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A Process-Based Model for Forecastin...
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Fiegelist, Robert A.
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A Process-Based Model for Forecasting Wave Runup Along the Coast of Georgia.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A Process-Based Model for Forecasting Wave Runup Along the Coast of Georgia./
作者:
Fiegelist, Robert A.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:
63 p.
附註:
Source: Masters Abstracts International, Volume: 85-03.
Contained By:
Masters Abstracts International85-03.
標題:
Environmental engineering. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30568230
ISBN:
9798380161848
A Process-Based Model for Forecasting Wave Runup Along the Coast of Georgia.
Fiegelist, Robert A.
A Process-Based Model for Forecasting Wave Runup Along the Coast of Georgia.
- Ann Arbor : ProQuest Dissertations & Theses, 2023 - 63 p.
Source: Masters Abstracts International, Volume: 85-03.
Thesis (M.S.)--University of Georgia, 2023.
Wave runup is an important nearshore process that impacts water levels, sediment transport, and coastal design. Current methods for forecasting wave runup implement an empirical model (Stockdon et al., 2006) which requires offshore wave height, wave period, and generalized beach slope. A new process-based methodology was created that implements site-specific cross-shore topo-bathy into the phase-resolving numerical model, XBeach non-hydrostatic (XBNH). Wave runup forecasts are generated from offshore wave conditions and a system of equations derived from simulation results at three different still water datums for each beach profile. Using forcings from Hurricanes Ian and Nicole (2022), the model predicts events of collision, overwash, and inundation for the coast of Georgia and suggests that wave runup is significantly impacted by the still water level and topo-bathy. Coupled with a field experiment that provides wave runup data using 12 pressure sensors and highly accurate RTK (Real-Time Kinematic positioning, < 2 cm vertical error), the results show that the pressure sensors effectively capture wave runup events and XBNH accurately models the total water level for the limited wave conditions throughout the experiment.
ISBN: 9798380161848Subjects--Topical Terms:
548583
Environmental engineering.
Subjects--Index Terms:
Coastal hazards
A Process-Based Model for Forecasting Wave Runup Along the Coast of Georgia.
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Wave runup is an important nearshore process that impacts water levels, sediment transport, and coastal design. Current methods for forecasting wave runup implement an empirical model (Stockdon et al., 2006) which requires offshore wave height, wave period, and generalized beach slope. A new process-based methodology was created that implements site-specific cross-shore topo-bathy into the phase-resolving numerical model, XBeach non-hydrostatic (XBNH). Wave runup forecasts are generated from offshore wave conditions and a system of equations derived from simulation results at three different still water datums for each beach profile. Using forcings from Hurricanes Ian and Nicole (2022), the model predicts events of collision, overwash, and inundation for the coast of Georgia and suggests that wave runup is significantly impacted by the still water level and topo-bathy. Coupled with a field experiment that provides wave runup data using 12 pressure sensors and highly accurate RTK (Real-Time Kinematic positioning, < 2 cm vertical error), the results show that the pressure sensors effectively capture wave runup events and XBNH accurately models the total water level for the limited wave conditions throughout the experiment.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30568230
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