The Delta is integral in managing California Water as a critical surface water conduit to meet domestic, agricultural and wildlife water needs. Water supply and quality management relies on a vast levee system, much on peat soils and all at risks from subsidence, climate change and earthquakes. Effective management of this levee system will increasingly rely upon more efficient and accurate assessments leveraging technological and data advances. This project is part of a Next Generation Multi-Hazard Levee Assessment for Delta levees to assess subsidence, climate change, and earthquakes impacts on levee integrity using Bacon Island levees as an example. For this project, RMA’s 3D SF Estuary Model predicts future water levels in response to climate change and Hydrofocus’ SUBCALC and SEDCALC models estimate future subsidence. Geophysical data collected by Lawrence Berkeley Lab will be groundtruthed against soil boring and cone penetrometer data records and used to map heterogeneous underlying soil conditions impacting levee strength and permeability estimates. Here, we provide an overview of our approach to integrate these data to better model levee failure mechanisms from seepage and overtopping risks. In greater detail, we focus on overtopping to follow initial erosion from wave overtopping toward likely overtopping failure. Future river stages are predicted higher from sea-level rise and tidal amplitude increases. We analyze potential overtopping in 2050 and 2100 due to 10, 20, 50, and 100-yr storms. We estimate erosion based upon Briaud (2017) who accurately predicted overtopping-induced failure in the New Orleans 2008 flood event. We calculate erosion caused by over-topping induced shear stresses by summing erosion for each time step during a storm event with significant erosion indicating potential failure. We will discuss the increasing likelihood of overtopping failure (2050, 2100) and the implications for future levee height requirements.

Integrating geophysical data, and climate drive hydrologic and subsidence models in predicting Delta Levee failure risks

Zimmaro P.
2021-01-01

Abstract

The Delta is integral in managing California Water as a critical surface water conduit to meet domestic, agricultural and wildlife water needs. Water supply and quality management relies on a vast levee system, much on peat soils and all at risks from subsidence, climate change and earthquakes. Effective management of this levee system will increasingly rely upon more efficient and accurate assessments leveraging technological and data advances. This project is part of a Next Generation Multi-Hazard Levee Assessment for Delta levees to assess subsidence, climate change, and earthquakes impacts on levee integrity using Bacon Island levees as an example. For this project, RMA’s 3D SF Estuary Model predicts future water levels in response to climate change and Hydrofocus’ SUBCALC and SEDCALC models estimate future subsidence. Geophysical data collected by Lawrence Berkeley Lab will be groundtruthed against soil boring and cone penetrometer data records and used to map heterogeneous underlying soil conditions impacting levee strength and permeability estimates. Here, we provide an overview of our approach to integrate these data to better model levee failure mechanisms from seepage and overtopping risks. In greater detail, we focus on overtopping to follow initial erosion from wave overtopping toward likely overtopping failure. Future river stages are predicted higher from sea-level rise and tidal amplitude increases. We analyze potential overtopping in 2050 and 2100 due to 10, 20, 50, and 100-yr storms. We estimate erosion based upon Briaud (2017) who accurately predicted overtopping-induced failure in the New Orleans 2008 flood event. We calculate erosion caused by over-topping induced shear stresses by summing erosion for each time step during a storm event with significant erosion indicating potential failure. We will discuss the increasing likelihood of overtopping failure (2050, 2100) and the implications for future levee height requirements.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/335516
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