Evapotranspiração de referência estimada por modelos simplificados para o Estado do Mato Grosso

Abstract

Reference evapotranspiration estimated with simplified models for the state of Mato Grosso, BrazilAbstract -The objective of this work was to evaluate the performance of 12 simplified models for the estimation of reference evapotranspiration (ETo) for the state of Mato Grosso, Brazil. The data were collected from automatic weather stations (AWS) of the Instituto Nacional de Meteorologia, located in 28 municipalities of the state. The following simplified estimation models were evaluated: Hargreaves-Samani, Camargo, Makkink, Linacre, McGinness-Bordne, Romanenko, Turc, Holdridge, Solar Radiation, Jensen-Haise, Hansen, and Caprio. The Fao 56 Penman-Monteith method (FPM) was used as reference for assessing the simplified estimates. Statistical performance was evaluated through relative mean error (RME), root mean square error (RMSE), Willmott's d index, and according to the numerical order of models for each index. The Makkink model overestimated ETo by 2.0 to 3.0 mm per day, with scattering values of 2.75 mm per day and 0.40 d index, which represented the worst results among models, regardless of the municipality evaluated. The Turc and McGinness-Bordne models showed the best performances for estimating ETo in 57.1 and 25% of the AWS, respectively. The Romanenko, Makkink, and Holdridge models are not recommended for the state of Mato Grosso, Brazil.Index terms: minimum data, Turc model, Penman-Monteith, solar radiation, air temperature. IntroduçãoO crescimento populacional, a demanda por alimentos e os níveis de industrialização têm acarretado aumento do consumo dos recursos hídricos em escalas regionais e locais, o que exige um planejamento eficiente de sua oferta e demanda, para diferentes escalas temporais. Entre os diferentes usos desses recursos, a irrigação é uma das atividades com maior consumo de água (Bezerra et al., 2010).

Reference evapotranspiration estimates by means of Hargreaves-samani and Penman-monteith fao methods with missing data in the northwestern Mato Grosso do Sul

“…These results can be explained based on the climate of the studied localities (Table 1) which are of type Aw (tropical hot and humid), with a rainy weather in summer and a dry weather in winter, according to the Köppen classification (KOTTEK et al, 2006), unlike the semi-arid conditions in which the Hargreaves-Samani method was derived. Tanaka et al (2016), working with data from 28 locations in the State of Mato Grosso found the worst statistical indicators to estimate ET0 at daily scale using Hargreaves-Samani method. They do not recommend its use.…”

Performance of different methods to estimate reference evapotranspiration in Cruz Alta - RS

“…Tanaka et al (2016) reported, in a study carried out in the state of Mato Grosso, that the JensenHaise method presented, as a whole, the worst statistical indicators in the estimation of ETo in daily scale, compared to the other methods studied. Moreover, the same authors, when observing the data dispersion around the 1:1 line regarding the ETo estimated by Penman-Monteith and by other methods, found that the Jensen-Haise method presents one of the worst correlations for ETo estimation.…”

“…One of the main parameters used to determine the water requirement of crops is evapotranspiration (Morais et al, 2015). Its correct obtention is of paramount importance for a proper irrigation management, since it represents the amount of soil water to be replenished for the plants, according to the climatic and soil water conditions in the region (Tagliaferre et al, 2010) The reference evapotranspiration (ETo) can be obtained directly -through the estimation of the soil water balance, using lysimeters -, or indirectly, through evaporimeters or through the use of physical-mathematical models of estimation (Alves Sobrinho et al, 2011;Carvalho et al, 2015;Tanaka et al, 2016). Among the existing models, the Penman-Monteith method, considered as standard by FAO (Allen et al, 1998), besides obtaining a better precision in the estimates, is the model that best represents the physical and physiological factors involved in ETo (Carvalho et al, 2015).…”

Comparative performance of empirical methods to estimate the reference evapotranspiration in Aquidauana, MS, Brazil

“…According to Tanaka et al (2016), the mean absolute error (MAE) indicator represents the deviation of the averages and provides information about the performance of the model. Thus, in the rainy period ( Figure 4A), the ET0HS and ET0JH methods underestimated the pattern.…”