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A Rapid Assessment Method to Identify Potential Groundwater Flooding Hotspots as Sea Levels Rise in Coastal Cities

Water, Multidisciplinary Digital Publishing Institute (MDPI) | October 25th, 2019

Summary

Sea level rise (SLR) will cause shallow unconfined coastal aquifers to rise. Rising groundwater can emerge as surface flooding and impact buried infrastructure, soil beh

Sea level rise (SLR) will cause shallow unconfined coastal aquifers to rise. Rising groundwater can emerge as surface flooding and impact buried infrastructure, soil behavior, human health, and nearshore ecosystems. Higher groundwater can also reduce infiltration rates for stormwater, adding to surface flooding problems. Levees and seawalls may not prevent these impacts. Pumping may accelerate land subsidence rates, thereby exacerbating flooding problems associated with SLR. Public agencies at all jurisdiction levels will need information regarding where groundwater impacts are likely to occur for development and infrastructure planning, as extreme precipitation events combine with SLR to drive more frequent flooding. We used empirical depth-to-water data and a digital elevation model of the San Francisco Bay Area to construct an interpolated surface of estimated minimum depth-to-water for 489 square kilometers along the San Francisco Bay shoreline. This rapid assessment approach identified key locations where more rigorous data collection and dynamic modeling is needed to identify risks and prevent impacts to health, buildings, and infrastructure, and develop adaptation strategies for SLR.

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A Summary of Water-Quality and Salt Marsh Monitoring, Humboldt Bay, California

U.S. Geological Survey (USGS) | September 16th, 2022

Summary

This report summarizes data-collection activities associated with the U.S. Geological Survey Humboldt Bay Water-Quality and Salt Marsh Monitoring Project. This work was u

This report summarizes data-collection activities associated with the U.S. Geological Survey Humboldt Bay Water-Quality and Salt Marsh Monitoring Project. This work was undertaken to gain a comprehensive understanding of water-quality conditions, salt marsh accretion processes, marsh-edge erosion, and soil-carbon storage in Humboldt Bay, California. Multiparameter sondes recorded water temperature, specific conductance, and turbidity at a 15-minute timestep at two U.S. Geological Survey water-quality stations: (1) Mad River Slough near Arcata, California (U.S. Geological Survey station 405219124085601) and (2) Hookton Slough near Loleta, California (U.S. Geological Survey station 404038124131801). At each station, discrete water samples were collected to develop surrogate regression models that were used to compute a continuous time series of suspended-sediment concentration from continuously measured turbidity. Data loggers recorded water depth at a 6-minute timestep in the primary tidal channels (Mad River Slough and Hookton Slough) in two adjacent marshes (Mad River marsh and Hookton marsh). The marsh monitoring network included five study marshes. Three marshes (Mad River, Manila, and Jacoby) are in the northern embayment of Humboldt Bay and two marshes (White and Hookton) are in the southern embayment. Surface deposition and elevation change were measured using deep rod surface elevation tables and feldspar marker horizons. Sediment characteristics and soil-carbon storage were measured using a total of 10 shallow cores, distributed across 5 study marshes, collected using an Eijkelkamp peat sampler. Rates of marsh edge erosion (2010–19) were quantified in four marshes (Mad River, Manila, Jacoby, and White) by estimating changes in the areal extent of the vegetated marsh plain using repeat aerial imagery and light detection and ranging (LiDAR)-derived elevation data. During the monitoring period (2016–19), the mean suspended-sediment concentration computed for Hookton Slough (50±20 milligrams per liter [mg/L]) was higher than Mad River Slough (18±7 mg/L). Uncertainty in mean suspended-sediment concentration values is reported using a 90-percent confidence interval. Across the five study marshes, elevation change (+1.8±0.6 millimeters per year [mm/yr]) and surface deposition (+2.5±0.5 mm/yr) were lower than published values of local sea-level rise (4.9±0.8 mm/yr), and mean carbon density was 0.029±0.005 grams of carbon per cubic centimeter. From 2010 to 2019, marsh edge erosion and soil carbon loss were greatest in low-elevation marshes with the marsh edge characterized by a gentle transition from mudflat to vegetated marsh (herein, ramped edge morphology) and larger wind-wave exposure. Jacoby Creek marsh experienced the greatest edge erosion. In total, marsh edge erosion was responsible for 62.3 metric tons of estuarine soil carbon storage loss across four study marshes. Salt marshes are an important component of coastal carbon, which is frequently referred to as “blue carbon.” The monitoring data presented in this report provide fundamental information needed to manage blue carbon stocks, assess marsh vulnerability, inform sea-level rise adaptation planning, and build coastal resiliency to climate change.

