The Engineering Journal of Application & Scopes, Volume 3, Issue 2, Dec 2018

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1 MULTI-CRITERIA DECISION ANALYSIS FOR IDENTIFYING OF GROUNDWATER POTENTIAL SITES IN HARIDWAR, INDIA Deep Gupta, Shashank Yadav, Deepak Tyagi,Lovee Tomar Civil Engineering Department, College of Engineering Roorkee, Roorkee Abstract-Water in the voids of the Earth is called groundwater. As surface water, groundwater is almost available everywhere, and although renewable, is not stable. The groundwater availability of depends on the type and physical properties of rocks, such as porosity, permeability, storage capacity, and transmissibility. Conventional methods to potentiality of groundwater are based largely on studies and field surveys. However, conventional exploration methods such as terrestrial surveys and geophysical methods do not always account for the diverse factors that control the occurrence and movement of groundwater. With the advent of remote sensing and GIS techniques, mapping of the potentiality within each geologic unit has become easier. Incorporation of remote sensing and GIS has become one of the tools for the discovery of groundwater resources that helps us in assessing, monitoring and protection of groundwater resources. The purpose of the project is to use Geographical Information Systems (GIS) and Remote Sensing for determining the best areas having ground water potential in Haridwar District. To achieve this objective, parameters such as precipitation, slope, lineament, vegetation, drainage density, land use land cover and lithology will be used. Regarding different weight of these parameters effect, Analytic Hierarchy Process (AHP) will be used. After developing informational layers in GIS and weighing each of them, a model will developed. The final map of ground waters potential will calculate through the above mentioned model. Through applying our developed model four areas having high, average, low potential and without required potential distinguished. Keywords: GIS, Remote Sensing, AHP, MCDA, Groundwater Potential I. INTRODUCTION Groundwater is a precious natural resource of water that is held in aquifers. It is an important source of water supply throughout the world. The management of groundwater resources is the pre-requisite for whole world due to increasing demand of water, as these resources remain constant. The total volume of water on Earth is about 1.4 billion km3, out of these 35 million km3 or about 2.5% of the total volume is freshwater as shown in Figure 1. The 70% or 24 million km 3 volume of the total freshwater resources are in the form of ice and permanently snow covered in mountainous regions, the Antarctic & Arctic regions. About 30% of the world s freshwater resources are available in the form of groundwater (Figure 1). The total usable freshwater supply for all living beings is about km 3 of water; which will be less than 1% of all freshwater resources. Fig. 1: World fresh water scenario (Source: Google) In India, groundwater table is declining, along with the degradation of groundwater quality due to rapid unplanned urbanization, high growth of population, modern agricultural practices (such as, extensive use of fertilizers and pesticides in agriculture), poor sewage system and not proper disposable sites for waste water of household and industrial activities. Once groundwater is contaminated, it is very expensive to make it uncontaminated as its takes long time to recover. Additionally, spatial inconsistency and data limitations preclude monitoring of all waters and make remediation activities expensive and often impractical. Groundwater contamination not only affects the water quality but also menaces to human health, economic development, and social wealth. II. NEED TO STUDY GROUNDWATER POTENTIAL The decreasing water table and groundwater contamination are critical problems in effective groundwater management of Haridwar watershed, the sub-watershed of Ganga basin in Uttarakhand State, India. In this study, spatio-temporal analysis has been carried out with the help of RS, GIS and groundwater flow modelling to manage groundwater resources of the watersheds in an effective way. Since the groundwater of the area is not adequately investigated, lack of information and knowledge may be a problem for the development and management of the aquifer in the area. In order to ensure a judicious management of groundwater, proper evaluation is required. In addition, its present status should be studied and prediction for the future status attempted. Then it is necessary to allocate areas with high groundwater potential to improve control of abstraction rates to ensure proper groundwater management. Due to the lack of reliable data on the particular basin, the proposed work will serve for the future hydro-geological study in this area. Moreover, this work can be extended to the entire catchment as more detail information is collected and added to the database. In addition to above, the scope of this work is to develop 9

