A large-scale categorization of sites in San Francisco Bay, USA, based on the sediment quality triad, toxicity identification evaluations, and gradient studies

2001 ◽  
Vol 20 (6) ◽  
pp. 1252-1265 ◽  
Author(s):  
John W. Hunt ◽  
Brian S. Anderson ◽  
Bryn M. Phillips ◽  
Ron S. Tjeerdema ◽  
Karen M. Taberski ◽  
...  
Keyword(s):  
San Francisco ◽  
Large Scale ◽  
San Francisco Bay ◽  
Sediment Quality ◽  
Sediment Quality Triad ◽  
Toxicity Identification

scholarly journals Adapting to sea level rise: Emerging governance issues in the San Francisco Bay Region

2018 ◽  
Author(s):  
Pedro J. Pinto ◽  
G. Mathias Kondolf ◽  
Pun Lok Raymond Wong
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
San Francisco ◽  
Urban Areas ◽  
Path Dependence ◽  
Large Scale ◽  
San Francisco Bay ◽  
Metropolitan Region ◽  
Environmental Benefit ◽  
Formidable Challenge

San Francisco Bay, the largest estuary on the Pacific Coast of North America, is heavily encroached by a metropolitan region with over 7 million inhabitants. Urban development and infrastructure, much of which built over landfill and at the cost of former baylands, were placed at very low elevations. Sea-level rise (SLR) poses a formidable challenge to these highly exposed urban areas and already stressed natural systems. “Green”, or ecosystem-based, adaptation is already on the way around the Bay. Large scale wetland restoration projects have already been concluded, and further action now often requires articulation with the reinforcement of flood defense structures, given the level of urban encroachment. While levee setback, or removal, would provide greater environmental benefit, the need to protect urban areas and infrastructure has led to the trial of ingenious solutions for promoting wetland resilience while upgrading the level of protection granted by levees.We analyzed the Bay’s environmental governance and planning structure, through direct observation, interviews with stakeholders, and study of planning documents and projects. We present two cases where actual implementation of SLR adaptation has led, or may lead to, the need to revise standards & practices or to make uneasy choices between conflicting public interests.Among the region’s stakeholders, there is an increasing awareness of the risks related to SLR, but the institutional arrangements are complex, and communication between the different public agencies/departments is not always as streamlined as it could be. Some agencies and departments need to adapt their procedures in order to remove institutional barriers to adaptation, but path dependence is an obstacle. There is evidence that more frank and regular communication between public actors is needed. It also emphasizes the benefits of a coordination of efforts and strategies, something that was eroded in the transition from government-led policies to a new paradigm of local-based adaptive governance.

scholarly journals When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond

2020 ◽  
Vol 6 (32) ◽  
pp. eaba2423
Author(s):  
Indraneel G. Kasmalkar ◽  
Katherine A. Serafin ◽  
Yufei Miao ◽  
I. Avery Bick ◽  
Leonard Ortolano ◽  
...  
Keyword(s):  
Sea Level ◽  
San Francisco ◽  
Large Scale ◽  
San Francisco Bay ◽  
Southern Oscillation ◽  
San Francisco Bay Area ◽  
Storm Surges ◽  
Urban Traffic ◽  
Bay Area ◽  
Flood Exposure

As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combinations of storm surges, tides, seasonal cycles, interannual anomalies driven by large-scale climate variability such as the El Niño Southern Oscillation, and sea level rise. When identifying inundated roads, we propose corrections for potential biases arising from model integration. Our results for the San Francisco Bay Area show that employee absences are limited to the homes and workplaces within the areas of inundation, while delays propagate far inland. Communities with limited availability of alternate roads experience long delays irrespective of their proximity to the areas of inundation. We show that metric reach, a measure of road network density, is a better proxy for delays than flood exposure.

Study of Park-and-Ride Facilities and Their Use in the San Francisco Bay Area of California

2005 ◽  
Vol 1927 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Manish Shirgaokar ◽  
Elizabeth Deakin
Keyword(s):  
San Francisco ◽  
Large Scale ◽  
San Francisco Bay ◽  
San Francisco Bay Area ◽  
Park And Ride ◽  
Bay Area ◽  
Transit Services ◽  
Focus Group Data ◽  
Schedule Adherence ◽  
Almost All

Park-and-ride lots are important support facilities for transit and ride-sharing in the San Francisco Bay Area of California. The authors designed and carried out the region's first large-scale, detailed study of park-and-ride facilities and users. Three Bay Area Rapid Transit (rail) station parking lots were also surveyed. The user survey results showed that almost all the parking users were commuters; at the freeway lots, half were transit users and the remainder were organized and casual car-poolers. Most drove alone to the park-and-ride lot and made long trips to work, many more than 30 mi one way. Users had concerns about lot security, the lack of lighting, and the quality of transit services offered. Analysis of focus group data determined that schedule adherence rather than frequency was the cause of most concerns. Participants expressed a willingness to pay for parking that was fenced, security patrolled, and lighted, with shelters for waiting. Together, the surveys and focus groups have provided insights into ways to improve the park-and-ride lots and the services offered there, as well as on how travelers view transit and carpooling options. The results provide a sound basis for planning improvements.

scholarly journals Effect of Fluvial Discharges and Remote Non-Tidal Residuals on Compound Flood Forecasting in San Francisco Bay

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2481
Author(s):  
Babak Tehranirad ◽  
Liv Herdman ◽  
Kees Nederhoff ◽  
Li Erikson ◽  
Robert Cifelli ◽  
...  
Keyword(s):  
San Francisco ◽  
Coastal Water ◽  
Large Scale ◽  
San Francisco Bay ◽  
Flood Forecasting ◽  
Water Levels ◽  
Global Ocean ◽  
Coastal Flood ◽  
Extreme Water Levels ◽  
Recent Emergence

Accurate and timely flood forecasts are critical for making emergency-response decisions regarding public safety, infrastructure operations, and resource allocation. One of the main challenges for coastal flood forecasting systems is a lack of reliable forecast data of large-scale oceanic and watershed processes and the combined effects of multiple hazards, such as compound flooding at river mouths. Offshore water level anomalies, known as remote Non-Tidal Residuals (NTRs), are caused by processes such as downwelling, offshore wind setup, and also driven by ocean-basin salinity and temperature changes, common along the west coast during El Niño events. Similarly, fluvial discharges can contribute to extreme water levels in the coastal area, while they are dominated by large-scale watershed hydraulics. However, with the recent emergence of reliable large-scale forecast systems, coastal models now import the essential input data to forecast extreme water levels in the nearshore. Accordingly, we have developed Hydro-CoSMoS, a new coastal forecast model based on the USGS Coastal Storm Modeling System (CoSMoS) powered by the Delft3D San Francisco Bay and Delta community model. In this work, we studied the role of fluvial discharges and remote NTRs on extreme water levels during a February 2019 storm by using Hydro-CoSMoS in hindcast mode. We simulated the storm with and without real-time fluvial discharge data to study their effect on coastal water levels and flooding extent, and highlight the importance of watershed forecast systems such as NOAA’s National Water Model (NWM). We also studied the effect of remote NTRs on coastal water levels in San Francisco Bay during the 2019 February storm by utilizing the data from a global ocean model (HYCOM). Our results showed that accurate forecasts of remote NTRs and fluvial discharges can play a significant role in predicting extreme water levels in San Francisco Bay. This pilot application in San Francisco Bay can serve as a basis for integrated coastal flood modeling systems in complex coastal settings worldwide.

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