Please use this identifier to cite or link to this item: https://ir.vidyasagar.ac.in/jspui/handle/123456789/7556
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dc.contributor.authorBarman, Dinabandhu-
dc.contributor.authorPatel, Priyank Pravin-
dc.date.accessioned2025-07-08T23:21:25Z-
dc.date.available2025-07-08T23:21:25Z-
dc.date.issued2025-06-23-
dc.identifier.issn0972-7388-
dc.identifier.urihttps://ir.vidyasagar.ac.in/jspui/handle/123456789/7556-
dc.descriptionPP : 141-171en_US
dc.description.abstractCompared to larger rivers, water quality assessments in small streams are institutionally undertaken less frequently, especially in resource-scarce communities in the Global South. Yet, smaller streams are more sensitive to the ongoing landscape changes within their riparian zone, whose physicochemical signatures may get dampened within the high flows of larger rivers or mixed with similar signals from other parts of the catchment. The Sutunga River in eastern India was thus studied given the intended work's specific focus on smaller rivers. Our objectives were to measure the surface water quality along this small alluvial river situated within agricultural landscapes during the monsoon, post-monsoon, and pre-monsoon periods using a weighted arithmeticbased WQI, to investigate seasonal turbidity, TSS, nitrate (NO3-N), and chloride (Cl- ) concentrations along the river's course; and to use NDTI to assess its turbidity following prolonged rainfall events and high flows, with field validation. The computed water quality index (WQI) was based on in-situ measurements from monsoon 2023 to pre-monsoon 2024 and the Normalized Difference Turbidity Index (NDTI) derived from Sentinel-2A images in the Google Earth Engine (GEE) platform. There was substantial variability in WQI between the monsoon and post-monsoon periods (p = 0.001), but no significant difference was noticed between the post-monsoon and pre-monsoon (p = 0.184), with the majority of sites reporting good quality. One-way ANOVA results showed that DO, NO3-N, Turbidity, and TSS were the key parameters related to water quality, with significant seasonal variations. The polynomial (6th order) line best fit the parameter distributions and a Pearson's correlation matrix highlighted both turbidity and TSS as significantly influencing the surface water quality. The diminishing flow in the post-monsoon and pre-monsoon periods indicate greater stress on the stream habitat environment, with a concomitant increase in nitrate and chloride concentration levels, despite the drop in turbidity and TDS levels from the monsoon period. This variability underlines the importance of conducting site-specific investigations along the river's course to better understand the underlying causes of such seasonal oscillations.en_US
dc.language.isoenen_US
dc.publisherThe Registrar, Vidyasagar University on behalf of Vidyasagar University Publication Division, Midnapore 721102, West Bengal, Indiaen_US
dc.relation.ispartofseriesVolume : 20;7-
dc.subjectwater qualityen_US
dc.subjectalluvial riveen_US
dc.subjectGoogle Earth Engineen_US
dc.subjectturbidityen_US
dc.subjectseasonal variationsen_US
dc.titleMulti-seasonal Water Quality Assessment of a Small Alluvial River Using In-Situ Measurements and Satellite Imagesen_US
dc.typeArticleen_US
Appears in Collections:Vidyasagar University Journal of Geography and Environment (Vol. 20 :: Year 2023-2024)

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