Using dredged material to restore the Chesapeake Marshlands Complex: Preliminary application of a risk-based optimization model for comparing placement options

dc.contributor.advisorKing, Dr. Dennis M.en_US
dc.contributor.authorShearin, Charlotte Bruceen_US
dc.contributor.departmentMarine-Estuarine-Environmental Sciencesen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2010-10-07T05:53:04Z
dc.date.available2010-10-07T05:53:04Z
dc.date.issued2010en_US
dc.description.abstractUsing dredged material to restore wetlands in the Chesapeake Marshlands Complex (CMC) could offer solutions to two separate problems: 1) restoring and protecting the marshes in the CMC; and 2) finding an innovative reuse for dredged material from the Chesapeake Bay approach channels. The risk-based optimization model presented here assesses and compares restoration options for two alternative years (2023 and 2036) when the project may begin and represents a preliminary screening of material placement locations. Restoration of Zones 2a (Barbados Island) and 2b (Confluence Area) appear to provide significant environmental benefits, suggesting that restoration at these locations would provide the best return on investment. Low marsh restoration also provides a significant amount of benefits accrued. Based on sensitivity analysis, it appears that the choice of when to begin the project also represents tradeoffs between onsite habitat benefits and recreational benefits. Model results should be interpreted cautiously, considering the model limitations.en_US
dc.identifier.urihttp://hdl.handle.net/1903/10866
dc.subject.pqcontrolledEnvironmental economicsen_US
dc.subject.pquncontrolleddredged materialen_US
dc.subject.pquncontrolledoptimization modelen_US
dc.subject.pquncontrolledrisken_US
dc.subject.pquncontrolledwetlands restorationen_US
dc.titleUsing dredged material to restore the Chesapeake Marshlands Complex: Preliminary application of a risk-based optimization model for comparing placement optionsen_US
dc.typeThesisen_US

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