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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #369321
Research Project: Design and Implementation of Monitoring and Modeling Methods to Evaluate Microbial Quality of Surface Water Sources Used for Irrigation

Location: Environmental Microbial & Food Safety Laboratory

Title: Analysis of spatial variability of soil water retention using the CDF matching

Author
item GUMMATOV, NIZAMI - AZERBAIJAN RESEARCH INSTITUTE OF CROP HUSBANDRY
item Pachepsky, Yakov

Submitted to: Soil Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/4/2020
Publication Date: 8/1/2020
Citation: Gummatov, N., Pachepsky, Y.A. 2020. Analysis of spatial variability of soil water retention using the CDF matching. Soil Science. https://doi.org/10.1139/cjss-2019-0130.
DOI: https://doi.org/10.1139/cjss-2019-0130

Interpretive Summary: Information on variability of soil water retention is needed in many applications related to soil water flow and storage as well as to pollutant transport. Large body of literature reports this variability via lumped values over the entire range of soil water contents. However, different applications need information specific to the degree of soil wetness, and such information is practically absent in literature. We used the data of extensive soil sampling and water retention measurement to determine the variability at 10 different levels of soil suction from very wet to practically dry. We found that soil variability followed normal distributions with parameters strongly deppendent of soil suction. A method was proposed to condense the water retention data and relate variability at different suction levels. Results of this work are important for water and pollutant transport modelers in that they indicate the need in requesting and applying site-specific variability parameters at the project-related levels of soil suctions.

Technical Abstract: Several models were proposed to simulate dependencies of soil water content on the matric potential. Modeling dependencies of spatial variability of soil water content on soil matric potential attracted less attention; importance of such modeling grows due to growth of ensemble modeling applications. The objective of this work was to use a large experimental dataset on spatial variability of water retention at different soil matric potential ranges for developing suggestions on modeling changes of the variability with matric potential. Eighty 100-cm^3 samples were taken in nodes of 5-meter grid to measure soil water retention using sand and sand-kaolin capillarimeters, and water vapor adsorption at absolute values of soil water potential of 0.001, 0.003, 0.01, 0.02, 0.05 MPa and at 3, 21, 39, 82, and 142 MPa, respectively. Probabilities of distributions of both non-transformed and log-transformed soil water contents appeared to be larger than 0.05 in the majority of cases. Using the probit function to represent the observed variability allowed us to match precumulative probability distributions. Slopes of dependences of probits on non-transformed and log-transformed water contents followed two different linear dependencies on logarithm of the absolute value of sol water potential in capillary range and in dry soil.