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Moore, S.; Hale, T.; Weisberg, S. B.; Flores, L.; Kauhanen, P. 2021. California Trash Monitoring Methods and Assessments Playbook. SFEI Contribution No. 1025. San Francisco Estuary Institute: Richmond, Calif.

As municipalities and water-quality regulatory agencies have implemented programs and policies to improve management of the trash loading to storm drain conveyances, there has been increased interest in using a common set of methods to quantify the effectiveness of management actions. To create a foundation for developing a consistent, standardized approach to trash monitoring statewide, the project team performed a method comparison analysis, based on two seasons of fieldwork. This analysis facilitated the assessment of the accuracy, repeatability, and efficiency of some already developed trash monitoring methodologies already in use, as well as help to investigate a new, innovative method (cf. Fielding Testing Report on trashmonitoring.org). Methods developed by the Bay Area Stormwater Management Agencies Association (BASMAA) for use in the San Francisco Bay Area were compared to methods developed by the Southern California Stormwater Monitoring Coalition (SMC) for use in coastal southern California. One of the chief goals of these comparisons was to understand the similarities and differences between the already existing methods for detecting, quantifying, and characterizing trash in selected environments. Readers will find that the data bear out remarkable levels of accuracy and precision with quantitative metrics that help to align methods and management concerns. Furthermore, the degree of correlation among tested methods were especially high, offering greater opportunities for inter-method comparisons.

The findings of this project are intended for use by public agencies, non-profit organizations, private consultants, and all of their various partners in informing a statewide effort to adopt rigorous, standardized monitoring methods to support the State Water Board’s Trash Amendments. Over the next couple of decades, such public mandates will require all water bodies in California to achieve water quality objectives for trash.

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Moore, S.; Hale, T.; Weisberg, S. B.; Flores, L.; Kauhanen, P. 2021. Field Testing Report: California Trash Monitoring Methods. SFEI Contribution No. 1026. San Francisco Estuary Institute: Richmond, Calif.

Trash has received renewed focus in recent years as policy makers, public agencies, environmental organizations, and community groups have taken many steps towards trash quantification and management across California. The range of management actions is matched by the diversity of monitoring approaches, designed to determine key attributes associated with trash pollution on California’s lands and in its waterways.

This report describes the field testing associated with a project designed to validate the accuracy, precision, and practicality of several trash monitoring methods, practiced across the state. Additionally, the project measured the efficacy of a novel monitoring method designed to detect trash via remote sensing and machine learning. Readers will find details about each respective method -- the specific approach to
landscape characterization, the qualitative or quantitative measures undertaken, the team-based quality assurance for data collection -- as well as the approach that the testing team adopted to ensure efficient, accurate, and useful validation of the methods.

Because the validation efforts integrated multiple methods, using multiple teams at a selection of common sites, the field testing report yields useful statistical information not only about each method individually, but about the comparability of the results. The report illustrates the
correlation factor associated with different forms of trash metrics, associated with different methods practiced on the same assessment sites. The results illustrated a generally high degree of correlation among different methods, which promises opportunities to compare results meaningfully across methods.

Furthermore, this field testing report provides quantitative measures to illustrate the repeatability of each method, the differences and insights yielded by assessment site sizing criteria varying among methods, the transferability / teach-ability of each method among trash monitoring practitioners, and how the degrees of accuracy might aid programs in performing mass balance analysis of known sources
to trash detected in a given site.

Regarding innovation, the project team leveraged multiple on-the-ground methods and special testing scenarios to compare conventional and novel (aerial) assessments to measure the relative accuracy and precision of this emergent technology that might address some of the resource constraints that currently limit the broader or more frequent deployment of conventional trash assessment methods. The analyses captured in this field testing report offer specific quantitative measures of the accuracy (bias), precision (repeatability), practicality and cost associated with each method. This information is subsequently used to inform a companion summary analysis found in the Trash Monitoring Playbook, which is designed to evaluate the applicability of the monitoring methods to address classes of
monitoring questions.

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Wu, J.; Kauhanen, P.; Hunt, J. A.; Senn, D.; Hale, T.; McKee, L. J. . 2019. Optimal Selection and Placement of Green Infrastructure in Urban Watersheds for PCB Control. Journal of Sustainable Water in the Built Environment 5 (2) . SFEI Contribution No. 729.

