Calibração de sensores de solo para determinação do teor de umidade em latosolos amarelos na Amazônia Central

Abstract

The Amazon forest develops an important evapotranspiration role responsible for maintaining processes of rain regimes in the country's great agricultural regions. However, changes in land use and deforestation can directly affect this system, compromising the country's economic scenario. Thus, scientists develop research that monitors water dynamics and seeks to understand their behavior in this system. In this context, the objective of this work was to calibrate soil moisture sensors in order to develop a standard curve that determines and quantifies soil water content. For this, samples of 22 kg of soil were taken from each of the eight points of the deep well of ZF2, for calibration of the sensors in a laboratory environment. Three deformed samples of each point were collected with the aid of the Kopecky Ring along the profile for analysis of soil density, gravimetric moisture and subsequent value of the real volumetric moisture of the field. The greenhouse method was adopted as the standard for the calibration of the eight soil sensors. The samples of each depth were slashed and sieved in 2 mm sieves to obtain the Dry Air Filler (TFSA) in order to initiate the calibration through Campbell Scientic sensors, model CS655. The equipment was calibrated in the moisture contents of 0% (TFSA), 5%, 10%, 20%, 25%, 30%, 35% and 45%.For data analysis multiple linear regression was applied and a single calibration curve was applied and a single calibration curve was generated for the seven soil levels. The mathematical model that best fit the data was the polynomial cubic model with coefficient of determination (R²) of 0.96 at a significance level of p <0.05. The model was considered satisfactory for all estimates of regression coefficients, considering the normality and homogeneity analyzes evaluated in the residues. The equation may be used in climate modeling studies, hydrological cycles and in the sciences that study the large soil-water-plant-atmosphere system.