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Adaptation Pathways: San Leandro Operational Landscape Unit

San Francisco Estuary Institute (SFEI) | May 15th, 2022

Summary

Given the diverse uses and conditions of San Francisco Bay’s 400-mile shoreline, a framework is needed to guide development of adaptation strategies appropriate to loca

Given the diverse uses and conditions of San Francisco Bay’s 400-mile shoreline, a framework is needed to guide development of adaptation strategies appropriate to local conditions. Operational Landscape Units (OLUs), outlined for the San Francisco Bay in the San Francisco Bay Shoreline Adaptation Atlas (SFEI and SPUR 2019), share common physical characteristics and therefore can benefit from being managed as individual units. OLUs cross traditional jurisdictional boundaries (cities, counties), and instead follow the boundaries of natural processes like tides, waves, and sediment movement. By planning at the OLU scale, it is possible to prioritize adaptation strategies that work synergistically. Coordinated OLU planning can help avoid unintended impacts on neighboring locales and identify synergies to make use of limited resources in a more efficient manner.

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Adaptation Planning for the Bay Point Operational Landscape Unit

San Francisco Estuary Institute (SFEI) | April 15th, 2022

Summary

This document is not a vision or an adaptation plan, but rather is meant to catalyze discussion and offer resources around nature-based opportunities for SLR adaptation a

This document is not a vision or an adaptation plan, but rather is meant to catalyze discussion and offer resources around nature-based opportunities for SLR adaptation along Bay Point’s shoreline. The engagement and leadership of community-based stakeholders is key to the success of any adaptation planning effort, especially around issues as long-term and far-reaching as SLR and associated storm and tidal flooding. Without transparency and intentional community engagement throughout the planning process, opportunities for creative solutions will surely be missed and might lead to new problems or exacerbate existing ones disproportionately felt by low-income communities and communities of color. At the time this memo was written, there was not an active SLR adaptation working group or equivalent effort happening along the Bay Point shoreline. Consequently, the intent of this memo is to offer useful resources and ideas to support meaningful dialogue among stakeholders about shoreline adaptation planning. The Bay Point OLU study area is a mix of open space and developed areas at the mouth of the Sacramento and San Joaquin rivers, where the Delta meets the San Francisco Bay. The Bay Point OLU comprises unincorporated land known as Bay Point, a census-designated place within ContraCosta County, the City of Pittsburg, the spheres of influence of Pittsburg and Concord, and District V of Contra Costa County (Figure 2). Chapter 2 examines how Bay Point’s landscape has changed over time and Chapter 3 summarizes some of the vulnerability studies, habitat goals, and adaptation plans that have been developed for the study area. Chapter 4 offers more in-depth descriptions of the Bay Point OLU along with detailed maps that can be used to kick start SLR adaptation planning with a stakeholder working group along this reach of shoreline. Chapter 5 concludes with conceptual ideas that may be appropriate for different reaches of the shoreline, as a menu of possibilities to be further developed through a stakeholder process. Chapter 6 suggests ideas on next steps needed to move this work forward and offers a list of potential stakeholders as a starting place towards an adaptation working group to identify, evaluate, and prioritize adaptation strategies to manage flood risks along Bay Point’s shoreline.

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Amplified Impact of Climate Change on Fine-Sediment Delivery to a Subsiding Coast, Humboldt Bay, California

Estuaries and Coasts (Springer) | May 28th, 2021

Summary

In Humboldt Bay, tectonic subsidence exacerbates sea-level rise (SLR). To build surface elevations and to keep pace with SLR, the sediment demand created by subsi

In Humboldt Bay, tectonic subsidence exacerbates sea-level rise (SLR). To build surface elevations and to keep pace with SLR, the sediment demand created by subsidence and SLR must be balanced by an adequate sediment supply. This study used an ensemble of plausible future scenarios to predict potential climate change impacts on suspended-sediment discharge (Qss) from fluvial sources. Streamflow was simulated using a deterministic water-balance model, and Qss was computed using statistical sediment-transport models. Changes relative to a baseline period (1981–2010) were used to assess climate impacts. For local basins that discharge directly to the bay, the ensemble means projected increases in Qss of 27% for the mid-century (2040–2069) and 58% for the end-of-century (2070–2099). For the Eel River, a regional sediment source that discharges sediment-laden plumes to the coastal margin, the ensemble means projected increases in Qss of 53% for the mid-century and 99% for the end-of- century. Climate projections of increased precipitation and streamflow produced amplified increases in the regional sediment supply that may partially or wholly mitigate sediment demand caused by the combined effects of subsidence and SLR. This finding has important implications for coastal resiliency. Coastal regions with an increasing sediment supply may be more resilient to SLR. In a broader context, an increasing sediment supply from fluvial sources has global relevance for communities threatened by SLR that are increasingly building resiliency to SLR using sediment-based solutions that include regional sediment management, beneficial reuse strategies, and marsh restoration.

