81±0.46 13.13±1.04 12.44±0.47
Range±S.D. 0.91±0.30 1.76±1.02 1.04±0.80 2.41±0.43 1.60±0.63 1.69±0.09 1.63±0.28 1.33±0.59 2.03±0.46
August
Mean±S.D. 16.64±0.61 16.13±0.89 16.51±0.86 14.76±0.35 15.47±0.65 15.81±0.49 15.31±0.41 16.45±0.56 15.28±0.41
Range±S.D. 1.90±0.54 2.68±2.07 1.78±0.92 2.08±1.95 2.17±1.44 2.22±1.35 2.15±1.25 1.27±1.16 2.22±1.37
September
Mean±S.D. 16.49±0.97 15.95±1.19 16.00±1.71 14.24±1.63 15.42±1.05 15.55±1.22 14.97±1.31 15.60±1.31 14.59±1.25
Range±S.D. 1.66±0.45 1.29±0.37 1.57±0.48 1.25±0.32 1.63±0.39 1.49±0.39 1.64±0.52 1.56±0.29 1..37±0.55
October
Mean±S.D. 15.13±0.39 14.78±0.56 14.20±0.44 13.38±0.35 13.89±0.53 14.20±0.56 13.64±0.55 13.80±0.71 13.08±0.74
Range±S.D. 0.63±0.18 0.43±0.08 0.47±0.11 0.41±0.06 0.44±0.07 0.48±0.10 0.72±0.29 0.53±0.05 0.73±0.35
November
Mean±S.D. 13.95±0.36 13.69±0.22 13.10±0.57 12.48±0.20 12.86±0.23 13.02±0.23 12.58±0.46 12.70±0.56 12.08±0.55
Range±S.D. 0.25±0.15 0.52±0.20 0.54±0.37 0.18±0.06 0.39±0.30 0.29±0.21 0.40±0.20 0.22±0.17 0.39±0.22
December
Mean±S.D. 13.40±0.37 13.40±0.28 12.49±0.45 12.11±0.22 12.43±0.12 12.56±0.20 11.92±0.21 12.20±0.45 11.41±0.21
at Naraj. The weekly river stage data near the study area was not available, and hence
the river-stage data available at an upstream gauging station at Naraj (Fig. 1) were
used in this study. As the river-water level at Naraj controls the river water level
around the study area, the river-stage data of Naraj were considered representative
for the study area. In addition, correlation analysis was performed between the
weekly groundwater levels at 19 sites and the weekly river stage using the data from
February 2004 to October 2007. Correlation analysis was also performed between
river stage lags and the groundwater levels at 19 sites considering 2-day to 10-day
lags of the river stage.

Figs. 16(a to d) show the well hydrograph at different sites along with the river stage
hydrograph at Naraj. These igures show similarity in trends of groundwater levels at
all the sites with the river stage at Naraj. The regression analysis between river stage
and groundwater level (Table 8) shows that there is a reasonably high correlation of
weekly river stage (r = 0.686 to 0.891) with the weekly groundwater level compared
to the weekly rainfall (r = 0.333 to 0.659). Thus, the increase in groundwater levels at
all the sites in the monsoon season is more due to increase in river stage than the
direct rainfall; and it can be inferred that there exists good stream-aquifer interaction
in the Kathajodi-Surua Inter-basin. In the downstream portion of the study area, there
is a better correlation between groundwater level and river stage (r = 0.812 to 0.891)
than the upstream portion (r = 0.686 to 0.741), suggesting a stronger stream-aquifer

Fig. 16(a): Well Hydrographs at Sites A to D with River Stage Hydrograph at Naraj

31
Fig. 16(b): Well Hydrographs at Sites E to I with River Stage Hydrograph at Naraj

Fig. 16(c): Well Hydrographs at Sites J to M with River Stage Hydrograph at Naraj

32
 Fig. 16(d): Well Hydrographs at Sites O to S with River Stage Hydrograph at Naraj

interaction in the downstream portion of the study area compared to the upstream
portion. This inding is in agreement with relatively large hydraulic conductivity in the
downstream region of the study area as discussed earlier.

