Groundwater Vulnerability Assessments: Integrating Experimental, Modeling, and Mapping Techniques

About this Research Topic

Background

Groundwater vulnerability is a critical area of research that examines the susceptibility of groundwater to contamination from surface pollutants. This field has gained increasing importance due to emerging contaminants such as heavy metals, radionuclides, and agricultural chemicals penetrating soil, surface water and groundwater worldwide. Shallow aquifers are particularly at risk from surface pollutants, while deeper aquifers are generally more protected unless compromised by faulty drilling or pollutant injection. Since the 1960s, the concept of groundwater vulnerability has evolved significantly, transitioning from basic hydrogeological assessments to using sophisticated numerical evaluations incorporating modern Geographic Information Systems (GIS) and machine learning (ML) techniques. Despite these advancements, significant gaps must be addressed to improve our understanding of the complex interactions between contaminants, soil, surface water, and groundwater systems. This necessitates further research to develop more accurate and comprehensive vulnerability assessments.

This research topic aims to advance the understanding and knowledge of groundwater vulnerability by integrating experimental, modeling, and mapping methods. The primary objective includes exploring new experimental and numerical methods, applying GIS and ML techniques, and conducting field and modeling investigations to map groundwater vulnerability at various scales—from local boreholes to the regional scale. Additionally, the research seeks to elucidate geochemical processes such as sorption-desorption, assess the impact of climate change on groundwater systems, and evaluate the attenuation capabilities of pollutants within both the unsaturated and saturated zones. The Special Issue will help fill knowledge gaps and provide more robust groundwater protection and management.

To gather further insights into the complexity of groundwater vulnerability, we welcome articles addressing, but not limited to, the following themes:
- Experimental and numerical deterministic and statistical methods, including applying GIS and ML techniques.
- Results of field and modeling investigations conducted for mapping groundwater vulnerability at different scales.
- Geochemical processes, including sorption-desorption processes.
- Effects of climate change include rising temperature, precipitation decrease or increase, land degradation, surface flooding, rising groundwater, flooding, and extreme events.
- Assessment of the attenuation ability of pollutants within the unsaturated (vadose) and saturated (aquifer) zones and the assessment of the environmental half-life of contaminants.
- Other research topics related to assessing soil and groundwater vulnerability and protectability.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: Groundwater Vulnerability Assessment, Risk Assessment and Decision Making, Remediation and Stewardship, Prediction and Uncertainty Evaluation, Field Observations, Numerical Modelling, Groundwater and Soil Pollution, Machine Learning, GIS and Mapping, Artificial Intelligence (AI) and Machine Learning Models

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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