A machine learning approach to investigate the impact of land use land cover (LULC) changes on groundwater quality, health risks and ecological risks through GIS and response surface methodology (RSM)-Reference-Cited by-同舟云学术

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A machine learning approach to investigate the impact of land use land cover (LULC) changes on groundwater quality, health risks and ecological risks through GIS and response surface methodology (RSM)

Published:2024-08 Issue: Volume:366 Page:121911
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Hossain Mobarok^ORCID,Wiegand Bettina,Reza Arif^ORCID,Chaudhuri Hirok,Mukhopadhyay Aniruddha,Yadav Ankit^ORCID,Patra Pulak Kumar

Publisher

Elsevier BV

Reference76 articles.

1. Water pollution indexing and health risk assessment due to PTE ingestion and dermal absorption for nine human populations in Southeast Nigeria;Agbasi;Groundwater for Sustainable Development,2023

2. Prediction of nickel concentration in peri-urban and urban soils using hybridized empirical bayesian kriging and support vector machine regression;Agyeman;Sci. Rep.,2022

3. An analysis of LULC changes for understanding the impact of anthropogenic activities on food security: a case study of Dudhganga watershed, India;Ahmad;Environ. Monit. Assess.,2024

4. Impact of land use/land cover changes on water quality and human health in district Peshawar Pakistan;Ahmad;Sci. Rep.,2021

5. RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments;Anderson,2016

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