Moreover, the correlation of groundwater level with river stages of 1 to 10 days lag is
shown in Table 10. Clearly, there is a better correlation between groundwater level
and river stage in the downstream portion of the basin than the upstream portion at
all the lag times. In the upstream side of the basin, the highest correlation is observed
at 9-day lag time (r = 0.733 to 0.769). In the downstream side of the basin, though the
highest correlation is observed at 2-day lag time (r = 0.855 to 0.894), signi icantly
good correlation between groundwater level and river stage (r = 0.726 to 0.891) is
observed up to 10-day lag time. Thus, it can be inferred that there is a signi icant
in luence of river stage on groundwater levels up to 10-day lag time. This inding
suggests that proper stream low management is necessary for enhanced and
sustainable groundwater supply, especially during dry periods.

4.5 Hydraulic connectivity in the study area

The groundwater-level data were further used to explore the hydraulic connectivity
in the study area. Weekly groundwater-level data from 10 selected wells distributed
over the study area for the period of 3 years and 9 months were used to develop a
correlation matrix, which was analyzed to explore the hydraulic connectivity between

33
 Table 10: Results of Correlation Analysis of Groundwater Levels and River Stages of Different Lag Times

Correlation Coefficient (r) for Different Lags of River Stage

Site 1-day 2-day 3-day 4-day 5-day 6-day 7-day 8-day 9-day 10-day
Lag Lag Lag Lag Lag Lag Lag Lag Lag Lag
A 0.728 0.730 0.705 0.692 0.740 0.721 0.751 0.765 0.767 0.741
B 0.729 0.735 0.709 0.692 0.738 0.724 0.746 0.753 0.756 0.729
C 0.720 0.723 0.698 0.684 0.726 0.711 0.733 0.744 0.746 0.716
D 0.737 0.740 0.713 0.701 0.749 0.730 0.754 0.767 0.769 0.744
E 0.703 0.707 0.682 0.668 0.715 0.701 0.726 0.738 0.742 0.717
F 0.722 0.725 0.699 0.684 0.730 0.715 0.737 0.749 0.752 0.724
G 0.886 0.883 0.862 0.855 0.849 0.846 0.858 0.847 0.831 0.806
hydraulic connectivity in the study area.

H 0.725 0.730 0.704 0.697 0.743 0.725 0.752 0.764 0.767 0.740
I 0.741 0.744 0.713 0.701 0.747 0.736 0.755 0.766 0.768 0.739

34
J 0.686 0.688 0.664 0.657 0.709 0.692 0.718 0.733 0.733 0.708
K 0.857 0.867 0.851 0.839 0.833 0.830 0.845 0.842 0.838 0.812
L 0.867 0.874 0.851 0.838 0.825 0.829 0.839 0.831 0.819 0.793
M 0.860 0.873 0.853 0.838 0.834 0.830 0.852 0.851 0.847 0.822
N 0.812 0.870 0.764 0.726 0.822 0.805 0.816 0.812 0.794 0.765
O 0.878 0.889 0.867 0.849 0.828 0.831 0.845 0.838 0.831 0.804
P 0.891 0.894 0.871 0.863 0.865 0.862 0.876 0.870 0.857 0.830
Q 0.887 0.893 0.869 0.861 0.861 0.858 0.872 0.867 0.855 0.828
R 0.844 0.855 0.833 0.822 0.821 0.815 0.834 0.828 0.824 0.800
S 0.879 0.890 0.867 0.852 0.851 0.852 0.872 0.866 0.860 0.832
groundwater level data in order to check the suitability of datasets for investigating
only wet-period (June to September) as well as only dry-period (October to May)
H and J) from the upstream portion of the basin and 5 sites (i.e., sites L, M, P, R and S)
individual sites. For this, ten sites were selected randomly with 5 sites (i.e., sites A, C, F,

