Assessment of groundwater quality in the coastal area of mallipattinam and its environs

dc.contributor.guideElangovan, G
dc.coverage.spatialAssessment of groundwater quality in the coastal area of mallipattinam and its environs
dc.creator.researcherVetri selvi, K
dc.date.accessioned2025-01-31T04:43:46Z
dc.date.available2025-01-31T04:43:46Z
dc.date.awarded2024
dc.date.completed2024
dc.date.registered
dc.description.abstractThis study addresses the critical need for regular monitoring and newlineassessment of groundwater quality in coastal regions, particularly in the newlineMallipattinam coastal area of Thanjavur District, Tamil Nadu, where water newlineconsumption for aquaculture significantly impacts local water resources. newlineDespite ongoing efforts, there exists a knowledge gap in understanding the newlinespecific hydrogeochemical interactions and the effectiveness of current newlineevaluation methods in predicting water quality issues, especially those related newlineto salinity and contamination levels. Furthermore, conventional methods may newlinenot adequately capture the dynamic and complex nature of groundwater newlinequality variations over time and space. To bridge this gap, this research newlineemploys a novel approach combining Geographic Information System (GIS) newlineand ion geochemistry analysis, alongside the implementation of machine newlinelearning techniques, specifically Artificial Neural Networks (ANN), to assess newlineand predict groundwater quality parameters effectively. By analyzing newlineempirical data from 15 locations, this study not only explores the relationship newlinebetween electrical conductivity, chloride, sodium, magnesium, sulphate, and newlinetotal dissolved solids concentrations but also evaluates the predictive accuracy newlineof ANN models in forecasting key water quality indicators such as sulphate, newlinetotal dissolved solids, potassium, sodium, and chloride. The findings reveal newlinethat approximately 60% of the sampled water does not meet potable water newlinestandards, highlighting the urgency of this issue. This research contributes to newlinethe existing body of knowledge by providing a comprehensive understanding newlineof groundwater-saltwater interactions and by demonstrating the potential of newlineANN models in enhancing water quality monitoring and prediction efforts in newlinecoastal areas newline
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions21cm
dc.format.extentxix,145p.
dc.identifier.researcherid
dc.identifier.urihttp://hdl.handle.net/10603/618909
dc.languageEnglish
dc.publisher.institutionFaculty of Civil Engineering
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.relationp.133-144
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordcoastal area
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Civil
dc.subject.keywordgroundwater
dc.subject.keywordmallipattinam
dc.titleAssessment of groundwater quality in the coastal area of mallipattinam and its environs
dc.title.alternative
dc.type.degreePh.D.

Files

Original bundle

Now showing 1 - 5 of 11
Loading...
Thumbnail Image
Name:
01_title.pdf
Size:
42.81 KB
Format:
Adobe Portable Document Format
Description:
Attached File
Loading...
Thumbnail Image
Name:
02_prelim pages.pdf
Size:
2.16 MB
Format:
Adobe Portable Document Format
Loading...
Thumbnail Image
Name:
03_content.pdf
Size:
526.53 KB
Format:
Adobe Portable Document Format
Loading...
Thumbnail Image
Name:
04_abstract.pdf
Size:
42.38 KB
Format:
Adobe Portable Document Format
Loading...
Thumbnail Image
Name:
05_chapter 1.pdf
Size:
1.03 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.79 KB
Format:
Plain Text
Description: