Subsurface Lithology
In most of the cases the top layer resistivity ranges from 5.0 ohm-m to 45.0 ohm-m with thickness varying from 1.0 m to 2.0 m which indicates the variable nature of surface soil (loose and moist, dry and hard). The second layer is predominantly clay / clay with kankar and is characterised by resistivity range of 4 .0 ohm-m to 23.0 ohm-m depending upon the proportion of constituents, its thickness varies between 1.0 m to 46.0 m . The third layer with resistivity ranges from 30 ohm-m to 110 ohm-m indicates the weathered / fractured sandstone which is water bearing and forms the aquifer zone in the area. The thickness of aquifer zone varies between 2m to 39m . Depth to the hard rock having very high resistivity in general, (compact & massive, occ. fractured sandstone) varies from 9m to 66m below ground surface. VES locations and details of the drilling results and layer parameter of representative sites are shown in fig. 1 and fig. 6.

From the above inferred lithology & their thickness clay (top impermeable layer) thickness and aquifer thickness maps were prepared (fig. 7, 8).

Integration of thematic layers and modelling through GIS
As discussed in earlier sections, each one of the classes in thematic layers was qualitatively placed into one of the following categories, viz. (i) very good, (ii) good, (iii) moderate and (iv) poor depending on their ground water potential level. After understanding their behavior with respect to groundwater control, the different classes were given with suitable weights, according to their importance with respect to other classes in the same thematic layer. The weights assigned to different classes of all the thematic layers are given in table 1. To cite an example, the maximum weight assigned for the aquifer thickness was 4 for thickness greater than 25m, whereas the lowest value of 1 was assigned to thickness less than 5m. On the other hand, in a hydrogeomorphology layer, a maximum weight of 3 was assigned for BPP-M and a minimum weight of 1 for DPT.

The thematic layers which include hydrogeomorphology, lineament, slope, aquifer thickness and clay thickness were converted into grid with related item weight and integrated with one another through GIS (Arc / Info grid environment). As per this analysis, the total weights of the final integrated grids were derived as sum of the weights assigned to the different layers based on suitability (ESRI 1997).

In the present study, the delineation of groundwater potential zones was made by grouping the grids of the final integrated layer into different potential zones ; very good, good, moderate to good, moderate and poor. Instead of just dividing the maximum and minimum values into different categories, which does not have any logical reasoning, a model has been developed using relevant logical conditions. Table 2 gives the way in which the upper and lower limits of the weights derived for demarcation of the groundwater prospecting areas. Theoretically, the upper weight of 17 can be possible, and derived by combining all the upper categories in all layers. However, in the study area, 16 was the highest value obtained.

The areas which are very good for groundwater prospects were delineated by grouping the grids which have weight between 13 to 16 in the final integrated layer. The upper limit of the weight was derived by good category of hydrogeomorphology and very good category in all other layers. The lower value was derived by good category of hydrogeomorphology, aquifer thickness, slope, and clay thickness, without the presence of lineament.

The grid which comes under good category were obtained by grouping grids having weights between 11 to 12. The lower weight 11 was derived from the combination of good category of hydrogeomorphology and clay thickness and moderate category of aquifer thickness and slope without presence of lineament.

The moderate to good category potential groundwater zones involve grids which have weights from 9 to 10. The lower value of this category was derived by adding the good category of hydrogeomorphology and moderate categories of aquifer thickness, and clay thickness and poor category of slope with the absence of lineament.

Moderate groundwater potential zones were delineated by grouping the grids which have weights from 7 to 8. The lower value of this category was derived by the combination of a moderate categories of hydrogeomorphology, aquifer thickness and poor categories of clay thickness and slope without the presence of lineament.

All other grids which have less than 7 weight, were grouped as a poor category. The lowest weight 5 was obtained in the study area. By utilising the above discussed model a map showing different groundwater potential zones was prepared (fig. 9).

Model Evaluation and Results
The validity of the model developed was checked against the bore well yield data which reflects the actual groundwater potential. Table 3 shows that groundwater potential zones prepared through this model have in good agreement with yield data. Yield of drilled sites occurred in this model have ranges from 162 to 639 lpm in very good zone, 135 to 225 lpm in good zone, 135 to 145 lpm in moderate to good zone and less than 100 lpm in moderate zone.

Conclusion
In order to delineate the groundwater potential zones, in general ,different thematic layers viz: hydrogeomorphology, lineaments, and slope, are used to be integrated without considering subsurface lithology .This provides a broad idea about the groundwater potentiality of any area. Presently, groundwater potential zones have been demarcated by integration of aquifer thickness and clay thickness derived from surface electrical resistivity survey and drilling data with above thematic layers, using a model developed through GIS technique.

The groundwater potential zones map generated through this model was verified with the yield data to ascertain the validity of the model developed and found that it is in agreement with the bore wells yield data. This illustrates that the approach outlined has merits and can be successfully used elsewhere with appropriate modifications. The above study has demonstrated the capabilities of using remote sensing, geoelectrical data and Geographical Information System for demarcation of different ground water zones, especially in diverse geological setup. This gives more realistic groundwater potential map of an area which may be used for any groundwater development and management programme.

Acknowledgement
The authors are gratefully to Dr. A.N. Singh, Director, RSAC-UP, Lucknow for his kind permission to undertake this study. The authors wish to acknowledge the help and suggestion of Dr. A.K. Tangri, Scientist-SF & Technical Secretary to Director, RSAC-UP.

References

• Central Ground Water Board, (CGWB), 1985, Report on hydrogeology and groundwater potential of Mirzaupr district U.P.
• Environmental System Research Institute (ESRI), 1997 user guide Arc / Info : The geographic Information System Software, (Redland, CA :ESRI, Inc).
• K.S.R. Murthy, 2000, Groundwater potential in a semi-arid region of Andhra Pradesh : A geographical Information System approach, International journal of Remote Sensing, Vol. 21 No. 9, 1867-1884.
• Krishnamurthy, J. Venkataesa Kumar, N, Jayraman, V. and Manivel, M. 1996 : An approach to demaracate groundwater potential zones through Remote Sensing and GIS. International Journal of Remote Sensing, 17, No. 10, 1867-1884.
• Moore, G., and Waltz, F.A. 1986, Objective procedure for lineament enhancement and extraction, photogrammetric Engineering and Remote Sensing, 49, 641-647.
• Saraf, A.K. and Chaudhary, P.R., 1998: Integrated remote sensing and GIS for groundwater exploration and identification of artificial recharges sites, International Journal of Remote Sensing, Vol. 19, No. 10, 1825-1841.