from the downstream portion. Correlation matrices were also developed considering
The correlation matrix of groundwater levels of 10 selected sites over the study area is
shown in Table 11. It can be seen from this table that except the highlighted
correlation coef icient (r) values, all the other correlation coef icient values are
appreciably high (r ≥0.90) and range from 0.942 (between sites L and R) to 0.986
(between sites P and S). This suggests that when both the sites are either in the
upstream side of the basin or in the downstream side of the basin, then the correlation
is stronger. However, the correlation between a well in the upstream side of the basin
and a well in the downstream side of the basin is relatively poor, with r values ranging
from 0.827 (between sites J and L) to 0.872 (between sites F and S). This indicates that
the hydraulic connectivity of the sites is very good in both upstream and downstream
parts of the basin, but the hydraulic connectivity between the upstream part of the
basin and the downstream part is relatively poor. This could be attributed to the
distance between the sites, pumping pattern, and/or presence of a less permeable
layer in between upstream and downstream ends of the basin.

Table 11 Correlation Matrix of Groundwater Levels at 10 Observation Sites for the

Whole Year

Correlation Coefficient (r)

Site A C F H J L M P R S
A 1
C 0.966 1
F 0.967 0.979 1
H 0.974 0.959 0.972 1
J 0.971 0.964 0.975 0.974 1
L 0.835 0.829 0.855 0.858 0.827 1
M 0.853 0.847 0.866 0.869 0.840 0.948 1
P 0.856 0.852 0.871 0.871 0.849 0.968 0.970 1
R 0.851 0.839 0.865 0.864 0.852 0.942 0.972 0.966 1
S 0.860 0.836 0.872 0.871 0.847 0.961 0.973 0.986 0.969 1

Moreover, Tables 12 and 13 show the correlation matrices of groundwater levels at 10

sites for the wet season (June to October) and dry season (November to May),
respectively. Except the highlighted correlation coef icient values, all the other
correlation coef icient values are higher than or equal to 0.90, which range from 0.907
to 0.996 for the wet season and 0.900 to 0.957 for the dry season. Tables 12 and 13
also indicate that when both the sites are either in the upstream side of the basin or in
the downstream side of the basin, then the correlation is generally better. In contrast,
the correlation of groundwater levels between a site in the upstream portion of the
basin and a site in the downstream portion of the basin is relatively poor. Based on the
above discussion, it can be inferred that either the wet season's data of groundwater

35
levels or the entire year's data could be used to explore the hydraulic connectivity in
the study area. This inding is very useful for the areas where, there are well distinct
wet and dry seasons like monsoon dominated regions.

Table 12 Correlation Matrix of Groundwater Levels at 10 Observation Sites for the Wet
Season
Correlation Coefficient (r)
Site A C F H J L M P R S
A 1
C 0.975 1
F 0.978 0.996 1
H 0.985 0.976 0.971 1
J 0.988 0.977 0.976 0.987 1
L 0.765 0.783 0.785 0.763 0.749 1
M 0.811 0.820 0.814 0.799 0.793 0.907 1
P 0.794 0.813 0.816 0.796 0.796 0.946 0.952 1
R 0.805 0.813 0.807 0.797 0.799 0.896 0.966 0.947 1
S 0.802 0.813 0.814 0.798 0.796 0.943 0.957 0.979 0.961 1

Table 13 Correlation Matrix of Groundwater Levels at 10 Observation Sites for the Dry
Season
Correlation Coefficient (r)
Site A C F H J L M P R S
A 1
C 0.903 1
F 0.899 0.921 1
H 0.907 0.872 0.934 1
J 0.906 0.897 0.957 0.930 1
L 0.712 0.681 0.823 0.836 0.827 1
M 0.729 0.706 0.834 0.836 0.830 0.878 1
P 0.831 0.802 0.892 0.889 0.914 0.913 0.880 1
R 0.700 0.650 0.806 0.775 0.838 0.879 0.866 0.896 1
S 0.852 0.818 0.911 0.908 0.919 0.872 0.900 0.943 0.857 1

4.6 Groundwater quality

Groundwater samples were collected from 8 tubewells spread over the basin in the
month of May 2005 (representative for the pre-monsoon season) and November
2005 (representative for the post-monsoon season) for assessing temporal variation
in the water quality. The groundwater samples were analyzed for pH, EC, Na+, Ca2+,

36
Mg2+, Cl-, CO32- and HCO3- by following standard methods (APHA, 1989; Richards,
1968). Sodium Adsorption Ratio (SAR) and Residual Sodium Carbonate (RSC) of the
water samples were also computed using standard procedure (Richards, 1968; Ayers
and Westcot, 1989).

