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Estimating spatial variability in soil moisture with a simplified dynamic model
Author(s) -
Clapp R. B.,
Hornberger G. M.,
Cosby B. J.
Publication year - 1983
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr019i003p00739
Subject(s) - soil science , spatial variability , environmental science , water content , infiltration (hvac) , soil water , spatial heterogeneity , pedotransfer function , moisture , precipitation , scaling , hydrology (agriculture) , geology , hydraulic conductivity , geotechnical engineering , mathematics , meteorology , geography , ecology , statistics , geometry , biology
Observed spatial variability of soil moisture in the field may be due to several factors. Topographic effects, soil heterogeneity, and spatial variability in precipitation and vegetation may induce variability in measured soil moisture. Scaling theory has been suggested as a promising tool for describing soil heterogeneity and, consequently, a portion of spatial variability of measured soil moisture. We investigate the appropriateness of ascribing soil moisture variability to heterogeneity of soil properties through the use of a model of soil moisture dynamics and scaling theory. The model, termed a wetting front model, is a simplified representation of water movement in soils. The model conceptually depicts the moisture profile as discrete blocks of soil moisture separated by sharp fronts. Probabilistic simulations were run with input data appropriate to watersheds R‐5 and R‐7 at Chickasha, Oklahoma. Results from the simulations indicate that variability due to soil heterogeneity remains relatively constant through time with only slight increases during redistribution following infiltration. A comparison of simulated and observed soil moisture integrated from the surface to the 15‐cm depth shows that heterogeneity in soil hydraulic properties may account for approximately 75% of observed standard deviation.