Estimating soil loss by laminar erosion using precision agriculture computational tools¹

Estimativa da perda de solo por erosão laminar usando ferramentas computacionais na agricultura de precisão

HIGHLIGHTS:

The greater the stability of the aggregates in water, the lower the surface runoff.

The USLE makes it possible to identify places susceptible to erosion.

Computational tools optimize environmental conservation techniques.

ABSTRACT

The study aimed to identify and evaluate the spatial variability in laminar erosion in areas using precision agriculture tools. Soil data from three properties in the western region of Paraná state, Brazil, were used: one in the municipality of Céu Azul (area A) and two in Serranópolis do Iguaçu (areas B and C). To identify discrepant data (outliers), analysis of the dispersion of quartiles was performed using a box-plot graph. Data normality was verified using the Kolmogorov-Smirnov test. A spatial analysis was performed using AgDataBox-Map software. The parameters of the universal soil loss equation were estimated and used with map algebra to produce a model to identify areas susceptible to erosion. Area A (soil loss estimate = 0-200 t ha^-1 per year) presented greater susceptibility to erosion than areas B and C (soil loss estimate = 0-150 t ha^-1 per year); however, all areas had a low susceptibility to erosion.

Key words:
precision agriculture; thematic maps; geostatistics; universal soil loss equation; kriging