The results of the detailed groundwater quality analysis at 8 sites in the pre-monsoon
and post-monsoon seasons of the year 2005 are summarized in Tables 14(a) and
14(b), respectively. The pH of the groundwater samples in the pre-monsoon season
ranges from 6.8 to 7.3, which is considered normal according to WHO guidelines
(WHO, 1971). The corresponding values for the post-monsoon season range from 5.3
to 6.3, which indicate that the groundwater is slightly acidic. The groundwater EC
ranges from 0.16 to 0.26 dS/m in the pre-monsoon season and 0.12 to 0.21 dS/m in
the post-monsoon season, which is within the prescribed limit of drinking water.
According to Palmar (1993), irrigation water is classi ied into four groups based on
salinity: low salinity (<0.25 dS/m); medium salinity (0.25-0.75 dS/m); high salinity
(0.75-2.25 dS/m); and very high salinity (>2.25 dS/m). Following this classi ication,
the groundwater of the study area can be characterized as of low salinity, and hence
+
suitable for the irrigation purpose. The relative abundance of Na with respective to
2+ 2+
Ca plus Mg , in luences the suitability of water for irrigation purpose and is
represented by SAR. According to Richards (1968), water with SAR values less than 10
can be used for irrigation on almost all types of soils. As the SAR values of groundwater
in the study area range from 0.09 to 0.39 in the pre-monsoon season and 0.07 to 1.80
in the post-monsoon season, there is no sodium hazard both in pre-monsoon and
post-monsoon seasons. The groundwater does not contain carbonate, but it contains
bicarbonate varying from 0.2 to 0.6 me/L in the pre-monsoon season and 0.19 to 0.42
me/L in the post-monsoon season.

Table 14(a): Groundwater Quality in the Study Area in Pre-monsoon Season (2005)

EC Ca2+ Mg2+ Na+ Cl- HCO3- Mg2+/

Site pH SAR
(dS/m) (me/L) (me/L) (me/L) (mg/L) (me/L) Ca2+
Site A 6.99 0.20 1.2 0.7 0.20 35.5 0.30 0.31 0.58
Site B 7.10 0.19 1.4 0.5 0.20 32.0 0.20 0.21 0.36
Site G 6.85 0.22 1.2 0.7 0.10 35.5 0.20 0.10 0.58
Site I 6.80 0.26 1.6 0.9 0.30 42.6 0.30 0.27 0.56
Site N 7.30 0.17 1.0 0.2 0.30 42.6 0.60 0.39 0.20
Site O 6.99 0.20 2.0 0.4 0.10 63.9 0.20 0.09 0.20
Site Q 7.03 0.16 0.8 0.3 0.20 24.8 0.40 0.27 0.38
Site S 6.79 0.24 1.6 0.8 0.10 31.9 0.20 0.09 0.50

37
Table 14(b):Groundwater Quality in the Study Area in Post-monsoon Season (2005)

EC Ca2+ Mg2+ Na+ Cl- HCO3- Mg2+/

Site pH SAR
(dS/m) (me/L) (me/L) (me/L) (mg/L) (me/L) Ca2+
Site A 5.90 0.19 1.8 1.9 0.93 55.8 0.29 0.68 1.05
Site B 6.10 0.13 1.4 1.3 2.10 58.3 0.41 1.80 0.93
Site G 5.30 0.14 1.7 2.3 1.24 60.4 0.19 0.88 1.35
Site I 6.30 0.20 2.0 1.3 0.85 67.7 0.36 0.66 0.65
Site N 6.00 0.12 2.1 1.5 1.73 62.9 0.31 1.29 0.71
Site O 6.20 0.20 1.6 2.4 0.10 68.6 nil 0.07 1.50
Site Q 5.80 0.20 3.2 1.2 1.23 58.7 nil 0.83 0.37
Site S 5.90 0.21 1.9 1.6 1.63 60.0 0.42 1.23 0.84

