Assessment of drought in agricultural areas by combining meteorological data and remote sensing data

Droughts during the growing season are projected to increase in frequency and severity in Iran. Thus, area-wide monitoring of agricultural drought in this region is becoming more and more important. Precipitation patterns changing is caused by extreme weather events such as drought which strongly affect agricultural production. In this study, two data sources are used in drought assessment. First, by calculating the Standardized Precipitation Index (SPI) in the periods of 1, 3, 6 months, and one year in the western agricultural areas of Isfahan province in the time series from 2016 to 2019, precipitation data were used to analyze and evaluate meteorological drought's spatial and temporal dynamics. Furthermore, the average loss of rainfall was calculated using TRMM satellite monthly rainfall data and the average Normalized Difference Vegetation Index (NDVI) monthly with Landsat 8 satellite images using remote sensing data. Then, the Composite Drought Index (CDI) is produced to assess agricultural drought in the 2017-2018-2019 time series. The correlation between the CDI and SPI varies between 0.19 and 0.81 in different months in the time series. The correlation between temperature and CDI in different months varies from 0.22 to 0.75 and between evaporation (E) and CDI from 0.25 to 0.70 in time series.