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.

Amidst global shifts in land use patterns due to urbanization, this study focuses on the rapid land use and land cover (LULC) changes in Midnapore City during the periods 2003–2014 and 2014–2024. The study employs Landsat 5 and 8 imagery with 30 m spatial resolution which were processed through Maximum Likelihood Classifier (MLC) algorithms. The results were attained through ArcGIS 10.2.2 and ERDAS IMAGINE 2014 software, with ground-truth validation using data from 117, 111, and 116 points for 2024, 2014, and 2003, respectively. For the validation, the kappa coefficient was calculated and achieved 87.3%, 88.1%, and 81.7% for 2024, 2014, and 2003, indicating substantial accuracy. Using statistical measures such as change matrix union, binary logistic regression, and correlation matrix analysis applied to classified LULC outputs and spatial drivers, the research highlights significant transformations in the region. The study reveals significant transformations, notably the conversion of 77% of forest areas and 5% of fallow land to built-up land. The increased rate of agricultural land conversion to built-up areas is evident after 2014, indicating rapid urban growth. These factors led to the reduction of LULC classes possessing substantial ecological value like forests and scrub lands which are becoming more accessible due to the increasing population. The results point out the drastic alteration of these developments and recommend a planning approach responsive to environmental needs for safeguarded ecological impacts. The research highlights the importance of reforestation, preservation of water bodies, and socio-economic surveillance in fostering urban management and sustainable development in Midnapore City.