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Application of local porosity to define pore networks and pore geometry in soils
Descriptive
TypeOfResource
Text
TitleInfo
(ID = T-1)
Title
Application of local porosity to define pore networks and pore geometry in soils
SubTitle
a case study along a carbon dioxide and temperature gradient
Identifier
ETD_1650
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051188
Language
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eng
Genre
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theses
Subject
(ID = SBJ-1)
Name
(authority = LC-NAF)
Subject
(ID = SBJ-1);
(authority = RUETD)
Topic
Environmental Sciences
Subject
(ID = SBJ-1);
(authority = ETD-LCSH)
Topic
Soil porosity
Abstract
Pore network models are useful tools to investigate soil pore geometry. These models provide quantitative information of pore geometry from 3D images. However, there are limitations in image sizes and resolutions to extract networks. This study presents a modified pore network model to characterize large images with local porosity. The objectives of this work were to apply the modified model to characterize pore structure from large images at different scales (aggregate and soil column), image sizes, and resolutions and to characterize changes in pore structure induced by different levels of CO2 and temperature. Soil samples were taken from three sites (urban site with the highest, suburban with intermediate and rural with the lowest CO2 concentration and temperature). Undisturbed columns (5.5 cm in diameter and 12 cm in height) and aggregate samples were taken from each site and scanned with a computer tomographer at resolutions of 22 (column) and 6 microns (aggregates).
Pore networks were extracted by medial-axis transformation from local porosities at a unit cell and were used to measure pore geometry from aggregates and bulk soils. Three image volumes and 12 cell sizes were used to define image and cell size scaling effects. The configuration entropy and universal multifractals were employed to characterize pore spatial distributions, and water retention and hydraulic conductivity were measured on bulk soils.
Pore numbers and pore volumes measured in soil columns and aggregates had a linear relationship in log-log plots across cell sizes, while pore length and tortuosity did not show any specific trend. These results imply that some properties cannot be accurately projected to different scales within aggregate and laboratory scales.
Pore spatial distribution in bulk soils from all three sites and pore geometry information from aggregates and bulk soils of urban and rural site showed that different level of CO2 and temperature affected pore structure formations. Pores from urban site were more widespread and were greater than rural site. Hydraulic properties confirmed that urban soil had more connected and less tortuous pores than rural soil.
The modified pore network model is a powerful tool to characterize pore properties from large size images.
Pore networks were extracted by medial-axis transformation from local porosities at a unit cell and were used to measure pore geometry from aggregates and bulk soils. Three image volumes and 12 cell sizes were used to define image and cell size scaling effects. The configuration entropy and universal multifractals were employed to characterize pore spatial distributions, and water retention and hydraulic conductivity were measured on bulk soils.
Pore numbers and pore volumes measured in soil columns and aggregates had a linear relationship in log-log plots across cell sizes, while pore length and tortuosity did not show any specific trend. These results imply that some properties cannot be accurately projected to different scales within aggregate and laboratory scales.
Pore spatial distribution in bulk soils from all three sites and pore geometry information from aggregates and bulk soils of urban and rural site showed that different level of CO2 and temperature affected pore structure formations. Pores from urban site were more widespread and were greater than rural site. Hydraulic properties confirmed that urban soil had more connected and less tortuous pores than rural soil.
The modified pore network model is a powerful tool to characterize pore properties from large size images.
PhysicalDescription
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electronic resource
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xviii, 173 p. : ill.
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text/xml
Note
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Ph.D.
Note
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Includes bibliographical references
Note
(type = statement of responsibility)
by Hyen Chung Chun
Name
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Chun
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Hyen Chung
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1973
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Hyen Chung Chun
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Gimenez
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Daniel
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chair
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Advisory Committee
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Daniel Gimenez
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Reinfelder
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Ying Fan
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Advisory Committee
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Ying Fan Reinfelder
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(type = family)
Huang
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(type = given)
Weilin
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Advisory Committee
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Weilin Huang
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Heck
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Richard
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outside member
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Advisory Committee
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Richard Heck
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Rutgers University
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degree grantor
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Graduate School - New Brunswick
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school
OriginInfo
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2009
DateOther
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2009-05
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xx
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Rutgers University Electronic Theses and Dissertations
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ETD
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Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
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NjNbRU
Identifier
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doi:10.7282/T3VM4CGD
Genre
(authority = ExL-Esploro)
ETD doctoral
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The author owns the copyright to this work.
Copyright
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Copyright protected
Availability
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Open
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Non-exclusive ETD license
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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