Abstract
Estimation of reference evapotranspiration (ET o ) is very relevant for water resource management. The Penman-Monteith (PM) equation was proposed by the Food and Agriculture Organization (FAO) as the standard method for estimation of ET o . However, this method requires various weather data, such as air temperature, wind speed, solar radiation and relative humidity, which are often unavailable. Thus, the objective of this study was to compare the performance of multivariate adaptive regression splines (MARS) and alternative equations, in their original and calibrated forms, to estimate daily ET o with limited weather data. Daily data from 2002 to 2016 from 8 Brazilian weather stations were used. ET o was estimated using empirical equations, PM equation with missing data and MARS. Four data availability scenarios were evaluated as follows: temperature only, temperature and solar radiation, temperature and relative humidity, and temperature and wind speed. The MARS models demonstrated superior performance in all scenarios. The models that used solar radiation showed the best performance, followed by those that used relative humidity and, finally, wind speed. The models based only on air temperature had the worst performance.
Highlights
Evapotranspiration is one of the main components of the water cycle, allowing the transfer of water and energy into the atmosphere (Fernandes, Paiva, & Rotunno Filho, 2012)
This study aims to compare the performance of multivariate adaptive regression splines (MARS) and alternative equations to estimate daily ETo with limited weather data
Where: EToPM represents the reference evapotranspiration estimated by the Penman-Monteith equation, Rn represents the net solar radiation (MJ m-2 day-1), G represents the soil heat flux (MJ m-2 day-1; considered to be null for daily estimates), T represents daily mean air temperature (°C), U2 represents the wind speed at a 2 m height (m s-1), es represents the saturation vapor pressure, ea represents the actual vapor pressure, ∆ represents the slope of the saturation vapor pressure function, and γ represents the psychometric constant
Summary
Evapotranspiration is one of the main components of the water cycle, allowing the transfer of water and energy into the atmosphere (Fernandes, Paiva, & Rotunno Filho, 2012). To estimate ETo with limited weather data, many studies have been conducted by using a reduced number of variables and developing empirical and semi-empirical models based on temperature (Hargreaves & Samani, 1985; Oudin et al, 2005), temperature and solar radiation (Makkink, 1957; Jensen & Haise, 1963), temperature and relative humidity (Valiantzas, 2013), and others These methods, unlike the PM equation, which can be used globally without additional adjustments (Pereira et al, 2015), require local calibrations to obtain more satisfactory performances (Gao, Peng, Xu, Yang, & Wang, 2015)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
