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

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NIAZI YAGHOUB; TALEBI ALI; MOKHTARI MOHAMMAD HOSSEIN; VAZIFEDOUST MAJID

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Journal: IRANIAN JOURNAL OF ECOHYDROLOGY Year:2016 | Volume:3 | Issue:1 Page(s): 31-43

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Title

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

Author(s)

NIAZI YAGHOUB | TALEBI ALI | MOKHTARI MOHAMMAD HOSSEIN | VAZIFEDOUST MAJID | Issue Writer Certificate

Keywords

Central IranQ2

combined drought indexQ2

drought monitoringQ2

remote sensingQ2

satellite dataQ2

soil moistureQ2

Abstract

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.

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APA: Copy

NIAZI, YAGHOUB, TALEBI, ALI, MOKHTARI, MOHAMMAD HOSSEIN, & VAZIFEDOUST, MAJID. (2016). Evaluating a new combined drought index based on remote sensing data (RCDI) in Central Iran. IRANIAN JOURNAL OF ECOHYDROLOGY, 3(1 ), 31-43. SID. https://sid.ir/paper/254070/en

Vancouver: Copy

NIAZI YAGHOUB, TALEBI ALI, MOKHTARI MOHAMMAD HOSSEIN, VAZIFEDOUST MAJID. Evaluating a new combined drought index based on remote sensing data (RCDI) in Central Iran. IRANIAN JOURNAL OF ECOHYDROLOGY[Internet]. 2016;3(1 ):31-43. Available from: https://sid.ir/paper/254070/en

IEEE: Copy

YAGHOUB NIAZI, ALI TALEBI, MOHAMMAD HOSSEIN MOKHTARI, and MAJID VAZIFEDOUST, “Evaluating a new combined drought index based on remote sensing data (RCDI) in Central Iran,” IRANIAN JOURNAL OF ECOHYDROLOGY, vol. 3, no. 1 , pp. 31–43, 2016, [Online]. Available: https://sid.ir/paper/254070/en

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