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2017 Regional Monitoring Program (RMP) Water Samples Quality Assurance Report

San Francisco Estuary Institute (SFEI) | June 1st, 2018

Summary

In 2017, grab water samples were collected from 22 sites, with samples analyzed for select trace elements (Cu, MeHg, Se), ancillary water quality parameters (DOC, POC,

In 2017, grab water samples were collected from 22 sites, with samples analyzed for select trace elements (Cu, MeHg, Se), ancillary water quality parameters (DOC, POC, SSC, hardness) and weak acid dissociable cyanide. Additionally, water samples were collected for toxicity tests from 7 sites, and one site (Golden Gate) sampled for nutrients (nitrogen species, silica). The sampling and analysis was conducted by the Regional Monitoring Program for Water Quality in San Francisco Bay. The details of the cruise and sample collection methods are described in the RMP Quality Assurance Program Plan, cruise plans, cruise reports, and field sampling reports.

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Anthropogenic Stressors and Changes in the Clear Lake Ecosystem as Recorded in Sediment Cores

Ecological Society of America (Wiley) | December 1st, 2008

Summary

Sediment cores were collected to investigate multiple stresses on Clear Lake, California, USA, through the period of European occupation to the present day. Earlier wor

Sediment cores were collected to investigate multiple stresses on Clear Lake, California, USA, through the period of European occupation to the present day. Earlier workers suggested the hypothesis that the use of mechanized earthmoving equipment, starting in the 1920s and 1930s, was responsible for erosion, mercury (Hg) contamination, and habitat loss stresses. Cores (;2.5 m in depth) were collected in 1996 and 2000 from each of the three arms of the lake. Carbon-14 dating suggests that these cores represent as much as 3000 years of the lake’s history, beginning long before European settlement. Total mercury (TotHg) and methylmercury (MeHg), dry matter, water, carbon, nitrogen, phosphorus, sulfur, and the stable isotopes 13C and 15N were measured at 5-cm intervals. Nearly all parameters show major changes at depths of 58–135 cm, beginning at ca. 1927 (dated with 210Pb). Accepting this date for concomitant major changes in seven cores yields an estimated 8.6 mm/yr average sedimentation rate after 1927. Pre-1927 sedimentation rates were ;1 mm/yr. Total mercury and MeHg, dry matter, phosphorus, and 15N increase significantly, whereas nitrogen, sulfur, carbon, and water content decrease significantly above the 1927 horizon. Both TotHg and MeHg show extremely large increases (roughly 10-fold) above the 1927 horizon. A peak in inorganic deposition rate and minimum values for percentage of water is present at depths corresponding to ca. 1970. Interestingly, the first 75 years of European settlement in the Clear Lake basin (including the most productive years of the Sulphur Bank Mercury Mine) appeared to have had undetectable effects on lake cores. Changes since 1927 were dramatic. The large increase in Hg beginning about 1927 corresponds to the use of heavy equipment to exploit the ore deposit at the mine using open-pit methods. Increases in sediment deposition from increased earthmoving in the basin and sulfate loading from the mine are the most likely explanations for the dramatic changes seen in the post-1927 sections of the cores.

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Bioaccumulation of Pollutants in California Waters: A Review of Historic Data and Assessment of Impacts on Fishing and Aquatic Life

San Francisco Estuary Institute (SFEI) | October 24th, 2007

Summary

This report was written for the State Water Resources Control Board’s Surface Water Ambient Monitoring Program (SWAMP) as a step toward the development of an im

