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EN
Elevating industrialization and urbanization have increased water demand, resulting in a water crisis and plummeting groundwater resources day by day. The present research proposed a model to decipher groundwater potential zones by integrating remote sensing (RS) data with fuzzy logic in an ArcGIS environment. Eleven groundwater potentiality influencing factors have been employed for the study. Each layer was passed through a multicollinearity check, resulting in no collinearity found between the layers. Furthermore, each layer was reclassified, ranked according to their potential to the groundwater occurrence, and assigned fuzzy values. The groundwater potential zones were developed by applying an overlay operation to integrate eleven fuzzy layers. According to the fuzzy value, the Surat district is divided into four potential zones: very poor, poor, moderate, and good. The result shows that 32.21% (1343 km2 ) and 31.63% (1319 km2 ) have good and moderate groundwater potential zones, respectively. Additionally, the map removal sensitivity study illustrated that drainage density, lineament density, and rainfall are more sensitive to potential zones in the study area. The potential zones have been verified by a false matrix, indicating substantial agreement between groundwater levels and potential zones with an overall accuracy of 81.1%. Thus, the integration of RS data and fuzzy-based method is an efficient method for deciphering groundwater potential zones and can be applied anywhere with necessary adjustment.
EN
Population growth and urbanization lead to urban heat island (UHI) phenomenon. Urbanization is occurring at a very high rate in the Surat city. Thus, the study of the urbanization impact on the UHI effect for the Surat city is performed in the present study through studying the impact of land use land cover on the land surface temperature of urban and sub-urban areas of the Surat city over the period May 1998 to May 2018. Also, these effects are compared with that of a nearby sub urban taluka Kamrej, which showed that temperature in urban areas is more than that of the sub-urban areas. Aforesaid facts clearly showing the existence of the UHI effect in the Surat city. As urbanization contributes to climate change, its effects on rainfall are studied by comparing rainfall trends of urban and sub-urban areas of the Surat city and nearby sub-urban area Kamrej. Trend analysis showed that trend magnitude values are higher for the urban areas than sub-urban areas, indicating that UHI effect increases rainfall in urban areas. Hotspot analysis is also performed for the Surat city corresponding to May 2018 to recognize hot spots and cold spots. As the Surat city is highly urbanized, thus, hotspots are more than cold spots.
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