Reference Evapotranspiration Forecasting by Artificial Neural Networks

Abstract

Evapotranspiration (ET) is the main component of water balance in agricultural systems and the most active variable of the hydrological cycle. In the literature, few studies have used the forecast the day before via Artificial Neural Networks (ANNs) for the northern region of São Paulo state, Brazil. Therefore, this aimed to predict the reference evapotranspiration for Jaboticabal, the major sugarcane-producing region of São Paulo state. We used a historical series of data on average air temperature, wind speed, net radiation, soil heat flux, and daily relative humidity from 2002 to 2012, for Jaboticabal, SP (Brazil). ET was estimated by Penman-Monteith method. To forecast reference evapotranspiration, we used a feed-forward Multi-Layer Perceptron (MLP), which is a traditional Artificial Neural Network. Numerous topologies and variations were tested between neurons in intermediate and outer layers until the most accurate were obtained. We separated 75% from data for network training (2002 to 2010) and 25% for testing (2011 to 2013). The criteria for assessing the ANN performance were accuracy, precision, and trend. ET could be accurately estimated with a day to spare at any time of the year, by means of artificial neural networks, and using only air temperature data as an input variable.

Nitrate and potassium movement in a sandy loam soil cultivated with fertigated grapevine (Vitis vinifera /L.) in the Brazilian semiarid

“…Irrigation management was performed based on the estimation of crop evapotranspiration (ETc). For this, the reference evapotranspiration (ETo, mm day -1 ) was estimated by the Penmam-Monteith FAO method (ALVES et al, 2017) using data collected by an automatic weather station located 60 m from the experimental area. The crop coefficients (kc) for wine vine cv.…”

Estudo da evapotranspiração máxima, mínima e anual sobre a bacia hidrográfica do rio Uruçuí Preto - Piauí, Brasil

“…A evapotranspiração potencial pode ser definida como sendo a transferência de água para a atmosfera, por evaporação e transpiração, de superfícies vegetadas extensas e uniformes, cobertas por vegetação de porte baixo e bem suprida de água. (Andrade Junior et al, 2018;Alves et al, 2017). Segundo Marengo, Torres e Alves (2017), a região Nordeste do Brasil (NEB) se caracteriza naturalmente, com alto potencial para evaporação da água em função da grande disponibilidade da energia solar e altas temperaturas.…”

Estimating Potential Evapotranspiration in Maranhão State Using Artificial Neural Networks

“…Evapotranspiration is the process in which water from the earth's surface evaporates into the atmosphere together with the transpiration of plants, being an important part of the hydrological cycle (Alves et al, 2017). The process of evapotranspiration occurs not only from surface water, but also involves the loss of soil water and moist vegetation in the form of water vapor and the loss of water from animals (perspiration) and plants through transpiration.…”

“…What makes it difficult to use is the need for various climatic elements, such as relative humidity, solar radiation, air temperature, and wind speed. This method requires a larger number of weather variables and these elements are often not available due to the small number of weather stations available in many regions, and when these are present they may contain insufficient data (Alves et al, 2017). In the literature there are other empirical methods with fewer requirements for climatic variables (Silva et al, 2018, Caporusso andRolim, 2015), such as Hargreaves-Samani, Solar Radiation, Blaney-Criddle and Priestley-Taylor (Allen et al, 1998), but these methods oftentimes have large deviations.…”