Dados do Trabalho

Título

SAMPLING DESIGN AND SPATIAL MODELING OF AVAILABLE PHOSPHORUS IN A COMPLEX AGRICULTURAL AREA

Resumo

The growing demand for food and the need to use natural resources sustainably require research that contributes to generating high-quality and high-spatial resolution maps of soil properties. There are few studies that compare different sampling designs in the same area in order to generate digital maps of soil properties. The purpose of this work was to compare three sampling designs and two modeling methods applied in the spatial prediction of available P in the soil. The study was conducted in a 160 ha where three sampling methods were tested - simple regular grid (RG) with a fixed distance between points, spatial coverage sampling (SCS) containing points over short distances, and simulated annealing sampling considering the marginal distribution of environmental covariates (DIST) - as a basis for prediction of the available phosphorus content in the soil, at a depth of 0-10 cm. Thus, each calibration set contains 160 samples (with the exception of the regular grid, which has 162), which were used to calibrate two predictive models: kriging with external drift (KED), considered a mixed model because it encompasses the geostatistical approach and deterministic; and ordinary kriging (OK). The results were validated with an external and independent set containing 50 points. The best prediction result was found by combining the DIST sampling with the KED model, which has a lower mean absolute error (MAE) = 14.62 mg dm-3, mean error (ME) = -3.12 mg dm-3, and root mean squared error (RMSE) = 23.44 mg dm-3 and higher Nash-Sutcliffe efficiency (NSE) = 0.13. Sampling designs that consider environmental covariables contribute to the increase in the quality of the predicted soil attribute maps.

Palavras-chave

Digital soil mapping, geostatistic, sampling methods, pedometric, precision agriculture.