site inventory and prioritization report
TRANSCRIPT
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ENVIRONMENTAL, GEOTECHNICAL, CONSTRUCTION SERVICES AND ANALYTICAL TESTING
SITE INVENTORY AND PRIORITIZATIONWESTSIDE BROWNFIELDS COALITION
ASSESSMENT PROJECT
LAKE COUNTY, NAPA COUNTY, SOLANO COUNTYCOLUSA COUNTY AND YOLO COUNTY, CALIFORNIA
BSK PROJECT E1601201S
PREPARED FOR:
MCCORD ENVIRONMENTAL759 BIANCO COURTDAVIS, CALIFORNIA
August 3, 2016
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SITE INVENTORY AND PRIORITIZATIONWESTSIDE BROWNFIELDS COALITION ASSESSMENT PROJECTLAKE COUNTY, NAPA COUNTY, SOLANO COUNTYCOLUSA COUNTY AND YOLO COUNTY, CALIFORNIA
Prepared for:
McCord Environmental759 Bianco CourtDavis, California
BSK Project: E1601201S
August 3, 2016
Martin B. Cline, P.G., C.E.G.Senior Engineering Geologist
Kevin GroveStaff Planner
BSK Associates3140 Gold Camp Drive, Suite 160Rancho Cordova, CA 95670(916) 853-9293(916) 853-9297 FAXwww.bskassociates.com
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Table of Contents
1 SITE INVENTORIES AND AREA PRIORITIES ........................................................................................ 11.1 Introduction ............................................................................................................................. 11.2 Initial Project Visualization ....................................................................................................... 2
2 SITE INVENTORY SPATIAL DATA ANALYSIS ....................................................................................... 33 RISK RANKING EVALUATION ............................................................................................................ 4
3.1 Rock Type Impact Ranking ........................................................................................................ 53.2 Landslide Impact Ranking ......................................................................................................... 53.3 Earthquake Ground Motion Impact Ranking ............................................................................. 53.4 Mercury Impaired Waters Impact Ranking ............................................................................... 63.5 Soil Loss Impact Ranking........................................................................................................... 63.6 Wetlands Impact Ranking ......................................................................................................... 73.7 Population Density Impact Ranking .......................................................................................... 73.8 Threatened and Endangered Species Impact Ranking ............................................................... 73.9 Streams and Rivers Impact Ranking .......................................................................................... 83.10 Cumulative Ranked Impacts ..................................................................................................... 8
4 SITE-SPECIFIC PRIORITIZATION CRITERIA ......................................................................................... 8
FIGURES
Figure 1, Vicinity MapFigure 2, Topographic Map Symbols (TOMS)Figure 3a, Principal Areas of Mine Pollution (PAMP)Figure 3b, USGS Mineral Resources Data System (MRS)Figure 3c, Complied Mine DataFigure 4, Rock Type MapFigure 4a, Mines Ranked by Rock TypeFigure 5, Landslide Hazard MapFigure 5a, Mines Ranked by Landslide Hazard Figure 6, Earthquake Ground MotionFigure 6a, Mines Ranked by Earthquake Ground Motion (PGA)Figure 7, 2010 Clean Water Act Section 303(d) Impaired Waters, MercuryFigure 7a Mine to Mercury Impaired Waterbody Ranked by DistanceFigure 8, RUSLE Estimated Soil Loss
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Figure 8a, Mines Ranked by RUSLE Estimated Soil LossFigure 9, National Wetland InventoryFigure 9a, Mine to Wetland Features Ranked by DistanceFigure 10, Poverty RateFigure 11, Population Density by Block 2010 CensusFigure 11a, Mines Ranked by Block Population DensityFigure 12, Land UseFigure 13, CNNDB MapFigure 13a, Mine to Threatened and Endangered Species Ranked by DistanceFigure 14, Streams/RiversFigure 14a, Mine to Flow Lines Ranked by DistanceFigure 15, All Mines Ranked by Summed ImpactsFigure 15a, Mercury Related Mines Ranked by Summed ImpactsFigure 15a2, Mercury Related Mines Ranked, Focus AreasFigures 15b, Mercury Related Mines Ranked by Summed Impacts, Vallejo AreaFigures 15c, Mercury Related Mines Ranked by Summed Impacts, St. Helena AreaFigures 15d, Mercury Related Mines Ranked by Summed Impacts, Upper Putah Creek ComplexFigures 15e, Mercury Related Mines Ranked by Summed Impacts, Middletown AreaFigures 15f, Mercury Related Mines Ranked by Summed Impacts, Quicksilver Complex
ATTACHMENTS
Attachment A. Summary of Mine DataAttachment B. Mine Ranking SynthesisAttachment C. Draft Site Scoring Sheet
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1 SITE INVENTORIES AND AREA PRIORITIES
1.1 Introduction
Aside from the physical safety concerns associated with abandoned mine openings, mine-impactedlands may provide a source for metals, acidity, and sediment contamination from exposed faces, minewastes (including, waste rock, tailings, process wastes), dust, and runoff. This contamination can causeboth direct and indirect exposure from migration of contaminants into local waterways.
