ارزیابی قابلیت مدل‌های سری زمانی و تئوری آشوب در برآورد تبخیر تعرق گیاه مرجع (ایستگاه سینوپتیک تربت حیدریه، خراسان رضوی)

نویسندگان

چکیده

برآورد تبخیر تعرق گیاه مرجع (ET0 ) برای طراحی سیستم‌های آبیاری،‏ مدیریت منابع آب،‏ تولید محصول و ارزیابی‌های زیست‌محیطی ضروری است. روش‌ها و مدل‌های مختلفی برای پیش‌بینی ET0 با استفاده از سری‌های زمانی ارائه شده‌اند که از آن جمله می‌توان مدل‌های سری زمانی AR،‏ MA و ARIMA را برشمرد. اما تاکنون از تئوری آشوب برای برآورد ET0 استفاده نشده است. در این پژوهش عملکرد هر یک از مدل‌های سری زمانی یاد شده در برآورد و تخمین تبخیر و تعرق گیاه مرجع به روش فائو- پنمن- مانتیس به‌صورت روزانه در ایستگاه سینوپتیک تربت حیدریه واقع در استان خراسان رضوی در دوره آماری 1991 تا 2000 میلادی بررسی شده است. نتایج نشان داد که مدل سری زمانی ARIMA و تئوری آشوب هر دو با دقتی نزدیک به یکدیگر تبخیر تعرق گیاه مرجع را برآورد می‌کنند. به طوری که ضریب تبیین بین مقادیر مشاهده شده و تخمین زده شده برای تبخیر تعرق گیاه مرجع از دو روش ARIMA و تئوری آشوب به‌ترتیب برابر 802‎/0 و 799‎/0 و مقدار RMSE برابر 585‎/0 و 611‎/0 میلی‌متر در روز است.

کلیدواژه‌ها


عنوان مقاله [English]

Capability evaluation of time series model and chaos theory in estimating reference crop evapotranspiration (Torbat-e-Heydarieh Synoptic station, Khorasan Razavi)

نویسندگان [English]

  • Hossein Babazadeh
  • Alireza Tavakoli
چکیده [English]

Estimating reference crop evapotranspiration (ETo) is necessary for designing irrigation systems, water resources management, yield production and environmental assessments. Different models and methods have been developed in order to predict ETo using time series, including AR, MA and ARIMA. However, Chaos Theory has not been utilized to estimate the ETo till now. In this study, the performance of the mentioned time series models was evaluated for estimating daily ETo in Torbat-e-Heydarieh synoptic station, Khorasan Razavi, during 1991-2000. Results showed that the ARIMA and Chaos Theory estimate the ETo with the same accuracy, so that the correlation coefficients between observed and estimated values for ARIMA and Chaos Theory were 0.895 and 0.894, and RMSE values were 0.585 and 0.611 mm day-1, respectively.
Estimating reference crop evapotranspiration (ETo) is necessary for designing irrigation systems, water resources management, yield production and environmental assessments. Different models and methods have been developed in order to predict ETo using time series, including AR, MA and ARIMA. However, Chaos Theory has not been utilized to estimate the ETo till now. In this study, the performance of the mentioned time series models was evaluated for estimating daily ETo in Torbat-e-Heydarieh synoptic station, Khorasan Razavi, during 1991-2000. Results showed that the ARIMA and Chaos Theory estimate the ETo with the same accuracy, so that the correlation coefficients between observed and estimated values for ARIMA and Chaos Theory were 0.895 and 0.894, and RMSE values were 0.585 and 0.611 mm day-1, respectively.
Estimating reference crop evapotranspiration (ETo) is necessary for designing irrigation systems, water resources management, yield production and environmental assessments. Different models and methods have been developed in order to predict ETo using time series, including AR, MA and ARIMA. However, Chaos Theory has not been utilized to estimate the ETo till now. In this study, the performance of the mentioned time series models was evaluated for estimating daily ETo in Torbat-e-Heydarieh synoptic station, Khorasan Razavi, during 1991-2000. Results showed that the ARIMA and Chaos Theory estimate the ETo with the same accuracy, so that the correlation coefficients between observed and estimated values for ARIMA and Chaos Theory were 0.895 and 0.894, and RMSE values were 0.585 and 0.611 mm day-1, respectively.
Estimating reference crop evapotranspiration (ETo) is necessary for designing irrigation systems, water resources management, yield production and environmental assessments. Different models and methods have been developed in order to predict ETo using time series, including AR, MA and ARIMA. However, Chaos Theory has not been utilized to estimate the ETo till now. In this study, the performance of the mentioned time series models was evaluated for estimating daily ETo in Torbat-e-Heydarieh synoptic station, Khorasan Razavi, during 1991-2000. Results showed that the ARIMA and Chaos Theory estimate the ETo with the same accuracy, so that the correlation coefficients between observed and estimated values for ARIMA and Chaos Theory were 0.895 and 0.894, and RMSE values were 0.585 and 0.611 mm day-1, respectively.
Estimating reference crop evapotranspiration (ETo) is necessary for designing irrigation systems, water resources management, yield production and environmental assessments. Different models and methods have been developed in order to predict ETo using time series, including AR, MA and ARIMA. However, Chaos Theory has not been utilized to estimate the ETo till now. In this study, the performance of the mentioned time series models was evaluated for estimating daily ETo in Torbat-e-Heydarieh synoptic station, Khorasan Razavi, during 1991-2000. Results showed that the ARIMA and Chaos Theory estimate the ETo with the same accuracy, so that the correlation coefficients between observed and estimated values for ARIMA and Chaos Theory were 0.895 and 0.894, and RMSE values were 0.585 and 0.611 mm day-1, respectively.
Estimating reference crop evapotranspiration (ETo) is necessary for designing irrigation systems, water resources management, yield production and environmental assessments. Different models and methods have been developed in order to predict ETo using time series, including AR, MA and ARIMA. However, Chaos Theory has not been utilized to estimate the ETo till now. In this study, the performance of the mentioned time series models was evaluated for estimating daily ETo in Torbat-e-Heydarieh synoptic station, Khorasan Razavi, during 1991-2000. Results showed that the ARIMA and Chaos Theory estimate the ETo with the same accuracy, so that the correlation coefficients between observed and estimated values for ARIMA and Chaos Theory were 0.895 and 0.894, and RMSE values were 0.585 and 0.611 mm day-1, respectively.

کلیدواژه‌ها [English]

  • Chaos Theory-Time Series Models.-ARIMA-Reference Crop Evapotranspiration-