Scrutinizing different predictive modeling validation methodologies and data-partitioning strategies: new insights using groundwater modeling case study.

Groundwater salinity is a critical factor affecting water quality and ecosystem health, with implications for various sectors including agriculture, industry, and public health. Hence, the reliability and accuracy of groundwater salinity predictive models are paramount for effective decision-making in managing groundwater resources. This pioneering study presents the validation of a predictive model aimed at forecasting groundwater salinity levels using three different validation methods and various data partitioning strategies.

Management of saltwater intrusion using 3D numerical modelling: a first for Pacific Island country of Vanuatu.

Small island countries like Vanuatu are facing the brunt of climate change, sea level rise (SLR), tropical cyclones, and limited or declining access to freshwater. The Tagabe coastal aquifer in Port Vila (the capital of Vanuatu) shows the presence of salinity, indicating saltwater intrusion (SWI). This study aims to develop and evaluate effective SWI management strategies for Tagabe coastal aquifer.

Integrating numerical modelling and scenario-based sensitivity analysis for saltwater intrusion management: case study of a complex heterogeneous island aquifer system.

Population growth, industrialisation and increasing agricultural demands have significantly stressed groundwater resources in Pacific Island countries (PICs). Climate change and sea-level rise also affect the groundwater resources in PICs. These anthropogenic and natural factors give rise to saltwater intrusion (SWI), a major growing environmental problem in the PICs.