Thornthwaite and mather soil water balance model adapted for estimation of real evapotranspiration of the pasture

Abstract

Determining the real water requirement for pastures is essential for the rational use of irrigation. The aim of this work was to assess the crop coefficient and performance of the Thornthwaite and Mather soil water balance (ThM) adapted to estimate the daily actual evapotranspiration (ETa) of a pasture in relation to the Bowen ratio - energy balance method (BREB). The experiment was carried out from July 2018 to June 2019 in Cachoeiras de Macacu, Rio de Janeiro State (RJ) (22º 27’S; 42º 45’W and 30 m altitude). Micrometeorological and meteorological measurements were conducted in a micrometeorological tower installed in the pasture and also in an automatic weather station, located 1 km from the pasture area. The ThM model was evaluated using linear regression between ETa determinate from BREB and the estimates from ThM using its coefficient of determination (R²) and the modified Willmott agreement index (dm). The ThM model underestimated (between 11 and 16%) the ETa for all seasons, except for spring, which overestimated by 1%. The highest precision and accuracy of the estimates were observed in autumn (R² = 0.84 and dm = 0.68) and spring (R² = 0.83 and dm = 0.82). In summer (R² = 0.56 and dm = 0.73) and winter (R² = 0.43 and dm = 0.66), the lower performance was caused by the inability of the model to represent water extraction from the soil in dry periods.

Evaluation of chemical attributes of soils: definition of management zones in silvipastoral system

“…In the SSP-FEBN, the elements Ca+Mg, Mat Org, and B showed a nugget effect, or error, with almost the totality of the variation. Oliveira Junior et al (2020) found a pure nugget effect for P and Barros et al (2021) found a pure nugget effect for K, Al, and Mat Org elements. The ratio between the nugget effect and the threshold (k) allows the classification of attributes according to the degree of spatial dependence (GDE), where if k ≤ 25% is considered strong spatial dependence, for the range of o 25% ≤ k ≤ 75% means that there is moderate dependence and above 75% there is weak spatial dependence (Barros et al, 2021).…”

“…Oliveira Junior et al (2020) found a pure nugget effect for P and Barros et al (2021) found a pure nugget effect for K, Al, and Mat Org elements. The ratio between the nugget effect and the threshold (k) allows the classification of attributes according to the degree of spatial dependence (GDE), where if k ≤ 25% is considered strong spatial dependence, for the range of o 25% ≤ k ≤ 75% means that there is moderate dependence and above 75% there is weak spatial dependence (Barros et al, 2021). In the spatial dependence analysis of the SSP-FEBN attributes, no GDE was found in the strong class, only in the moderate and weak classes.…”

“…According to Yan et al (2020), several factors, such as the nature of the data, sampling errors, measurement errors, or even micro regionalizations of the variable under analysis, can be the causes of a low GDE. Barros et al (2021) used R² and SQR as metrics to evaluate the performance of the methods so that R² with values close to 1 indicate better performance. All soil attributes that presented R² greater than 0.75 were submitted to the cross-validation test, to validate the method used.…”

Monthly potential evapotranspiration estimated using the Thornthwaite method with gridded climate datasets for Rio de Janeiro state, Brazil

“…Thereby, ET is fundamental for identifying the intensity, frequency, and duration of droughts, and areas susceptible to deserti cation, and the consequences of these phenomena on different ecosystems (Beguería et al 2014). Also, ET is essential for agricultural planning and management (Todote et al 2021), soil water balance modeling (Barros et al 2021;Martins et al 2021), and for hydrological and agrometeorological models (Monteiro et al 2021).…”