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Using the Fuzzy Clustering and Principle Component Analysis for Assessing the Impact of Potential Evapotranspiration Calculation Method On the Modified RDI Index

Author

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  • Abdol Rassoul Zarei

    (Fasa University)

  • Mohammad Reza Mahmoudi

    (Fasa University)

  • Ali Shabani

    (Fasa University)

Abstract

The modified reconnaissance drought index (RDIe) which is a modified version of RDI is presented for assessing drought conditions with an emphasis on agricultural drought. The potential evapotranspiration (PET) and effective rainfall are required climatic variables to calculate RDIe. Although the FAO Penman–Monteith (FPM) equation is the reference method for determining the PET, due to the need for data of a large number of climatic variables it is difficult to use in areas with shortage climatic data. Therefore, in this research, using the fuzzy clustering (FC) and principle component analysis (PCA) methods, the influence of PET calculation methods including FPM (used as reference method), FAO Penman (FP), Hargreaves-Samani (HS), Blaney-Criddle (BC), Turc (Tu), Jensen-Haise (JH), Priestley–Taylor (PT) and FAO24 Radiation (Ra) methods on the RDIe (in 1, 3 and 12-month time scales) was assessed. In this study the climatic data series of 5 stations in Fars province, Iran from 1989 to 2018 was used. Based on the results of PCA model, in short-term time scales (1 and 3-month), the calculated RDIe values based on the HS method (at 100% of stations) and in long-term time scale (annual) based on the FP method (at 60% of stations) had the highest correlation with RDIe based on the FPM method. According to the results of FC method, in 1-month time scale, the values of RDIe using PT and HS methods (at 100% and 80% of selected stations, respectively), in 3-month time scale, the values of RDIe using PT, HS and Ra methods (at 100% of stations) and in annual time scale, the values of RDIe using FP method (at 60% of stations) had the highest similarities with the values of RDIe using FPM. Therefore, it is recommended to replace the FPM method with HS (in 1 and 3-month time scales) and FP (in 12-month time scales) methods in areas with minimum available meteorological data.

Suggested Citation

  • Abdol Rassoul Zarei & Mohammad Reza Mahmoudi & Ali Shabani, 2021. "Using the Fuzzy Clustering and Principle Component Analysis for Assessing the Impact of Potential Evapotranspiration Calculation Method On the Modified RDI Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3679-3702, September.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:11:d:10.1007_s11269-021-02910-7
    DOI: 10.1007/s11269-021-02910-7
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    References listed on IDEAS

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    1. Neda Khanmohammadi & Hossein Rezaie & Majid Montaseri & Javad Behmanesh, 2017. "The Effect of Temperature Adjustment on Reference Evapotranspiration and Reconnaissance Drought Index (RDI) in Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 5001-5017, December.
    2. Seyed Banimahd & Davar Khalili, 2013. "Factors Influencing Markov Chains Predictability Characteristics, Utilizing SPI, RDI, EDI and SPEI Drought Indices in Different Climatic Zones," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(11), pages 3911-3928, September.
    3. Hamid Jamalinia & Saber Khalouei & Vahideh Rezaie & Samad Nejatian & Karamolah Bagheri-Fard & Hamid Parvin, 2018. "Diverse classifier ensemble creation based on heuristic dataset modification," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(7), pages 1209-1226, May.
    4. Abdol Rassoul Zarei & Mohammad Reza Mahmoudi, 2017. "Evaluation of changes in RDIst index effected by different Potential Evapotranspiration calculation methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4981-4999, December.
    5. Quang-Tuong Vo & Jae-Min So & Deg-Hyo Bae, 2020. "An Integrated Framework for Extreme Drought Assessments Using the Natural Drought Index, Copula and Gi* Statistic," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(4), pages 1353-1368, March.
    6. Davar Khalili & Tohid Farnoud & Hamed Jamshidi & Ali Kamgar-Haghighi & Shahrokh Zand-Parsa, 2011. "Comparability Analyses of the SPI and RDI Meteorological Drought Indices in Different Climatic Zones," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(6), pages 1737-1757, April.
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    1. 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.
    2. Mohammad Reza Mahmoudi & Abdol Rassoul Zarei, 2022. "Using Periodic Copula to Assess the Relationship Between Two Meteorological Cyclostationary Time Series Datasets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4363-4388, September.
    3. Jin Hyuck Kim & Jang Hyun Sung & Shamsuddin Shahid & Eun-Sung Chung, 2022. "Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 2913-2930, July.
    4. Dilip Kumar Roy & Kowshik Kumar Saha & Mohammad Kamruzzaman & Sujit Kumar Biswas & Mohammad Anower Hossain, 2021. "Hierarchical Fuzzy Systems Integrated with Particle Swarm Optimization for Daily Reference Evapotranspiration Prediction: a Novel Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(15), pages 5383-5407, December.

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