Predicting surface water profiles in sand
type: CreativeWork
description: Electromagnetic (EM) wave methods are used in many civil engineering applications for non-destructive investigations such as locating reinforcing steel and voids in concrete, sinkholes, buried utilities, the groundwater table, seepage through dams and determining the thickness of pavements. All of the applications depend on knowing the velocity of the EM wave through the material of interest. The velocity of EM waves through a vacuum is equivalent to the speed of light; however, as a material's ability to hold a charge increases (ability to be a capacitor), the velocity of the EM wave is slowed through that material. The relative permittivity (dielectric constant) of a material is a measure of a material's ability to hold a charge. Knowing the relative permittivity enables one to calculate the velocity of an EM wave through the material. The goal of a larger research program is to predict the relative permittivity of soils. A principal factor determining the relative permittivity of soil is the water content of the soil. In order to predict accurate relative permittivity for a soil, the water content of the soil must be known. The objective of the research project reported in this thesis was to choose a method to predict the water content of a soil and to quantify the accuracy of the method. The focus of the larger project is on the earth's near subsurface, 0 to about 1 m below ground surface. This depth is often characterized by alternately wet (saturated) to dry pores within the soil and is referred to as the vadose zone. Knowing the soil water condition at any time is paramount to being able to predict the relative permittivity and subsequently the velocity of EM waves through the soil. A computer code was selected to be used to predict the soil water along a vertical profile in the vadose zone. WinUNSAT-H, a Windows(R)-based version of the code UNSAT-H was used to model the subsurface and predict vertical soil water profiles as a function of time. Inputs into Wi…
abstract: Electromagnetic (EM) wave methods are used in many civil engineering applications for non-destructive investigations such as locating reinforcing steel and voids in concrete, sinkholes, buried utilities, the groundwater table, seepage through dams and determining the thickness of pavements. All of the applications depend on knowing the velocity of the EM wave through the material of interest. The velocity of EM waves through a vacuum is equivalent to the speed of light; however, as a material's ability to hold a charge increases (ability to be a capacitor), the velocity of the EM wave is slowed through that material. The relative permittivity (dielectric constant) of a material is a measure of a material's ability to hold a charge. Knowing the relative permittivity enables one to calculate the velocity of an EM wave through the material. The goal of a larger research program is to predict the relative permittivity of soils. A principal factor determining the relative permittivity of soil is the water content of the soil. In order to predict accurate relative permittivity for a soil, the water content of the soil must be known. The objective of the research project reported in this thesis was to choose a method to predict the water content of a soil and to quantify the accuracy of the method. The focus of the larger project is on the earth's near subsurface, 0 to about 1 m below ground surface. This depth is often characterized by alternately wet (saturated) to dry pores within the soil and is referred to as the vadose zone. Knowing the soil water condition at any time is paramount to being able to predict the relative permittivity and subsequently the velocity of EM waves through the soil. A computer code was selected to be used to predict the soil water along a vertical profile in the vadose zone. WinUNSAT-H, a Windows(R)-based version of the code UNSAT-H was used to model the subsurface and predict vertical soil water profiles as a function of time. Inputs into Wi…
author: Turner, Keyden Kriens
language: eng
language: English
date published: 2015
date modified: 2026-07-24T03:09:27Z
provider: University of Missouri
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Missouri--Columbia

PropertyValue
property ID: Handle
value: https://hdl.handle.net/10355/58518