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An assessment of future tidal marsh resilience in the San Francisco Estuary through modeling and quantifiable metrics of sustainability

Frontiers in Environmental Science (Frontiers) | November 25th, 2022

Summary

Quantitative, broadly applicable metrics of resilience are needed to effectively manage tidal marshes into the future. Here we quantified three metrics of temporal marsh

Quantitative, broadly applicable metrics of resilience are needed to effectively manage tidal marshes into the future. Here we quantified three metrics of temporal marsh resilience: time to marsh drowning, time to marsh tipping point, and the probability of a regime shift, defined as the conditional probability of a transition to an alternative super-optimal, suboptimal, or drowned state. We used organic matter content (loss on ignition, LOI) and peat age combined with the Coastal Wetland Equilibrium Model (CWEM) to track wetland development and resilience under different sea-level rise scenarios in the Sacramento-San Joaquin Delta (Delta) of California. A 100-year hindcast of the model showed excellent agreement (R2 = 0.96) between observed (2.86 mm/year) and predicted vertical accretion rates (2.98 mm/year) and correctly predicted a recovery in LOI (R2 = 0.76) after the California Gold Rush. Vertical accretion in the tidal freshwater marshes of the Delta is dominated by organic production. The large elevation range of the vegetation combined with high relative marsh elevation provides Delta marshes with resilience and elevation capital sufficiently great to tolerate centenary sea-level rise (CLSR) as high as 200 cm. The initial relative elevation of a marsh was a strong determinant of marsh survival time and tipping point. For a Delta marsh of average elevation, the tipping point at which vertical accretion no longer keeps up with the rate of sea-level rise is 50 years or more. Simulated, triennial additions of 6 mm of sediment via episodic atmospheric rivers increased the proportion of marshes surviving from 51% to 72% and decreased the proportion drowning from 49% to 28%. Our temporal metrics provide critical time frames for adaptively managing marshes, restoring marshes with the best chance of survival, and seizing opportunities for establishing migration corridors, which are all essential for safeguarding future habitats for sensitive species.

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An ongoing shift in Pacific Ocean sea level

American Geophysical Union (AGU) | July 30th, 2016

Summary

Based on the satellite altimeter data, sea level off the west coast of the United States has increased over the past 5 years, while sea level in the western tropical Pac

Based on the satellite altimeter data, sea level off the west coast of the United States has increased over the past 5 years, while sea level in the western tropical Pacific has declined. Understanding whether this is a short-term shift or the beginning of a longer-term change in sea level has important implications for coastal planning efforts in the coming decades. Here, we identify and quantify the recent shift in Pacific Ocean sea level, and also seek to describe the variability in a manner consistent with recent descriptions of El Nino-Southern Oscillation (ENSO) and particularly the Pacific Decadal Oscillation (PDO). More specifically, we extract two dominant modes of sea level variability, one related to the biennial oscillation associated with ENSO and the other representative of lower-frequency variability with a strong signal in the northern Pacific. We rely on cyclostationary empirical orthogonal function (CSEOF) analysis along with sea level reconstructions to describe these modes and provide historical context for the recent sea level changes observed in the Pacific. As a result, we find that a shift in sea level has occurred in the Pacific Ocean over the past few years that will likely persist in the coming years, leading to substantially higher sea level off the west coast of the United States and lower sea level in the western tropical Pacific.

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Analysis of the costs and benefits of using marsh restoration as a sea level rise adaptation strategy in San Francisco Bay

Bay Institute | February 22nd, 2013

Summary

The purpose of this study is to examine opportunities to protect San Francisco Bay’s recovering tidal marsh ecosystems while helping bayshore communities to manage the

The purpose of this study is to examine opportunities to protect San Francisco Bay’s recovering tidal marsh ecosystems while helping bayshore communities to manage the impacts of sea level rise. Specifically, it considers the flood risk management functions that tidal marshes perform naturally and evaluates the possibility of integrating those functions into a co-beneficial shoreline management strategy. The study’s intended audience is planners, politicians, regulators, and other stakeholders with the authority to make or affect decisions that influence the configuration and use of the San Francisco Bay shoreline. The study examines the current functions of San Francisco Bay tidal marshes as well as existing flood risk management strategies. It considers how environmental conditions are likely to change in the era of climate change, and how we can adapt our marshes and our flood risk management practices to accommodate these changes.

