Estimation of Daily Reference Evapotranspiration in Humid Climates Using Data-Driven Methods of Gaussian Process Regression, Support Vector Regression and Random Forest

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SAMADIANFARD SAEED; Salarifar Mobarak; Javidan Sahar; Mikaeili Fatemeh

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Journal: JOURNAL OF ENVIRONMENT AND WATER ENGINEERING Year:2021 | Volume:6 | Issue:4 Page(s): 360-373

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Title

Estimation of Daily Reference Evapotranspiration in Humid Climates Using Data-Driven Methods of Gaussian Process Regression, Support Vector Regression and Random Forest

Author(s)

SAMADIANFARD SAEED | Salarifar Mobarak | Javidan Sahar | Mikaeili Fatemeh | Issue Writer Certificate

Keywords

Data Driven Methods

FAO Penman–

Monteith Method

Hargreaves-Samani Equation

North of Iran

Reference Evapotranspiration

Abstract

Accurate estimation of Reference Evapotranspiration has great importance in irrigation scheduling. Moreover, the lack of availability of lysimetric data has led researchers to use indirect methods, including data-driven approaches. In the present study, the ability of Gaussian process regression (GPR), support vector regression (SVR) and random forest (RF) data-driven methods was investigated to estimate the evapotranspiration of the reference plant. For this purpose, meteorological data on average temperature, wind speed, relative humidity and sunny hours in the period 2013-18 were collected in nine northern stations of Iran including Astara, Bandar Anzali, Rasht, Ramsar, Nowshahr, Sari, Turkmen port, Gorgan, and Gonbad Kavous. Evapotranspiration calculated using FAO-Penman-Montith method was considered as the target output and four combined scenarios of meteorological parameters were considered to calibrate and validate the studied methods. The accuracy of the mentioned methods was compared using the statistical parameters of correlation coefficient, scatter index, and Wilmott’ s coefficient. The results showed that GPR4 model with scatter index in the range of 0. 132 to 0. 179 in Astara, Bandar Anzali, Rasht, Ramsar, Nowshahr and Sari stations, SVR4 model with dispersion index of 0. 116 to 0. 120 in Turkmen and Gonbad Kavous stations and the Hargreaves-Samani method with a scatter index of 0. 509 at Gorgan station had much more accurate estimates of the evapotranspiration of the reference plant.

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APA: Copy

SAMADIANFARD, SAEED, Salarifar, Mobarak, Javidan, Sahar, & Mikaeili, Fatemeh. (2021). Estimation of Daily Reference Evapotranspiration in Humid Climates Using Data-Driven Methods of Gaussian Process Regression, Support Vector Regression and Random Forest. JOURNAL OF ENVIRONMENT AND WATER ENGINEERING, 6(4 ), 360-373. SID. https://sid.ir/paper/360087/en

Vancouver: Copy

SAMADIANFARD SAEED, Salarifar Mobarak, Javidan Sahar, Mikaeili Fatemeh. Estimation of Daily Reference Evapotranspiration in Humid Climates Using Data-Driven Methods of Gaussian Process Regression, Support Vector Regression and Random Forest. JOURNAL OF ENVIRONMENT AND WATER ENGINEERING[Internet]. 2021;6(4 ):360-373. Available from: https://sid.ir/paper/360087/en

IEEE: Copy

SAEED SAMADIANFARD, Mobarak Salarifar, Sahar Javidan, and Fatemeh Mikaeili, “Estimation of Daily Reference Evapotranspiration in Humid Climates Using Data-Driven Methods of Gaussian Process Regression, Support Vector Regression and Random Forest,” JOURNAL OF ENVIRONMENT AND WATER ENGINEERING, vol. 6, no. 4 , pp. 360–373, 2021, [Online]. Available: https://sid.ir/paper/360087/en

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