Engineering

1. • To avoid the water scarcity problems, it is very much important to understand
the whole process of River-Aquifer interactions because such interactions play
a vital role for providing important information regarding sustainable planning
and management of water resources.
• Despite the River-Aquifer interaction being a natural process, but it is very
difficult to understand the complex physical dynamic process involved in it.
• Several past studies show that and most of the researchers used physically
based mathematical models to know the exact situation of River-Aquifer
interactions process.
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2. SELECTED LITERATURE REVIEW
Sl.
NO.
TITLETITLE AUTHOR KEY FINFDINGS
1. A continental-scale
hydrology and water
quality model for Europe:
Calibration and
uncertainty of a high-
resolution large-scale
SWAT model
Abbaspour et al.
(2015)
• The use of large-scale, high-resolution water
resources model enables consistent comprehensive
examination of integrated system behaviour
through physically-based, data data-driven
simulation.
• Leaching of nitrate into groundwater is also
simulated at finer spatial level.
2. Development and
application of the
integrated SWAT-
MODFLOW model
Kim et al.(2007) • THE application demonstrates that an integrated
SWAT-MODFLOW is capable of simulating a
spatio-temporal distribution of groundwater
recharge rates, aquifer evapotranspiration and
groundwater levels.
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3. 3. Groundwater recharge
estimation using empirical
methods from rainfall and
streamflow record
Andualem et
al.,(2021)
• The study area has high groundwater recharge
volume which could be used for different
groundwater development projects.
• This study provides evidence for the groundwater
potential areas identified by using geospatial
methods.
4. Subsurface Drainage and
Storage Properties in the
Western Ghats - A Study in the
Basin of Netravati
Chaitra et
al.(2015)
• The study indicate that the surface soils are sandy,
while even at great depths, soils are Silty sands or
Sandy silts, with high porosities and low drainage
rates.
• The study interpreted to mean that preferential
pathways of macro-pores and soil piping would be
an important feature in these areas.
5. Assessing distributed
groundwater recharge rate
using integrated surface water-
groundwater modelling:
application to Mihocheon
watershed, South Korea
Chung et
al.(2010)
• The SWAT-MODFLOW model integrates
hydro(geo)logical processes of physical flow,
providing a more accurate representation of the
dynamic relationships between natural and
anthropogenic factors that control the SW and GW
of the region’s flow system.
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4. 9/25/2023 4
6. A QGIS-based graphical
user interface for
application and
evaluation of SWAT-
MODFLOW model
Park et
al.(2019)
• QSWATMOD includes options for using an existing
MODFLOW or creating a new one, with a variety of
options for linking MODFLOW river cells with SWAT
sub-basins for groundwater-surface water interactions.
7. Groundwater
connectivity of a sheared
gneissaquifer in the
Cauvery River basin,
India
Collins et
al.(2020)
• The study indicates a well-connected system, both
laterally and vertically, that has evolved with high
abstraction from a laterally to a vertically dominated flow
system. Likely as a result of shearing, a high degree of
lateral connectivity remains at low groundwater levels.
Because of their low storage and logarithmic reduction in
hydraulic conductivity with depth.
8. Long-term groundwater
recharge rates across
India by in situ
measurements
Bhanja et
al.(2019)
• The extensive plains of the Indus–Ganges– Brahmaputra
(IGB) river basins are subjected to prevalence of
comparatively higher recharge. This is mainly attributed
to occurrence of coarse sediments, higher rainfall, and
intensive irrigation-linked groundwater-abstraction
inducing recharge.

