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Investigating translated data of the German soil‐quality assessment using pinpoint field validation
Author(s) -
Hangen Edzard,
Förster Helmwart
Publication year - 2013
Publication title -
journal of plant nutrition and soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.644
H-Index - 87
eISSN - 1522-2624
pISSN - 1436-8730
DOI - 10.1002/jpln.201300021
Subject(s) - soil texture , soil science , topsoil , silt , subsoil , soil map , environmental science , soil quality , weathering , pedotransfer function , texture (cosmology) , soil horizon , soil morphology , geology , soil classification , hydrology (agriculture) , hydraulic conductivity , soil water , geomorphology , geotechnical engineering , computer science , artificial intelligence , image (mathematics)
In contrast to modern soil‐profile characterization, alternative soil classifications, such as the German soil‐quality assessment ( Bodenschätzung ), bear a lower degree of scientific quality. However, despite originally created to determine the tax value of arable land and grassland, its high spatial resolution and complete areal coverage makes soil‐quality assessment a valuable tool. To assess its performance in a mountainous setting soil‐layer data of 60 soil pits, recorded in Bavaria (SE Germany) in the course of the soil‐quality assessment, were translated into German soil‐science terminology using the translation program NIBIS®. With regard to soil type and texture the translation was checked using pinpoint field validation based on soil‐science terminology. 57% of soil types and 61% of texture were correctly translated by NIBIS®. To obtain information about probable parameters that can explain the different results readily available parameters such as elapsed time between soil‐quality assessment and validation, altitude, slope, aspect, horizon thickness, lower edge of horizon, as well as weathering surface and silicate‐weathering rate derived from geological maps were used. Differences in topsoil texture were somewhat related to petrographic parameters, those of the lower subsoil showed a weak dependence to topographic parameters. The NIBIS® translation overrated the silt content to the expense of sand. Clay was the best‐matched texture class. The shift towards silty texture classes was the dominant factor for the differences of texture‐related values of the available water capacity and hydraulic conductivity. Both parameters as derived from the NIBIS® translation on the one and from field validation on the other hand were used to evaluate the water‐retention capacity of individual soil profiles. Despite differing input data the soils' water‐retention capacity was rated identical. Thus, a certain degree of disagreement between the texture data obtained from NIBIS® translation and from field validation is tolerable, if the eventual soil‐function evaluation is based on wide classes of texture or of secondary parameters derived from texture.