Document Type : Original Article
Authors
1 Department of Agricultural, Payame Noor university, Tehran, Iran
2 Department of Agricultural, Payame Noor university, Tehran, Iran.
Abstract
The lack of coverage of meteorological stations and the spatial-temporal heterogeneity of data have made accurate assessment of drought in metropolitan cities such as Tehran uncertain. This study aims to provide an integrated framework for drought monitoring by integrating remote sensing indices VCI from MOD13A2, TCI from MOD11A2, PCI from satellite precipitation product, and SMCI from soil moisture along with meteorological-hydrological indices (SPI, SPEI, and PDSI) for Tehran and its suburbs during the period 2000 to 2022. Preprocessing and extraction of indices were performed in Google Earth Engine and then correlation between indices at monthly, seasonal, and annual scales was analyzed using Mann-Kendall and age-slope tests, trends, and Pearson coefficient. The results showed that precipitation-based indices (SPI and PCI) have the greatest ability to explain short-term changes and show a high correlation with the soil moisture status index SMCI; in contrast, VCI responds to moisture fluctuations with a time lag, and TCI has an inverse and significant relationship with drought severity at long-term scales (PDSI/SPEI). From a temporal perspective, summers, with a combination of rainfall deficiency and heat stress, recorded the highest vulnerability, and the years 2008, 2010, and 2016 were the most severe drought periods. Convergence of evidence shows that the proposed multi-attribute approach, while reducing uncertainty, provides a more accurate picture of urban drought dynamics and can be the basis for water demand management planning, early warning, and urban greening model modification.
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