This component of the Westside Brownfields Coalition Assessment Project will identify and prioritizemine-impacted Brownfields on private and public lands, collectively and consistently, for public benefit.However it is important to note that the field investigation elements of this study, the Phase I and IIefforts can only be completed on private properties that have not participated in federally fundedcleanup activities or public lands, as required under the Brownfields program. This program by law is notintended to be applied to the study or remediation of public properties. Primary target Brownfield siteswill be those which (1) contaminate the watershed, (2) may result in other public health andenvironmental health concerns, and (3) inhibit reuse for open space, economic development or otherbeneficial uses.
To identify priority regions or areas associated with documented mine sites or geologic areas associatedwith cinnabar (mercury containing mineral), the project team developed an initial set of physicalscreening criteria based on Brownfields Program constraints and stakeholder input. Criteria scores areweighed as described in the supporting documentation, and based on the scorers understanding of thepropertys perceived scores in each category.
In order to assist that evaluation, we applied various geospatial mapping techniques using readilyavailable geospatial data. This data can inform the scorer about geo- or bio-physical characteristics thatmay not have been apparent. In the final analysis, the scored geo- and bio-physical elements which canbe aggregated meaningfully will be used to show the relative rankings of individual sites.
For example, the initial data analysis laid out the geography, physical features and hydrography at thefive-county scale (Lake, Napa, Solano, Yolo, and Colusa counties). This analysis is done at the largest ofthree scales: (1) the entire five IRWMP counties, (2) the Cache and Putah watersheds, and (3) futurepotential individual project sites.
The initial area-wide analysis and mapping work products allowed the team to identify data gaps for thesite-specific project screening analysis, assess spatial analysis of single and multiple variables andsupport the ultimate Area-wide Brownfields Planning analysis (Task 5). These products are intended toinform stakeholders on how to conceptually prioritize areas for further investigation and how to weigh
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the relative difference among sites that were subject to erosion, proximate to streams or wetlands, etc.This map-based analysis will be necessary given the very large, remote area containing many of thepotential sites, which means that informants will not likely have personal knowledge of the sites.
While reviewing available geospatial data, it became clear that the draft analyses and maps wouldprovide a conceptual framework for stakeholders to visualize what the project could accomplish througha spatial analysis of physical variables, in support of their local understanding, and also as a means bywhich to communicate the ultimate tiering (or scaling) of the geospatial work products.
These scales then formed the context to display the various data that were collected for the projectincluding: stream class, topography, land slope/elevation, soil type, geologic origin, 303(d) status, mine(multiple sources and classes), land ownership type, and census data. In order to accelerate the timelineand to bridge the site analysis process with relevant portions of the Area-Wide supporting analysis andfigures, the project completed the five-counties and two-watersheds analyses concurrently.
1.2 Initial Project Visualization
To aid in the visualization of the five counties and the two watersheds, several maps were created thatshow the overall project analysis boundaries:
Figure 1, Vicinity Map; the documented mining features and mines;
Figure 2, Topographic Map Symbols (TOMS);
Figure 3a, Principal Areas of Mine Pollution (PAMP); and,
Figure 3b, USGS Mineral Resources Data System (MRS).
To better understand the geology of the study area, and potential risk factors of landslide, andearthquakes, stream impaired by mercury, and annual estimated loss of soils, additional maps werecreated:
Figure 4, Rock Type Map;
Figure 5, Landslide Hazard Map;
Figure 6, Earthquake Ground Motion;
Figure 7, 2010 Clean Water Act Section 303(d) Impaired Waters, Mercury; and,
Figure 8, RUSLE Estimated Soil Loss.
Similarly to the geologic analyses, we identified and documented wetlands, population, land use, anddocumented listed species observations:
Figure 9, National Wetland Inventory;
Figure 10, Poverty Rate over 20%;
Figure 11, Population Density by Block 2010 Census;
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Figure 12, Land Use; and,
Figure 13, CNNDB Map.
2 SITE INVENTORY SPATIAL DATA ANALYSISAs shown on Figure 1, the Project Area consists of the area in the boundaries of the counties of Solano,Colusa, Napa, Yolo and Solano. These counties encompass the largest scale of analysis in order toprovide information relevant to the IRWMP member counties. The Project Area is located in the GreatValley and Coast Ranges geomorphic provinces in Northern California. Two significant watersheds, theUpper Cache Creek and Upper Putah Creek are located in the Project Area. Other watersheds in theProject Area include:
Upper Eel;
San Pablo Bay;
Suisun Bay;
Lower Sacramento;
Sacramento-Stone Corral;
Butte Creek; and,
Upper Stony.
