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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. 

This document summarizes a study conducted for the Regional Monitoring Program for Water Quality in San Francisco Bay (RMP) to re-evaluate the use of the Floating Percentile Method
(FPM) to derive sediment screening guidelines for dredged material reuse in the San Francisco Bay Region. The Long Term Management Strategy (LTMS) has a goal to use at least 40% of the sediment dredged from San Francisco Bay for beneficial reuse (USACE, 1998). The suitability of dredged sediment for beneficial reuse is in part determined by concentrations of toxic pollutants.The San Francisco Regional Water Quality Control Board (SFB-RWQCB) issued draft screening criteria in 2000 to categorize the suitability of sediment for reuse as either “surface” sediment, that may be placed near the surface for re-use in wetlands, or “foundation” sediment, that is buried under sediment that meets surface criteria. Contaminant concentration guidelines for surface sediment are lower than foundation sediment, based on the assumption that biota are more likely to be exposed to surface sediment than deeper foundation sediment.

The overarching goal of the Regional Monitoring Program for Water Quality in San Francisco Bay (RMP) is to answer the highest priority scientific questions faced by managers of Bay water quality. The RMP is an innovative collaboration between the San Francisco Bay Regional Water Quality Control Board, the regulated discharger community, the San Francisco Estuary Institute, and many other scientists and interested parties. The purpose of this document is to provide a concise overview of recent RMP activities and findings, and a look ahead to significant products anticipated in the next two years. The report includes a description of the management context that guides the Program; a brief summary of some of the most noteworthy findings of this multifaceted Program; and a summary of progress to date and future plans for addressing priority water quality topics.

This report presents a strategy and multi-year workplan for modeling polychlorinated biphenyls (PCBs), contaminants of emerging concern (CECs), and sediment in San Francisco Bay (the Bay). Robust in-Bay fate modeling is needed to address priority management questions that have been identified for these constituents.

The strategy for in-Bay modeling presented in this report is a major element of a broader, integrated strategy that is being developed across RMP Workgroups for modeling contaminants flowing from the Bay watersheds and other pathways into the Bay. The broader project is expected to yield an integrated strategy in 2022, followed by implementation of a pilot effort in 2023. Coordination of the in-Bay modeling effort with the broader integrated strategy and other modeling work (e.g., nutrient modeling under the Nutrient Management Strategy) will be critical to optimizing use of the funds allocated to modeling.