干旱区生态安全与可持续发展服务平台

Estimation of reference evapotranspiration using multivariate fractional polynomial, Bayesian regression, and robust regression models in three arid environments

Khoshravesh, Mojtaba ， Sefidkouhi, Mohammad Ali Gholami ， Valipour, Mohammad

2017-07-01 null null 7(卷), null(期), (null页)

The proper evaluation of evapotranspiration is essential in food security investigation, farm management, pollution detection, irrigation scheduling, nutrient flows, carbon balance as well as hydrologic modeling, especially in arid environments. To achieve sustainable development and to ensure water supply, especially in arid environments, irrigation experts need tools to estimate reference evapotranspiration on a large scale. In this study, the monthly reference evapotranspiration was estimated by three different regression models including the multivariate fractional polynomial (MFP), robust regression, and Bayesian regression in Ardestan, Esfahan, and Kashan. The results were compared with Food and Agriculture Organization (FAO)Penman-Monteith (FAO-PM) to select the best model. The results show that at a monthly scale, all models provided a closer agreement with the calculated values for FAO-PM (R-2 > 0.95 and RMSE < 12.07 mm month(-1)). However, the MFP model gives better estimates than the other two models for estimating reference evapotranspiration at all stations.

关键词

Evapotranspiration Iran Multivariate fractional polynomial Bayesian regression Robust regression

Estimation of reference evapotranspiration using multivariate fractional polynomial, Bayesian regression, and robust regression models in three arid environments

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