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Examination of Data Collected from Experiments on Soil Disturbance Using Fuzzy Indicator Approach
Author(s) -
H. Allen Torbert,
Dmitry Kurtener,
Elena Krueger
Publication year - 2016
Publication title -
european agrophysical journal
Language(s) - English
Resource type - Journals
eISSN - 2296-7664
pISSN - 2296-763X
DOI - 10.17830/j.eaj.2016.03.025
Subject(s) - disturbance (geology) , environmental science , fuzzy logic , hydrology (agriculture) , computer science , geology , geotechnical engineering , artificial intelligence , geomorphology
Soil disturbance can have important impacts on soil quality and productivity which impact management decisions.  However, the extent of potential damage to soil due to soil disturbance is not always obvious.  Methods are needed to determine the level of soil disturbance from soil testing.  A methodology for this problem could be found using a tool for computations of two soil disturbance indicators called “Disturbance Factor Simple (DFS)” and “Disturbance Factor Complex (DFC)”.  This study examined this tool for the examination of data collected from experiments on soil disturbance in two different climatic reagions: Fort Riley, KS, and Fort Benning, GA, USA.  Results for Fort Riley indicate that the best indicator of disturbance was the DFS calculated for Ni, Ca, Mg, and C while DFS calculated for Cr, Pb, Ni, and Ca was best for Fort Benning.  Results also indicate that the use of DFS calculated for Cu and Ni as affected by changes in soil depth may be useful for detecting archeological sites across soil types.

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