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GIS for Aquifer Monitoring and Modeling - From Field Surveys to Simulation Models: A case study of Kaluvelly Pondicherry basin, South India

The method chosen for contour mapping is the Natural Neighbour Interpolation Technique. The Natural Neighbour method is a technique based on geometric parameters that uses area-weighting regions generated around each point of the sample data set to determine new values for every grid node. A network of centroid is created from the input data set by connecting edges from adjacent points. From this generated area for each data point, new values are assigned to the overlying grid cells. The new grid value is calculated as the average of the surrounding point values proportionally weighted according to the intersecting area of each point. This method is very effective for interpolation of geographic data showing a clustered spatial distribution. It gives the best results for our project according to the input data type and the results expected from the model. This interpolation technique is particularly appropriate to the methodology followed here, where results are re-calibrated by the user. As it is based on geometric parameters, it allows the user to directly give orientation to the results by working on the input data points.

The output grid cell size is defined according to data entry resolution and results expected from the study. A resolution of 100 meters is selected, as it is the highest resolution of the data spatial distribution. A high resolution will allow the transfer of a 2D model to a 3D model without loosing accuracy in the process. The vertical resolution is in centimeter range thanks to the GIS interpolation tools and precise original set of points. Results of decimeter accuracy are expected for the hydrological study. Accuracy is higher in areas where the density of samples is more important, mainly for the upper layers of the aquifer system. For the deeper formations, less data were available, as few very deep bore wells have been drilled. However, for the deeper formation, according to the depth and thickness of the formation, a larger margin error can be tolerated. The top of the upper layers are generated from the outcropping spread areas marked on the surface geological map, together with altitude data imported from the Digital Elevation Model. The whole sedimentary series has a 2 to 5% slope directed to the sea, following a North-West to South-East inclination. The sedimentary beds dip and thicken towards the sea, and towards the south.

3D Modeling and aquifer capacity calculation

The results of the surface contour mapping of the bottom of the geological formations are the base used to build the 3 dimensions model. The 2D layers created in GIS can be converted to 3D layers. The result will be 3D layers of the formations showing their geometry and structure. The extent, the depth, thickness, and spatial variations of the geological layers can then be analyzed and studied.

The model is built by exporting data from the contour layers, at a predefined resolution. The 3D model is created by using a triangulation method from a regular and dense grid of points. The accuracy of the triangulated features relies on the grid spatial resolution, as well as on the precision of the elevation attribute data. It is here needed to mention that for computer processing, higher resolution grids require a good memory capacity to run the application, and limited systems may face difficulties to apply such parameters in their GIS. Resolution can therefore be re-defined following this constraint.

Over the whole Pondicherry basin, a particular area corresponding to the first aquifer of the region is targeted for a capacity evaluation. This top aquifer with the largest natural recharge area, namely Cuddalore sandstone, is studied more in depth to estimate its capacity. The 3D model allows direct volume calculation for a well defined area, using values of the top and bottom depths of the aquifer. In this case, the aquifer top corresponds to the ground surface as it is outcropping on a large extent. The same work is then overtaken to calculate the volume of the water saturated part of the aquifer, according to the water table measurements. This is done by entering water level values and generating the equivalent model. (FIGURE 5 and 6)

For a targeted area of 135 Sq.km, the volume of the Cuddalore sandstone formation is about 8,425 Million Cubic meters. With an average water table about 20 meters below mean sea level, the volume of this aquifer is about 5,550 Million Cubic meters. Finally, porosity parameters are applied to estimate the actual groundwater potential for the same selected area. For a volume of 5,550 Million Cubic meters, the aquifer capacity is about 830 Million Cubic meters for a porosity index of 15 %, and 1110 Mcum for a porosity index of 20%. These results can then be analyzed together with the groundwater extraction reports generated from the GIS database.

Conclusion

In this project, all thematic quantitative and qualitative data collected are part of an integrated database structured in a GIS. The administration of such a hydro geological database is an advanced and suitable tool for identifying existing problems, and searching adequate solutions for a better integrated water management. The result is an effective tool for groundwater analyses, with the possibility to generate scaled maps and cross sections for any particular studied area. By locating a point by GPS, the model is able to give a report on the geological patterns for this location up to 500 meters depth.

The resulting scientific assessments are for an important part based on the accuracy of the data processed. For a project at this particular scale, a huge amount of detailed data has been gathered and processed. This project has been able to set up an interactive database, which can be easily updated regularly, creating a direct link from the ground situation to the planning stage. The strength of the GIS is also its flexibility. The methodology followed here made use of combined automatic computer processing together with standards scientific methods for geological mapping. For the whole processing, from the field surveys to the modeling, different GIS packages have been used, according to their capacity to overtake every specific task. The GIS user has been mastering the complete processing work, from planning the data collection on the field and designing the database, to the spatial analyses. The next step will be to go further in hydro geological modeling by transferring GIS data to other professional specialized platform for advanced simulations.

One can see, through the results of the project, that the investments put by local agencies to collect data and process it themselves, allows the objectives to be realized, and also helps to build up a solid basis for long term GIS investigations and management. This process involving local agencies, and local communities to a minor extent, helps them to build up their capacities and knowledge and prepare valuable reports for decision making and planning. Knowledge and awareness will act as a key of empowerment and own governance for the different stake holders. Thanks to the emphasis put on research and development, the Pondicherry Kaluvelly basin is part of the UNESCO Hydrology for Environment Life and Policy (HELP) Basin Program.

REFERENCES:

Vincent A., Violette S., Marsilly G. DE, Boulicot G., Jorcin P., Krishnamurthy R.S., Sivasubramaniam K. (2006) “Infiltration quantification at the watershed scale using hydrological models, in a semi-arid context (Kaluvelly-Pondicherry coastal sedimentary basin, Pondicherry territories and Tamil Nadu state, India)”, European Geosciences Union General Assembly, Vienna, comm.
Vincent A., Violette S., Krishnamurthy R.S., Sivasubramaniam K., Jorcin P., Boulicot G. (2004), “Preliminary report on the hydro geological study of the Kaluvelly-Pondicherry coastal sedimentary basin (Pondicherry territories and Tamil Nadu state, India) HELP – Project”, In Progress Report program UNESCO HELP, 31 p.
Gassama N., Violette S., D’Ozouville N., Dia A., Jendrzejewski N. (2003), “Multiple origin of water salinization in a coastal aquifer in the bay of Bengal”, WOM, New Delhi, comm.
Gassama N., Violette S., D’Ozouville N., Dia A. (2002), “ Multiple origin of salinization in a coastal aquifer, South India, geochemical point of view”, Geochemica and Cosmochemica Acta 66(15A), pp. 265.
Violette S., Gassama N., Jendrzejewski N. (2001), “Coastal aquifer in the bay of Bengal – Is water salinization due to sea water intrusion or does it have multiple origin?” Proceeding of 1st international conference on salt water intrusion and coastal aquifers, Essouira, Morocco, 4p.