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dc.contributor.advisorBrubaker, Kaye Len_US
dc.contributor.authorMardones, Javieren_US
dc.date.accessioned2019-06-20T05:43:02Z
dc.date.available2019-06-20T05:43:02Z
dc.date.issued2019en_US
dc.identifierhttps://doi.org/10.13016/fxpd-jhco
dc.identifier.urihttp://hdl.handle.net/1903/22051
dc.description.abstractPredicting stream flow is essential for safe and economic planning and design of hydraulic structures. This study uses the observed channel cross-section from LiDAR data and physical concepts of shear stress to estimate bankfull discharge (Qbf). Assuming that Qbf is the median of the annual peak flow distribution, a 2-parameter Extreme Value Type I distribution was fitted to predict discharge to a 200-year return period. The method was compared with gauged sites in low-order streams (less than 90-meter bankfull width) resulting in SE/SY=1.31 for Qbf and SE/SY=1.90 for the 200-year return period discharge; model precision is poor. However, the relative bias (-15\% to +15\%) demonstrates that on average results are similar to gauged data. Relationships between flow and channel geometry assure a quick way to estimate stream data and can serve as a tool used prior to applying conventional hydrologic methods such as flow routing and regional regression equations.en_US
dc.language.isoenen_US
dc.titlePredicting Low Probability Streamflow Using Lidar Data and Hydraulic Geometryen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentCivil Engineeringen_US
dc.subject.pqcontrolledWater resources managementen_US
dc.subject.pqcontrolledHydraulic engineeringen_US
dc.subject.pqcontrolledHydrologic sciencesen_US
dc.subject.pquncontrolledBankfull dischargeen_US
dc.subject.pquncontrolledGumbelen_US
dc.subject.pquncontrolledHydraulic geometryen_US
dc.subject.pquncontrolledShield's numberen_US
dc.subject.pquncontrolledStreamflow predictionen_US
dc.subject.pquncontrolledUngauged streamsen_US


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