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Research Project: MECHANISTIC PROCESS-LEVEL CROP SIMULATION MODELS FOR ASSESSMENT OF AGRICULTURAL SYSTEMS

Location: Crop Systems & Global Change

Title: Toward improving global estimates of field soil water capacity

Authors

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 22, 2010
Publication Date: March 14, 2011
Repository URL: http://hdl.handle.net/10113/49676
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.

   

 
Project Team
Timlin, Dennis
Fleisher, David
Reddy, Vangimalla
 
Publications
   Publications
 
Related National Programs
  Climate Change, Soils, and Emissions (212)
  Agricultural System Competitiveness and Sustainability (216)
 
Related Projects
   DEVELOPMENT, VALIDATION AND VERIFICATION OF NEW MODULES FOR CORN MODEL, MAIZSIM AND POTATO MODEL, SPUDSIM
   DEVELOPMENT OF DATASETS AND IMPROVED MODULES FOR CROP SYSTEMS & GLOBAL CHANGE LAB CROP AND SOIL MODELING SYSTEMS
   Enhancing Food Security of Underserved Populations in the Northeast Through Sustainable Regional Food Systems
 
 
Last Modified: 05/23/2013
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