Spatial resolution analysis of TRMM satellite images to estimate meteorological drought index, case study: Iran

One of the most important last century challenges in the world was drought and monitoring and assessing drought severity and duration to combat and mitigate its impacts is very necessary. In recent decades, with developing of remote sensing issues, satellite-based estimating drought with high spatial resolution and different time steps were widely used. Hence, the aim of this study was focused on the analyzing drought and error distribution of TRMM satellite data-based estimation with ground data over the period 1998 to 2014. In this regard, in order to assess the accuracy of meteorological drought index based on the TRMM satellite data, 41 synoptic stations were used in Iran. In this study, error assessment criteria were included NSE, RMSE, ME, Bias and correlation coefficient and also the IDW interpolation method in ArcGIS 10.3 was used for spatial analysis. Results of drought index showed that in terms of severity, Kerman, Bushehr, Kashmar, Ghazvin, Bojnurd, Kashan stations have suffered from at least one extreme status for 1998 to 2014 and in terms of frequency, the most frequent drought was in Karaj station. Results of spatial analysis of error criteria  showed that the drought index estimated of TRMM satellite had the lower error in northeast of Iran (around Mashhad and Kashmar stations) and southwest of Iran (around Shahrkord, Esfahan, Yasouj, and Shiraz stations) while the most error was in central region of Iran (around Biarjomand, Tabass stations), respectively. In most areas of the country, drought index estimated by TRMM data had acceptable agreement with ground stations data. Calibrating the TRMM data with ground stations can be used for drought monitoring in areas without stations for networks 0.25*0.25 latitude and longitude degrees.