This report was written for the State Water Resources Control Board’s Surface Water Ambient Monitoring Program (SWAMP) as a step toward the development of an improved bioaccumulation monitoring program for California. The report provides a review of bioaccumulation monitoring data generated under three historic State Board programs (the Toxic Substances Monitoring Program, the State Mussel Watch Program, and the Coastal Fish Contamination Program) and other major bioaccumulation studies since 1970. Future monitoring will be guided by assessment questions developed for the SWAMP. The objective of this report was to evaluate how well the historic data from the State Board programs and from other major monitoring efforts since 1970 address these questions. This exercise has provided a substantial amount of information about present and historical impacts of pollutant bioaccumulation on shing and aquatic life in California, and has also highlighted areas where improved sampling approaches can better address the assessment questions. Present concentrations of pollutants in many California water bodies are high enough to cause concern for possible effects on human health and to have a significant impact on the fishing beneficial use. Consumption advisories, 303(d) listings, and the bioaccumulation database as a whole provide three indices of the status of this impact. Consumption advisories exist for an increasing number of water bodies, but these represent only a fraction of the areas likely to need them. Lack of suitable data is a major impediment to developing advice for additional water bodies. A US E.P.A. evaluation of the 2002 303(d) List indicated that large portions of the state had not been assessed, especially rivers and coastline. Most of the lake area in the state (61%) had been assessed, and a relatively small percentage of the total area (6%) was classified as impaired. Assessment of lakes, however, has focused primarily on the largest lakes, leaving the vast majority of smaller lakes unsampled. Many of these small lakes are near population centers and are popular for shing. Bays and estuaries had been thoroughly assessed (98% of the area) and 93% of the total area was impaired. Evaluation of the most recent monitoring data (collected from 1998-2003) indicates that, for the locations sampled, 32% had low concentrations of pollutants, 42% had moderate concentrations, 18% had high concentrations, and 8% had very high concentrations (Figure 1). Concentrations in the low category are in a range where consumption is generally encouraged by the California Office of Environmental Health Hazard Assessment (OEHHA) (Klasing and Brodberg 2006). OEHHA is the agency responsible for managing health risks due to contaminated sport fish in California. Concentrations in the very high category are in a range where OEHHA discourages consumption (Klasing and Brodberg 2006). Lakes assigned to the moderate, high, or very high concentration categories were primarily affected by mercury, with PCBs also playing a lesser role.

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California Bay - Delta Authority Fish Mercury Project: The Relationship between Landscape Features and Sport Fish Mercury in the Sacramento-San Joaquin Delta Watershed

San Francisco Estuary Institute (SFEI) | November 2nd, 2007

Summary

The goal of this study was to quantify the relationship between landscape features and mercury in sport fish. We hypothesized that spatial variation in sport fish mercury

The goal of this study was to quantify the relationship between landscape features and mercury in sport fish. We hypothesized that spatial variation in sport fish mercury would most strongly relate to major point sources associated with mining activity, habitat features (e.g., abundance of wetlands), and watershed-scale patterns in mercury deposition from the atmosphere. Geographic information system (GIS) techniques were used to evaluate the influence of these features on the bioaccumulation of mercury in sport fish. In addition, we attempted to determine the most appropriate spatial scale for analysis of these influences. Fish mercury data were selected from a state-wide historical bioaccumulation database, which also included data collected by the Fish Mercury Project (FMP) in 2005. Based on the geographic distribution of the sampling locations, three species common across the study area were chosen for analysis: largemouth bass, channel catfish, and white catfish. For the time interval examined (1990 – 2005), the mean wet weight concentration for each species at a given location was calculated. By superimposing hydrologic flow paths with watershed delineations, we were able to determine flow direction and pathways from upstream sources to downstream habitats. “Fish watersheds” (watershed areas upstream of fish sampling locations) were created for a subset of locations in the CalFed Ecosystem Restoration Program Geographic Scope. Regions heavily influenced by mining within each watershed were also delineated. We examined landscape features in fish watersheds and within close proximity (circular buffers) of fish locations. Using a GIS database, several statistics were derived for each fish watershed area and buffer, including the percent covered by habitat features (vegetated vs. non-vegetated wetlands, permanent vs. temporary inundation), number of gold and mercury mines, total land area (km2), and total length (km) of all streams and rivers. The work presented in this report is the first attempt the authors are aware of to relate landscape features to fish mercury concentrations using GIS on a large regional scale. Fish mercury concentrations appeared to be influenced by many complex and interacting factors that obscured any obvious correlations with atmospheric deposition, historic mining districts, and wetlands at the watershed scale. Some features seemed to have an influence at the proximal-scale (buffer) analyses, namely vegetated wetland and temporarily inundated aquatic habitat. Though these tentative conclusions were based on small sample sizes, they contradicted the prevailing notion that wetlands generally increase methylmercury accumulation in the food web. The lack of clear relationships in the dataset analyzed is probably due to shortcomings in the available data, rather than a true absence of influence of atmospheric deposition, mining, or wetlands on spatial patterns in mercury bioaccumulation. Future attempts to relate landscape features with mercury in the food web at the watershed scale should focus on watersheds with a stronger linkage between landscape features and mercury in fish and fewer confounding factors. Statewide monitoring of sport fish is currently being planned that should provide a better basis for conducting this type of analysis in the future.

