{"id":{"repo_id":"colo-mines","oai_identifier":"oai:repository.mines.edu:11124/170319"},"canonical_url":"https://search.dev.ndltd.org/etd/colo-mines/oai:repository.mines.edu:11124/170319","repository":{"repo_id":"colo-mines","name":"Colorado School of Mines","base_url":"https://repository.mines.edu/server/oai/request"},"display":{"title":"Examination of the impact of the natural environment on levee sustainability, An","abstract":"Artificially constructed levees provide a series of valuable services including flood protection, tidal protection, and fresh water storage. Extending the life and status of levees reduces the potential for levee failures and enhances their benefits. The objective of this study was to improve our ability to predict the sustainability of a levee by examining the character of the environment surrounding the levee. Utilizing geographic information systems (GIS), approximately 225 kilometers (~140 miles) of levees within the Lower Mississippi River Valley are divided into small segments and a series of environmental factors are assigned to each levee segment. These factors include, amongst others, the configuration of Quaternary Geology with respect to the levee alignment, the hydrogeological nature of the alluvial aquifer beneath the levee, and soil physical properties. A binary logistic regression was then applied to the dataset to evaluate the correlation between these environmental factors and the development of levee distress features (seepage lines and sand boils) and generate a model capable of predicting distress features. Results of the logit model were then fed into a multiple criteria decision making (MCDM) system to categorize environments into levee sustainability groups. Results from the logistic regression indicated significant correlation between the development of levee distress indicators and four environmental characteristics: paleo channel orientation, AASHTO soil classification, normalized difference vegetation index (NDVI), and saturated hydraulic conductivity of the soil. The predictive model generated using these significant factors was moderately successful, correctly predicting the status of distress feature development with up to 62% accuracy. The MCDM system identified forests composed of sweetgum, nuttal oak, and willow oak as being highly sustainable for the construction and maintenance of levees. Plots of sycamore, pecan, and American elm trees and water bodies identified by ecophysiography were rated as the least sustainable environments for levees. With additional development, future models may serve as tools to improve our ability to assess, maintain, and design levee systems.","abstract_html":"Artificially constructed levees provide a series of valuable services including flood protection, tidal protection, and fresh water storage. Extending the life and status of levees reduces the potential for levee failures and enhances their benefits. The objective of this study was to improve our ability to predict the sustainability of a levee by examining the character of the environment surrounding the levee. Utilizing geographic information systems (GIS), approximately 225 kilometers (~140 miles) of levees within the Lower Mississippi River Valley are divided into small segments and a series of environmental factors are assigned to each levee segment. These factors include, amongst others, the configuration of Quaternary Geology with respect to the levee alignment, the hydrogeological nature of the alluvial aquifer beneath the levee, and soil physical properties. A binary logistic regression was then applied to the dataset to evaluate the correlation between these environmental factors and the development of levee distress features (seepage lines and sand boils) and generate a model capable of predicting distress features. Results of the logit model were then fed into a multiple criteria decision making (MCDM) system to categorize environments into levee sustainability groups. Results from the logistic regression indicated significant correlation between the development of levee distress indicators and four environmental characteristics: paleo channel orientation, AASHTO soil classification, normalized difference vegetation index (NDVI), and saturated hydraulic conductivity of the soil. The predictive model generated using these significant factors was moderately successful, correctly predicting the status of distress feature development with up to 62% accuracy. The MCDM system identified forests composed of sweetgum, nuttal oak, and willow oak as being highly sustainable for the construction and maintenance of levees. Plots of sycamore, pecan, and American elm trees and water bodies identified by ecophysiography were rated as the least sustainable environments for levees. With additional development, future models may serve as tools to improve our ability to assess, maintain, and design levee systems.","abstract_has_math":false,"creators":["Semmens, Stephen"],"institution":"Colorado School of Mines. 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(Paul Michael), 1964-"],"year":2016,"date_issued":"2016","date_published":"2016","updated_at":"2026-07-24T01:43:31Z","subjects":["artificial levee","MCDM","Mississippi","NDVI","sand boil","seepage line"],"languages":["eng","English"],"rights":["Copyright of the original work is retained by the author."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["T 8092"],"render_values":[{"text":"T 8092","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/11124/170319","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Zhou, Wendy"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["van Wesenbeeck, Bregje K.","Santi, Paul M. 