Assessment and Monitoring of Drought Using Satellite and Meteorological Time Series Data (Case Study: Zanjan Province)
Objective: This study aims to conduct a comparative analysis of drought indices by integrating meteorological and satellite-based indices to enhance the spatial and temporal monitoring of drought in Zanjan Province.Method: Two meteorological drought indices, Standardized Precipitation Index (SPI) an...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | fas |
| Published: |
University of Terhan press
2025-03-01
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| Series: | اکوهیدرولوژی |
| Subjects: | |
| Online Access: | https://ije.ut.ac.ir/article_100742_c1bbe6b350313cb3431991c49a3ea267.pdf |
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| Summary: | Objective: This study aims to conduct a comparative analysis of drought indices by integrating meteorological and satellite-based indices to enhance the spatial and temporal monitoring of drought in Zanjan Province.Method: Two meteorological drought indices, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI), were calculated for different time scales (1, 3, 6, 9, and 12 months) from 2004 to 2022. Additionally, five satellite-based drought indices—Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI)—were extracted for the same period. The results of these indices were compared to evaluate their effectiveness in drought monitoring.Results: The SPI and SPEI indices indicated that most of the studied years were in a normal condition, with excessive rainfall in 2019. SPEI identified drought conditions in 2008, 2011, and 2022, while SPI recorded drought in 2007 and 2022. Among the satellite-based indices, NDVI showed the highest correlation with meteorological indices (R² = 0.82), whereas VHI exhibited the lowest correlation (R² = 0.57).Conclusions: The study highlights the effectiveness of NDVI in monitoring drought compared to other satellite-based indices. The findings provide a basis for informed decision-making in utilizing remote sensing data for rapid drought assessment. |
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| ISSN: | 2423-6101 |