Performance evaluation of composite remote sensing indices in drought assessment (case study: Chaharmahal and Bakhtiari Province, Iran)

Document Type : Original Article

Authors

1 M.A of Watershed Science and Engineering, Faculty of Natural Resources and Desert Studies, Yazd University, Iran

2 Assistant Professor, Faculty of Natural Resources and Desert Studies, Yazd University, Iran

3 Associate professor, Faculty of Natural Resources and Desert Studies, Yazd University, Iran

4 M.A of RS & GIS, Geography group, Yazd University, Iran

Abstract

Drought is a significant natural disaster that requires monitoring to control and minimize its damages. In addition to climate-based drought indices, remote sensing drought monitoring indices are widely used today, especially in regions with limited climate data. These indices utilize satellite images and provide valuable information, resulting in relatively good performance. Furthermore, composite drought indicators are relatively new and multi-variable indices that combine remote sensing indicators for monitoring drought. Studies have shown that the effectiveness of these indicators can also be influenced by the study region. Given the importance of evaluating the performance of new methods in monitoring drought, this study compared the performance of a composite drought monitoring index, CDI, with the VCI, TCI, VHI, and PCI in Chaharmahal and Bakhtiari Province, Iran. CDI is a combination of VCI, TCI, and PCI. The values of the indices were compared with the SPI for the period of 2001-2020, with a time lag of 0 to 8 months by calculating the determination coefficient. For each index, the lag time that provided the highest R2 was identified. Precipitation data from 19 rain gauge stations in the study area were used to calculate the SPI on 3 and 6-month time scales. The results showed that the CDI presents by far the highest correlation with SPI values. The coefficient of determination for the VCI on a 6-month time scale with a 3-month time lag was on average 0.30. For the TCI, the average R2 is 0.50 in both the 3 and 6-month time scales without a time lag. The average R2 for the VHI on a 6-month time scale with a 2-month time lag was 0.41. The average coefficient of determination for the PCI index on a 3-month time scale without a time lag was just 0.32. The CDI index provided the best performance, with an average R2 of 0.73 in both the 3 and 6-month time scales without a time lag. While VCI, TCI, and PCI individually showed weak matching with the SPI, combining them into the CDI resulted in a significant correlation with the SPI.

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References

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History

  • Receive Date: 13 September 2024
  • Revise Date: 14 November 2024
  • Accept Date: 04 December 2024

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