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dc.contributor.authorSingh, Alka*
dc.contributor.authorBehrangi, Ali*
dc.contributor.authorFisher, Joshua B.*
dc.contributor.authorReager, John T.*
dc.date.accessioned2018-08-15T23:46:30Z
dc.date.available2018-08-15T23:46:30Z
dc.date.issued2018-05
dc.identifier.citationSingh A, Behrangi A, Fisher JB, Reager JT. On the Desiccation of the South Aral Sea Observed from Spaceborne Missions. Remote Sensing. 2018; 10(5):793.en_US
dc.identifier.issn2072-4292
dc.identifier.doi10.3390/rs10050793
dc.identifier.urihttp://hdl.handle.net/10150/628548
dc.description.abstractThe South Aral Sea has been massively affected by the implementation of a mega-irrigation project in the region, but ground-based observations have monitored the Sea poorly. This study is a comprehensive analysis of the mass balance of the South Aral Sea and its basin, using multiple instruments from ground and space. We estimate lake volume, evaporation from the lake, and the Amu Darya streamflow into the lake using strengths offered by various remote-sensing data. We also diagnose the attribution behind the shrinking of the lake and its possible future fate. Terrestrial water storage (TWS) variations observed by the Gravity Recovery and Climate Experiment (GRACE) mission from the Aral Sea region can approximate water level of the East Aral Sea with good accuracy (1.8% normalized root mean square error (RMSE), and 0.9 correlation) against altimetry observations. Evaporation from the lake is back-calculated by integrating altimetry-based lake volume, in situ streamflow, and Global Precipitation Climatology Project (GPCP) precipitation. Different evapotranspiration (ET) products (Global Land Data Assimilation System (GLDAS), the Water Gap Hydrological Model (WGHM)), and Moderate-Resolution Imaging Spectroradiometer (MODIS) Global Evapotranspiration Project (MOD16) significantly underestimate the evaporation from the lake. However, another MODIS based Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) ET estimate shows remarkably high consistency (0.76 correlation) with our estimate (based on the water-budget equation). Further, streamflow is approximated by integrating lake volume variation, PT-JPL ET, and GPCP datasets. In another approach, the deseasonalized GRACE signal from the Amu Darya basin was also found to approximate streamflow and predict extreme flow into the lake by one or two months. They can be used for water resource management in the Amu Darya delta. The spatiotemporal pattern in the Amu Darya basin shows that terrestrial water storage (TWS) in the central region (predominantly in the primary irrigation belt other than delta) has increased. This increase can be attributed to enhanced infiltration, as ET and vegetation index (i.e., normalized difference vegetation index (NDVI)) from the area has decreased. The additional infiltration might be an indication of worsening of the canal structures and leakage in the area. The study shows how altimetry, optical images, gravimetric and other ancillary observations can collectively help to study the desiccating Aral Sea and its basin. A similar method can be used to explore other desiccating lakes.en_US
dc.description.sponsorshipNASA GRACE; GRACE-FO [NNH15ZDA001NGRACE]; NASA Energy and Water Cycle Study [NH13ZDA001N-NEWS]; NASA SUSMAPen_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.urlhttp://www.mdpi.com/2072-4292/10/5/793en_US
dc.rights© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.en_US
dc.subjectlake levelen_US
dc.subjectlake volumeen_US
dc.subjectevaporationen_US
dc.subjectstreamflowen_US
dc.subjectGravity Recovery and Climate Experiment (GRACE)en_US
dc.subjectaltimetryen_US
dc.subjectLandsaten_US
dc.subjectAral Seaen_US
dc.titleOn the Desiccation of the South Aral Sea Observed from Spaceborne Missionsen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Dept Hydrol & Atmospher Scien_US
dc.identifier.journalREMOTE SENSINGen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
dc.source.journaltitleRemote Sensing
dc.source.volume10
dc.source.issue5
dc.source.beginpage793
refterms.dateFOA2018-08-15T23:46:31Z


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