Impact of Long-Term Drought on Surface Water and Water Balance Variations in Iran: Insights from Highland and Lowland Regions.
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| Title: | Impact of Long-Term Drought on Surface Water and Water Balance Variations in Iran: Insights from Highland and Lowland Regions. |
|---|---|
| Authors: | Kazemi Garajeh, Mohammad1,2 (AUTHOR), Abdoli, Nastaran3 (AUTHOR), Seyedebrahimi, Ebrahim4 (AUTHOR), Naboureh, Amin5 (AUTHOR) amin.nabore@mails.ucas.ac.cn, Kurdpour, Iman6 (AUTHOR), Bakhshi Lomer, Amir Reza7 (AUTHOR), Sadeqi, Amin8 (AUTHOR), Mirzaei, Saham9 (AUTHOR) |
| Source: | Remote Sensing. Oct2024, Vol. 16 Issue 19, p3636. 19p. |
| Subjects: | Time series analysis, Remote computing, Computing platforms, Remote sensing, Water supply, Drought management |
| Geographic Terms: | Iran |
| Abstract: | Droughts have a significant impact on surface water resources, especially in arid and semi-arid regions. Computational and data handling limitations have constrained previous time-series analyses. However, advances in cloud computing services and remote sensing technology allow for a more detailed examination. This study integrates multi-source satellite-derived data with a cloud computing platform to assess the impact of long-term drought on surface water and water balance in Iran from 2000 to 2021. Given the varying effects of drought on highlands and lowlands, the analysis was conducted at three levels: the entire country, the highlands, and the lowlands. The results of this study reveal imbalances between water balance from 2000 to 2021, with notable disparities observed during 2000–2007, 2009–2014, and 2016–2019. The results also show varying drought trends (e.g., −1.22 in 2000 and −0.73 in 2021), with severe conditions captured in 2008 (SPI: −1.92). Additionally, our analysis illustrated that lowlands were more impacted by droughts compared to highlands. Long-term drought and permanent surface water had correlation values of 0.33 across the country, 0.33 in the highlands, and 0.31 in the lowlands. For seasonal surface water, coefficients were 0.18 for the entire country, 0.16 for the highlands, and 0.18 for the lowlands. Overall, long-term drought had minimal effect on reducing surface water. These findings show that drought is only part of the explanation for the decrease in surface water resources. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 180271386 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Impact of Long-Term Drought on Surface Water and Water Balance Variations in Iran: Insights from Highland and Lowland Regions. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kazemi+Garajeh%2C+Mohammad%22">Kazemi Garajeh, Mohammad</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Abdoli%2C+Nastaran%22">Abdoli, Nastaran</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Seyedebrahimi%2C+Ebrahim%22">Seyedebrahimi, Ebrahim</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Naboureh%2C+Amin%22">Naboureh, Amin</searchLink><relatesTo>5</relatesTo> (AUTHOR)<i> amin.nabore@mails.ucas.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Kurdpour%2C+Iman%22">Kurdpour, Iman</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bakhshi+Lomer%2C+Amir+Reza%22">Bakhshi Lomer, Amir Reza</searchLink><relatesTo>7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sadeqi%2C+Amin%22">Sadeqi, Amin</searchLink><relatesTo>8</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mirzaei%2C+Saham%22">Mirzaei, Saham</searchLink><relatesTo>9</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Oct2024, Vol. 16 Issue 19, p3636. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Time+series+analysis%22">Time series analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+computing%22">Remote computing</searchLink><br /><searchLink fieldCode="DE" term="%22Computing+platforms%22">Computing platforms</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Water+supply%22">Water supply</searchLink><br /><searchLink fieldCode="DE" term="%22Drought+management%22">Drought management</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Iran%22">Iran</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Droughts have a significant impact on surface water resources, especially in arid and semi-arid regions. Computational and data handling limitations have constrained previous time-series analyses. However, advances in cloud computing services and remote sensing technology allow for a more detailed examination. This study integrates multi-source satellite-derived data with a cloud computing platform to assess the impact of long-term drought on surface water and water balance in Iran from 2000 to 2021. Given the varying effects of drought on highlands and lowlands, the analysis was conducted at three levels: the entire country, the highlands, and the lowlands. The results of this study reveal imbalances between water balance from 2000 to 2021, with notable disparities observed during 2000–2007, 2009–2014, and 2016–2019. The results also show varying drought trends (e.g., −1.22 in 2000 and −0.73 in 2021), with severe conditions captured in 2008 (SPI: −1.92). Additionally, our analysis illustrated that lowlands were more impacted by droughts compared to highlands. Long-term drought and permanent surface water had correlation values of 0.33 across the country, 0.33 in the highlands, and 0.31 in the lowlands. For seasonal surface water, coefficients were 0.18 for the entire country, 0.16 for the highlands, and 0.18 for the lowlands. Overall, long-term drought had minimal effect on reducing surface water. These findings show that drought is only part of the explanation for the decrease in surface water resources. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs16193636 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 3636 Subjects: – SubjectFull: Time series analysis Type: general – SubjectFull: Remote computing Type: general – SubjectFull: Computing platforms Type: general – SubjectFull: Remote sensing Type: general – SubjectFull: Water supply Type: general – SubjectFull: Drought management Type: general – SubjectFull: Iran Type: general Titles: – TitleFull: Impact of Long-Term Drought on Surface Water and Water Balance Variations in Iran: Insights from Highland and Lowland Regions. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kazemi Garajeh, Mohammad – PersonEntity: Name: NameFull: Abdoli, Nastaran – PersonEntity: Name: NameFull: Seyedebrahimi, Ebrahim – PersonEntity: Name: NameFull: Naboureh, Amin – PersonEntity: Name: NameFull: Kurdpour, Iman – PersonEntity: Name: NameFull: Bakhshi Lomer, Amir Reza – PersonEntity: Name: NameFull: Sadeqi, Amin – PersonEntity: Name: NameFull: Mirzaei, Saham IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 16 – Type: issue Value: 19 Titles: – TitleFull: Remote Sensing Type: main |
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