Chilika Lake, a RAMSAR site, is an environmentally and ecologically pivotal coastal lagoon in India facing significant emerging environmental challenges due to anthropogenic activities and natural processes. Traditional in situ water quality monitoring methods are often labor intensive and time consuming. This study presents a novel approach for ex situ water quality monitoring in Chilika Lake, located on the east coast of India, utilizing Google Earth Engine (GEE) and spectral indices, such as the Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and total suspended solids (TSS). The methodology involves the integration of multi-temporal satellite imagery and advanced spectral indices to assess key water quality parameters, such as turbidity, chlorophyll-a concentration, and suspended sediments. The NDTI value in Chilika Lake increased from 2019 to 2021, and the Automatic Water Extraction Index (AWEI) method estimated the TSS concentration. The results demonstrate the effectiveness of this approach in providing accurate and comprehensive water quality assessments, which are crucial for the sustainable management of Chilika Lake. Maps and visualization are presented using GIS software. This study can effectively detect floating algal blooms, identify pollution sources, and determine environmental changes over time. Developing intuitive dashboards and visualization tools can help stakeholders engage with data-driven insights, increase community participation in conservation, and identify pollution sources.

Fresh groundwater is essential for sustaining life and socio-economic development, particularly in regions with limited safe drinking water alternatives. However, contamination from natural and anthropogenic sources poses severe health and environmental risks. This research examines the health risks linked to groundwater quality in the agroeconomic region of Boudh district, Odisha, India, where residents depend on untreated groundwater due to limited access to alternative sources. A total of 82 groundwater samples were analyzed during pre- and post-monsoon of the year 2023 using multivariate statistical methods (PCA, correlation analysis) to determine pollutant sources and regulatory factors, while XRD was employed to characterize fluoride-bearing minerals in associated rock samples. Fluoride concentrations range from 0.14 to 4.6 mg/L, with 49% of samples exceeding the WHO limit of 1.5 mg/L, which raises significant health concerns. Nitrate levels fluctuate between 1.57 and 203.51 mg/L, primarily due to agricultural fertilizers. A health risk assessment (hazard quotient and hazard index) indicates that 63% of samples fall into the low-risk category, 21% into moderate-risk, and 16% into high-risk. Children (HI = 29.23) and infants (HI = 19.51) are at the greatest health risk, surpassing that of adult males (HI = 12.2) and females (HI = 11.2). Findings provide scientific evidence for policymakers to implement groundwater protection and remediation strategies. Immediate interventions, including water quality monitoring, defluoridation measures, and community awareness programs, are essential for ensuring long-term water security and public health.

Marine pollution poses significant risks to both human and marine health. This investigation explores the limnological status of the Odisha and West Bengal coasts during the annual cruise program, focusing on the influence of riverine inputs on coastal marine waters. To assess this impact, physicochemical parameters such as pH, salinity, total suspended solids (TSS), dissolved oxygen (DO), biochemical oxygen demand (BOD), and dissolved nutrients (NO₂-N, NO₃-N, NH₄-N, PO₄-P, SiO₄-Si, total-N, and total-P) were analyzed from samples collected along 11 transects. Multivariate statistics and principal component analysis (PCA) were applied to the datasets, revealing four key factors that account for over 70.09% of the total variance in water quality parameters, specifically 25.01% for PC1, 21.94% for PC2, 13.13% for PC3, and 9.99% for PC4. The results indicate that the increase in nutrient and suspended solid concentrations in coastal waters primarily arises from weathering and riverine transport from natural sources, with nitrate sources linked to the decomposition of organic materials. Coastal Odisha was found to be rich in phosphorus-based nutrients, particularly from industrial effluents in Paradip and the Mahanadi, while ammonia levels were attributed to municipal waste in Puri. In contrast, the West Bengal coast exhibited higher levels of nitrogenous nutrients alongside elevated pH and DO values. These findings provide a comprehensive understanding of the seasonal dynamics and anthropogenic influences on coastal water quality in Odisha and West Bengal, highlighting the need for targeted conservation and management efforts.

In this study, we focused on the rapid land use and land cover (LULC) changes in Bankura in 1990, 2000, 2010, and 2024, employing an integrated remote sensing, geospatial, and statistical approach to track land use changes. The supervised classification technique and change detection analysis were applied with the Supper Vector Machine (SVM), Maximum Likelihood (ML), and Random Forest (RF) methods to identify land use classes in various categories like Dense Forest, Open Forest, water body, agricultural land, settlement, barren land, and sand. The Kappa Coefficient was used for the accuracy assessment, which revealed that the overall accuracy of 1990 was 93.33%, 2000 was 93.23%, 2010 was 93.43%, and 2024 was 90%. The analysis revealed a significant increase in built-up land from agricultural and forested areas, with a higher percentage of agricultural land converted to built-up areas observed between 1990 and 2024. During this interval, the built-up land area increased by approximately 13.6%, primarily due to the conversion of agricultural land and forest cover. Agricultural land decreased by 11.45%, while dense forest cover declined by 7.75%, indicating a significant anthropogenic influence on landscape transformation. Our findings underscore the importance of sustainable land use planning, conservation efforts, and policy interventions in mitigating environmental degradation, leveraging the effectiveness of space-based inputs and geospatial techniques. The research emphasizes the need for continuous monitoring and further investigation into socio-economic drivers and environmental consequences to ensure resilient urban management and sustainable development. This reveals the importance of reforestation, preserving water bodies, and developing ecologically sensitive infrastructure. Moreover, the study highlights the importance of sustainable land use planning in mitigating adverse environmental impacts and preserving ecological balance.