Application of geospatial modelling technique in delineation of fluoride contamination zones within Dwarka Basin, Birbhum, India

Dwarka River Basin is one of the fluoride affected river basin in Birbhum, West Bengal. In the present research work, various controlling factors for fluoride contamination in groundwater i.e., geology, aquifer type, groundwater table, soil, rainfall, geomorphology, drainage density, land use land cover, lineament and fault density, slope and elevation were considered to delineate the potential fluoride contamination zones within Dwarka River Basin in Birbhum. Assigning weights and ranks to various inputs factor class and their sub-class respectively was carried out on the basis of knowledge driven method. Weighted overlay analysis was carried out to generate the final potential fluoride contamination zones which are classified into two broad classes i.e., 'high' and 'low', and it is observed that major portion of the study area falls under low fluoride contamination category encompassing 88.61% of the total area which accounts for 759.48 km^2 and high fluoride contaminated region accounts for 11.40% of the total study area encompassing an area of about 97.67 km^2. Majority of high fluoride areas fall along the flood plain of Dwarka River Basin. Finally, for validation 197 reported points within Dwarka having fluoride in underground water are overlaid and an overall accuracy of 92.15% is observed. An accuracy of 83.21% and84.24% is obtained for success and prediction rate curve respectively.

Spatial and Temporal Variation of Urban Air Quality: A GIS Approach

This study investigated the seasonal variation of ambient air quality status of Burdwan town using GIS approach. Concentration of SOR2R (sulphur dioxide), NOR2R (nitrogen dioxide) and RSPM (respiratory suspended particulate matter) were measured once a week for 24 hour in both premonsoon and postmonsoon season. The seasonal average concentration of the RSPM, SOR2R and NOR2R in premonsoon season was observed to be 188.56 ± 88.63, 5.12 ± 6.27 and 92.51 ± 64.78 mg/mP3P respectively whereas in postmonsoon it was 53.03 ± 38.27, 8.51 ± 7.11 and 162.85 ± 184.80 mg/mP3P respectively. Statistical analysis showed the significant monsoonal effect on mean difference of RSPM, SOR2R and NOR2R concentration. Postmonsoon concentration of ambient SOR2R and NOR2R were observed to be higher than premonsoon, suggesting longer residence times of these pollutants in the atmosphere due to stagnant conditions and low mixing height. Spatial distribution of pollutants throughout the town in both the season was represented by digital elevation model (DEM). On the basis of Air Quality Index (AQI) a GIS based air pollution surface models were generated in both the seasons by means of Inverse Distance Interpolation (IDINT) technique. From the output surface model it was found that in comparison to premonsoon there was a significant increase of clean and fairly clean area and decrease of moderately polluted area of the town during postmonsoon.