Abstract
ABSTRACT The Cerrado biome is a strategic region for Brazilian agriculture, and obtaining physical hydraulic properties is fundamental to understanding the dynamics of soil water and its impact on productivity. However, the lack and difficulty of obtaining such properties opens an opportunity to use pedotransfer functions (PTFs). In the context, the objective of the present study was to develop PTFs using multiple linear regression to estimate hydraulic conductivity of the saturated soil (Ks) and soil moisture at tensions of 0, 6, 10, 33, 100, and 1,500 kPa for the Cerrado biome. For this, two different predictor datasets were used. Dataset 1 consists of sand, silt, clay, bulk density, particle density, total porosity, microporosity, and macroporosity, and dataset 2 consists of the variables in dataset 1 plus soil moisture at field capacity (FC) and soil moisture at the permanent wilting point (PMP). Dataset 2 presented the best performance compared to Dataset 1 for estimating Ks and soil moisture, highlighting the importance of moisture in FC and PWP as predictors in the development of PTFs. However, the PTFs developed for Ks presented a low predictive capacity in all predictor datasets, unlike the soil moistures that presented high precision, with R² greater than 0.8 and errors close to zero.
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More From: Revista Brasileira de Engenharia Agrícola e Ambiental
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