Hydrostratigraphic analysis of the Darling River valley (Australia) using electromagnetic induction data and a spatially constrained algorithm for quasi-three-dimensional electrical conductivity imaging

Efforts are being made to improve the irrigation efficiency in the Murray-Darling River Basin, Australia, to deal with predicted rainfall decline and to reduce the incidence of secondary soil and water salinization. The latter commonly occurs as a result of locating water reservoirs upon relic drain...

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Vydáno v:	Hydrogeology journal Ročník 19; číslo 5; s. 1053 - 1063
Hlavní autoři:	Triantafilis, John, Santos, Fernando Acácio Monteiro
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer-Verlag 01.08.2011 Springer Nature B.V
Témata:	Algorithms Aquatic Pollution Constraints Earth and Environmental Science Earth Sciences Electrical conductivity Electrical resistivity Environmental monitoring Freshwater Geology Geophysics Geophysics/Geodesy Hydrogeology Hydrology Hydrology/Water Resources Imaging Irrigation Irrigation efficiency Resistivity River basins Rivers Salinity Salinization Soil (material) Soil types Spatial distribution Stratigraphy Waste Water Technology Water Management Water Pollution Control Water Quality/Water Pollution Australia Salinization General hydrogeology Australia Electromagnetic induction Geophysical methods
ISSN:	1431-2174, 1435-0157
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Abstract	Efforts are being made to improve the irrigation efficiency in the Murray-Darling River Basin, Australia, to deal with predicted rainfall decline and to reduce the incidence of secondary soil and water salinization. The latter commonly occurs as a result of locating water reservoirs upon relic drainage channels. To better manage irrigation, information is required about the spatial distribution of soil type and the stratigraphic features capable of redistributing deep-draining water. In previous research, electromagnetic (EM) induction instruments (e.g. EM38 and EM34) have been used to map the distribution of soil type, hydrological processes (e.g. deep drainage) and vadose-zone features. The aim of this research is to demonstrate how a joint inversion of EM38 and EM34 data, using a one-dimensional spatially constrained algorithm for quasi three-dimensional (quasi-3D) electrical conductivity imaging, can be used to infer the areal distribution of soil types and physiographic and hydrogeological units. The quasi-3D modeling of true electrical conductivity provides a framework for future environmental monitoring and management to mitigate the hydrological processes that drive localized secondary salinization in the study area.
AbstractList	Efforts are being made to improve the irrigation efficiency in the Murray-Darling River Basin, Australia, to deal with predicted rainfall decline and to reduce the incidence of secondary soil and water salinization. The latter commonly occurs as a result of locating water reservoirs upon relic drainage channels. To better manage irrigation, information is required about the spatial distribution of soil type and the stratigraphic features capable of redistributing deep-draining water. In previous research, electromagnetic (EM) induction instruments (e.g. EM38 and EM34) have been used to map the distribution of soil type, hydrological processes (e.g. deep drainage) and vadose-zone features. The aim of this research is to demonstrate how a joint inversion of EM38 and EM34 data, using a one-dimensional spatially constrained algorithm for quasi three-dimensional (quasi-3D) electrical conductivity imaging, can be used to infer the areal distribution of soil types and physiographic and hydrogeological units. The quasi-3D modeling of true electrical conductivity provides a framework for future environmental monitoring and management to mitigate the hydrological processes that drive localized secondary salinization in the study area.Original Abstract: Dans le bassin de la riviere Murray-Darling, Australie, des efforts sont deployes afin d'ameliorer l'efficacite de l'irrigation pour faire face a la diminution prevue de la pluviometrie et pour reduire l'incidence de la salinisation secondaire des sols et de l'eau. Cette derniere est habituellement due aux consequences du positionnement de reservoirs d'eau sur d'anciens chenaux de drainage. Pour ameliorer la gestion de l'irrigation, il est necessaire de disposer d'informations sur la distribution spatiale des types de sols et sur les caracteristiques stratigraphiques capables de modifier l'ecoulement des eaux de drainage profond. Au cours d'une recherche anterieure, des appareils d'induction electromagnetique - EM - (tels que EM38 et EM34) ont ete utilises pour cartographier la distribution des types de sols, les processus hydrologiques (comme le drainage profond) et les proprietes de la zone non saturee. L'objectif de la presente recherche est de demontrer comment une inversion conjointe de donnees EM38 et EM34, a l'aide d'un algorithme contraint spatialement en une dimension pour l'imagerie quasi-tridimensionnelle (quasi-3D) de la conductivite electrique, peut etre utilisee pour deduire la distribution spatiale des types de sol et des unites geomorphologiques et hydrogeologiques. La modelisation quasi-3D de la conductivite electrique