Remote sensing and GIS techniques can contribute significantly to groundwater modeling efforts. Remote sensing provides spatial data on land cover, vegetation, rainfall, and terrain that are important model inputs. GIS allows integration of diverse data layers, conceptualization of recharge/discharge areas, and output visualization. However, remote sensing has limitations, such as an inability to directly measure groundwater levels or recharge. Overall, combining remote sensing, GIS, and field data can improve conceptual models and produce more accurate modeling results for groundwater management.

1. Application of remote sensing
and GIS for groundwater
modeling
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2. What is Remote Sensing?
“The science and art of obtaining information about an object, area, or
phenomenon through the analysis of data acquired by a device that is
not in contact with the object, area, or phenomenon under
investigation”
Remote sensing is the science (and to some extent, art) of acquiring
information about the Earth's surface without actually being in contact
with it( Lillesand & Kiefer,2004)
This is done by sensing and recording reflected or emitted energy and
processing, analyzing, and applying that information
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3. What is GIS?
• A system for capturing, storing, checking, integrating, manipulating,
analyzing and displaying data which are spatially referenced to the
earth
• This is normally considered to involve a spatially referenced computer
database and appropriate applications software
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4. What is ground water modeling?
• A conceptual model is a schematic, simplified representation of a
‘real-world’ system
• A tool that can analyze many groundwater problems
• Hard copy or digital projection of a flow system using cross-sections
and/or 2D maps, eventually 3D distributions of various model input
components which helps to understand and build up the conceptual
model based on data from various sources
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5. • groundwater modelling is an important tool for groundwater
management because,
1.the effects of exploitation of aquifers can be simulated
2.effects of climatic change on the groundwater resource
3.the fate of groundwater pollution
can be identified
The models require spatial data input and in many regions such data
is scarce
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6. GIS for modeling
• As the geographical location of every item of information stored in a
GIS is known, GIS technology makes it possible to relate,
• the quality of groundwater at a site with the health of its inhabitants
• to predict how the vegetation in an area will change as the irrigation
facilities increases
• to compare development proposals with restrictions on land use
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7. • The data for the development of numerical groundwater flow model
includes time-constant parameters and time-variant parameters.
The time-constant parameters were mainly extracted from thematic
data layers generated from GIS and image processing of remote
sensing data.
Time Constant Parameters
• Aquifer geometry (areal and
vertical distribution of
subsurface strata, aquifer
thickness etc.). It also requires
river network, land cover, soil,
surface and subsurface
hydrological data input
• Hydraulic parameters
Time Variant Parameters
• Hydro-meteorological data
• Water level monitoring data
• Number, distribution and
pumpage from
irrigation/drainage tube wells
• River and canal flows and
hydraulic features
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8. Advantages of GIS application in groundwater
modeling
• GIS provides decision support for groundwater management
• GIS saves much time
• GIS can handle large datasets
• With GIS, complex maps can be created and edited much faster
• GIS can utilize a satellite image to extract useful information
• GIS has capability to integrate with many hydrological models and
techniques, and transform spatial data according to the modeling
requirements(Ashraf & Ahmad,2008).
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9. Major steps
• Application of GIS technology to hydrological modeling requires
careful planning and extensive data manipulation work
• In general, the following three major steps are required:
1.Development of spatial database
2.Extraction of model layers
3.Linkage to computer models
(Anderson & Woessner,1992).
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10. GIS functions involved groundwater flow
modeling
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11. GIS functions involved groundwater flow
modeling
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Table 1. GIS functions involved in different phases of groundwater flow modeling

12. • The groundwater models output may include:
water pressure (head) distribution
flow rates
flow directions
plume movement and particle tracking
water chemistry changes and budgeting
Integration of GIS and hydrologic models follows one of the two
approaches;
a) To develop hydrologic models that operate within a GIS framework
b) To develop GIS techniques that partially define the parameters of
existing hydrologic models (Jain et. al., 1997).
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13. • In most of groundwater modeling software such as,
Feflow
Modflow
GMS
there is an interface that links vector data through
compatible GIS formats - i.e. .shp, .lin, .dxf etc.
and raster data formats - i.e. .tif, .bmp, .img etc.
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14. Remote Sensing for modeling
• The RS data are cost effective as a primary data source
• There are many types of remote sensing techniques, which differ in
their applicability to groundwater modelling
• provides a valuable source of data contributing to the setting up of
groundwater models
• Space-borne and/or air-borne images are an inexpensive
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15. • Ground-based remote sensing (i.e. geophysics) is usually more
expensive
• But more accurate and still cheaper than invasive methods
• RS data can be imported into modelling environments in,
1.original form
2.processed form
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16. Types of modeling environments
• Complex software modelling environment-GMS
• Less sophisticated modelling environments- PMWIN
• Remote sensing data transfer to a modelling package is dependent upon the
type of software modelling environment
• Move all relevant, point, vector and raster data into the modelling environment
• All the remote sensing data is rather pre-processed in the GIS environment and
then the output is interactively (by import-export options) linked to the
modelling environment
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17. Steps for modelling using RS
• Model grid
• Setting model boundaries
• Spatial input data (model parameters)
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18. 18
Fig 1 :Numerical model grid build over the integrated image of Landsat TM false
colour composite (bands 4, 7, 1)

