Premium
Hydraulic Conductivity as Related to Certain Soil Properties in a Number of Great Soil Groups—Sampling Errors Involved
Author(s) -
Mason D. D.,
Lutz J. F.,
Petersen R. G.
Publication year - 1957
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/sssaj1957.03615995002100050025x
Subject(s) - hydraulic conductivity , silt , bulk density , soil science , soil texture , permeability (electromagnetism) , sampling (signal processing) , soil water , conductivity , environmental science , mathematics , hydrology (agriculture) , mineralogy , geology , chemistry , geotechnical engineering , geomorphology , physics , biochemistry , membrane , detector , optics
This study was undertaken to provide information about hydraulic conductivity, percent large pores, and bulk density, their interrelationships, and the magnitude of the sampling error components involved over a wide range of soil conditions. Data from approximately 10,000 individual core samples from about 900 sites in 7 states, furnished in a cooperative project with the Soil Conservation Service, United States Department of Agriculture, were analyzed. Each sample was classified according to management, genetic unit (great soil group, high family, low family, and series), texture, and horizon. Mean values for hydraulic conductivity, percent large pores and bulk density, when classified by textural groups, showed a consistent decrease in magnitude with increases in silt and clay content. Mean values for the three properties, when classified by great soil groups, showed consistent differences between groups. Correlations between hydraulic conductivity and percent large pores was positive and comparatively consistent; correlations between hydraulic conductivity and bulk density were negative and generally of a low absolute value. The indicated conclusion was that bulk density, in itself, is a poor indicator of soil permeability. Variance components for among cores within sites and horizons, and between sites, after removal of all other classifiable variation, indicated that the between site component of the sampling error was 2 to 3 times larger than the within site component. These components are used to estimate “distinguishable permeability classes” for various sampling schemes, and by assuming various cost ratios, optimum sampling rates are estimated.