Spatial patterns of soil attributes in a fluvent in the semiarid region, Brazil
Author(s) -
Wanessa Lins de Andrade Carolyne,
Antonio de Assunçao Montenegro Abelardo,
M. Suzana,
Soares da Silva Jucicleia,
Elisa Tavares Uilka
Publication year - 2017
Publication title -
african journal of agricultural research
Language(s) - English
Resource type - Journals
ISSN - 1991-637X
DOI - 10.5897/ajar2016.11986
Subject(s) - geostatistics , soil texture , environmental science , spatial variability , water content , soil science , soil water , hydrology (agriculture) , dryland salinity , soil fertility , soil biodiversity , mathematics , geology , statistics , geotechnical engineering
Spatial variability studies on soil attributes are fundamental for adoption of best agricultural practices concerned with irrigated agricultural sustainability. This study aims to infer the spatial variability patterns of soil moisture, soils salinity and soil texture in an irrigated area of Pernambuco State (Brazil) under cultivation of carrot (Daucus Carota L.), during the dry period of 2012. The area is a typical system in the semiarid under small scale agricultural practices. For the study, it was adopted a 4 × 4 m regular mesh, with 49 sampling points collected at 0-0.2 m and 0.2-0.4 m layers. Data were submitted to classical statistical procedure, followed by geostatistical analysis. For soil moisture at 0.2-0.4 m layer and clay content, the degree of variability was considered low. For soil moisture at 0-0.2 m the degree of variability was moderate, while the electrical conductivity showed a high degree of variability. Occurrence of soil salinity is higher at the soil surface. Water flow occurs from the borders to the central plot, as evidenced by contour maps. Geostatistics allowed the characterization of the spatial variability patterns for the main soil attributes in an irrigated plot in the semiarid of Brazil, and it has been shown as an important tool for the prediction of soil attributes. Such results are important for issuing guidance for sustainable small scale agriculture practices in the region. Key words: Geostatistics, soil moisture, salinity, texture, communal farming.
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