Estimating daily pan evaporation using machine learning methods
Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Evaporation is the one of main processes in the hydrological cycle, and one of the most important factors in the related studies, namely agriculture, hydrology, aerology, exploitation of reservoirs, designing of irrigation and drainage systems, irrigation scheduling, and water resources management. Therefore, accurate simulation of evaporation rates has of the high importance in hydrology researches. In this regard, intelligent methods of Genetic Programming, Support Vector Regression, and Artificial Neural Networks have been used for evaluation and simulation of the pan evaporation rates over Tabriz and Golfa synoptic stations, in the present research. For this purpose, meteorological data including evaporation, temperature, relative humidity, wind speed, and solar radiation during the period of 1993-2013 were used and the accuracy of studied methods were investigated by using statistical parameters of root mean square error, mean absolute error, correlation coefficient and Taylor diagram. The results showed that in the optimum case of Tabriz and Golfa stations, genetic programming with error of 2.18 and 2.68, support vector regression with error of 2.19 and 2.22, and artificial neural network with error of 2.14 and 2.21, respectively, had reasonable performance in evaporation simulation. Conclusively, the second scenario of artificial neural network method through the input parameters of temperature and wind speed and the seventh scenario of artificial neural network method through the input parameters of temperature, humidity, wind speed, and solar radiation by having the best performance, were suggested as the accurate models with reasonable precision for simulating pan evaporation at Tabriz and Golfa stations, respectively.
Language:
Persian
Published:
Iranian Journal of Irrigation & Drainage, Volume:12 Issue: 4, 2018
Pages:
1004 to 1015
magiran.com/p1910338  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 990,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
دسترسی سراسری کاربران دانشگاه پیام نور!
اعضای هیئت علمی و دانشجویان دانشگاه پیام نور در سراسر کشور، در صورت ثبت نام با ایمیل دانشگاهی، تا پایان فروردین ماه 1403 به مقالات سایت دسترسی خواهند داشت!
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 50 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!