2 The Engineering Journal of Application & Scopes, Volume 3, Issue 2, Dec 2018 a web interface, and online decision making tool that supports GIS to facilitate sustainable development of groundwater resources. III. in the study and Table 2 description of Satellite Landsat 8 and its Spectral bands used in Study. Table 1.Specification of satellite data used THE S TUDY AREA Haridwar is regarded as one of the religious city to Hindus and the second largest city of Uttarakhand. It is situated in the southwestern part of Uttarakhand is chosen as the study area. Haridwar is situated on the bank of river Ganga and many other seasonal streams flow though it, most of the region of this city is covered with forest. Haridwar is referred as the main religious, commercial and financial centre of the state. Having such a high importance and densely populated area this city offers plethora of education and business opportunities, provide shelter to many people from the nearby villages and town. Haridwar is facing exploitation of groundwater at a faster rate due to which it should be properly classified and sustainably used. S atellite Sensor Path Row Resolution Landsat 8 OLI/TIRS meter Cartosat I DEM V. Haridwar, a district of Uttarakhand is situated at cardinal points at Latitude and Longitude to Latitude and Longitude and have an altitude of 1030 ft. above mean sea level covering an area of hectare. The study area is focused on groundwater potential of region as it is being exploited at a high rate due to urban sprawl and growth of industries in nearby region. The Figure 2 represents the study area map. Haridwar has subtropical climate which on average lies from 29 degree centigrade to 39 degree centigrade and is generally high on humidity and faces three distinctive seasons i.e. winters, summers and rains meter METHODOLOGY To estimate groundwater potential analysis we compare Earth s physical parameter i.e. Geology, Elevation, Slope, Drainage Density and others. Study of these parameters in preparation of site suitability map is very important. There are several methods used by researchers to study groundwater potential analysis and mapping. They can mainly be classified under three groups: expert evaluation, statistical method and deterministic method. The successful use of one method over the other strongly depends on many factors such as scale of the area, accuracy of the expected results, availability of data, parameters considered etc. In the present study of AHP is used to determine the site suitability. AHP is multi criteria decision making approach and technique introduced by Thomas L. Satty. AHP is a decision support tool it helps to solve complex decision making problems, which uses weights of different classes to generate proper result. AHP is implemented in three simple steps (Saaty, 1980) The first step includes identification of all parameters, criteria, subcriteria and alternatives which will be responsible for problems. The second step is to set datasets in the hierarchic structure with the help of expert human decision. Experts can rate the comparison as good, medium, moderate and poor. The third step is pair wise comparisons of multi criteria generated in step 2 are organized in square matrix formats (m x n). This comparison matrix giv es the relative importance of the multi criteria being compared. Comparisons made by this method are subjective and the AHP tolerates inconsistency through the amount of redundancy in approach. If this consistency index has failed to reach a required level then answers to comparisons may be re-examined. CI = λmax n n 1 Where λmax is the maximum Eigen value of the judgment matrix. CI can be compared with random matrix, RI. Fig 2:Study area map (As Generated in ArcGIS) IV. Computing the vertex of criteria weights Computing the matrix of option scores. Ranking the options DATA US ED One scene has been taken from Landast-8 OLI data acquired on 19 October 2016 from US Geological Survey (USGS) Global Visualization Viewer. The obtained Landsat data were georeferenced to UTM zone 43 North projection using WGS-84 datum with the help of topographic maps of the area. Another satellite data has been acquired from BHUVAN (Indian Geographic satellite portal) about the elevation model of the region. The Table 1 explains the specification of satellite data used The ratio derived. CI/RI, is termed as the consistency ratio, CR. Saaty suggests the value of CR should be less than 0.1. The rating of each alternative is to be multiplied by the weights assigned to 10