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Assessing and communicating the impacts of climate change on the Southern California coast

California Natural Resources Agency (CNRA) | August 27th, 2018

Summary

Over the course of this and the next century, the combination of rising sea levels, severe storms, and coastal erosion will threaten the sustainability of coastal commu

Over the course of this and the next century, the combination of rising sea levels, severe storms, and coastal erosion will threaten the sustainability of coastal communities, development, and ecosystems as we currently know them. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies for projected increased levels of coastal flooding and erosion, coastal managers need user-friendly planning tools based on the best available climate and coastal science. In anticipation of these climate change impacts, many communities are in the early stages of climate change adaptation planning but lack the scientific information and tools to adequately address the potential impacts. In collaboration with leading scientists worldwide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections and translate that information using sophisticated physical process models into planning-scale physical, ecological, and economic exposure, shoreline change, and impact assessments, all delivered in two simple, user-friendly, online tools. Our results show that by the end of the 21st century, over 250,000 residents and nearly $40 billion in building value across Southern California could be exposed to coastal flooding from storms, sea level rise, and coastal change. Results for the other major population center in California (the greater San Francisco Bay Area) are also available but not explicitly discussed in this report. Together, CoSMoS has now assessed the exposure of 95% of the 26 million coastal residents of the State (17 million in Southern California)

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Benefit Accounting of Nature-Based Solutions for Watersheds

Pacific Institute | March 1st, 2021

Summary

Nature-based solutions (NBS) have the potential to combat pressing global problems, including climate change, water security and biodiversity loss. This guide builds on

Nature-based solutions (NBS) have the potential to combat pressing global problems, including climate change, water security and biodiversity loss. This guide builds on Benefit Accounting of Nature-Based Solutions for Watersheds Landscape Assessment (Shiao et al., 2020), which highlights the barriers for businesses to implement NBS at a large scale. The primary challenge for corporations is that there is no standardized method to identify, estimate and monitor the benefits that NBS can provide, making it hard to build the case for investments in these solutions.

