Groundwater Quality Evaluation of Fractured Aquifers Using Machine Learning Models and Hydrogeochemical Approaches to Sustainable Water-Irrigation Security in Arid Climate (Central Tunisia)

Groundwater Quality Evaluation of Fractured Aquifers Using Machine Learning Models and Hydrogeochemical Approaches to Sustainable Water-Irrigation Security in Arid Climate (Central Tunisia)

The primary aims of this research paper involve the creation and verification of machine learning-based quality models that utilize Integrated Irrigation Water Quality Indices (IIGWQIs) through an integrated GIS approach. We utilize the Least-Squares Support Vector Machines (LS-SVM) and the Pearson...

Full description

Bibliographic Details
Main Authors: Mohamed Haythem Msaddek, Yahya Moumni, Lahcen Zouhri, Ismail Chenini, Adel Zghibi
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Water
Subjects:
sustainable water security
geochemistry
machine learning
groundwater quality evaluation
fractured aquifer
Online Access:https://www.mdpi.com/2073-4441/15/19/3332

Internet

https://www.mdpi.com/2073-4441/15/19/3332

Similar Items