Briz-Kishore (1990) reported that wells located on flat uplands have yield higher than those located on the middle slopes. Therefore, analysis of all the above ...
GIS Integration of Remote Sensing and Topographic Data Using Fuzzy Logic for Ground Water Assessment in Midnapur District, India Shamsuddin Shahid Department of Applied Physics & Electronics Rajshahi University, Rajshahi-6205, Bangladesh
Sankar Kumar Nath Department of Geology & Geophysics Indian Institute of Technology, Kharagpur-721 302, India
A.S.M. Maksud Kamal Department of Geology Dhaka University, Dhaka-1000, Bangladesh
Abstract A GIS based approach is proposed for the integration of three thematic maps viz. geomorphology, drainage density and slope using fuzzy logic for the assessment of ground water resource potential of a soft rock terrain of Midnapur District, West Bengal, India. The geomorphology and drainage density maps of the area are prepared from IRS-1B LISS-II data, and the slope map is obtained from the contours depicted on the topographic map of Survey of India. Each feature of all the thematic maps is assigned with individual fuzzy set values within a range between 0 to 1 according to their relative importance in the prediction of ground water occurrence. The maps are then integrated through fuzzy operation to model the ground water potential zone of the study area. The evolved model while verified with surface geophysical results is found to be in good agreement.
Introduction Geomorphology, drainage density and slope are the most important surficial indicators of ground water occurrence of a soft rock area. According to Brown (1996). geomorphology deals with land formation, its mode of occurrence and material composition and thereby defining its ground water prospect. Sander (1998) described the drainage of an area as an important clue of ground water occurrence. Venkateswara Rao and Briz-Kishore (1990) reported that wells located on flat uplands have yield higher than those located on the middle slopes. Therefore, analysis of all the above three factors in an integrated way can provide a better model of ground water resource potential of an area by reducing the uncertainty in the individual data sets. Geographic lnformation System (GIS) is a tool which is widely used for efficiently capturing, storing, updating, manipulating, displaying and analyzing a large volume of spatial and attribute data. It can be effectively used in the integration of multiple data sets indicating the probable ground water potential. In the present study, a GIS integration of geomorphology, drainage density and slope maps using fuzzy logic is proposed for the assessment of ground water Geocarto International, Vol. 17, No. 3, September 2002 Published by Geocarto International Centre, G.P.O. Box 4122, Hong Kong.
potential of a soft rock terrain of Midnapur District. West Bengal, India. The geomorphological and drainage density maps of the study area are prepared from remote sensing data. IRS-IB, LISS-II data is used for this purpose. The slope map, on the other hand, is prepared from the contours depicted on the topographic map of Survey of India. The features of all the thematic maps are assigned with an individual fuzzy set value within the range of 0 to 1. The thematic maps are then integrated using fuzzy AND operation to generate the map of ground water potential. The evolved model is verified with the surface geophysical data. A total of twenty-two Vertical Electrical Soundings (VES) are conducted at different sites of the area. The inverted layer parameters which indicate the spatial variation of ground water prospect of the area are found to be in good match with the evolved GIS based model.
Study area The study area in Midnapur District (figure 1) is situated on a mild topographic high with an average annual rainfall of 152 cm and temperature of 31°C. The area is covered mainly 69
Figure 1 Location map of the study area in Midnapur District, West Bengal, India.
by three types of lithology (Shahid et al., 1999a) viz. Laterite, older alluvium and newer alluvium. Adequate water supply, particularly during summer, has always been a problem in the area. In view of necessary augmentation of present water supply, a 535 km2 area around Kharagpur and Midnapur towns is selected for the proposed study.
