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Combining remote sensing and hydrological modeling for assessing the dynamics of soil salinity in the Aral Sea Basin

Ibrakhimov, Mirzahayot and Sultanov, Murod and Conrad, Christopher and Lamers, John (2018) Combining remote sensing and hydrological modeling for assessing the dynamics of soil salinity in the Aral Sea Basin. Volkswagen Status Conference Between Europe and the Orient, 16-19 April 2018, Almaty.

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Abstract

Land salinization threatens sustainability of irrigated agriculture. It severely limits land productivity and hence rural livelihoods in the Aral Sea Basin (ASB). Sound monitoring and mapping techniques are required to define proper management countermeasures. However, traditional salinity monitoring methods are resource and time demanding yet limited in spatial and temporal coverage. This study aimed at assessing the predictive quality of soil salinity assessment with remote sensing (RS) tools in the basin’s irrigated areas. Salinity was assessed indirectly, from vegetation indices estimated from Landsat 5TM imagery in 75.5 ha irrigated area during 2008-2009. To assess the precision of salinity prediction, the HYDRUS-1D model was employed based on in-situ sampling for soil EC at depths of 0-30, 30-90 and >100 cm, measurements of groundwater depth and EC, irrigation amounts and evapotranspiration (FAO-56) from climate data. Daily salinity dynamics were modelled in slightly, moderately and highly saline spots, identified in the RS maps. The findings showed that an RS-based salinity assessment alone allows for modest reliable prediction only: the relationship of the salinity maps and empirical data collected with an electromagnetic EM38 device were weak (R2=0.15-0.29) during, but became more reliable (R2=0.35-0.56) beyond irrigation periods. Salinity modelling with HYDRUS-1D at slightly, moderately and highly saline sites at various depths underlined that under present irrigation and drainage infrastructure, salts tend to only move to deeper layers during water applications, but reappear in the profile during dry periods. In contrast, beyond irrigation events, salts gradually increased in the upper soil layers without fluctuations. We argue that coupling RS techniques with numerical modelling provided valuable insight into within-season salinity dynamics than any of these approaches alone. This should be of interest to farmers and policy makers in the ASB since the combination of methods will allow for better planning and management of melioration measures.

Item URL in elib:https://elib.dlr.de/125729/
Document Type:Conference or Workshop Item (Poster)
Title:Combining remote sensing and hydrological modeling for assessing the dynamics of soil salinity in the Aral Sea Basin
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ibrakhimov, MirzahayotUNSPECIFIEDUNSPECIFIED
Sultanov, MurodUNSPECIFIEDUNSPECIFIED
Conrad, ChristopherChristopher.Conrad (at) uni-wuerzburg.deUNSPECIFIED
Lamers, JohnCenter for Development Research (ZEF)UNSPECIFIED
Date:2018
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:remote sensing, hydrological modeling, dynamics of soil salinity, Aral Sea Basin
Event Title:Volkswagen Status Conference Between Europe and the Orient
Event Location:Almaty
Event Type:international Conference
Event Dates:16-19 April 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Deposited By: Wöhrl, Monika
Deposited On:08 Jan 2019 13:12
Last Modified:08 Jan 2019 13:12

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