Evidence map›Paper›PMID 41214157›Full record

ArticleScientific reports2025

Spatio-temporal patterns of land use and land cover, and their impact on groundwater quality in the industrialized Muvattupuzha basin.

K Alagulakshmi, G Prince Arulraj, Sneha Gautam, Suneel Kumar Joshi

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

K AlagulakshmiDivision of Civil Engineering, Karunya Institute of Technology and Sciences, Deemed University, Karunya Nagar, Coimbatore, Tamil Nadu, 641114, India.
G Prince ArulrajDivision of Civil Engineering, Karunya Institute of Technology and Sciences, Deemed University, Karunya Nagar, Coimbatore, Tamil Nadu, 641114, India.
Sneha GautamDivision of Civil Engineering, Karunya Institute of Technology and Sciences, Deemed University, Karunya Nagar, Coimbatore, Tamil Nadu, 641114, India. snehagautam@karunya.edu.
Suneel Kumar JoshiGeo Climate Risk Solutions Pvt. Ltd, Visakhapatnam, Andhra Pradesh, 530048, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid urbanization and industrialization drive profound land use and land cover (LULC) transformations across India, placing unprecedented pressure on groundwater resources. This study presents a two-decade (2003-2023) spatio-temporal assessment of LULC dynamics and groundwater quality in the industrialized Muvattupuzha River Basin, Kerala. Multi-temporal Landsat imagery was classified using the Support Vector Machine (SVM) algorithm, achieving high classification performance (overall accuracy 89%, Kappa 0.86). Results reveal a striking 32.09% expansion of built-up areas, accompanied by a 17.91% decline in forest cover and a 4% reduction in agricultural land, reflecting accelerated urban sprawl and landscape conversion. The Entropy-based Groundwater Quality Index (EGWQI) exhibited a strong inverse relationship with built-up areas (r = - 0.91) and a highly positive association with forests and water bodies (r ≥ 0.98), underscoring the buffering role of natural ecosystems. Although 86.7% of wells remain in the 'Excellent' category, persistent contamination hotspots were identified near industrial and agricultural clusters, with risks amplified during monsoonal runoff events. Proximity and correlation analyses confirmed that industrial zones and quarries are critical drivers of localized groundwater degradation. These findings highlight the urgent need for integrated land-water governance, implementation of green infrastructure, and strict effluent management protocols to mitigate anthropogenic impacts and safeguard long-term groundwater sustainability in rapidly urbanizing tropical basins.

Indexed as

Groundwater quality indexLand coverLand useRiver basinSupporting vector machine

Identifiers

PMID41214157
PMCPMC12602701

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.