Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/6/2005
Publication Date: 9/1/2006
Citation: Saxton, K.E., Rawls, W.J. 2006. Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Science Society of America Journal. 70:1569-1578. Interpretive Summary: Statistical analyses of a large, modern data set of measured soil water properties were conducted to develop equations that improved estimates of soil moisture retention and hydraulic conductivity for a broad range of textures and organic matter. These equations were enhanced with improved estimates of air and reported equations of conductivity, gravel and salinity to provide a water characteristic model useful for a wide variety of hydrologic and soil water applications. Since the model results are based on statistical analyses or laboratory data and auxiliary methods tp approximate those of a specific soil type and characteristic, local knowledge and data should be used if available to calibrate the results by varying the input parameters within acceptable limits. A graphical computer program of the model readily provides equation solutions for many agricultural and hydrologic applications (http://hydrolab.arsusda.gov/SPAW/Index.htm). Applied with this insight and respect, this predeictive system will enhance the opportunity to integrate the vast available soils knowledge into hydrologic and water management analyses and decisions.
Technical Abstract: Hydrologic analyses often involve the evaluation of soil water infiltration, conductivity, storage, and plant-water relationships. To define the variable soil water effects requires estimating soil water relationships for water potential and hydraulic conductivity which depend on soil characteristics such as texture, organic matter and structure. Field or laboratory measurement of these relationships is difficult, costly and often impractical for many hydrologic analyses. Estimates based on the generalities of reported data are often adequate for many purposes. Previous studies have shown that statistical correlations between soil texture, soil water potential and hydraulic conductivity can provide sufficiently accurate estimates for hydrologic analyses and decisions. An extensive data set based on modern laboratory methods were assembled and analyzed to provide improved estimates of soil water characteristics. These new equations based on a wide range of soil textures and organic matter and were combined with adjustments for the effects of density, gravel and salinity. These equations provide reasonably accurate soil water characteristic estimates and computer efficiency when combined with modern computer methodology to provide rapid and graphical solutions. It is recognized that the equations are the statistical average of a large data set, thus the results will vary somewhat for specific soils due to additional variables such as mineral type structure.