تحلیل طیف توانی (اسپکترومی) برای بررسی مقیاس‌پذیری بارش ماهانه 33 ایستگاه باران‌سنجی ایران

نویسندگان

چکیده

بارش و مقیاس‌های زمانی مختلف آن از پارامترهای مهم در پژوهش‌های منابع آب به شمار می‌روند. دارا بودن مقیاس‌های زمانی مختلف با ماهیت فرکتالی قابل بیان است. یکی از ابزارهای استاندارد در بررسی فرکتالی فرآیندهای هیدرولوژیکی استفاده از تحلیل طیف توانی یا اسپکترومی است. در این روش،‏ طیف توانی با انتقال مشاهدات از فضای زمان به فضای بسامد محاسبه شده و در صورتی که تمام یا بخشی از طیف،‏ از توابع توانی پیروی کنند،‏ داده‌ها در بازه موردنظر دارای خصوصیات فرکتالی خواهند بود. در این پژوهش طیف توانی حاکم بر بارش‌های ماهانه 33 ایستگاه باران‌سنجی در ایران بررسی و رژیم‌های مقیاس‌گذاری به همراه مقادیر توان طیفی برای هر ایستگاه مشخص گردید. نتایج نشان داد که 81 درصد ایستگاه‌ها در دوره تناوب کمتر از یک سال دارای خاصیت مقیاس‌پذیری و ماهیت فرکتالی قوی هستند. همچنین علاوه بر رژیم مقیاس‌گذاری اول،‏ 17 ایستگاه دارای رژیم مقیاس‌گذاری دوم و 3 ایستگاه دارای رژیم مقیاس‌گذاری سوم هستند. هیچ‌یک از ایستگاه‌ها در رژیم مقیاس‌گذاری دوم خود دارای ماهیت فرکتالی نبوده و فقط یک ایستگاه در رژیم مقیاس‌گذاری سوم خود ماهیت فرکتالی نشان داد.

کلیدواژه‌ها


عنوان مقاله [English]

Power spectrum analysis to investigate monthly precipitation Scalability of 33 rain gauge stations in Iran

نویسندگان [English]

  • masoud gharibdoust
  • mohammad ali ghorbani
  • mohammad hasan fazeli fard
  • esmail asadi
چکیده [English]

Precipitation with multiple time scales is considered as one of the most important parameters in water resources studies. Precipitation with different time scales can be expressed with fractal nature. One of the standard tools in the fractal investigation of hydrological processes is the power spectrum method. In this method, the power spectrum is calculated with transmitted observation from time space to frequency space. When all or a part of the spectral follow the power functions, the data in this power range will have fractal properties. In this study, the power spectrum of monthly precipitation of the 33 rain gauge stations in Iran was analyzed and scaling regimes with spectral exponent value are shown for each station. The results indicate that 81 percent of the stations have fractal nature and scaling properties in a period less than one year. In addition to the first scaling regime, 17 stations have second scaling regime and 3 stations have the third scaling regime. None of the stations in its second scaling regime have fractal nature and only one station in the third scaling regime has fractal nature.Precipitation with multiple time scales is considered as one of the most important parameters in water resources studies. Precipitation with different time scales can be expressed with fractal nature. One of the standard tools in the fractal investigation of hydrological processes is the power spectrum method. In this method, the power spectrum is calculated with transmitted observation from time space to frequency space. When all or a part of the spectral follow the power functions, the data in this power range will have fractal properties. In this study, the power spectrum of monthly precipitation of the 33 rain gauge stations in Iran was analyzed and scaling regimes with spectral exponent value are shown for each station. The results indicate that 81 percent of the stations have fractal nature and scaling properties in a period less than one year. In addition to the first scaling regime, 17 stations have second scaling regime and 3 stations have the third scaling regime. None of the stations in its second scaling regime have fractal nature and only one station in the third scaling regime has fractal nature.Precipitation with multiple time scales is considered as one of the most important parameters in water resources studies. Precipitation with different time scales can be expressed with fractal nature. One of the standard tools in the fractal investigation of hydrological processes is the power spectrum method. In this method, the power spectrum is calculated with transmitted observation from time space to frequency space. When all or a part of the spectral follow the power functions, the data in this power range will have fractal properties. In this study, the power spectrum of monthly precipitation of the 33 rain gauge stations in Iran was analyzed and scaling regimes with spectral exponent value are shown for each station. The results indicate that 81 percent of the stations have fractal nature and scaling properties in a period less than one year. In addition to the first scaling regime, 17 stations have second scaling regime and 3 stations have the third scaling regime. None of the stations in its second scaling regime have fractal nature and only one station in the third scaling regime has fractal nature.Precipitation with multiple time scales is considered as one of the most important parameters in water resources studies. Precipitation with different time scales can be expressed with fractal nature. One of the standard tools in the fractal investigation of hydrological processes is the power spectrum method. In this method, the power spectrum is calculated with transmitted observation from time space to frequency space. When all or a part of the spectral follow the power functions, the data in this power range will have fractal properties. In this study, the power spectrum of monthly precipitation of the 33 rain gauge stations in Iran was analyzed and scaling regimes with spectral exponent value are shown for each station. The results indicate that 81 percent of the stations have fractal nature and scaling properties in a period less than one year. In addition to the first scaling regime, 17 stations have second scaling regime and 3 stations have the third scaling regime. None of the stations in its second scaling regime have fractal nature and only one station in the third scaling regime has fractal nature.

کلیدواژه‌ها [English]

  • Power Spectrum-Fractal-Monthly Precipitation-Time scale.-Iran-