3 sub-criteria and aggregated to get local ratings with respect to each criterion. The local ratings are then multiplied by the weights of the criteria and aggregated to get global ratings. The AHP produces weight values for each alternative based on the importance of one alternative over another with respect to common criteria. 11 Soil Fig.3.Model used in present study Table 2:.Ranking for different Parameters in Site Suitability Zone Mapping Compare criteria Weight Sub-criteria 12 LINEAMENT 19 GEOLOGY 11 DRAINAGE DENSITY 9 SLOPE 12 ELEVATION 7 LULC 19 Water Table Landsat 8 image has been aquired from USGS Glovis online portal, which has been used for preparation several thematic layer. Another data of Cartosat has been aquired from BHUVAN online portal. In order to generate LULC Map supervised classification method is adopted using Maximum Likelihood classifier using ERDAS software. DEM data has been captured from CARTOSAT satellite. Slope, Aspect and Elevation are developed using DEM data in Arc GIS software. The soil layer is developed by georefrencing soil map of India obtained from the National Bureau of Soil Survey and Land Use Planning (NBSS & LUP). Softwares like ArcGIS and ERDAS have been used for editing, digitization and topology criteria. Then combining all these raster layers final model is prepared as shown in Figure 3 in ArcGIS The next step is to assign weights value to each raster layer (based on expert person judgement) as shown in Table 3. Then these steps are applied in AHP for pair wise comparision matrix, Normalized Matrix etc. AHP is a structured technique for organising and analysing complex decision making problem based on psychological and mathematical method which was developed by Thomas L. Saaty in 1970 AHP model used in study which was made in ArcGIS and finally the site suitability map is generated by using these parameters. VI. RESULT AND DISCUSSION The result is developed using various thematic map layers, these layers are defined in following section. 1. Degital Elevation Model (DEM) DEM is derived from Cartosat satellite whose data is present on BHUVAN. The study area has almost flat topography with small variation at the northern region due to presence mountains. DEMis raster layer whose each pixel contains a fix elevation value. DEM are very comfortable for calculations, manilulation and further analysis of area which are based on elevation of area. ArcGIS has many built in features which can convert elevation map into derivative map. Figure 4 represents the elevation map of study area. The elevation map is devided into 10 classes as depicted in figure. 11

4 Fig. 5.Slope map 3. Land Use Land Cover (LULC) Land use land cover layer is generated by supervised classification with maximum likelihood algorithm which is applied in ERDAS Imagine software. Maximum likelihood algorithm is one of the most widely used algoritthm of supervised classififcation used with remote sensing image data. Land use land cover is the most significant method depicts the urban development of a particular study area. In most of the conditions it is used to find the open land, vegetation land, urban cover area and water. Plants and vegetation play an important role cleanig the enviroment by removing harmful gasses. Image classification resulted into four land use land cover classes namely devided as Open land, vegetation, water, urban as denoted in Figure 6. Fig. 4.Elevation Map 2. Slope Map Site suitability of an area is highly dependant on the evenness of slope, bedding of rocks and extent of faulting and folding of rocks. As the evenness of slope remains constant, the probablity of suitability of site increases. Figure 5 and represents the slope map with 10 classes for the study area. Slope of the study area lies between , this area is mediumly ranked as the area has flat terrain in some region while it also includes mountainous region. The class having higher value is categorized with lower rank relatively due to high run-off and low recharge. Fig. 6.LULC Map 4. Drainage Density Map The drainage network of the area is calculated using ArcGIS. Drainage network of an area are important as they decides the run off and groundwater recharge level of that area. Thus drainage density of this area is calculated using ArcGIS, so we can easily locate the area with high density. The places nearer to these sites have high potenial for future development as this factor is of high importance settlement in any area.figure 7 shows the drainage density map. 12

