Software data news: Software to estimate -33 and -1500kPa soil water retention using the non-parametric k-Nearest Neighbor technique

Authors:
A. Nemes;R. T. Roberts;W. J. Rawls;Ya. A. Pachepsky;M. Th. van Genuchten
Affiliations:
University of Maryland, Department of Plant Science and Landscape Architecture, College Park, MD 20742, USA and USDA - ARS Crop Systems and Global Change Laboratory, 10300 Baltimore Avenue, Bldg. ...;USDA - ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705, USA;USDA - ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705, USA;USDA - ARS Environmental Microbial Safety Laboratory, Beltsville, MD 20705, USA;USDA - ARS George E. Brown, Jr. Salinity Laboratory, Riverside, CA 92507, USA
Venue:
Environmental Modelling & Software
Year:
2008

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Computers and Electronics in Agriculture

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Abstract

A computer tool has been developed that uses a k-Nearest Neighbor (k-NN) lazy learning algorithm to estimate soil water retention at -33 and -1500kPa matric potentials and its uncertainty. The user can customize the provided source data collection to accommodate specific local needs. Ad hoc calculations make this technique a competitive alternative to publish pedotransfer equations, as re-development of such equations is not needed when new data become available.