Islamabad serves as the Federal Capital of Pakistan and is home to 1.12 million people with a population growth rate of 4. 9%. Statistically, Pakistan is yet to face the water scarcity by the year of 2025. As being the statistically 4th great nation to rely on Groundwater for most domestic and agricultural needs, definite steps need to be ensured for continuous supply of Groundwater and elevation of Groundwater table. This study aims to use an integrated approach of RS [ Remote Sensing ] and GIS [ Geographic Information System ] for delineating groundwater recharge potential zones of Islamabad using IF [ Influence Factor ] technique.
Water scarcity is a major global issue and is continuously been increasing. Groundwater continues to serve as the best option for drinkable and residential water needs. Half of the drinkable water across the globe is groundwater. This study aims to use an integrated approach of RS [ Remote Sensing ] and GIS [ Geographic Information System ] for delineating groundwater recharge potential zones of Islamabad using IF [ Influence Factor ] technique
The ground water level of Islamabad has lowered five times over the past 5 years as reported by Ministry of Interior in 2018 [i] due to extensive pumping by departments and residents to meet water requirements and due to below normal rainfall. Ministry of Interior also emphasized upon the recharging of aquifers to upscale the ground water level. This study uses an integrated approach of RS and GIS to delineate groundwater zones in the federal capital of Pakistan using the Influence Factor (IF) technique. The Survey of Pakistan toposheets were used for the preparation of thematic maps. The imagery was visually interpreted to delineate distance to faults, land use, lithology, drainage density, slope, soil, rainfall, plan curvature, fault density, profile curvature, TWI, elevation, aspect (the front-facing direction of a slope), drainage distance, slope length with the help of slandered characteristic image interpretation elements like tone, texture, shape, size, pattern, and association. The thematic maps were converted into raster form to easily integrate into GIS platform. Weights to factors under consideration were assigned Alongside their newly assigned weights for thematic maps, they are over-layered using the ArcGIS tool 9.3 to prepare a weighted thematic map that uncover the regions with the highest probability of groundwater. Five different assessment analogies were assigned, termed as poor, low, medium, high, and best. The final map shows a region of 14% with an area of 127.68 km2 to be under the “Best” zone for extracting groundwater. Furthermore, the map designates high, medium, low and poor to 21%,14%,32%,19% with respective areas 191.52 km2, 127.68 km2, 291.84 km2 and 173.28 km2. These percentages and area represent the land with its capability in terms of best, high, medium low and poor to contribute towards the ground water recharge. This research outlines the zones in Islamabad which are best to least favorable in terms of ground water extraction. As deemed necessary by the Ministry of Interior for constructing small reservoirs and ponds in the existing natural streams and installing recharging wells to maintain the ground water level [ii], this study outlines the zones that are most to least favorable in terms of Ground water extraction treatments and efforts.
Multiple contributing factors will be considered for Groundwater potential zone recharge. These include Drainage Distance, Profile Curvature, Distance to fault, Plan Curvature, Aspect, Drainage Density, Lithology, Slope Length, Elevation, TWI, Soil, Fault Density, Land Use, Slope, Rainfall, well data. Selection of contributing factor will be from the past publications and expert analysis. Directly influencing factors such as rainfall and slope will be given higher weightages while appropriate weightages will be assigned to all the factors. The Survey of Pakistan toposheets for each of the contributing factor will be used for making Thematic maps. The imagery will be visually interpreted and will be converted into Raster form for GIS software integration. Shuttle Radar Topography Mission (SRTM) DEM data on a global scale will be used for Topographical analysis. Suitable Weightage Factors will be assigned to each factor afterwards. Weightage Overlay Analysis will be performed and appropriate rankings will be assigned with Influence Factor technique. Spatial Analysis tool in Arc GIS 9.3 will be used to process Thematic maps. Thematic layers will be produced for contributing factors with the Remotely sensed data under assigned weightages. These thematic layers will be processed with the GIS software to come up with a final thematic map that highlights the potential recharge zones.
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