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Coagulant and Sorbent Efficacy in Removing Mercury from Surface Waters in the Cache Creek Watershed, California

U.S. Geological Survey (USGS) | February 25th, 2019

Summary

Cache Creek drains part of northern California’s Coast Ranges and is an important source of mercury (Hg) to the Sacramento–San Joaquin Delta. Cache Creek is c

Cache Creek drains part of northern California’s Coast Ranges and is an important source of mercury (Hg) to the Sacramento–San Joaquin Delta. Cache Creek is contaminated with Hg from several sources, including historical Hg and gold mines, native Hg in the soils, and active mineral springs. In laboratory experiments in a study conducted by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, the use of coagulants and sorbents to immobilize Hg in water samples from high- concentration sources in the Cache Creek watershed was investigated. Three sites were selected for the collection of surface-water samples containing high and low concentrations of particulate-associated Hg. The high-particulate Hg samples were collected from Cache Creek Settling Basin duringstormflow conditions. The low-particulate Hg samples werecollected from two geochemically contrasting sites duringbase-flow conditions (downstream from a geothermal springand at the emergence point of a connate-water spring). Three coagulants were chosen for laboratory testing with the high-particulate sample— (1) ChitoVanTM HV 1.5 percent (shell based), (2) FerralyteTM 8131 (ferric sulfate based), and (3) UltrionTM 8186 (aluminum based). Each coagulant was tested at various dose amounts to determine the optimum dose rate for the high-particulate sample. The low-particulate source samples were passed through three sorbents— (1) chitosan flakes, (2) coconut shell-based activated carbon,and (3) coal-based activated carbon. In-line columns were packed with each material, and the untreated sample waspassed through each column at three different flow rates (0.1,0.5, and 1.0 liter per minute, L/min). For dose rates used in this study, ChitoVanTM reduced turbidity of the particulate sample by 85–91 percent, FerralyteTM reduced turbidity by 54–93 percent, and UltrionTMreduced turbidity by greater than 90 percent. At the lowest dose rate, ChitoVanTM achieved a 59- to 61-percent reduction in whole-water methylmercury (MeHg) concentrations and a 71- to 75-percent decrease in whole-water total mercury (THg) concentrations. FerralyteTM achieved a 37- to 48-percent decrease in whole-water MeHg concentrations and a 37- to 48-percent reduction in whole-water THg concentrations. UltrionTM achieved a greater than 90-percent decrease in whole-water MeHg and THg concentrations. Mercury removal from the low-particulate samples was less efficient for the sorbent materials compared to the coagulants; less than 30 percent of THg was removed from any 500-milliliter aliquot using sorbent materials. The coal-based sorbent was the most versatile of the sorbents, removing THg to a similar extent from both low-particulatesource waters. The chitosan sorbent was the most effective atremoving THg from the low-particulate stream sample, but less effective for the low-particulate connate-spring sample. The Hg removal efficiency of the coconut sorbent decreasedquickly compared to the other two sorbents, indicating that sorption may be limited by the short contact times evaluated in this study.

