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Evaluation of Drought Condition in Arid and Semi- Arid Regions, Using RDI Index

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  • Abdol Rassoul Zarei

    (Fasa University)

Abstract

Investigation of drought event has a great importance in the natural resources management and planning water resources management. One strategy to manage drought is to predict drought conditions by probabilistic tools. In this study climate data of 11 synoptic stations in south of Iran during 1980–2014 were used to estimate of seasonal drought based on RDI index. To prediction of drought (from 2015 to 2020) and analysis of changes trend of it, time series model, first-order Markov Chain model and parametric and non- parametric statistical methods were used. Results showed that MA (5), MA (10), AR (12) and AR (15) were the best time series models that fitted in data of all stations. According to results of prediction of drought classes, classes with normal and moderate dry condition had allocated the most frequency of seasonal drought classes from 2015 to 2020 based on time series model and Markov Chain method. Analysis of changes trend of drought classes showed that based on observed data (1980–2014) and predicted data (1980–2020) changes trend of drought classes in all stations had increasing trend based on parametric and non- parametric statistical methods but increasing trend in about 27% of stations include: Bandar Abbas, Bandar Lengeh, Jask and Shiraz had significant level of 5%. Finally result showed that the study area in 2020 compared to 2014 will be drier.

Suggested Citation

  • Abdol Rassoul Zarei, 2018. "Evaluation of Drought Condition in Arid and Semi- Arid Regions, Using RDI Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1689-1711, March.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:5:d:10.1007_s11269-017-1898-9
    DOI: 10.1007/s11269-017-1898-9
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    References listed on IDEAS

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    1. G. Tsakiris & I. Nalbantis & H. Vangelis & B. Verbeiren & M. Huysmans & B. Tychon & I. Jacquemin & F. Canters & S. Vanderhaegen & G. Engelen & L. Poelmans & P. Becker & O. Batelaan, 2013. "A System-based Paradigm of Drought Analysis for Operational Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5281-5297, December.
    2. Mostafa Dastorani & Mohammad Mirzavand & Mohammad Taghi Dastorani & Seyyed Javad Sadatinejad, 2016. "Comparative study among different time series models applied to monthly rainfall forecasting in semi-arid climate condition," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(3), pages 1811-1827, April.
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    Cited by:

    1. U. Surendran & B. Anagha & P. Raja & V. Kumar & K. Rajan & M. Jayakumar, 2019. "Analysis of Drought from Humid, Semi-Arid and Arid Regions of India Using DrinC Model with Different Drought Indices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(4), pages 1521-1540, March.
    2. Abdol Rassoul Zarei & Ali Shabani & Mohammad Reza Mahmoudi, 2020. "Evaluation of the Influence of Occurrence Time of Drought on the Annual Yield of Rain-Fed Winter Wheat Using Backward Multiple Generalized Estimation Equation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2911-2931, July.
    3. Mohammad Amin Asadi Zarch, 2022. "Past and Future Global Drought Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 5259-5276, October.
    4. Abdol Rassoul Zarei & Mohammad Reza Mahmoudi, 2020. "Ability Assessment of the Stationary and Cyclostationary Time Series Models to Predict Drought Indices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 5009-5029, December.

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