Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/12250
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dc.contributor.authorKhorrami, Behnamen_US
dc.contributor.authorGündüz, Orhanen_US
dc.date.accessioned2022-08-03T08:41:40Z-
dc.date.available2022-08-03T08:41:40Z-
dc.date.issued2022-
dc.identifier.urihttps://doi.org/10.1080/10106049.2022.2066197-
dc.identifier.urihttps://hdl.handle.net/11147/12250-
dc.description.abstractUnder the severe impacts of climate change, drought has become one of the most undesirable and complex natural phenomena with critical consequences for the environment, economy and society. The orthodox drought monitoring approaches use observations of meteorological stations, which are typically restricted in time and space. Remote sensing, conversely, provides continuous global coverage of a variety of hydro-meteorological variables that are influential in drought, and data extracted from remote sensing and modeling missions are now considered more practical and alluring for researchers. In this study, we applied a combination of field data, remotely sensed data and modeled data to detect and quantitatively analyze drought phenomena. To achieve this objective, we utilized Terrestrial Water Storage Anomalies (TWSA) estimations from GRACE mission, Normalized Difference Vegetation Index (NDVI) from MODIS mission, Surface Runoff (R) and Evapotranspiration from ERA5 reanalysis datasets and Soil Moisture (SM) from GLDAS data model to evaluate their feasibility in detecting recent droughts over Turkey. We validated the accuracy of several remote sensing-based indices (GRACE Drought Severity Index, Water Storage Deficit Index [WSDI], Soil Moisture Index, Standardized Runoff Index and NDVI) with the traditional indices (SPI and SPEI) calculated from in situ observations of precipitation. The results revealed that the GRACE-based WSDI gave the best performance with high correlations with the SPI index both temporally and spatially over Turkey. We also found that monthly and annual time series of WSDI agreed well with the SPI index with correlations of 0.69 and 0.73, respectively. The results of drought analysis also indicated that WSDI could be used as a proxy to standard meteorological drought indices over Turkey as it performed well to detect and characterize the recent droughts of Turkey based on its comparisons to SPI results.en_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.relation.ispartofGeocarto Internationalen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectDroughten_US
dc.subjectDrought severity indexen_US
dc.subjectGRACEen_US
dc.titleDetection and analysis of drought over Turkey with remote sensing and model-based drought indicesen_US
dc.typeArticleen_US
dc.authorid0000-0001-6302-0277en_US
dc.institutionauthorGündüz, Orhanen_US
dc.departmentİzmir Institute of Technology. Environmental Engineeringen_US
dc.identifier.wosWOS:000787226200001en_US
dc.identifier.scopus2-s2.0-85128747769en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1080/10106049.2022.2066197-
dc.contributor.affiliationDokuz Eylül Üniversitesien_US
dc.contributor.affiliationIzmir Institute of Technologyen_US
dc.relation.issn1010-6049en_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextembargo_20250701-
crisitem.author.dept03.07. Department of Environmental Engineering-
Appears in Collections:Environmental Engineering / Çevre Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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