Evaluating a new combined drought index based on remote sensing data (RCDI) in Central Iran

Document Type : Research Article


1 PhD Candidate of Watershed Management Engineering, Faculty of Natural Resources, Yazd University

2 Faculty of Natural Resources, Yazd University

3 3Water Engineering Department, Guilan University


Monitoring and evolution of drought is the first step in any drought management system. In this study, evaluation of a new indexa new method is provided to monitor the severity of drought with Remote Sensing Combined Drought Index (RCDI). The index is based on the fact that drought is a natural phenomenon caused by a combination of various factors such as a shortage in the amount of precipitation, less than the average long-term rainfall, temperature higher than normal and the properties of the soil moisture. The new index is a statistical index comparing the present hydrometeorological conditions with the long-term average characteristics in the same interest period within the year. Three data sources used in the RCDI index includes rainfall, temperature and vegetation data. In the present study, remote sensing data of TRMM and MODIS are used to provide the required data of RCDI index in central Iran for mapping the spatial distribution of drought over the period 2001-2004. Accuracy of the RCDI index based on satellite data carried out using the evaluation criteria of R and RMSE compared with soil moisture values based on monthly data of 50 synoptic stations in 95% confidence levels. The results of the evaluation criteria showed that drought severity index calculated by the RCDI index in accordance with soil moisture values had the significant correlation (0.61) and the lowest estimation error (1.98). Thus, a RCDI index could well use in drought early warning systems.


Main Subjects

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Volume 3, Issue 1
March 2016
Pages 31-43
  • Receive Date: 10 January 2016
  • Revise Date: 05 August 2016
  • Accept Date: 15 April 2016
  • First Publish Date: 15 April 2016
  • Publish Date: 20 March 2016