4.5 Article

A minimalistic approach for evapotranspiration estimation using the Prophet model

Journal

HYDROLOGICAL SCIENCES JOURNAL
Volume 65, Issue 12, Pages 1994-2006

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2020.1787416

Keywords

machine learning; Prophet model; support vector regression; evapotranspiration; minimalistic approach

Funding

  1. ministry of culture, sports, science and technology (MEXT)

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This study aimed to evaluate the potential of the recently introduced Prophet model for estimating reference evapotranspiration (ETo). A comparative study was conducted for benchmarking the model results with support vector regression (SVR) and temperature-based empirical models (Thornthwaite and Hargreaves) in southern Japan. The performance of the Prophet, SVR and temperature-based empirical models was evaluated by Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R-2). The results indicate that temperature-based Prophet and SVR models have greater accuracy than the empirical models. The Prophet model with sole input of relative humidity, sunshine hours or windspeed showed acceptable accuracy (NSE > 0.80; R-2 > 0.80), while SVR models with similar inputs showed greater errors. Accuracy improved with increasing number of input parameters, giving excellent performance (NSE > 0.95; R-2 > 0.95) with all input parameters. Hence, the Prophet model is a new promising approach for modelling ETo with limited input variables.

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