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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Adaptive Cropping Systems Laboratory » Research » Publications at this Location » Publication #255591
Title: Toward improving global estimates of field soil water capacity

Author
item NEMES, ATTILA - University Of Maryland
item Pachepsky, Yakov
item Timlin, Dennis

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/22/2010
Publication Date: 3/14/2011
Citation: Nemes, A., Pachepsky, Y.A., Timlin, D.J. 2011. Toward improving global estimates of field soil water capacity. Soil Science Society of America Journal. 75(3):807-812.

Interpretive Summary: Field capacity is a critical agronomic and environmental parameter that shows the amount of water that the soil holds after rainfall followed by drainage. It is impractical to measure it where estimations are needed for large areas of land; therefore it is commonly estimated from laboratory measurements of soil water retention. Attempts to standardize this estimation procedure failed. We hypothesized that the accuracy of such estimates may depend on soil particle size composition. We tested this hypothesis on a unique large database on U.S. soils and developed a correction for laboratory values. This correction is solely based on clay content, and it has markedly improved the field capacity estimates. The approach and results will be useful worldwide in climate-change and management-change related modeling of crop and ecosystem functioning and response.

Technical Abstract: Field capacity or field water capacity (FC) is defined as the water content of a soil after having been wetted with water and after free drainage is negligible. Different recommendations exist world-wide on which, if any, pressure head should be used in laboratory measurements to approximate the FC of the soil. Literature often deems any such pressure heads 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 successfully 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. Such solution may allow the reliable use of a single pressure head in the laboratory to approximate FC, which may be the only feasible option for large scale studies.