vraie fournit un guide pour la gestion et la surveillance futures de l'environnement dans le but de limiter les processus hydrologiques qui conduisent a des salinisations locales secondaires dans le secteur d'etude. Efforts are being made to improve the irrigation efficiency in the Murray-Darling River Basin, Australia, to deal with predicted rainfall decline and to reduce the incidence of secondary soil and water salinization. The latter commonly occurs as a result of locating water reservoirs upon relic drainage channels. To better manage irrigation, information is required about the spatial distribution of soil type and the stratigraphic features capable of redistributing deep-draining water. In previous research, electromagnetic (EM) induction instruments (e.g. EM38 and EM34) have been used to map the distribution of soil type, hydrological processes (e.g. deep drainage) and vadose-zone features. The aim of this research is to demonstrate how a joint inversion of EM38 and EM34 data, using a one-dimensional spatially constrained algorithm for quasi three-dimensional (quasi-3D) electrical conductivity imaging, can be used to infer the areal distribution of soil types and physiographic and hydrogeological units. The quasi-3D modeling of true electrical conductivity provides a framework for future environmental monitoring and management to mitigate the hydrological processes that drive localized secondary salinization in the study area. Efforts are being made to improve the irrigation efficiency in the Murray-Darling River Basin, Australia, to deal with predicted rainfall decline and to reduce the incidence of secondary soil and water salinization. The latter commonly occurs as a result of locating water reservoirs upon relic drainage channels. To better manage irrigation, information is required about the spatial distribution of soil type and the stratigraphic features capable of redistributing deep-draining water. In previous research, electromagnetic (EM) induction instruments (e.g. EM38 and EM34) have been used to map the distribution of soil type, hydrological processes (e.g. deep drainage) and vadose-zone features. The aim of this research is to demonstrate how a joint inversion of EM38 and EM34 data, using a one-dimensional spatially constrained algorithm for quasi three-dimensional (quasi-3D) electrical conductivity imaging, can be used to infer the areal distribution of soil types and physiographic and hydrogeological units. The quasi-3D modeling of true electrical conductivity provides a framework for future environmental monitoring and management to mitigate the hydrological processes that drive localized secondary salinization in the study area.[PUBLICATION ABSTRACT]
Author	Santos, Fernando Acácio Monteiro Triantafilis, John
Author_xml	– sequence: 1 givenname: John surname: Triantafilis fullname: Triantafilis, John email: j.triantafilis@unsw.edu.au organization: School of Biological, Earth and Environmental Sciences, The University of New South Wales – sequence: 2 givenname: Fernando Acácio Monteiro surname: Santos fullname: Santos, Fernando Acácio Monteiro organization: Universidade de Lisboa, CGUL-Instituto Don Luís Laboratório Associado
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CitedBy_id	crossref_primary_10_2136_sssaj2015_06_0238 crossref_primary_10_1190_geo2012_0053_1 crossref_primary_10_1016_j_compag_2015_02_013 crossref_primary_10_1002_nsg_12238 crossref_primary_10_1016_j_envsoft_2013_01_012 crossref_primary_10_1190_geo2011_0507_1 crossref_primary_10_1016_j_scitotenv_2016_10_224 crossref_primary_10_1016_j_scitotenv_2019_05_037 crossref_primary_10_1016_j_geoderma_2019_01_033 crossref_primary_10_3390_rs15143527 crossref_primary_10_1002_ldr_3684 crossref_primary_10_1016_j_jappgeo_2013_06_004 crossref_primary_10_2136_sssaj2014_02_0078 crossref_primary_10_1016_j_agwat_2023_108330
Cites_doi	10.1071/SR09013 10.1071/SR05037 10.2136/vzj2009.0088 10.1071/SR08240 10.1071/EA02176 10.2136/sssaj2002.0673 10.1016/0022-1694(94)90155-4 10.1016/j.compag.2004.11.006 10.1071/SR03149 10.2136/vzj2006.0120 10.1071/SR09149 10.1016/j.jappgeo.2009.12.003 10.2134/agronj2008.0112 10.1016/j.jappgeo.2004.04.005 10.1079/SUM2002178 10.1111/j.1745-6584.2008.00490.x 10.5962/bhl.title.131080 10.1190/1.2895521 10.1190/1.1512744 10.1190/1.1439028 10.1190/1.1443571
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Keywords	Salinization General hydrogeology Australia Electromagnetic induction Geophysical methods
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SubjectTerms	Algorithms Aquatic Pollution Constraints Earth and Environmental Science Earth Sciences Electrical conductivity Electrical resistivity Environmental monitoring Freshwater Geology Geophysics Geophysics/Geodesy Hydrogeology Hydrology Hydrology/Water Resources Imaging Irrigation Irrigation efficiency Resistivity River basins Rivers Salinity Salinization Soil (material) Soil types Spatial distribution Stratigraphy Waste Water Technology Water Management Water Pollution Control Water Quality/Water Pollution
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Title	Hydrostratigraphic analysis of the Darling River valley (Australia) using electromagnetic induction data and a spatially constrained algorithm for quasi-three-dimensional electrical conductivity imaging
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