[HTML][HTML] Groundwater vulnerability to contamination in the gulf cooperation council region: A review

F Baig, M Sherif, A Sefelnasr, MA Faiz - Groundwater for Sustainable …, 2023 - Elsevier
Aquifer vulnerability arises from the degradation of groundwater quality due to a wide range
of contaminants and pollutants. The escalating concern regarding groundwater …

[HTML][HTML] Developing a novel tool for assessing the groundwater incorporating water quality index and machine learning approach

AM Sajib, MTM Diganta, A Rahman… - Groundwater for …, 2023 - Elsevier
Groundwater plays a pivotal role as a global source of drinking water. To meet sustainable
development goals, it is crucial to consistently monitor and manage groundwater quality …

Enhancing groundwater vulnerability assessment: comparative study of three machine learning models and five classification schemes for Cuddalore district

S Subbarayan, S Thiyagarajan, S Karuppannan… - Environmental …, 2024 - Elsevier
Most of the groundwater vulnerability assessment methods using machine learning are
binary classification. This study attempts multi-class classification models to map the …

Innovative approach for predicting daily reference evapotranspiration using improved shallow and deep learning models in a coastal region: A comparative study

HE Elzain, OA Abdalla, M Abdallah… - Journal of …, 2024 - Elsevier
Accurate and reliable estimation of Reference Evapotranspiration (ETo) is crucial for water
resources management, hydrological processes, and agricultural production. The FAO-56 …

An innovative approach for predicting groundwater TDS using optimized ensemble machine learning algorithms at two levels of modeling strategy

HE Elzain, O Abdalla, HA Ahmed, A Kacimov… - Journal of …, 2024 - Elsevier
Groundwater salinization in coastal aquifers is a major socioeconomic challenge in Oman
and many other regions worldwide due to several anthropogenic activities and natural …

Evaluation and mapping of predicted future land use changes using hybrid models in a coastal area

H Ahmad, M Abdallah, F Jose, HE Elzain… - Ecological …, 2023 - Elsevier
Future prediction modeling of land use/land cover (LULC) is crucial for coastal regions due
to unique challenges and vulnerabilities associated with these areas. This research aims to …

Advancing SDGs: Predicting Future Shifts in Saudi Arabia's Terrestrial Water Storage Using Multi-Step-Ahead Machine Learning Based on GRACE Data

MA Yassin, SI Abba, A Pradipta, MH Makkawi… - Water, 2024 - mdpi.com
The availability of water is crucial for the growth and sustainability of human development.
The effective management of water resources is essential due to their renewable nature and …

[HTML][HTML] Interpretable machine learning for predicting the fate and transport of pentachlorophenol in groundwater

M Rad, A Abtahi, R Berndtsson, US McKnight… - Environmental …, 2024 - Elsevier
Pentachlorophenol (PCP) is a commonly found recalcitrant and toxic groundwater
contaminant that resists degradation, bioaccumulates, and has a potential for long-range …

A Comprehensive Review of Machine Learning Algorithms and Its Application in Groundwater Quality Prediction

H Pandya, K Jaiswal, M Shah - Archives of Computational Methods in …, 2024 - Springer
Groundwater is among the utmost essential renewable resources for every organism
existing on Earth. Assessing water quality is critical for the ecosystem's stability and …

Assessment of groundwater nitrate vulnerability using DRASTIC and modified DRASTIC in upper catchment of Sabarmati basin

T Gupta, R Kumari - Environmental Earth Sciences, 2023 - Springer
Contamination from agriculture diffuse particularly nitrate is an important concern due to its
impact on groundwater quality and human health. To ensure the protection of groundwater …