Preprint Article Version 1 This version is not peer-reviewed

Drought Forecast Using Standardized Precipitation Index and Markov Chain in Iran

Version 1 : Received: 22 December 2018 / Approved: 24 December 2018 / Online: 24 December 2018 (12:27:30 CET)

How to cite: Siasar, H.; Shahrdarazi, F.; Shojaei, S. Drought Forecast Using Standardized Precipitation Index and Markov Chain in Iran. Preprints 2018, 2018120276 (doi: 10.20944/preprints201812.0276.v1). Siasar, H.; Shahrdarazi, F.; Shojaei, S. Drought Forecast Using Standardized Precipitation Index and Markov Chain in Iran. Preprints 2018, 2018120276 (doi: 10.20944/preprints201812.0276.v1).

Abstract

Drought is a natural disaster which occurs as a result of a lack of ambient humidity due to reduced rainfall compared to normal conditions. Successful planning and management of water in agriculture and proper use of water resources is subject to recognition of this disaster. As drought is inevitable, we can minimize its damages through monitoring and forecasting. It is therefore important to predict drought in the planning and management of water resources. In studying the status of drought in Saravan city, rain annual data of synoptic station in the period (1976-2015) and the Standardized Precipitation Index (SPI) in a twelve-month time scale have been used. Then the Markov chain model was used to calculate the probabilities of the balance of the periods of wet, dry, and normal in SPI. The results showed that the probability of balance in wet, dry, and normal periods in Saravan station is 80.2, 24.20, and 96.76 respectively. This means that the area is most of the time in normal conditions and the probability of draught is about 7 times bigger than rain.

Subject Areas

drought, SPI index, Markov chain, Iran.

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