A generalized machine learning approach for cost-effective monitoring of irrigation suitability: A demonstration case in El Fahs aquifer (Tunisia)-Reference-Cited by-同舟云学术

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A generalized machine learning approach for cost-effective monitoring of irrigation suitability: A demonstration case in El Fahs aquifer (Tunisia)

Published:2024-11 Issue: Volume:27 Page:101324
ISSN:2352-801X
Container-title:Groundwater for Sustainable Development
language:en
Short-container-title:Groundwater for Sustainable Development

Author:

Panagiotou Constantinos F.,Konstantinou Charalampos^ORCID,Chekirbane Anis

Publisher

Elsevier BV

Reference40 articles.

1. Groundwater quality assessment for irrigation purposes based on irrigation water quality index and its zoning with GIS in the villages of Chabahar, Sistan and Baluchistan, Iran;Abbasnia;Data Brief,2018

2. Application of neural network and time series modeling to study the suitability of drain water quality for irrigation: A case study from Egypt;Abdel-Fattah;Environ. Sci. Pollut. Control Ser.,2021

3. Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches;Aldrees;J. Water Process Eng.,2024

4. Application of Bi-LSTM method for groundwater quality assessment through water quality indices;Alfwzan;J. Water Process Eng.,2023

5. Evaluation of Irrigation Water Quality Index (IWQI) for Habbaniya Lake in Anbar Governorate, Iraq;Al-Kubaisi,2022

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