2+ 2+
Waters containing carbonate and bicarbonate ions in excess of Ca plus Mg often
lead to much greater alkali formation than is indicated by their SAR values and this
excess is denoted by Residual Sodium Carbonate (RSC) (Richards, 1968). In the study
area, RSC values in both the seasons were found nil in all the samples, which suggests
that the water is suitable for the irrigation purpose. Ca2+ and Mg2+ do not behave
2+
equally in the soil system, and Mg deteriorates soil structures particularly when
irrigation water is sodium dominated and highly saline. Therefore, the Mg2+ and Ca2+
2+ 2+
ratio is also used as a useful index for water quality assessment. The Mg / Ca ratio of
the groundwater samples varies from 0.2 to 0.58 in the pre-monsoon season and 0.37
to 1.5 in the post-monsoon season, which is within the allowable safe limit of 1.5.
Further, the chloride content of the groundwater samples ranges from 24.8 to 63.9
mg/L in the pre-monsoon season and 55.8 to 68.6 mg/L in the post-monsoon season.
As the chloride contents of all the groundwater samples are less than 70 mg/L, they
are generally safe for all the plants (Ayers and Westcot, 1989). As far as potable water
- 2+
is concerned, the values of EC, Cl , and Mg are within the permissible limits for
drinking water as prescribed by WHO (1971).

Since the above water quality assessment is based upon short-term and limited
number of water quality parameters, there is a need to monitor water quality in the
study area at least seasonally on a long-term basis considering recommended suites
of water quality parameters so as to have a better understanding of groundwater
chemistry and degree of pollution, if any. Such a comprehensive and long-term
groundwater quality monitoring is of great importance for protecting vital
groundwater resources from point and non-point sources of pollution.

38
 5. CONCLUSION

The detailed hydrologic and hydrogeologic analysis were carried out in the Kathajodi-
Surua Inter-basin of Mahanadi Delta for the ef icient planning and management of
water resources. Analysis of stream low data indicated that maximum stream low in
the Kathajodi River is most likely during July to September, while the stream low is
signi icantly reduced during dry periods (February to May). The runoff estimates for
the study area were found to range from 10.2 to 43.3% of the total monsoon rainfall,
which indicated good potential for rainwater harvesting. The geologic investigation
indicated that the study area is underlain by a con ined or leaky con ined aquifers of
20 to 55 m thickness. The aquifer comprises coarse sand, medium to coarse sand and
pebbles, with coarse sand being dominant formation. Based on pumping tests, the
aquifer hydraulic conductivity varies from 11.3 m/day to 96.8 m/day with a mean
value of 46.1 m/day, which is characterized as 'high'. The storage coef icient of the
aquifer system was found to range between 1.43 × 10-4 and 9.9 × 10-4. These indings
indicate signi icant aquifer heterogeneity in the study area.

Moreover, the groundwater level attains its peak during August-September, with
April-May-June being the critical period. The majority of the study area exhibits a
strong river-aquifer interaction, and the river stage in luences groundwater levels
much more than direct rainfall. Also, there is a good hydraulic connectivity among the
wells in the upstream and downstream regions of the basin, but the hydraulic
connectivity was found to be relatively 'poor' in between the upstream and
downstream regions. Although the quality of groundwater was found suitable for
both irrigation and drinking purposes based on short-term data, a comprehensive
and long-term water quality monitoring is recommended for protecting vital
groundwater resources from point and non-point sources of pollution. Based on the
results of this study, development of a groundwater low simulation model and
simulation of management scenarios in essential for sustainable utilization of water
resources in the study area.

