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Predictions of the Soil Water Flux Based upon Field‐measured Soil‐water Properties
Author(s) -
Warrick A. W.,
Mullen G. J.,
Nielsen D. R.
Publication year - 1977
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/sssaj1977.03615995004100010009x
Subject(s) - flux (metallurgy) , hydraulic conductivity , log normal distribution , soil water , monte carlo method , water content , soil science , hydrology (agriculture) , mathematics , environmental science , chemistry , statistics , geology , geotechnical engineering , organic chemistry
Predictions of soil water flux are made taking into account spatial variability of the soil water parameters. A conductivity of the form K = K o exp [α(θ − θ o )] is utilized where θ is the volumetric water content with K o and θ g the values of hydraulic conductivity and water content for steady‐state intake from water ponded on the soil surface. The value of α is an empirical constant for each site and for each depth. Monte Carlo simulations are used to simulate the flux distribution from the simplified drainage equation J L = K o (1 + α K o t/L ) ‐1 . The flux of J L is a random output dependent upon the stochastic nature of K o and α. Long‐normal distributions of K o and α are chosen from field data published for Panoche soil. Output of J L is approximately lognormal for all times studied. The mean value of J L is larger than the flux calculated using the average K o and α values in the above equation. Sample numbers necessary to estimate the means of the flux at t = 0, 1, and 10 days are plotted. For t = 0, samples of 1,000, 100, and 50 result in estimates of J L within 16, 50, and 60% of the true mean 95% of the time. For t = 1 and 10 days similar figures for samples of 1,000, 100, and 50 are 4, 14, and 20%. Values of water content stored in the profile using the above equations are also examined as a random function. Unlike the flux values the range in values stays about the same for at least 20 days. The research points out a need for meaningful methods for sample stratification in order to reduce variances.