5 6. Soil Layer The soil map of the study area was obtained from the National Bureau of Soil Survey and Land Use Planning and converted into digital format. The soil map was updated with the Landsat TM image. The soils for the study area reveal five main soil categories, namely; Typic Urdorthents, Udic Haplustepts, Typic Haplustepts and Udifluventic Haplustepts as described in Figure 9. Fig. 7. Drainage density map 5. Geology Map Geology map is prepared using visual interpretation of satellite image with the aid of Geological Survey of India (GSI) map. In the present study area, four types of geology namely; Damtha group, Berinag group, Bajinath group and Ramgarh formation are present, as shown in Figure 8. Fig. 9.Soil Map 7. Depth to Water Table Layer Depth to water table layer of pre-monsoon and post-monsoon season has been prepared using IDW interpolation technique. The depth to water table is divided into two zones: at 5 meter depth and 10 m depth. In both pre-monsoon and post-monsoon seasons major part of the study area have 5 to 10 m depth to water table as shown in Figure 10. Fig. 8.Geology Map of water table Fig. 10.Depth 13

6 8. Lineament Density Layer Lineament density layer informs about the movement and storage surface run off water which makes it important for the study. The area is divided into five classes from indicating a density near the each lineament layer. The Figure 11 depicts the lineament density map of our study area. Fig.12.Groundwater Potential Map Density Map 9. Preparation of Groundwater Potential Map Fig. 11.Lineament All the criteria in the map are converted in raster format, so that each pixel can be calculated and result can be determined. All the criteria are integrated and overlaid to generate a site suitability map with a specific weightage according to their role in future development. Suitability map = (Criteria map x weight) Suitability index = {[Lineament x (0.12)] + [Geology x (0.03)] + [Drainage density x (0.11)] + [Slope x (0.09)] + [Elevation x (0.12)] + [LULC x (0.07)] + [Water table x (0.19)] + [Soil x (0.11)]}. Table 4.Area covered by each resultant class Suitable Area Area in sq. Percentage Meter Most suitable % ly suitable % Suitable % Less Suitable % Permanently not suitable % After applying weights to develop raster layer final map for potential site for future urban development is developed as shown in Fig.12 and the total area is divided into five classes as displayed in Table 4. VII. CONCLUSION This study is focused on selection of sites as most suitable, moderately suitable, suitable,less suitable and permanently not suitable land for groundwater potential. AHP matrix along with GIS is used to analyses of different criteria considered for groundwater suitability. AHP along with GIS was found to be very useful for groundwater suitability identification. The result is adopted for decision making process for site suitability analysis of an area. The study includes physical parameters for expansion and need to include social and economic parameters. Decision support system has been preferred to identify appropriate site for best location for living in Haridwar city. To determine site suitability for Haridwar city mainly threesteps are followed: 1. To determine best suitable site in city for groundwater potential. 2. Survey of city in Study area. 3. Analytical Hierarchy Process (AHP). VIII. REFERENCES 1. Saaty, T. A scaling method for priorities in hierarchical structures. Journal of mathematical psychology. Volume 15, Issue 3, PP The Analytic Hierarchy Process, McGraw-Hill International Book Company, U.S.A. A scaling 14

7 method for priorities in hierarchical structures. Journal of mathematical psychology. Volume 15, Issue 3, PP Chowdhury, A., Jha, M. K., Chowdary, V. M., & Mal, B. C. (2009). Integrated remote sensing and GIS based approach for assessing groundwater potential in West Medinipur district, West Bengal, India. International Journal of Remote Sensing, 30(1), Kaliraj, S., Chandrasekar, N., & Magesh, N. S. (2014). Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique. Arabian Journal of Geosciences, 7(4), Prashant K. Srivastava, Dawei Han, Manika Gupta, Saumitra Mukherjee. (2012) Integrated framework for monitoring groundwater pollution using a geographical information system and multivariate analysis. Hydrological Sciences Journal 57:7, pages Tiwari, A., & Jain, K. (2014). GIS Steering smart future for smart Indian cities. International Journal of Scientific and Research Publications, 4(8), Tiwari, Anuj, Merugu Suresh, and Arun Kumar Rai. "Ecological Planning for Sustainable Development with a Green Technology: GIS." International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)3, no. 3 (2014):