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Innovative Trend Methodology Applications to Precipitation Records in Turkey

Author

Listed:
  • Ahmet Öztopal

    (Istanbul Technical University)

  • Zekâi Şen

    (Istanbul Technical University)

Abstract

There are trend identification methodologies in the literature but they have three crucial points that should be cared with great attention in practical applications. These points are that the available time series should have independent serial correlation structure, Gaussian (normal) distribution and monotonic trend fitting to whole time series through the least square technique. The existing methods consider the whole duration of the time series and try to identify a monotonic trend in increasing or decreasing forms. This paper presents partial trend methodology as an innovative and simple trend identification method, which yields low, medium and high cluster trends separately. It provides the opportunity to segregate between the low, high and medium flow trends and their relative intensities, durations as well as magnitudes. The application of the partial trend methodology is presented for 7 precipitation stations from 7 different sub-climatic regions of Turkey leading to spatial and temporal trend interpretations.

Suggested Citation

  • Ahmet Öztopal & Zekâi Şen, 2017. "Innovative Trend Methodology Applications to Precipitation Records in Turkey," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(3), pages 727-737, February.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:3:d:10.1007_s11269-016-1343-5
    DOI: 10.1007/s11269-016-1343-5
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    References listed on IDEAS

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    1. Sheng Yue & ChunYuan Wang, 2004. "The Mann-Kendall Test Modified by Effective Sample Size to Detect Trend in Serially Correlated Hydrological Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(3), pages 201-218, June.
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    Cited by:

    1. Sadık Alashan, 2018. "Data Analysis in Nonstationary State," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(7), pages 2277-2286, May.
    2. Sinan Nacar, 2023. "Trends of High and Low Values of Annual and Seasonal Precipitation in Turkey," Sustainability, MDPI, vol. 15(23), pages 1-18, December.

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