The purpose of this document is to guide efforts and summarize plans developed within the RMP. The intended audience includes representatives of the many organizations who directly participate in the Program. This document will also be useful for individuals who are not directly involved with the RMP but are interested in an overview of the Program and where it is heading.
The organization of this Multi-Year Plan parallels the RMP planning process (Figure 2). Section 1 presents the long-term management plans of the agencies responsible for managing water quality in the Bay and the overarching management questions that guide the Program. The agencies’ long-term management plans provide the foundation for RMP planning (Figure 2). In order to turn the plans into effective actions, the RMP distills prioritized lists of management questions that need to be answered (Page 8). The prioritized management questions then serve as a roadmap for scientists on the Technical Review Committee, workgroups, and strategy teams to plan and implement scientific studies to address the most urgent information needs. This information sharpens the focus on management actions that will most effectively and efficiently improve water quality in the Bay.
The San Francisco Bay total maximum daily loads (TMDLs) call for a 50% reduction in mercury (Hg) loads by 2028 and a 90% reduction in PCBs loads by 2030. In support of these TMDLs, the Municipal Regional Permit for Stormwater (MRP) (SFBRWQCB, 2009, SFBRWQCB, 2015, SFBRWQCB, 2022) called for the implementation of control measures to reduce PCBs and Hg loads from urbanized tributaries. In addition, the MRP has identified additional information needs associated with improving understanding of sources, pathways, loads, trends, and management opportunities of pollutants of concern (POCs). In response to the MRP requirements and information needs, the Small Tributary Loading Strategy (STLS) was developed, which outlined a set of management questions (MQs) that have been used as the
guiding principles for the region’s stormwater-related activities. In recognition of the need to evaluate changes in loads or concentrations of POCs from small tributaries on a decadal scale, the updated 2018 STLS Trends Strategy (Wu et al., 2018) prioritized the development of a new dynamic regional watershed model for POCs (PCBs and Hg focused) loads and trends. This regional modeling effort will provide updated estimates of POC concentrations and loads for all local watersheds that drain to the Bay. The Watershed Dynamic Model (WDM) will also provide
a mechanism for evaluating the impact of management actions on future trends of POC loads or concentrations.
As a multi-use modeling platform, the WDM is being developed to include other pollutants, such as contaminants of emerging concern (CECs), sediment, and nutrients and to be coupled with a Bay fate model to form an integrated watershed-Bay modeling framework to address Regional Monitoring Program (RMP) management questions. As this model is developed, flexibility to link with other models will be an important consideration.
A comprehensive, non-targeted analysis of polar organic pollutants using high resolution/accurate mass (HR/AM) mass spectrometry approaches has been applied to water samples from San Francisco (SF) Bay, a major urban estuary on the western coast of the United States, to assess occurrence of emerging contaminants and inform future monitoring and management activities. Polar Organic Chemical Integrative Samplers (POCIS) were deployed selectively to evaluate the influence of three contaminant pathways: urban stormwater runoff (San Leandro Bay), wastewater effluent (Coyote Creek, Lower South Bay), and agricultural runoff (Napa River). Grab samples were collected before and after deployment of the passive samplers to provide a quantitative snapshot of contaminants for comparison. Composite samples of wastewater effluent (24 hours) were also collected from several wastewater dischargers. Samples were analyzed using liquid-chromatography coupled to high resolution mass spectrometry. Resulting data were analyzed using a customized workflow designed for high-fidelity detection, prioritization, identification, and semi-quantitation of detected molecular features. Approximately 6350 compounds were detected in the combined data set, with 424 of those compounds tentatively identified through high quality spectral library match scores. Compounds identified included ethoxylated surfactants, pesticide and pharmaceutical transformation products, polymer additives, and rubber vulcanization agents. Compounds identified in samples were reflective of the apparent sources and pathways of organic pollutant inputs, with stormwater-influenced samples dominated by additive chemicals likely derived from plastics and vehicle tires, as well as ethoxylated surfactants.
