Hybrid Methodologies for Groundwater Vulnerability Assessment
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Green Sustainable Science and Technology".
Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 4248
Special Issue Editors
Interests: water resources management and protection in the coastal plains, with a focus on water and nitrogen balance at basin scale and salinization processes; characterization and monitoring of dissolved contaminants in aquifers via different assessment methods; implementation of density-dependent groundwater flow models and reactive transport models
Special Issues, Collections and Topics in MDPI journals
Interests: hydrology; hydrogeology; groundwater flows; environmental science; water quality; geostatistical analysis; digital mapping; ecohydrology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Collegues,
The Sustainable Development Goals (SDGs) to be achieved by 2030, and in particular the sixth SDG, state the primary importance of protecting and restoring water-related ecosystems. Assessing the vulnerability of aquifers therefore becomes an essential preventive tool to achieve sustainable management of groundwater resources since population growth, along with the fast development in agricultural, commercial, industrial, and residential spheres of human life, has triggered the depletion and pollution of water resources, with clear detrimental effects at both regional and local scales. Vulnerability depends on the natural attenuation capacity offered by a set of physicochemical processes which are spatially dependent on morphological, hydrological, and geological characteristics of the site. Aquifer vulnerability can be estimated via different approaches which vary in terms of complexity, computational efforts, and data requirement, each of them with drawbacks and advantages: i) overlay/index methods, ii) process-based models, iii) statistical methods, and iv) hybrid methods. The latter integrate previously mentioned approaches using numerical strategies (e.g., machine learning) or different modeling approaches. This Special Issue calls for high-quality research papers on introducing new hibridizations strategies in the topics of groundwater vulnerability to agrochemicals leaching.
Dr. Micòl Mastrocicco
Dr. Gianluigi Busico
Guest Editors
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Keywords
- groundwater vulnerability
- agrochemicals leaching
- surface–groundwater modelling
- artificial intelligence
- hybridization
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