Combining remote sensing and modeling approaches to assess soil salinity in irrigated areas of the Aral Sea Basin

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cg.contributor.affiliationInternational Water Management Instituteen
cg.coverage.countryUzbekistan
cg.coverage.iso3166-alpha2UZ
cg.coverage.regionCentral Asia
cg.creator.identifierKakhramon Djumaboev: 0000-0002-0061-3603
cg.identifier.doihttps://doi.org/10.29258/cajwr/2019-r1.v5-2/64-81engen
cg.identifier.urlhttps://cloud.mail.ru/public/25iy/4eATZdfpwen
cg.issn2522-9060en
cg.issue2en
cg.journalCentral Asian Journal of Water Researchen
cg.reviewStatusPeer Reviewen
cg.volume5en
dc.contributor.authorIbrakhimov, M.en
dc.contributor.authorAwan, U. K.en
dc.contributor.authorSultanov, M.en
dc.contributor.authorAkramkhanov, A.en
dc.contributor.authorDjumaboev, Kakhramonen
dc.contributor.authorConrad, C.en
dc.contributor.authorLamers, J.en
dc.date.accessioned2020-06-15T05:36:58Zen
dc.date.available2020-06-15T05:36:58Zen
dc.identifier.urihttps://hdl.handle.net/10568/108474
dc.titleCombining remote sensing and modeling approaches to assess soil salinity in irrigated areas of the Aral Sea Basinen
dcterms.abstractAccurate assessment of the soil salinization is an important step for mitigation of agricultural land degradation. Remote sensing (RS) is widely used for salinity assessment, but knowledge on prediction precision is lacking. A RS-based salinity assessment in Khorezm allows for modest reliable prediction with weak (R2=0.15–0.29) relationship of the salinity maps produced with RS and interpolation of electromagnetic EM38 during growth periods and more reliable (R2=0.35–0.56) beyond irrigation periods. Modeling with HYDRUS-1D at slightly, moderately and highly saline sites at various depths showed that irrigation forces salts to move to deeper layers: salts reappear in the upper profile during dry periods. Beyond irrigation events, salts gradually accumulated in the upper soil layers without fluctuations. Coupling RS techniques with numerical modeling provided better insight into salinity dynamics than any of these approaches alone. This should be of interest to farmers and policy makers since the combination of methods will allow for better planning and management.en
dcterms.accessRightsOpen Access
dcterms.available2020-05-27
dcterms.bibliographicCitationIbrakhimov, M.; Awan, U. K.; Sultanov, M.; Akramkhanov, A.; Djumaboev, Kakhramon; Conrad, C.; Lamers, J. 2019. Combining remote sensing and modeling approaches to assess soil salinity in irrigated areas of the Aral Sea Basin. Central Asian Journal of Water Research, 5(2):100-116. [doi: https://doi.org/10.29258/CAJWR/2019-R1.v5-2/64-81eng]en
dcterms.extentp. 64-81en
dcterms.issued2020-05-27
dcterms.languageen
dcterms.licenseCopyrighted; all rights reserved
dcterms.publisherKazakh-German Universityen
dcterms.subjectsoil salinizationen
dcterms.subjectirrigated landen
dcterms.subjectremote sensingen
dcterms.subjectmodellingen
dcterms.subjectforecastingen
dcterms.subjecttechniquesen
dcterms.subjectsoil profilesen
dcterms.subjectgroundwateren
dcterms.subjectirrigated farmingen
dcterms.subjectcottonen
dcterms.subjectcase studiesen
dcterms.typeJournal Article

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