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Needles Valley 7-044
Ocotillo-Clark Valley 7-025
Ogilby Valley 7-035
Ojai Valley 4-002
Orocopia Valley - 7-031
Owens Valley - Fish Slough 6-012.02
Owens Valley 6-012.01
Owl Lake Valley 6-088
Pahrump Valley 6-028
Palo Verde Mesa 7-039
Palo Verde Valley 7-038
Pamo Valley 9-024
Panamint Valley 6-058
Peach Tree Valley 3-032
Petaluma Valley 2-001
Pilot Knob Valley 6-051
Pinto Valley 7-006
Pipes Canyon Fault Valley 7-049
Pittsburgh Plain 2-004
Piute Valley 7-045
Pleasant Valley 4-006
Potrero Valley 9-029
Poway Valley 9-013
Raymond 4-023
Red Pass Valley 6-024
Redding Area - Anderson 5-006.03
Redding Area - Bowman 5-006.01
Redding Area - Enterprise 5-006.04
Redding Area - Millville 5-006.05
Redding Area - South Battle Creek 5-006.06
Rice Valley 7-004
Riggs Valley 6-023
Russell Valley 4-020
Sacramento Valley - Antelope 5-021.54
Sacramento Valley - Bend 5-021.53
Sacramento Valley - Butte 5-021.70
Sacramento Valley - Colusa 5-021.52
Sacramento Valley - Corning 5-021.51
Sacramento Valley - Los Molinos 5-021.56
Sacramento Valley - North American (5-021.64)
Sacramento Valley - North Yuba 5-021.60
Sacramento Valley - Red Bluff 5-021.50
Sacramento Valley - Solano 5-021.66
Sacramento Valley - South American 5-021.65
Sacramento Valley - South Yuba 5-021.61
Sacramento Valley - Sutter 5-021.62
Sacramento Valley - Vina 5-021.57
Sacramento Valley - Wyandotte Creek 5-021.69
Sacramento Valley - Yolo 5021.67
Salinas Valley - 180/400 Foot Aquifer 3-004.01
Salinas Valley - Atascadero Area 3-004.11
Salinas Valley - East Side Aquifer 3-004.02
Salinas Valley - Forebay Aquifer 3-004.04
Salinas Valley - Langley Area 3-004.09
Salinas Valley - Monterey 3-004.10
Salinas Valley - Paso Robles Area 3-004.06
Salinas Valley - Upper Valley Aquifer 3-004.05
Saline Valley 6-017
Salt Wells Valley 6-053
San Antonio Creek Valley 3-014
San Dieguito Creek 9-012
San Elijo Valley 9-023
San Felipe Valley 7-027
San Fernando Valley 4-012
San Gabriel Valley 4-013
San Jacinto 8-005
San Joaquin Valley - Chowchilla 5-022.05
San Joaquin Valley - Cosumnes (5-022.16)
San Joaquin Valley - Delta-Mendota 5-022.07
San Joaquin Valley - East Contra Costa 5-022.19
San Joaquin Valley - Eastern San Joaquin 5-022.01
San Joaquin Valley - Kaweah 5-022.11
San Joaquin Valley - Kern 5-022.14
San Joaquin Valley - Kings 5-022.08
San Joaquin Valley - Madera 5-022.06
San Joaquin Valley - Merced 5-022.04
San Joaquin Valley - Modesto 5-022.02
San Joaquin Valley - Pleasant Valley 5-022.10
San Joaquin Valley - Tracy 5-022.15
San Joaquin Valley - Tulare Lake 5-022.12
San Joaquin Valley - Tule 5-022.13
San Joaquin Valley - Turlock 5-022.03
San Joaquin Valley - Westside 5-022.09
San Joaquin Valley - White Wolf 5-022.18
San Juan Valley 9-001
San Luis Obispo Valley 3-009
San Luis Rey Valley - Lower San Luis Rey Valley 9-007.02
San Luis Rey Valley - Upper San Luis Rey Valley 9-007.01
San Marcos Area 9-032
San Mateo Valley 9-002
San Onofre Valley 9-003
San Pasqual Valley 9-010
Santa Barbara 3-017
Santa Clara River Valley - Fillmore 4-004.05
Santa Clara River Valley - Mound 4-004.03
Santa Clara River Valley - Oxnard 4-004.02
Santa Clara River Valley - Piru 4-004.06
Santa Clara River Valley - Santa Clara River Valley East 4-004.07
Santa Clara River Valley - Santa Paula 4-004.04
Santa Clara Valley - East Bay Plain 2-009.04
Santa Clara Valley - Niles Cone 2-009.01
Santa Clara Valley - San Mateo Plain 2-009.03
Santa Clara Valley - Santa Clara 2-009.02
Santa Cruz Mid-County 3-001
Santa Margarita 3-027
Santa Maria River Valley - Arroyo Grande 3-012.02
Santa Maria River Valley - Santa Maria 3-012.01
Santa Maria River Valley 3-012.02
Santa Maria Valley 9-011
Santa Rosa Valley - Santa Rosa Plain 1-055.01
Santa Ynez River Valley 3-015
Scott River Valley 1-005
Searles Valley 6-052
Seven Oaks Valley 8-008
Shasta Valley 1-004
Sierra Valley 5-012.01
Silver Lake Valley 6-034
Simi Valley 4-009
Soda Lake Valley 6-033
South San Diego River Valley 9-015
Superior Valley 6-049
Temecula Valley 9-005
Terwilliger Valley 7-026
Thousand Oaks Area 4-019
Tule Lake 1-002-01
Twentynine Palms Valley 7-010
Ukiah Valley 1-052
Upper Kingston Valley 6-022
Upper Mojave River Valley 6-042
Upper Ojai Valley 4-001
Upper Santa Ana Valley - Chino 8-002.01
Upper Santa Ana Valley - Cucamonga 8-002.02
Upper Santa Ana Valley - Rialto-Colton 8-002.04
Upper Santa Ana Valley - Riverside-Arlington 8-002.03
Upper Santa Ana Valley - San Bernardino 8-002.06
Upper Santa Ana Valley - San Timoteo 8-002.08
Upper Santa Ana Valley - Temescal 8-002.09
Upper Santa Ana Valley - Yucaipa 8-002.07
Vallecito-Carrizo Valley 7-028
Ventura River Valley - Lower Ventura River 4-003.02
Ventura River Valley - Upper Ventura River 4-003.01
Vidal Valley 7-042
Ward Valley 7-003
Warren Valley 7-012
West Salton Sea
Wingate Valley 6-019
Yuma Valley 7-036

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