19. Potentiometric surface (hydraulic head)
• Remote sensing methods have little to offer for measurement of
heads with high precision
• However, field observations of piezometric levels may be expensive
• Ground penetrating radar (GPR) seems to be the most suitable
geophysical tool for efficient groundwater table depth assessment
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20. Evapotranspiration
• Discharge of groundwater (also in groundwater models) can take
place not only by outflow from the aquifer (Qg) but also by
groundwater evapotranspiration (ETg)
• So far there is no direct way to estimate
ETg or
ET
from Remote Sensing
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21. Groundwater recharge
• Recharge (R) is the amount of water that reaches the groundwater
table
• Rn = R- ETg
• Groundwater recharge is probably the most difficult and often the
most uncertain data type used in groundwater modelling
• There is as yet no remote sensing based method to evaluate recharge
directly in a quantitative way
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22. However, the RS and GIS methods can contribute to recharge assessment at least
indirectly through:
1.Scaling up recharge assessed with other methods using GIS modelling
(Lubczynski and Gurwin 2005;Shaban, 2006)
2.GIS-based solution of water balance with some input of RS technique (e.g.
vegetation)
3.RS-based assessment of P and ET followed by spatial mapping of P-ET
further used for scaling up chloride based recharge estimates (Brunner et
al., 2004)
4.Stochastic modelling of the P-ET using recharge measurements as
modelling reference (Hendrics-Franssen,2006)
5.RS-based determination of soil moisture applied as input for unsaturated
recharge models (e.g HYDRUS)
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23. Contribution from sinks and sources
• Sinks and sources are known in groundwater modelling protocol as
man-driven water losses or additions from or to the aquifer system
• Sinks of groundwater are not detectable with remote sensing
• Remote sensing cannot contribute to well management but can
attempt to control irrigation losses in space and in time.
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24. River discharge in ungauged catchments
• River discharges, particularly river base flows, are critical for
reliable modelling
• field surveys (including spot measurements, visual observation
and enquiring), hydrological simulation modelling or by
regionalization methods
• Remote sensing techniques provide substantial data input (e.g.
land cover, vegetation density, rainfall, DEM data and derivatives)
for such models
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25. Conclusion of RS for Modelling
• Numerical groundwater modelling is an important tool for
groundwater management, because the effects of
exploitation of aquifers can be simulated, but also effects
of climatic change on the groundwater resource and the
fate of groundwater pollution.
• The models require spatial data input and in many regions
such data is scarce.
• Remote sensing can provide a part of the input, especially
when data from geological and hydrogeological surveys
and from geophysical surveys, airborne or on the ground
are included.
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26. Conclusion of RS for Modelling
• The major steps in setting up a groundwater model is starting
with defining the conceptual model
• Transient modelling is even more data intensive because time
series are needed. To some degree remote sensing can assist in
such data acquisition, such as groundwater evaporation using
satellite data
• However, limitations are mentioned such as the measurement of
piezometric levels
• The RS data of high spectral and spatial resolutions would be
helpful in reliable assessment of landcover/landuse and
identification of potential recharge/discharge areas that could
ultimately enhance the quality of groundwater modeling results
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27. Conclusion for GIS for Modelling
• GIS application has provided help in an accurate and manageable way
of estimating model input parameters, integration of disparate data
layers, conceptualizing of model recharge and discharge sources and
visualization of the model output
• GIS-based modeling also provides an updated database that can be
used for non-modeling activities such as water resource planning and
facilities management
• The developed model would thus provides a decision support tool for
evaluating better management options for sustainable development
of land, surface and groundwater resources on micro as well as on
macro levels in future
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28. References
• Lubczynski, M.W. and Gurwin, J. 2005. Integration of various data
sources for transient groundwater modelling with spatio-temporally
variable fluxes—Sardon study case, Spain. Journal of Hydrology, Vol.
306(1–4), pp. 1–26.
• Brunner, P., Bauer, P., Eugster, M. and Kinzelbach, W. 2004. Using
remote sensing to regionalize local precipitation recharge rates from
the chloride methods. Journal of Hydrology, Vol. 294(4), pp. 241–50.
• Hendricks-Franssen, H.J.W.M., Brunner, P., Kgothlang, L. and
Kinzelbach, W. 2006. Inclusion of remote sensing information to
improve groundwater flow modelling in the Chobe region. IAHS,
ModelCARE (Redbook series).
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29. • Anderson, M. P. and Woessner W. W. (1992) Applied groundwater
modeling simulation of flow and advective transport. Academic Press.
• Arshad Ashraf and Zulfiqar Ahmad (2012). Integration of
Groundwater Flow Modeling and GIS, Water Resources Management
and Modeling, Dr. Purna Nayak (Ed.), ISBN: 978-953-51-0246-5
• Lillesand, T.M., Kiefer, R.W. and Chapman, J.W. 2004. Remote Sensing
and Image Interpretation 5th edn. John Wiley & Sons.
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