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Toward Improving Global Estimates of Field Soil Water Capacity
Author(s) -
Nemes Attila,
Pachepsky Yakov A.,
Timlin Dennis J.
Publication year - 2011
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2010.0251
Subject(s) - soil water , silt , saturation (graph theory) , soil science , drainage , soil texture , environmental science , field capacity , linear regression , regression analysis , water content , field (mathematics) , water retention , pedotransfer function , scale (ratio) , mathematics , hydrology (agriculture) , statistics , geotechnical engineering , geology , hydraulic conductivity , paleontology , ecology , physics , combinatorics , quantum mechanics , pure mathematics , biology
Field capacity or field water capacity (FC) is defined as the water content of a soil following saturation with water and after free drainage is negligible. Different recommendations exist worldwide on which, if any, pressure should be used in laboratory measurements to approximate the FC of the soil. Research has often deemed any such pressures to be inadequate to approximate FC for soils of all textures. We used a data collection from the literature to evaluate if corrections can be made to improve the estimation of FC from −33 kPa water retention (W33). Regression tree modeling coupled with jack‐knife cross‐validation was used to identify the best predictors—sand, silt, clay and the measured W33 value—to estimate the difference between W33 and FC. Such predictions were then used to adjust the W33 value as the estimate of FC. An improvement in estimating FC was seen in general statistical terms, and texture‐specific bias was also greatly reduced. This solution may allow the reliable use of a single pressure in the laboratory to approximate FC, which may be the only feasible option for large‐scale studies.