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Τίτλος: Application of geostatistical methods to groundwater salinization problems: A review
Συγγραφείς: Panagiotou, Constantinos F. 
Kyriakidis, Phaedon 
Tziritis, Evangelos 
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Λέξεις-κλειδιά: Geostatistical simulations;Groundwater salinization;Kriging;Multivariate statistics;Surrogate models
Ημερομηνία Έκδοσης: 1-Δεκ-2022
Πηγή: Journal of Hydrology, 2022, vol. 615
Volume: 615
Περίληψη: Groundwater salinization is considered to be one of the most severe and complex phenomena affecting coastal regions worldwide, occurring when high concentrations of water-soluble salts are present in groundwater systems. Geostatistics is a branch of statistics used to analyze and predict the spatio-temporal variability of such complex phenomena. In particular, numerous geostatistical approaches and technologies are currently used to identify and map salinity-affected regions, investigate how salinity indicators influence groundwater mechanisms, and eventually design optimal groundwater management policies. This article reviews recent key applications of geostatistical methods to address challenges relevant to groundwater salinization. The basic principles of geostatistics are briefly described, and numerous studies are discussed that employ geostatistical and multivariate tools for identifying the origin of salinity sources, clarifying the relationship among salinity indicators and groundwater processes, and propagating the uncertainty of the inputs to the outputs of either physically-based or surrogate models of relevant geological systems. Finally, several recommendations and future directions are identified with regards to the most popular methods and with regards to key geostatistical methods whose application in this thematic area is still very limited.
URI: https://hdl.handle.net/20.500.14279/29908
ISSN: 00221694
DOI: 10.1016/j.jhydrol.2022.128566
Rights: © Elsevier B.V.
Type: Article
Affiliation: Cyprus University of Technology 
ERATOSTHENES Centre of Excellence 
Soil and Water Resources Institute 
Geospatial Analytics Lab 
Publication Type: Peer Reviewed
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