San Francisco Bay and its watersheds are polluted by legacy polychlorinated biphenyls (PCBs), resulting in the establishment of a total maximum daily load (TDML) that requires a 90% PCB load reduction from municipal stormwater. Green infrastructure (GI) is a multibenefit solution for stormwater management, potentially addressing the TMDL objectives, but planning and implementing GI cost-effectively to achieve management goals remains a challenge and requires an integrated watershed approach. This study used the nondominated sorting genetic algorithm (NSGA-II) coupled with the Stormwater Management Model (SWMM) to find near-optimal combinations of GIs that maximize PCB load reduction and minimize total relative cost at a watershed scale. The selection and placement of three locally favored GI types (bioretention, infiltration trench, and permeable pavement) were analyzed based on their cost and effectiveness. The results show that between optimal solutions and nonoptimal solutions, the effectiveness in load reduction could vary as much as 30% and the difference in total relative cost could be well over $100 million. Sensitivity analysis of both GI costs and sizing criteria suggest that the assumptions made regarding these parameters greatly influenced the optimal solutions. 

If you register for access to the journal, then you may download the article for free through July 31, 2019.

DOI: 10.1061/JSWBAY.0000876

Kauhanen, P.; Lowe, S. 2019. Prioritizing Candidate Green Infrastructure Sites within the City of Ukiah: A Demonstration of the Site Locator Tool of GreenPlan-IT. Report prepared for the City of Ukiah Department of Public Works under Supplemental Environmental Project # R1-018-0024. San Francisco Estuary Institute: Richmond. CA.

This report describes the application of GreenPlan-IT’s Site Locator Tool to identify and rank candidate GI installation sites within the City of Ukiah.  The Site Locator Tool is the first (foundational) tool of the GreenPlan-IT toolkit, meaning that the outputs are required inputs for both the Hydrologic Modeling and Optimization tools.   The Site Locator Tool addresses the question: where are the best locations for GI implementation based on local planning priorities? 

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Wu, J.; Kauhanen, P.; Hunt, J.; McKee, L. 2018. Green Infrastructure Planning for North Richmond Pump Station Watershed with GreenPlan-IT. SFEI Contribution No. 882. San Francisco Estuary Institute: Richmond, CA.
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Wu, J.; Kauhanen, P.; Hunt, J.; McKee, L. 2018. Green Infrastructure Planning for the City of Oakland with GreenPlan-IT. SFEI Contribution No. 884. San Francisco Estuary Institute : Richmond, CA.
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Wu, J.; Kauhanen, P.; Hunt, J.; McKee, L. 2018. Green Infrastructure Planning for the City of Richmond with GreenPlan-IT. SFEI Contribution No. 883. San Francisco Estuary Institute: Richmond, CA.
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Wu, J.; Kauhanen, P.; Hunt, J.; McKee, L. 2018. Green Infrastructure Planning for the City of Sunnyvale with GreenPlan-IT. SFEI Contribution No. 881. San Francisco Estuary Institute : Richmond, CA.
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Kauhanen, P.; Wu, J.; Hunt, J.; McKee, L. 2018. Green Plan-IT Application Report for the East Bay Corridors Initiative. SFEI Contribution No. 887. San Francisco Estuary Institute: Richmond, CA.
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Schoellhamer, D.; McKee, L.; Pearce, S.; Kauhanen, P.; Salomon, M.; Dusterhoff, S.; Grenier, L.; Marineau, M.; Trowbridge, P. 2018. Sediment Supply to San Francisco Bay. SFEI Contribution No. 842. San Francisco Estuary Institute : Richmond, CA.
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Wu, J.; Kauhanen, P.; Lowe, S.; Pearce, S.; Josh Collins. 2017. Demonstration of a Watershed Approach to Wetland Restoration Planning for Load Reductions: A Pilot Demonstration Project Using GreenPlan-IT in the Santa Rosa Plain, Sonoma County, California. SFEI Contribution No. 996. San Francisco Estuary Institute: Richmond. CA.

