Development and Evaluation of a Principal Component-Based Composite Drought Index Considering Temporal Lag Dependencies Among Indices.
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| Title: | Development and Evaluation of a Principal Component-Based Composite Drought Index Considering Temporal Lag Dependencies Among Indices. |
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| Authors: | Raziei, Tayeb1 (AUTHOR) tayebrazi@yahoo.com, Miri, Morteza1 (AUTHOR), Santos, João Filipe2 (AUTHOR), Zand, Mehran1 (AUTHOR), Pereira, Luis S.3 (AUTHOR) |
| Source: | Water Resources Management. Sep2025, Vol. 39 Issue 11, p5949-5970. 22p. |
| Subject Terms: | *Principal components analysis, *Soil moisture, *Statistical correlation, *Normalized difference vegetation index, *Plant health |
| Geographic Terms: | Iran |
| Abstract: | This study introduces a composite drought index (CDI) that integrates multiple drought indices, including the Simplified Standardized Precipitation Index (SSPI), Simplified Standardized Precipitation-Evapotranspiration Index (SSPEI), soil moisture measured at depths of 0–10 cm (SM1) and 10–40 cm (SM2), Normalized Difference Vegetation Index (NDVI), and Vegetation Health Index (VHI), using principal component analysis (PCA). Data for Precipitation, temperature, SM1, SM2, NDVI, and VHI were re-gridded to a spatial resolution of 0.25° × 0.25° and used to compute SSPI and SSPEI over 3-, 6-, 9-, and 12-month timescales for grid points across Iran. SM1, SM2, NDVI, and VHI were similarly aggregated at these timescales and standardized using Box-Cox transformation. To facilitate PCA, the temporal lag dependency was adjusted to align all indices with SSPI as the primary reference, eliminating lag correlations. The analysis revealed a strong correlation between SSPI and SSPEI (r > 0.8) across most grids and timescales, alongside significant but weaker correlations with SM1 and SM2 (r > 0.5), VHI (r > 0.6), and NDVI (r > 0.4). The first principal component (PC1), representing the CDI, captured the majority of variance in the data matrix. Additional PCs explaining over 10% of the variance were combined to form a weighted version of the index (CDIw). While CDI showed the strongest correlation with SSPI and SSPEI, CDIw exhibited greater correlations with SM1, SM2, VHI, and NDVI, though with a slight reduction in its relationship with SSPI and SSPEI. Both CDI and CDIw demonstrated strong correlations with the Palmer Drought Severity Index, confirming their effectiveness in monitoring drought conditions in the study area. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 188452514 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Development and Evaluation of a Principal Component-Based Composite Drought Index Considering Temporal Lag Dependencies Among Indices. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Raziei%2C+Tayeb%22">Raziei, Tayeb</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> tayebrazi@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Miri%2C+Morteza%22">Miri, Morteza</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Santos%2C+João+Filipe%22">Santos, João Filipe</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zand%2C+Mehran%22">Zand, Mehran</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pereira%2C+Luis+S%2E%22">Pereira, Luis S.</searchLink><relatesTo>3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Water+Resources+Management%22">Water Resources Management</searchLink>. Sep2025, Vol. 39 Issue 11, p5949-5970. 22p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Principal+components+analysis%22">Principal components analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Soil+moisture%22">Soil moisture</searchLink><br />*<searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink><br />*<searchLink fieldCode="DE" term="%22Normalized+difference+vegetation+index%22">Normalized difference vegetation index</searchLink><br />*<searchLink fieldCode="DE" term="%22Plant+health%22">Plant health</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Iran%22">Iran</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study introduces a composite drought index (CDI) that integrates multiple drought indices, including the Simplified Standardized Precipitation Index (SSPI), Simplified Standardized Precipitation-Evapotranspiration Index (SSPEI), soil moisture measured at depths of 0–10 cm (SM1) and 10–40 cm (SM2), Normalized Difference Vegetation Index (NDVI), and Vegetation Health Index (VHI), using principal component analysis (PCA). Data for Precipitation, temperature, SM1, SM2, NDVI, and VHI were re-gridded to a spatial resolution of 0.25° × 0.25° and used to compute SSPI and SSPEI over 3-, 6-, 9-, and 12-month timescales for grid points across Iran. SM1, SM2, NDVI, and VHI were similarly aggregated at these timescales and standardized using Box-Cox transformation. To facilitate PCA, the temporal lag dependency was adjusted to align all indices with SSPI as the primary reference, eliminating lag correlations. The analysis revealed a strong correlation between SSPI and SSPEI (r > 0.8) across most grids and timescales, alongside significant but weaker correlations with SM1 and SM2 (r > 0.5), VHI (r > 0.6), and NDVI (r > 0.4). The first principal component (PC1), representing the CDI, captured the majority of variance in the data matrix. Additional PCs explaining over 10% of the variance were combined to form a weighted version of the index (CDIw). While CDI showed the strongest correlation with SSPI and SSPEI, CDIw exhibited greater correlations with SM1, SM2, VHI, and NDVI, though with a slight reduction in its relationship with SSPI and SSPEI. Both CDI and CDIw demonstrated strong correlations with the Palmer Drought Severity Index, confirming their effectiveness in monitoring drought conditions in the study area. [ABSTRACT FROM AUTHOR] |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11269-025-04235-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 5949 Subjects: – SubjectFull: Principal components analysis Type: general – SubjectFull: Soil moisture Type: general – SubjectFull: Statistical correlation Type: general – SubjectFull: Normalized difference vegetation index Type: general – SubjectFull: Plant health Type: general – SubjectFull: Iran Type: general Titles: – TitleFull: Development and Evaluation of a Principal Component-Based Composite Drought Index Considering Temporal Lag Dependencies Among Indices. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Raziei, Tayeb – PersonEntity: Name: NameFull: Miri, Morteza – PersonEntity: Name: NameFull: Santos, João Filipe – PersonEntity: Name: NameFull: Zand, Mehran – PersonEntity: Name: NameFull: Pereira, Luis S. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 09204741 Numbering: – Type: volume Value: 39 – Type: issue Value: 11 Titles: – TitleFull: Water Resources Management Type: main |
| ResultId | 1 |