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Contaminant Concentrations in Sport Fish from San Francisco Bay: 2014

San Francisco Estuary Institute (SFEI) | January 1st, 2014

Summary

This summary report presents results from a 2014 survey of contaminants in San Francisco Bay sport fish, as well as an additional 2015 sampling of sport fish in Artesian

This summary report presents results from a 2014 survey of contaminants in San Francisco Bay sport fish, as well as an additional 2015 sampling of sport fish in Artesian Slough in Lower South Bay. This monitoring effort represents the seventh round of sport fish contaminant monitoring conducted by the Regional Monitoring Program for Water Quality in San Francisco Bay (RMP). This technical report is intended for agency staff charged with managing water quality issues related to bioaccumulation of contaminants in San Francisco Bay. The RMP began sport fish monitoring in 1997, following a pilot study conducted by the Bay Protection and Toxic Cleanup Program in 1994. Data collected through this monitoring program provides updates on the status and long-term trends of contaminants in Bay sport fish, and are used to update human health consumption advisories and evaluate the effectiveness of regulatory and management efforts to reduce the impacts of contaminants of concern in the Bay. Key analyses in this report include comparisons of concentrations to human health and regulatory thresholds, spatial trend evaluation, and temporal trend evaluation. Mercury, polychlorinated biphenyls (PCBs), dioxins, selenium, polybrominated diphenyl ethers (PBDEs), and perfluoroalkylated substances (PFASs) were analyzed across sixteen fish species collected at eight locations in San Francisco Bay and Artesian Slough. Fish species were selected based on a number of criteria, including species that are popular for consumption, are sensitive indicators of problems (accumulating relatively high concentrations of contaminants), are widely distributed, represent different exposure pathways (benthic vs. pelagic), and have been monitored in the past. Concentrations were compared to numeric human health thresholds established by the California Office of Environmental Health Hazard Assessment (OEHHA) for mercury, PCBs, selenium, and PBDEs. Results were also compared to regulatory thresholds for mercury, PCBs, and selenium, as well as non-regulatory screening value for dioxins, which have been established in Total Maximum Daily Load (TMDL) regulations by the San Francisco Bay Regional Water Quality Control Board (Water Board). The OEHHA fish consumption advisory is primarily driven by human exposure risks to mercury and PCBs. The 2014 data show that mercury and PCB concentrations remain high and widespread, indicating that these contaminants continue to pose the greatest human and wildlife health risks. Mercury concentrations exceeded OEHHA’s no consumption threshold for the sensitive population (women 18-45 and children 1-17) in several white sturgeon and striped bass samples, while PCB concentrations exceeded the no consumption threshold in Pacific sardine and white sturgeon samples. The spatial distribution of contamination has remained consistent over time, reflecting current knowledge of contaminated source areas targeted for management activities. Recent data showed no clear evidence of Bay-wide declines in either mercury or PCBs, although progressively lower PCB concentrations have been observed in recent years near Berkeley and in San Pablo Bay.

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Contaminant Effects on California Bay-Delta Species & Human Health

University of California, Davis (UC Davis) | December 1st, 2016

Summary

Many contaminants in the California Bay-Delta exceed regulatory standards, impact aquatic species, and potentially affect human health. Recent studies provide evidence th