39
 REFERENCES

Alley, W.M. and Leake, S.A. (2004). The journey from safe yield to sustainability.
Ground Water, 42(1): 12-16.

Anderson, M.P. and Woessner, W.W. (1992). Applied Groundwater Modeling:

Simulation of Flow and Advective Transport. Academic Press Inc., San Diego,
California, 381 pp.

APHA (1989). Standard Methods for the Examination of Water and Wastewater.
American Public Health Association, Port City Press, Baltimore, Maryland.

Ayers, R.S. and Westcot, D.W. (1989). Water Quality for Agriculture. FAO Irrigation and
Drainage Paper 29 (Rev. 1), Food and Agriculture Organization (FAO), Rome,
Italy, 174 pp.

Biswas, A.K., Tortajada, C. and Izquierdo, R. (editors) (2009). Water Management in

2020 and Beyond. Springer, Berlin, 268 pp.

CGWB (1997). Ground Water Resource Estimation Methodology. Report of the

Ground Water Resource Estimation Committee, Central Ground Water Board
(CGWB), Ministry of Water Resources, Government of India, New Delhi, India,
107 pp.

CGWB (2006). Dynamic Groundwater Resources of India (as on March, 2004). Central
Ground Water Board (CGWB), Ministry of Water Resources, New Delhi, India.

Doorenbos, J. and Pruitt, W.O. (1977). Guidelines for Predicting Crop Water
Requirements. FAO Irrigation and Drainage Paper 24. Food and Agriculture
Organization of the United Nations, Rome, Italy, 144 pp.

Fetter, C.W. (2000). Applied Hydrogeology. 4th Edition. Prentice Hall, NJ, 691 pp.

Gupta, S.K. and Deshpande, R.D. (2004). Water for India in 2050: First-order
assessment of available options. Current Science, 86(9): 1216-1224.

Jha, M.K., Chikamori, K., Kamii, Y. and Yamasaki, Y. (1999). Field investigations for
sustainable groundwater utilization in Konan basin. Water Resources
Management, 13: 443-470.

40
Kumar, R., Singh, R.D. and Sharma, K.D. (2005). Water resources of India. Current
Science, 89(5): 794-811.

Mall, R.K., Gupta, A., Singh, R., Singh, R.S. and Rathore, L.S. (2006). Water resources and
climate change: An Indian perspective. Current Science, 90(12): 1610-1626.

Rangarajan, R. and Athavale, R.N. (2000). Annual replenishable groundwater

potential of India: An estimate based on injected tritium studies. Journal of
Hydrology, 234(1&2): 38-53.

Richards L.A. (editor) (1968). Diagnosis and Improvement of Saline and Alkali Soils.
Handbook no. 60, US Salinity Laboratory Staff, USA, 160 pp.

Rodell, M., Velicogna, I. and Famiglietti, J.S. (2009). Satellite-based estimates of

groundwater depletion in India. Nature, 460: 999-1002.

Shah, T., Molden, D., Sakthivadivel, R. and Seckler, D. (2000). The Global Groundwater
Situation: Overview of Opportunities and Challenges. IWMI, Colombo, Sri
Lanka.

SCS (1985). National Engineering Handbook. Section-4, Hydrology, Washington D.C.

Sophocleous, M.A. (2005). Groundwater recharge and sustainability in the High Plains
aquifer in Kansas, USA. Hydrogeology Journal, 13(2): 351-365.

Subramanya, K. (2008). Engineering Hydrology. Tata McGraw-Hill Education Private

Limited, New Delhi, India, 434 pp.

Todd, D.K. (1980). Groundwater Hydrology. John Wiley & Sons, New York, pp. 64-110.

WHI (2002). User's Manual For AquiferTest. Waterloo Hydrogeologic Inc., Ontario,
Canada.

Zektser, I.S. (2000). Groundwater and the Environment: Applications for the Global
Community. Lewis Publishers, Boca Raton, Florida, 175 pp.

41