Comparative analysis of multi-sensor integrated indices for agricultural drought monitoring during the monsoon season in the Helmand River Basin, Afghanistan


Nabizada M. J., KÖYLÜ Ü.

Theoretical and Applied Climatology, vol.156, no.4, 2025 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 156 Issue: 4
  • Publication Date: 2025
  • Doi Number: 10.1007/s00704-025-05432-z
  • Journal Name: Theoretical and Applied Climatology
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, IBZ Online, PASCAL, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, BIOSIS, CAB Abstracts, Environment Index, Geobase, Index Islamicus, INSPEC, Pollution Abstracts, Veterinary Science Database
  • Erciyes University Affiliated: Yes

Abstract

In arid to semi-arid regions like Afghanistan, where climate uncertainty and limited water resources amplify the impact, agricultural drought poses a serious threat to food security and livelihoods. This study investigates the spatiotemporal dynamics of agricultural drought during the monsoon season (March to August) from 2000 to 2023 using the Vegetation Health Index (VHI) and Scaled Drought Condition Index (SDCI) in the Helmand River Basin (HRB), Afghanistan. The research evaluates the effectiveness of the standard VHI (α = 0.5) compared to a modified VHI (α = 0.68) and provides optimized combination weights for the SDCI based on correlation analysis with the Standardized Precipitation Index (SPI). The results indicate that drought was predominantly concentrated in the western, central, southern, and southwestern parts of HRB, including Hirat, Farah, Helmand, Uruzgan, Kandahar, Zabul, Paktika, and Paktya provinces over the study period. The findings identify 2000 as the driest year and 2020 as the greenest year within the study period. Peaks in extreme and severe drought were noted in 2000 and 2001, with a decreasing trend towards 2023. These findings confirm that both VHI and SDCI are effective tools for monitoring agricultural drought in this region, with SDCI displaying a slightly higher sensitivity to extreme drought conditions. This research underscores the importance of continuous drought monitoring through the integration of remotely sensed, observational data and methods such as Principal component analysis (PCA) and Analytical hierarchy process (AHP) for the determination of weights to enhance drought preparedness and resilience, ultimately supporting sustainable agricultural practices and food security in Afghanistan.