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Extending the life and status of levees reduces the potential for levee failures and enhances their benefits. The objective of this study was to improve our ability to predict the sustainability of a levee by examining the character of the environment surrounding the levee. Utilizing geographic information systems (GIS), approximately 225 kilometers (~140 miles) of levees within the Lower Mississippi River Valley are divided into small segments and a series of environmental factors are assigned to each levee segment. These factors include, amongst others, the configuration of Quaternary Geology with respect to the levee alignment, the hydrogeological nature of the alluvial aquifer beneath the levee, and soil physical properties. A binary logistic regression was then applied to the dataset to evaluate the correlation between these environmental factors and the development of levee distress features (seepage lines and sand boils) and generate a model capable of predicting distress features. Results of the logit model were then fed into a multiple criteria decision making (MCDM) system to categorize environments into levee sustainability groups. Results from the logistic regression indicated significant correlation between the development of levee distress indicators and four environmental characteristics: paleo channel orientation, AASHTO soil classification, normalized difference vegetation index (NDVI), and saturated hydraulic conductivity of the soil. The predictive model generated using these significant factors was moderately successful, correctly predicting the status of distress feature development with up to 62% accuracy. The MCDM system identified forests composed of sweetgum, nuttal oak, and willow oak as being highly sustainable for the construction and maintenance of levees. Plots of sycamore, pecan, and American elm trees and water bodies identified by ecophysiography were rated as the least sustainable environments for levees. With additional development, future models may serve as tools to improve our ability to assess, maintain, and design levee systems."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["born digital","masters theses"]},{"key":"dc:title","label":"Title","values":["Examination of the impact of the natural environment on levee sustainability, An"]}]}],"canonical_facts":{"dc:contributor.advisor":["Zhou, Wendy"],"dc:contributor.committeemember":["van Wesenbeeck, Bregje K.","Santi, Paul M. (Paul Michael), 1964-"],"dc:creator":["Semmens, Stephen"],"dc:date.accessioned":["2016-07-05T13:33:12Z","2022-02-03T12:56:03Z"],"dc:date.available":["2016-07-05T13:33:12Z","2022-02-03T12:56:03Z"],"dc:date.issued":["2016"],"dc:description":["Includes bibliographical references.","2016 Summer."],"dc:description.abstract":["Artificially constructed levees provide a series of valuable services including flood protection, tidal protection, and fresh water storage. Extending the life and status of levees reduces the potential for levee failures and enhances their benefits. The objective of this study was to improve our ability to predict the sustainability of a levee by examining the character of the environment surrounding the levee. Utilizing geographic information systems (GIS), approximately 225 kilometers (~140 miles) of levees within the Lower Mississippi River Valley are divided into small segments and a series of environmental factors are assigned to each levee segment. These factors include, amongst others, the configuration of Quaternary Geology with respect to the levee alignment, the hydrogeological nature of the alluvial aquifer beneath the levee, and soil physical properties. A binary logistic regression was then applied to the dataset to evaluate the correlation between these environmental factors and the development of levee distress features (seepage lines and sand boils) and generate a model capable of predicting distress features. Results of the logit model were then fed into a multiple criteria decision making (MCDM) system to categorize environments into levee sustainability groups. Results from the logistic regression indicated significant correlation between the development of levee distress indicators and four environmental characteristics: paleo channel orientation, AASHTO soil classification, normalized difference vegetation index (NDVI), and saturated hydraulic conductivity of the soil. The predictive model generated using these significant factors was moderately successful, correctly predicting the status of distress feature development with up to 62% accuracy. The MCDM system identified forests composed of sweetgum, nuttal oak, and willow oak as being highly sustainable for the construction and maintenance of levees. Plots of sycamore, pecan, and American elm trees and water bodies identified by ecophysiography were rated as the least sustainable environments for levees. With additional development, future models may serve as tools to improve our ability to assess, maintain, and design levee systems."],"dc:format.medium":["born digital","masters theses"],"dc:identifier":["T 8092"],"dc:identifier.uri":["https://hdl.handle.net/11124/170319"],"dc:language":["English"],"dc:language.iso":["eng"],"dc:publisher":["Colorado School of Mines. Arthur Lakes Library"],"dc:rights":["Copyright of the original work is retained by the author."],"dc:subject":["artificial levee","MCDM","Mississippi","NDVI","sand boil","seepage line"],"dc:title":["Examination of the impact of the natural environment on levee sustainability, An"],"dc:type":["Text"],"thesis:degree_discipline":["Geology and Geological Engineering"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Master of Science (M.S.)"],"thesis:institution_name":["Colorado School of Mines"]},"updated_at":"2026-07-24T01:43:31Z"}