Abstract
One of the natural resources having the latent for home, agrarian, and engineering use is surface and groundwater. Due to humanoid and certain natural reasons, the eminence of the groundwater serving Baramati City and Tehsil has deteriorated. Agriculture is using more pesticides and fertilizer, therefore this supply is being affected. Municipal water pollution can be caused by “septic boilers”, “bathe sewage”, “polluted aquatic”, “improper discarded management”, “public excretion”, “improper waste structure”, “public sewage discharges”, and “unorganized solid waste disposal”. The current study will improve the accuracy of the water quality index for areas in Baramati Tehsil that are affected by industry and drinking water supplies. The groundwater zones were created using a weighted index overlay analysis, which assigned weights based on several classes of individual water quality metrics and drinking water standards. Based on few observations, fuzzy logic offers an effective and practical tool for categorizing drinking water quality. This study's objective is to provide a fuzzy logic-based water quality indicator for basin-wide reservoirs. For a weight-based fuzzy quality index, a minimum of 6 physico-chemicals are needed.
Publisher
Asian Research Association
Subject
General Earth and Planetary Sciences,General Environmental Science
Reference28 articles.
1. M. Jalali, Geochemistry characterization of groundwater in an agricultural area of Razan, Hamadan, Iran. Environmental Geology, 56 (2009) 1479–1488. https://doi.org/10.1007/s00254-008-1245-9
2. Jimenez-Madrid, R. Gogu, C. Martinez-Navarrete, F. Carrasco, Groundwater for human consumption in karst environment: vulnerability, protection, and management. Karst Water Environment. Springer, 68 (2019) 45–63. https://doi.org/10.1007/978-3-319-77368-1_2
3. Y. Ostovari, Z. Sh, H. Harchegani, K. Asgari, Effects of geological formation on groundwater quality in Lordegan Region, Chahar-mahal-va-Bakhtiyari, Iran. International Journal of Agriculture and Crop Sciences. 5 (2013) 1983–1992.
4. S.R. Naganna, B.H. Beyaztas, N. Bokde, A.M Armanuos, On the Evaluation of the Gradient Tree Boosting Model for Groundwater Level Forecasting. Knowledge-Based Engineering and Sciences, 1 (2020) 48–57. https://doi.org/10.51526/kbes.2020.1.01.48-57
5. D. Machiwal, M.K. Jha, V.P. Singh, C. Mohan, Assessment and mapping of groundwater vulnerability to pollution: Current status and challenges. Earth-Science Reviews, 185 (2018) 901–927. https://doi.org/10.1016/j.earscirev.2018.08.009