Faculty Publications

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Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques
(Springer Verlag, 2018) Gulgundi, M.S.; Shetty, A.
Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water. © 2018, The Author(s).
Assessing forest health using remote sensing-based indicators and fuzzy analytic hierarchy process in Valmiki Tiger Reserve, India
(Institute for Ionics, 2023) Roshani; Sajjad, H.; Rahaman, M.H.; Rehman, S.; Masroor, M.; Ahmed, R.
Anthropogenic activities, climate variability and environmental stresses have greatly affected forest ecosystems globally. Thus, monitoring of forest health is essential for proper planning and effective management. The present study employed an integrated approach of remote sensing and fuzzy analytic hierarchy process to assess the forest health in the Valmiki Tiger Reserve in India. Advanced vegetation index, normalized difference vegetation index, normalized difference moisture index, forest fragmentation, rainfall and soil types were derived from remote sensing data. Multiple buffer zones of villages, roads, railways and canals were also determined for analyzing the forest health status. These layers were prepared in the geographical information system. These layers were given weightage using fuzzy analytic hierarchy process. These layers were integrated to prepare forest health map using weighted overlay method. The results revealed that the largest forest area was found under moderately healthy forest (37%) followed by healthy forest (31%) and unhealthy forest (13%). Of the total area of the Reserve, 19% area was under non-forest category. Human-induced disturbances such as encroachment, illegal sand mining, livestock grazing and forest conversion to agriculture have been attributed to the unhealthy forest in the Reserve. The receiver operating characteristic curve value and area under curve (0.792) show reliability of forest health map. The findings of this study may be helpful for forest managers, conservationists and local communities in devising sustainable strategies for effective management of the forest. The methodological framework adopted in this study may be utilized in other geographical regions interested in assessing forest health. © 2022, The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University.
Development of polymeric ionic poly(VBC-co-VI) nanoparticle incorporated thin film nanocomposite membranes for dye and salt rejection
(Royal Society of Chemistry, 2025) Mendonca, N.R.; Isloor, A.M.; Farnood, R.
Water is an important life-sustaining liquid. However, due to the current anthropogenic activities, this resource is diminishing. This work explores a method for the potential reuse of textile wastewater containing salts by utilization of thin film composite (TFC) membranes fabricated by means of interfacial polymerization on a macroporous membrane substrate composed of 15% polysulfone (PSf). A relatively lesser known variety of nanoparticles termed ionic polymeric nanoparticles were integrated into the dense polyamide (PA) layer. The ionic poly(VBC-co-VI) nanoparticles were synthesized in the laboratory via quaternary precipitation polymerization (QPP) of the monomers 1-vinyl imidazole (VI) and 4-vinybenzyl chloride (VBC) by the utilization of 2,2?-azobis(2-methylpropionitrile) (AIBN) as the free radical initiator in the solvent acetonitrile (ACN) in a single step. The synthesized nanoparticles existing in the PA layer improved the water permeability as well as the rejection capacity of the membranes. The fabricated membranes showed a dye rejection of 98% for Reactive Black 5 and >95% for Sunset Yellow FCF having a concentration of 100 ppm. The salt rejection for NaCl, MgCl, Na2SO4 and MgSO4 at 1000 ppm concentration was found to be 36%, >50%, 85% and 85%, respectively. © 2025 The Royal Society of Chemistry.

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