5. • Nowadays, one of the major problems in the developing countries like India is the
water scarcity which is due to the extensive extraction of groundwater for different
purposes like irrigation, drinking, industrial, etc.
• It has been reported that in many parts of the country, the water table is declining
at the rate of 1–2 m/year.
• Hence, quantitative estimation of the temporal and spatial variations in
groundwater storage (GWS) is critically important for the sustainable management
of water resources.
PROBLEM STATEMENT
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6. OBJECTIVES:
• To quantify water availability using (SWAT) and understand the surface and
groundwater interaction exchange pattern using water balance study.
• To study of water balance and groundwater recharges using a suitable model. In the
present case, the subsurface hydrological model, MODFLOW, has been used.
• To study the long-term trend analysis of the groundwater recharge.
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7. STUDY AREA:
FIGURE 3: Study Area
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8. • The Harangi river takes birth in the Pushpagiri hills near Somvarpet town in
the Kodagu district of Karnataka. The watershed is situated in the Western
Ghats, among the range of mountains known for its rich biodiversity and
ecological significance.
• The Harangi watershed lies between 75° 38' E and 75°55' E longitude and
12° 24' N and 12° 40' N latitudes.
• The Harangi river is a tributary of the Cauvery. The basin is located at an
average elevation of around 1170 meters. The catchment area of the river is
about 420 km2 and is 50 km long from its origin to the confluence with
the Cauvery.
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9. • The drainage pattern in the study area is
influenced by the lithology and the bed
rock or the geological structures.
• The geological formations of the study
area belong to the Archaean metamorphic
complex, comprising igneous and
metamorphic rocks and the major part of
the study area is covered by granitic
gneisses.
• The watershed receives its rainfall from
the southwest monsoon which brings
huge amount of precipitation to the
watershed.
Source: India Water Resources Information System
INDIA WATER RESOURCES INFORMATION
SYSTEM
FIGURE 4: Aquifer material and water level
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10. DATA
DATA RESOLUTION TIME PERIOD SOURCE
DEM 30m - USGS SRTM
LULC 30m - ESRI
SOIL - - FAO
Precipitation 0.25◦*0.25◦ 1995-2018 IMD PUNE
Temperature 1◦*1◦ 1995-2018 IMD PUNE
Observed
Streamflow
- 1995-2018 WRIS
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Table 1 Data used in SWAT

11. • Aquifer characteristics : Aquifer properties such as hydraulic
conductivity, porosity, specific storage and specific yield were obtained
from CGWB website and also from literature. (Satish et al.,2020 and
Anusha et al.,2020).
• Initial groundwater head : The initial heads or the starting head are
required and it was taken from WRIS website.
• Riverbed Conductance : The Riverbed Conductance is defined as the
hydraulic conductivity of the bed material of the river divided by the
vertical thickness (it is the length of travel based on vertical flow) of the
river bed materials, multiplied by the area (width times the length) of the
river in the cell.
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12. METHODOLOGY
Simulation and Calibration of SWAT-MODFLOW
START
Constructing MODFLOW
Constructing SWAT
DEM
Aquifer thickness
Hydraulic conductivity
Specific storage
Initial GW head
DEM
Soil data
LULC
Precipitation
Temperature Calibrating SWAT Calibrating MODFLOW
Simulating SW at HRU level Simulating GW at grid level
Linking SWAT and MODFLOW using QGIS
Deep percolation(recharge)
Grid discharge
Water table
Results(R2, NSE, RMSE)
Comparing simulated and
observed streamflow
Comparing simulated and
observed water head
Inputs
Inputs
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13. • SWAT is a river based or watershed , scale model to predict the impact od land
management practices on water, sediment and agricultural chemical yields and
large, complex watersheds with varying soils, land use and management
conditions over a long period of time.
• The SWAT model is calibrated and validated with streamflow of 22 years
duration. The warm-up period for this model is 2 years and it is from 1995 to
1996. The calibration period for the model is from 1997 to 2012 and the
validation period is from 2013 to 2018.
• The model gives the simulated value of streamflow and for sensitivity analysis
of the parameters, SWAT-CUP was used.
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14. • The governing groundwater flow equation is in finite difference form (which is
based on Darcy’s law and the conservation of the fluid mass equation) is given in
Eq. 1.
𝜕
𝜕𝑥
𝐾
𝜕ℎ
𝜕𝑥
+
𝜕
𝜕𝑦
𝐾
𝜕ℎ
𝜕𝑦
+
𝜕
𝜕𝑧
𝐾
𝜕ℎ
𝜕𝑧
= 𝑆𝑠
𝜕ℎ
𝜕𝑧
+ 𝑤 𝑥. 𝑦. 𝑧. 𝑡 (1)
• The model was discretized into grids into 500 * 500 using conceptual approach.
The state of simulation was steady state simulation of groundwater flow.
• The average value used on the basis of literature for different parameters used in
the study area are: Kx (Horizontal hydraulic conductivity) = 0.132 m/d; Ky
(Vertical hydraulic conductivity) = 0.1512 m/d; n (Porosity) = 0.3; Specific
Storage = 0.0015 m-1 and Specific Yield = 0.33. (Anusha et al., 2020)
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15. • The last part is to interlink SWAT and MODFLOW model using shapefiles for the
river network, subbasins, and HRUs from the existing SWAT model and the
MODFLOW model using QGIS.
• Through the linking process the HRUs are disaggregated to create DHRUs. Then
interlinking in QGIS includes three parts.
(i) pre-processing modules to prepare input data for model execution,
(ii) configuration modules for SWAT-MODFLOW options i.e., the simulation, and
(iii) post-processing modules to view and interpret model results.
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Fig.7 Scatter plot of observed and simulated discharge for the calibration period (1997-2012)