Many contaminants in the California Bay-Delta exceed regulatory standards, impact aquatic species, and potentially affect human health. Recent studies provide evidence that contaminants impact species of concern in the Bay-Delta (e.g., the decline of several important fish species referred to as the “Pelagic Organism Decline”). Multiple chemicals impair processes at cellular and physiological levels (measured as growth, development, and behavior abnormalities), ultimately affecting populations. As an important example, the population decline of the endangered delta smelt (Hypomesus transpacificus) is significantly associated with multiple stressors, including insecticide use. New analyses presented in this paper show significant correlations between pyrethroid (an insecticide) use and declining abundance of POD fish species. Water sampled from the Bay-Delta causes multiple harmful effects in fish and delta smelt. Fish prey items are also impacted by contaminants; this may have an indirect effect on their populations. Co-occurrence with thermal changes or disease can worsen contaminant effects. Contaminants also pose threats to human health via consumption of fish, drinking water, and contact recreation, in particular, mercury, toxins, disinfection byproducts, pesticides, pharmaceuticals, and personal care products. The role of contaminants in the decline of Bay-Delta species is difficult to accurately assess in a complex, dynamic system. However, tools and approaches are available to evaluate contaminant impacts on Bay-Delta species, and separate the effects of multiple stressors. Integrated monitoring and focused mechanistic studies are instrumental for addressing management needs. Impact and risk assessments should be conducted for different species across multiple life stages, with emphasis on early life stages of high-priority Bay-Delta species.

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DRERIP Ecosystem Conceptual Model: Chemical stressors

California Department of Fish and Wildlife (CDFW) | February 5th, 2008

Summary

The Sacramento-San Joaquin Delta ecosystem comprises many different habitat types, and is home to a large number of species. Thousands of chemical contaminants have been

The Sacramento-San Joaquin Delta ecosystem comprises many different habitat types, and is home to a large number of species. Thousands of chemical contaminants have been or are being introduced into the Delta. The conceptual model presented here is therefore general in nature, and is intended to provide a framework for more refined models for individual species, habitats and, in particular, contaminants of interest, for example selenium, mercury and pyrethroids. The model consists of three major submodels (Figure 1). Submodel 1: Exposure assessment which includes fate and transport of contaminants and the co-occurrence of chemicals with Delta organisms; the intermediate outcome of this submodel is “Exposure Concentration”. Submodel 2: Bioavailability of contaminants to Delta organisms; the intermediate outcome of this submodel is “Bioavailable Concentration” or “Dose”. Submodel 3: Toxic effects assessment with the final model outcome “Population Level Effects”. In the following narrative, we provide a description for each submodel, its parameters, and linkages to other models. We discuss the model’s limitations and provide recommendations for its application in management.

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DRERIP Ecosystem Conceptual Model: Mercury

California Department of Fish and Wildlife (CDFW) | January 24th, 2008

Summary

Mercury has been identified as an important contaminant in the Delta, based on elevated concentrations of methylmercury (a toxic, organic form that readily bioaccumulates

Mercury has been identified as an important contaminant in the Delta, based on elevated concentrations of methylmercury (a toxic, organic form that readily bioaccumulates) in fish and wildlife. There are health risks associated with human exposure to methylmercury by consumption of sport fish, particularly top predators such as bass species. Original mercury sources were upstream tributaries where historical mining of mercury in the Coast Ranges and gold in the Sierra Nevada and Klamath-Trinity Mountains caused contamination of water and sediment on a regional scale. Remediation of abandoned mine sites may reduce local sources in these watersheds, but much of the mercury contamination occurs in sediments stored in the riverbeds, floodplains, and the Bay-Delta, where scouring of Gold-Rush-era sediment represents an ongoing source. Conversion of inorganic mercury to toxic methylmercury occurs in anaerobic environments including some wetlands. Wetland restoration managers must be cognizant of potential effects on mercury cycling so that the problem is not exacerbated. Recent research suggests that wetting-drying cycles can contribute to mercury methylation. For example, high marshes (inundated only during the highest tides for several days per month) tend to have higher methylmercury concentrations in water, sediment, and biota compared with low marshes, which do not dry out completely during the tidal cycle. Seasonally inundated flood plains are another environment experiencing wetting and drying where methylmercury concentrations are typically elevated. Stream restoration efforts using gravel injection or other reworking of coarse sediment in most watersheds of the Central Valley involve tailings from historical gold mining that are likely to contain elevated mercury in associated fines. Habitat restoration projects, particularly those involving wetlands, may cause increases in methylmercury exposure in the watershed. This possibility should be evaluated. The DRERIP mercury conceptual model and its four submodels (1. Methylation, 2. Bioaccumulation, 3. Human Health Effects, and 4. Wildlife Heath Effects) can be used to understand the general relationships among drivers and outcomes associated with mercury cycling in the Delta. Several linkages between important drivers and outcomes have been identified as important but highly uncertain (i.e. poorly understood). For example, there may be significant wildlife health effect of mercury on mammals and reptiles in the Delta, but there is currently very little or no information about it. The characteristics of such linkages are important when prioritizing and funding restoration projects and associated monitoring in the Delta and its tributaries.