Preparation of thematic maps All the thematic maps are prepared in the 1:50 000 scale with a spatial accuracy of 0.1 km2. The preparation of different thematic maps is described below: Geomorphology: A hybrid False Colour Composite (FCC) of the first three principal components of IRS-1B LlSS-II image is used for the preparation of the geomorphological map of the study area. On the basis of physiographic characteristic, the landforms are classified into seven geomorphic units. The geomorphic boundaries are digitized on the enhanced image through GIS and the geomorphology thematic map is prepared as shown in figure 2(a). Various landforms, their importance in ground water occurrence and distribution are discussed below. (i) Hardcrust of Laterites: The hardcrust of Laterite occurs as patches in the study district with a thick plantation of ‘Sal’ trees (Soren robasta). They can he identified on the satellite image by a bluish red tone and coarse texture. Ground water in this formation generally occurs under the water table and is recharged directly by the percolation of surface water through pores and fractures of the crust of Laterite. The water 70
table has a very high seasonal variation. In summer it recedes up to 6 m. Bulk water supply is, therefore, not possible from this formation (Ray and Dutta, 1972). (ii) Mottled clay of Laterites: This formation occurs around the hardcrust Laterite with a smooth surface. On the satellite image it can be identified by a greenish tone and fine to medium texture. This is completely devoid of fluvial landforms and moderately cultivated. Ground water condition of this geomorphic unit is very similar to that of the hard crust Laterite (Ray and Dutta, 1972). (iii) OIder deltaic formation: Older deltaic formation occurs at a level lower than the Laterite upland. The fluvial landforms are obscured and discontinuous due to the prolonged erosion and pedogenic processes. On the satellite image it can be recognized by a reddish tone and fine texture. Aquifers in older deltaic formation are semiconfined in nature. Ground water prospect varies from place to place. (iv) Older filled valley cuts: This formation comprises of valleys carved on the Laterite, whose walls are generally formed by the mottled clay. Due to the subsequent rise of the base level, the valley cuts on the Laterite upland were filled up by the younger sediments equivalent to the older deltaic formation. The valley tills generally maintain the level of the older deltaic formation with which they merge. It can be identified on the satellite image by light green tone and medium texture. Though the seasonal variation of water table in this formation is minimum, it is not suitable for bulk water supply due to its limited areal extent. (v) Younger deltaic formation: The Younger deltaic
formation is built by forerunners of the river Kasai. It occurs at a level lower than the older deltaic formation and sculptured by many fluviatile landforms. In the satellite imagery younger deltaic formation can be recognized by a bluish tone and medium to coarse texture. Ground water in this formation mainly occurs in the water table condition. A prolific water supply is possible from this formation (Roy and Niyogi, 1961). (vi) Younger filled valley cuts: This valley cuts occurring on older deltaic formation is filled by younger sediments. The valley cuts are very small and narrow and can be distinguished on the satellite image by the same feature as used for the younger deltaic formation. High yield of ground water is not possible from this formation. (vii) Recent deltaic formation: The Recent sediments are generally confined to the present day channels and their immediate vicinity. The landforms over this formation are very fresh and comprise light colored loose sediments. It can be recognized on the satellite image by a light yellow tone and fine texture. Aquifers in this formation are interconnected and can act as excellent source of ground water supply.
the elevation contours of topographic sheet No. 73N/7 and 73N/3 of Survey of India in a 231.25 m × 231.25 m grid. The grids are classified according to the percentage of slope following the DRASTIC (Aller et al., 1987) slope classes. The generated thematic map of slope is given in Figure 2(c). This map shows that most of the area is almost flat with a slope less than 1%.
Integration and modelling In ground water potential investigation, certain factors are more
Drainage: The drainage density Dd is expressed in terms of km km-2: indicating the closeness of spacing of channels of an area. It can be calculated from drainage network by using Horton’s (1945) method of average length of stream channel per unit area. Dd = L/A
(l)
Where, L is the total length of streams and A is the area of the basin. The drainage density is calculated using equation (1) from the drainage map of the study area prepared from standard FCC of IRS-1B, LlSS-II data. Following Krishnamurthy et al. (1996) the density values are classified at a step of 0.75 km km-2 and the thematic map of drainage density is generated as shown in Figure 2(b). This map exhibits that most of the area is poorly drained with a density less than 0.75 km km-2. Topography: The percentage of slope of an area can be calculated as: Percentage of slope = (dz/dx) × 100
(2)
where, dz is the change of elevation to the distance dx. Using this equation, the slope is calculated from
Figure 2 (a): Geomorphological map of the study area. (b): Thematic map of drainage density. (c): Thematic map of slope of the study area. 71
important than the others are and hence it is desirable to differentiate as to how they meet certain criteria. The relative importance of various features of a thematic map may be taken into consideration by attaching numerical values to different features according to their importance in prediction of ground water occurrence. For reducing the uncertainty of the evolved model all the pieces of evidence for a hypothesis must be present together for the hypothesis to be true. This condition could be fulfilled by using fuzzy AND operation over different maps of ground water evidence. The theory of fuzzy sets deals with a subset A of the universe of discourse X, where the transition between full membership and no membership is gradual rather than abrupt. In the present context, let us consider, P is the set of ground water potential of different features of an area X. A fuzzy set P in X is a set of ordered pair.
P = {(x, Xp(x))},
x∈X
where Xp(x) is termed as the grade of membership of x in A. Traditionally, it is assumed that Xp(x) is a member in the interval [0.1] with the grades 1 and 0 representing full membership and non-membership in a fuzzy set respectively. The grade of membership I is assigned to those feature that fully belong to P, or highly potential to ground water, while 0 is assigned to those that do not belong to P at all, that means completely devoid of ground water. The more a feature x belongs to P, the closer to I is its grade of membership Xp(x). This grade of membership of x in A is normally represented by curves. The nature of the curve for a particular type of feature varies according the potential of ground water occurrence of that feature, Xp(x), in an area. Figure 3(a) shows the membership
Figure 3 Fuzzy membership curves of (a) geomorphology, (b) drainage density and (c) slope. 72
(3)
curve for geomorphology, which is drawn by considering the ground water potential of different geomorphic unit as discussed earlier. Similarly, the membership curves for different features of drainage density and slope are drawn in figures 3(b) and 3(c) respectively following the concept of Krisnamurthy et al. (1996). Each feature of the three thematic maps is assigned with a rating according to their fuzzy value. All the thematic maps are then registered with one another and integrated step by step through GIS by using fuzzy AND operation, Xp(x) = min (Gp(g), Dp(d), Sp(s))
(4)
where Gp(g) is the membership value for geomorphology map at a particular location, Dp(d) is the value for drainage density map and Sp(s) is the value for slope map at the same location.