This summary memorandum presents technical recommendations to the 401 Certification and Waste Discharge Program (401 Program) of the State Water Resources Control Board (State Board) for a coherent, scientifically sound, repeatable, watershed approach to wetland restoration site evaluation, compliance monitoring and assessment, and Tracking. The recommendations are drawn from the previous four memoranda produced for the Pilot Demonstration Project (Project) that address the following subjects: project work plan and information flow diagram; scientific literature review; landscape scenario planning (to map and prioritize restoration opportunities); and a framework for a watershed-approach to evaluate and report the capacity of a wetland restoration site to protect wetland beneficial uses.

This Project focused on a sub-watershed of the Santa Rosa Plain, in Sonoma County, California. The area was chosen for the Project for three reasons: (1) it is integral to an existing nutrient TMDL and therefore is supported relatively well with hydrological and nutrient data; (2) the historical and existing wetlands and streams of the area were mapped recently in sufficient detail to inform landscape planning; and (3) implementation of the TMDL will involve wetland restoration to reduce downstream nutrient loads, and therefore the Project may help implement the TMDL.

The primary overall purpose of this Project was to explore how numerical simulation and statistical modeling could be combined with existing wetland assessment and reporting tools to create a coherent, watershed-based approach to wetland beneficial use protection. Any relevance to the existing nutrient TMDL for the demonstration area is an intentional, but secondary benefit of this Project.

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Doehring, C.; Beagle, J.; Lowe, J.; Grossinger, R. M.; Salomon, M.; Kauhanen, P.; Nakata, S.; Askevold, R. A.; Bezalel, S. N. 2016. San Francisco Bay Shore Inventory: Mapping for Sea Level Rise Planning. SFEI Contribution No. 779. San Francisco Estuary Institute: Richmond, CA.

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:

  1. identify areas vulnerable to flooding.
  2. identify adaptation constraints due to present Bay shore alignments; and
  3. 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:

  1. Mapping of Bay shore features (levees, berms, roads, railroads, embankments, etc.) which could affect flooding and flood routing.
  2. 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.

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Wu, J.; Kauhanen, P.; Mckee, L. 2015. GreenPlan-IT Toolkit Demonstration Report. SFEI Contribution No. 958. San Francisco Estuary Institute: Richmond, CA.

GreenPlan-IT is a planning level tool that was developed by SFEP and SFEI with support and oversight from BASMAA to provide Bay Area municipalities with the ability to evaluate multiple management alternatives using green infrastructure for addressing stormwater issues in urban watersheds. GreenPlan-IT combines sound science and engineering principles with GIS analysis and optimization techniques to support the cost-effective selection and placement of Green Infrastructure (GI) at a watershed scale.  Tool outputs can be used to develop quantitatively-derived watershed master plans to guide future GI implementation for improving water quality in the San Francisco Bay and its tributary watersheds.

This report provides an overview of the GreenPlan-IT Tool and demonstrates its utility and power through two pilot studies which is summarized in this report as a case study. The pilot studies with the City of San Mateo and the City of San Jose explored the use of GreenPlan-IT for identifying feasible and optimal GI locations for mitigation of stormwater runoff. They are provided here to give the reader an overview of the user application process from start to finish, including problem formulation, data collection, GIS analysis, establishing a baseline condition, GI representation, and the optimization process. Through the pilot study application process the general steps and recommendations for how GreenPlan-IT can be applied and interpreted are presented.

Wu, J.; Kauhanen, P.; Mckee, L. 2015. GreenPlan-IT Toolkit User Guide. SFEI Contribution No. 958. San Francisco Estuary Institute: Richmond, CA.

Structurally, the GreenPlan-IT is comprised of three components: (a) a GIS-based Site Locator Tool to identify potential GI sites; (b) a Modeling Tool that quantifies anticipated watershed-scale runoff and pollutant load reduction from GI sites; and (c) an Optimization Tool that uses a cost-benefit analysis to identify the best combinations of GI types and number of sites within a watershed for achieving flow and/or load reduction goals. The three tool components were designed as standalone modules to provide flexibility and their interaction is either through data exchange, or serving as a subroutine to another tool. This user manual addresses each of the tools separately, though they are designed to complement each other.

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