Application of geostatistical methods to groundwater salinization problems: A review

被引:22
|
作者
Panagiotou, Constantinos F. [1 ,2 ]
Kyriakidis, Phaedon [1 ]
Tziritis, Evangelos [3 ]
机构
[1] Cyprus Univ Technol, Dept Civil Engn & Geomat, CY-3036 Limassol, Cyprus
[2] Eratosthenes Ctr Excellence, Dept Environm & Climate, Fragklinou Rousbelt 82, CY-3012 Limassol, Cyprus
[3] Hellen Agr Org, Soil & Water Resources Inst, Sindos 57400, Greece
关键词
Geostatistical simulations; Kriging; Multivariate statistics; Groundwater salinization; Surrogate models; ENSEMBLE KALMAN FILTER; SOUTH-EASTERN TUNISIA; SEAWATER INTRUSION; COASTAL AQUIFER; SALTWATER INTRUSION; QUALITY VARIABLES; SURROGATE MODELS; SALINITY; CONTAMINATION; UNCERTAINTY;
D O I
10.1016/j.jhydrol.2022.128566
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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 sys-tems. 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 mecha-nisms, and eventually design optimal groundwater management policies. This article reviews recent key appli-cations 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 multi-variate 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 di-rections 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.
引用
收藏
页数:12
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