Browsing by Subject "Vertisol"
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Item Systematic Variability of Soil Hydraulic Conductivity Across Three Vertisol Catenas(2011-10-21) Rivera, Leonardo DanielSoil hydraulic properties, such as saturated hydraulic conductivity (Ks), have high spatial variation, but little is known about how to vary a few measurements of Ks over an area to model hydrology in a watershed with complex topography and multiple land uses. Variations in soil structure, macropores (especially in soil that shrink and swell), land use, and soil development can cause large variations in Ks within one soil type. Characterizing the impacts of soil properties that might vary systematically with land use and terrain attributes on Ks rates would provide insight on how management and human activity affect local and regional hydrology. The overall objective of this research was to develop a strategy for using published infiltration and Ks measurements by the Natural Resources Conservation Service for watershed hydrology applications in a Vertisol, and to extend this knowledge toward developing recommendations for future infiltration measurements. To achieve this goal, soil infiltration measurements were collected across three catenas of Houston Black and Heiden clays (fine, smectitic, thermic Udic Haplusterts) under three land uses (improved pasture, native prairie, and conventional tillage row crop). Measurement locations were selected to account for variation in terrain attributes. Overall, Ks values were not significantly different across different landscape positions; however, in fields under similar land uses, Ks values were found to be lower in the footslope positions and higher in the backslope positions. The pedotransfer function, ROSETTA, provided estimates of 64 percent of the overall variability in Ks while also providing accurate estimates of the mean of Ks when particle size distribution and bulk density are used as inputs in the model. Through the use of multiple regression analysis, soil antecedent water content, bulk density, clay content, and soil organic carbon along with two indicator variables for the catenas were highly correlated (r2 = 0.59) with Ks. The indicator variables explained 17 percent of the variation in Ks that could not be explained by measured soil properties. It is recommended that when NRCS measures Ks on benchmark soils, especially high clay soils, that they collect particle size distribution, bulk density, organic carbon, and antecedent water content data.Item Testing a Mesopore and Matrix Model for Use on Shrink-Swell Soils(2014-10-15) Bagnall, Dianna KathleenVoid space caused by drying of shrink-swell soils forms desiccation cracks and mesopores which conduct water from the soil surface, influencing water redistribution and complicating the partitioning infiltration and runoff. These paths impact hydrology, but often are not included in models because the standard method of modeling flow through soil (Richards? equation) assumes a continuous matrix of particles-this assumption is invalidated by voids, the changing volume of paths is difficult to characterize, and parameters to simulate water flow are difficult to obtain for preferential flow routines. The Precision Agriculture Landscape Modeling System (PALMS) contains a Mesopore and Matrix (M&M) module, which was tested on cracking soil at the plot and field scale. The M&M module predicted 10 times more mesopore area than, but was linearly related to, measurements of crack area. Four irrigation events on plots of cracked soil and volumetric water content (VWC) output for the M&M module was compared to neutron moisture meter readings. Previous measurements of VWC and runoff on a 4.4 ha subwatershed were compared to predictions. The M&M module moved water down the profile quickly and eliminated unobserved ponding (plot) and runoff (field) that were simulated without the mesopores, modeling mesopore flow did produce more drainage. Simulations of water content of the soil profile were generally improved when the M&M module was used. The M&M module had easily obtainable and physically relevant parameters. The M&M module is a useful tool for model assisted decision making on landscapes where preferential flow occurs.