Agricultural drought monitoring in semi-arid and arid areas using perpendicular drought indices

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Thursday, 27 January 2011
Agricultural drought monitoring in semi-arid and arid areas using perpendicular drought indices
Washington State Convention Center
Alireza Shahabfar, University of Natural Resources and Applied Life Sciences , Vienna, Austria; and J. Eitzinger

In this study, the performance of two remote sensing drought indices, the Perpendicular Drought Index (PDI) and the Modified Perpendicular Drought Index (MPDI), derived from MODIS satellite images (MOD13A3 V005), were evaluated to detect the severity of drought phenomena based on temporal and spatial extensions. The correlations between these perpendicular indices and two other remote sensing indices (the Enhanced Vegetation Index (EVI) and Vegetation Condition Index (VCI)) with four water balance parameters (climatic water balance (CL), crop water balance (CR), monthly reference crop evapotranspiration (ETo), crop evapotranspiration (ETc) and required irrigation water (I)) in ten different agro-climatological zones of Iran from February 2000 until December 2005 were analyzed. In this study, winter wheat was selected as the reference crop because it grows in the majority of climatic conditions in Iran. Our results indicated that there is a statistically significant correlation between the PDI and MPDI indices and the mentioned water balance indices in several climatic regions. However, the correlations between EVI and VCI and the selected water balance parameters were not statistically significant. Furthermore, spatial analyses revealed that both PDI and MPDI showed acceptable performance in detecting crop water balance conditions. In a temporal analysis, the PDI index showed a greater ability to detect crop water balance conditions than the MPDI index in several winter wheat growing stages. As the majority of the area of Iran is characterized by semi-arid or arid climatic conditions and consider winter wheat as a main agricultural crop, the PDI index could be used as a simple structured remote sensing-based drought index in Iran and in other developing countries with similar climatic conditions.