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Environmental Health Risks from Abandoned Mines in the Sierra Nevada

Sierra Fund | June 9th, 2014

Summary

The widespread pollution from Gold Rush mining activities, including mercury, arsenic and lead, constitutes the oldest and longest neglected environmental justice problem

The widespread pollution from Gold Rush mining activities, including mercury, arsenic and lead, constitutes the oldest and longest neglected environmental justice problem in California. The effects of this pollution on human health and the environment are only now beginning to be addressed. Today, the effects of historic mining pollution are an invisible but very real threat to people who live, work or recreate in the Sierra Nevada. Toxins of concern include mercury, arsenic, lead and asbestos. There is little information about these potential exposures available to Sierra residents. State-issued fish consumption advisories in the region do not provide site-specific advice for many locations people fish, or the species people eat. In 2006, The Sierra Fund, in partnership with California State University Chico, conducted a survey of Sierra clinics. This study found that not one of 13 surveyed clinics included information on mercury in fish as part of their maternal/infant health programs, whether caught locally or not. Additionally, the study learned that none of the clinics surveyed administer an environmental health history form, so it is difficult to connect current health problems to environmental exposures. In order to address this lack of information and provide a springboard for more research, The Sierra Fund conducted three pilot studies of potential environmental exposures in 2009 and 2010 and a pilot outreach program to present these findings to Sierra communities in 2013-14. This report summarizes findings and recommendations from these efforts, in order to encourage continued research into these potentially serious health exposures.

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Elsinore - Elsinore Valley 8-004.01
Escondido Valley 9-009
Fenner Valley 7-002
Fish Lake Valley 6-014
Fremont Valley 6-046
Gilroy-Hollister Valley - Llagas Area 3-003.01
Goldstone Valley 6-048
Goleta 3-016
Harper Valley 6-047
Helendale Fault Valley 7-048
Hemet Lake Valley 8-006
Hidden Valley 4-016
Imperial Valley 7-030
Indian Wells Valley - 6-054
Iron Ridge Area 7-050
Ivanpah Valley 6-030
Jacumba Valley 7-047
Johnson Valley - Soggy Lake 7-018.01
Johnson Valley - Upper Johnson Valley 7-018.02
Joshua Tree 7-062
Kane Wash Area 6-089
Kelso Valley 6-031
Lanfair Valley 7-001
Langford Valley - Irwin 6036.02
Langford Valley - Langford Well Lake 6-036.01
Langford Valley 6-036.02
Las Posas Valley 4-008
Lavic Valley 7-014
Leach Valley 6-027
Lockwood Valley 4-017
Long Valley 6-011
Los Osos Valley - Los Osos 3-008.01
Los Osos Valley - Warden Creek 3-008.02
Lost Horse Valley 7-051
Lower Kingston Valley 6-021
Lower Mojave River Valley 6-040
Lucerne Valley 7-019
Malibu Valley 4-022
Means Valley 7-017
Mesquite Valley 6-029
Middle Amargosa Valley - 6-020
Middle Mojave River Valley 6-041
Mission Valley 9-014
Modoc) 5-004
Morongo Valley 7-020
Morro Valley 3-041
Napa-Sonoma Valley - Napa-Sonoma Lowlands 2-002.03
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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