Figure 4
In the first step of integration 56 polygons of geomorphology are integrated with 32 polygons of drainage density. This yields a layer of 223 polygons, which in then integrated with 3 polygons of slope. The integrated layer comprises a total of 243 polygons belonging to a fuzzy set of membership within a range of 0 to 1. The polygons are then classified into four zones according to their fuzzy set values and the thematic map of ground water potential of the study area is prepared as shown in figure 4(a).
Field verification The accuracy of the estimates from the GIS model is verified with surface geophysical measurements. For this purpose 22 Vertical Electrical Sounding (VES) are conducted in different zone of ground water potentials. The locations of
(a): Ground water potential index map of the study area. (b): Location of VES points along with the litholog sections. 73
VES are shown over the ground water potential map of figure 4(b). The VES data are interpreted using Evolutionary Programming (EP) technique (Shahid et al., 1999b) based on global optimization (GA) method. The resistivity of different interpreted layers is correlated with the available litholog data and the litholog section at different VES points is prepared as shown in figure 6(b). The result clearly shows that approximately 20 m thick shallow aquifers of medium to coarse sand are present in the high potential zone of ground water. Approximately 7 to 15 m thick aquifers of fine sand are present in the moderate zone of potential, whereas in the poor zone the aquifers are composed of lateritic or morum sand with a thickness varies between 5 to 20 m. It can also be noted that the aquifers in the high potential zone are interconnected, and therefore, could be a good source for bulk water supply.
Conclusions A model is developed by integrating the thematic maps of geomorphology, drainage density and slope through geographic information system using fuzzy logic for the assessment of ground water potential of Midnapur District, West Bengal, India. The field verification of this model establishes the efficacy of the approach in demarcating the potential zone of ground water. A fuzzy operation through GIS over the thematic maps indicating ground water occurrence can certainly reduce the uncertainly of the estimated model generated from a single data set. The model could be used in any other area for ground water prospecting with proper modification.
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pollution potential using hydrogeologic settings. National Water Works Association/EPS series, EPA 600/2-87-035. Brown, A.G., 1996. Geomorphology and Groundwater. John Wiley & Sons Ltd., New York, 224 pp. Horton, R.E., 1945. Erosional development of streams and their drainage basins: Hydrophysical approach to quantitative morphology. Bulletin of Geological Society of America, 56, 275-370. Krishnamurthy, J., Kumar Venkates, N., Jayaraman, V., and Manival, M., 1996 An approach to demarcate ground water potential zones through remote sensing and a geographic information system. International Journal of Remote Sensing. 17(10) 1867-1884. Ray, S.P.S. and Dutta, D.K., 1972. Pleistocene aquifers and the development potential of the upland tract in Kasai-Silai interfluve area, Midnapur Dist., West Bengal. Proceedings of the Seminar on Geomorphology, Geohydrology and Geotechniques of the lower Ganga Basin, 27-29 May, Indian Institute of Technology, Kharagpur, India. Roy, A. and Niyogi, D., 1961. Geological and geophysical investigations for ground water around Hijli. Dt. Midnapore. Unpublished Report, Dept. of Geology & Geophysics, Indian Institute of Technology, Kharagpur, India, 62 pp. Sander, P., 1998. Hard rock aquifers in arid and semi-arid zones. Water resources of hard rock aquifers in arid and (semi-arid) zones - studies and reports in Hydrology, 58 (edited by J.W. Lloyd), UNESCO publication, Paris, 224 pp. Shahid. S., Nath, S.K. and Patra, H.P., 1999a. An integrated approach for ground water investigation around Nazarganj near Kasai river bed, Midnapur Dist., West Bengal. Journal of Applied Hydrology, X11(4), 15-21. Shahid, S., Nath, S.K., Sircar, A. and Patra, H.P., 1999b. Estimation of model parameters from one-dimensional vertical electrical sounding data using evolutionary programming technique. Acta Geophysica Polonica, XLVII(3), 335-348. Venkateshwara Rao, B. and Briz-Kishore, B.H., 1991. A methodology for locating potential aquifers in a typical semi-arid region in India using resistivity and hydrogeologic parameters. Geoexploration, 27, 55-64.
