Random Forest modelling framework for sustainable management of traditional groundwater systems in data-scarce regions

Integrating CCME-WQI and Machine Learning for Groundwater Quality in the Sedrata Plain

Abstract The quality of groundwater in the Sedrata plain in northeastern Algeria is under increasing pressure due to semi-arid climatic conditions, geological mineralisation and growing agricultural demand. This study provides a thorough physicochemical characterisation of phreatic aquifer waters collected from 25 open...

Machine Learning Approaches for Groundwater Salinity Prediction Under Salt Dome Influence in Arid Regions

Groundwater salinization near salt domes is a major threat to water resources in arid and semi-arid plains, causing a persistent decline in water quality worldwide. Machine learning offers an effective approach for evaluating this risk. This study tested three algorithms—Artificial Neural Network (ANN), Support Vector...

Machine Learning-Based Groundwater Level Forecasting in a Semi-Arid Agricultural Area: Insights from SHAP, PELT, and Mann–Kendall Analyses in the Saïss Basin, Morocco

This study proposes an innovative framework that combines hydroclimatic and agro-environmental predictors, including nitrate concentration and NDVI, with climatic factors such as Rainfall, temperature, and evapotranspiration to forecast piezometric level variations in the Saïss Basin, Morocco. Eight Machine Learning (M...

Hybrid machine learning and kriging approaches for predicting and mapping soil salinity in an arid region

Results showed that hybrid ML-Kriging models outperformed standalone algorithms, with RF–SK achieving the best performance, and highlight the value of hybrid ML-Kriging for accurate and transferable salinity prediction in arid irrigated systems.

Machine Learning-Based Groundwater Level Simulation for Industrial Water Management: A Comparative Study of ARIMA, BP-ANN and Random Forest

Timely and accurate simulation of regional groundwater level dynamics is critical to guarantee stable water supply for agricultural production and manufacturing sectors in arid semi-arid loess regions. This study adopts Variable Projection Importance (VPI) to screen feature variables controlling groundwater fluctuation...

Daily River Suspended Sediment Load Forecasting Using Artificial Intelligence Models