The Lahontan Water Board (Regional Water Board 6) has formally adopted EcoAtlas and the California Rapid Assessment Method (CRAM). This will enable the Water Board to visually track and assess the extent of project impacts on a watershed basis throughout the region.
Beginning August 1 of this year, 401 Certifications and Waste Discharge Requirements will require applicants to upload project information into EcoAtlas. Applicants will be encouraged to use CRAM in pre- and post- project assessments.
Eelgrass (Zostera marina and Z. pacifica) is recognized as an important ecological resource in nearshore open coast areas, shallow bays, and estuaries throughout coastal California. Access to regional maps and related monitoring reports for eelgrass is crucial to monitor the extent of eelgrass habitat and how it is changing over time, evaluate the effects of coastal development projects on eelgrass habitat, and inform interested stakeholders and the public about eelgrass distribution.
GreenPlan-IT, a toolset created in a collaboration with SFEP, US EPA, and local partners, has been featured in the newsletter of the National Water Quality Monitoring Council, which has in turn been distributed broadly to subscribers throughout the nation and beyond.
SediMatch is a web tool for matching restoration projects that need sediment with navigational and flood protection dredging projects and other "sediment suppliers" throughout the region to meet current and future sediment supply needs.
SFEI and the San Francisco Estuary Partnership are proud to announce the release of the SF Bay Shore Inventory: Mapping for Sea Level Rise. This dataset provides a comprehensive and consistent picture of today’s Bay shore (up to MHHW + 10ft) for all nine Bay Area counties. The mapping captures features which affect flooding and flood routing (e.g., engineered levees, berms, embankments, roads, wetlands, etc.).
With rising sea levels and the increased likelihood of extreme weather events, it is important for regional agencies and local municipalities in the San Francisco Bay Area to have a clear understanding of the status, composition, condition, and elevation of our current Bay shore, including both natural features and built infrastructure.
The purpose of this Bay shore inventory is to create a comprehensive and consistent picture of today’s Bay shore features to inform regional planning. This dataset includes both structures engineered expressly for flood risk management (such as accredited levees) and features that affect flooding at the shore but are not designed or maintained for this purpose (such as berms, road embankments, and marshes). This mapping covers as much of the ‘real world’ influence on flooding and flood routing as possible, including the large number of non-accredited structures.
This information is needed to:
identify areas vulnerable to flooding.
identify adaptation constraints due to present Bay shore alignments; and
suggest opportunities where beaches, wetlands, and floodplains can be maintained or restored and integrated into flood risk management strategies.
The primary focus of the project is therefore to inform regional planners and managers of Bay shore characteristics and vulnerabilities. The mapping presented here is neither to inform FEMA flood designation nor is it a replacement for site-specific analysis and design.
The mapping consists of two main elements:
Mapping of Bay shore features (levees, berms, roads, railroads, embankments, etc.) which could affect flooding and flood routing.
Attributing Bay shore features with additional information including elevations, armoring, ownership (when known), among others.
SFEI delineated and characterized the Bay shore inland to 3 meters (10ft) above mean higher high water (MHHW) to accommodate observed extreme water levels and the commonly used range of future sea level rise (SLR) scenarios. Elevated Bay shore features were mapped and classified as engineered levees, berms, embankments, transportation structures, wetlands, natural shoreline, channel openings, or water control structures. Mapped features were also attributed with elevation (vertical accuracy of <5cm reported in 30 meter (100ft) segments from LiDAR derived digital elevation models (DEMs), FEMA accreditation status, fortification (e.g., riprap, buttressing), frontage (e.g., whether a feature was fronted by a wetland or beach), ownership, and entity responsible for maintenance. Water control structures, ownership, and maintenance attributes were captured where data was available (not complete for entire dataset). The dataset was extensively reviewed and corrected by city, county, and natural resource agency staff in each county around the Bay. This report provides further description of the Bay shore inventory and methods used for developing the dataset. The result is a publicly accessible GIS spatial database.