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Fig.8 Comparison of observed and simulated discharge for validation period (2013-2018)

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• The coefficient of determination (R2) and (NSE) Nash Sutcliffe efficiency for
the streamflow for the calibration period (1997 - 2012) are 0.74 and 70 %
respectively.
• The coefficient of determination (R2) and (NSE) Nash Sutcliffe Efficiency for
the streamflow for the validation period (1997 - 2012) are 0.68 and 65 %
respectively.

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Fig.10 Monthly groundwater recharge variation for the study period

20. CONCLUSIONS
• The hydrological SWAT model is setup and calibration and validation are done for
the time period for streamflow. The monthly discharge time series is plotted and it
was found that total six parameters are sensitive for the study area.
• The study area is mostly covered with forest and range grasses and brush land.
• The monthly groundwater recharge in the month of February, March, April, May
and June are less compared to other months.
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21. • The annual groundwater recharge is highest in the year 2012 and it is equal to
6891.65 mm. The annual variation graph of recharge shows that from the year
1997 to the year 2018, there is a 32.7% increase in groundwater recharge in study
area.
• The percentage increase of groundwater recharge in pre-monsoon, monsoon and
post-monsoon from the year 1997 to 2018 are 11.6%,51.11% and 33.77%
respectively.
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22. SELECTED REFERENCES
• Abbaspour K C,E. Rouholahnejad, S. Vaghefi, R. Srinivasan, H. Yang, B.
Kløve, A continental-scale hydrology and water quality model for Europe:
Calibration and uncertainty of a high-resolution large-scale SWAT model,
Journal of Hydrology, Volume 524, 2015, Pages 733-752,
https://doi.org/10.1016/j.jhydrol.2015.03.027.
• Andualem, T.G., Demeke, G.G., Ahmed, I., Dar, M.A., Yibeltal, M., 2021.
Groundwater recharge estimation using empirical methods from rainfall and
streamflow records. J. Hydrol. Reg. Stud. 37, 100917.
https://doi.org/10.1016/j.ejrh.2021.100917
• Bhanja, S.N., Mukherjee, A., Rangarajan, R., Scanlon, B.R., Malakar, P.,
Verma, S., 2019. Long-term groundwater recharge rates across India by in
situ measurements. Hydrol. Earth Syst. Sci. 23, 711–722.
https://doi.org/10.5194/hess-23-711-2019
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23. • Chaitra, Yadupathi Putty, M.R., Prasanna, H.S., 2015. Subsurface Drainage
and Storage Properties in the Western Ghats – A Study in the Basin of
Netravati. Aquat. Procedia 4, 617–624.
https://doi.org/10.1016/j.aqpro.2015.02.080
• Chung, I.-M., Kim, N.-W., Lee, J., Sophocleous, M., 2010. Assessing
distributed groundwater recharge rate using integrated surface water-
groundwater modelling: application to Mihocheon watershed, South Korea.
Hydrogeol. J. 18, 1253–1264. https://doi.org/10.1007/s10040-010-0593-1
• Kim, N. W., Chung, I. M., Won, Y. S., & Arnold, J. G. (2008).
Development and application of the integrated SWAT-MODFLOW model.
Journal of Hydrology, 356(1–2), 1–16.
https://doi.org/10.1016/j.jhydrol.2008.02.024
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24. • L. Collins, S., Loveless, S. E., Muddu, S., Buvaneshwari, S.,
Palamakumbura, R. N., Krabbendam, M., Lapworth, D. J., Jackson, C. R.,
Gooddy, D. C., Nara, S. N. V., Chattopadhyay, S., & MacDonald, A. M.
(2020). Groundwater connectivity of a sheared gneiss aquifer in the
Cauvery River basin, India. Hydrogeology Journal, 28(4), 1371–1388.
https://doi.org/10.1007/s10040-020-02140-y
• Park, S., Nielsen, A., Bailey, R. T., Trolle, D., & Bieger, K. (2019). A
QGIS-based graphical user interface for application and evaluation of
SWAT-MODFLOW models. Environmental Modelling and Software, 111,
493–497. https://doi.org/10.1016/j.envsoft.2018.10.017
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25. THANK YOU
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