The site inventory began with an assessment of identified mines and mine features, such as tailingspiles, waste process materials (calcines) and mine related structures located in the Project Area. Suchfeatures are typically much more numerous than the mines themselves; however, specific features areoften important sources of chemical impacts. The inventory search included County, State and Federallists or databases of mining related features. Each county search revealed that counties do not compileand maintain mine related lists or databases. Mine and mine feature information came from thefollowing State and Federal sources:
Topographically Occurring Mine Symbols, TOMS (Figure 2), Source: California Department ofConservation, Office of Mine Reclamation, 2001. TOMS originated by digitizing mining featuresfrom scanned USGS topographic quadrangles. Each of the 7.5-minute USGS topographicquadrangles was examined and all mining features were digitized and annotated with informationderived from the map. (Total 414 mines)
Principal Areas of Mine Pollution, PAMP, (Figure 3a) Source: California Department ofConservation, Office of Mine Reclamation, 1972, The PAMP data set is a compilation of 2,422mining operations and their potential water-quality problems. This information was originallycompiled in 1972 by the Division of Mines and Geology for the State Water Resources ControlBoard. It was published in a series of volumes of tabular data. The data set includes operations
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where production exceeded $100,000 or where other factors indicated a high potential forpollution. (Total 74 Mines)
USGS Mineral Resources Data System, MRDS, (Figure 3b) Source: U.S.G.S Mineral Resources DataSystem, MRDS is a collection of reports describing metallic and nonmetallic mineral resourcesthroughout the world. Included are deposit name, location, commodity, deposit description,geologic characteristics, production, reserves, resources, and references. It subsumes the originalMRDS and MAS/MILS. (Total 929 Mines)
The TOMS data appears to lack critical information, such as type of material being mined, for a completeanalysis. The PAMP data contains necessary information, but has a limited number of mines in thedataset. The MRDS contains a significant amount of data and had the most number of mines/featureslisted. Figure 3c presents all the compiled mine site and feature data plotted by type or commoditymined. Each site (or feature) is included in Attachment A Summary of Mine Data. The summary ofmine data may include multiple entries for a single mine location. Further filtering by commodity minedeliminated multiple listings from the TOMS data due to the lack of commodity type listing in thatdataset.
3 RISK RANKING EVALUATIONThe risk ranking evaluation consisted of compiling and plotting available spatial data, then applying twodifferent analytical methods depending on the spatial distribution of the potential impact source.Spatial distributed impact data were evaluated using an extraction method that determines the value atthe source point (mine location). Impact sources such as impaired waterbodies, streams andendangered species locations were evaluated using the distance from source (mine location) to impact.The implied risks are to waterbodies or wetlands from runoff, erosion, landslide, inundation, and othertransport mechanisms from the mine features to the environment.
Ranking provides the greatest spread to the values associated with each ranking criterion, rankingeach location relative to all other locations. It does not rank each factor relative to the others, but ratherweighs each factor independently and equally. This process does not quantify risk relative to anyestablished threshold, as such comparisons will be done for subsequent site-specific analyses of thehighest ranking sites.
In order to establish a ranking system data was grouped according to values and a graded ranking valuewas assigned to the grouped value. Pre-processing the spatial data included classifying the data byassigning a value if the mine site (mine or feature) overlapped with the spatial data set, or by assigning avalue for each relative distance from, each mine site to analytical object or class, and then re-classifyingto ranked values. The classified values, generally grouped by natural breaks, were then reclassifiedaccording to integer values scaled (or weighted) from 0 to 5, or 0 to 2 depending of the relativesignificance of the impact. Analysis was performed using ESRI ArcGIS 10.4 for Desktop with SpatialAnalyst Tools. The distance method evaluation utilized straight line (Euclidean) distances that do not
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account for paths based on the slopes of terrain. An attempt was made to perform a flow line (terrain-network cost-based) path analysis using a Digital Elevation Model (DEM). An initial run of the analysisrequired in excess of 18 hours of processing time. Therefore, the path analysis was determined to beunfeasible considering the project scope and size of the Project Area.
3.1 Rock Type Impact Ranking
Figure 4 presents a regional geologic map showing the generalized rock types present in the ProjectArea. The two rock types that are generally more likely to contain significant occurrence of mercury-bearing rock are serpentinite and mlange. Other rocks that are near or in contact with those two rocktypes may also contain mercury.
As shown on Figure 4a, rock types were grouped into three classes (serpentinite, mlange and other)and then re-classed into ranked values (2, 1 and 0, respectively). The combined mine points were usedto extract ranked values from the ranked rock types dataset using the ArcMap Extract Multi Values toPoints Tool. Prioritizing Brownfields with greater occurrences of mercury-bearing rock is more likely toreduce downstream loads of eroded mercury containing sediments.
3.2 Landslide Impact Ranking
Figure 5 presents the landslide hazard in the Project Area. Landslide hazard is an important indicator ofmercury mine site contamination risk because naturally occurring mercury containing minerals could bemobilized in a landslide, or mine debris piles, such as mill tailings, processed calcines and constructedponds could fail and release these materials to the environment. The landslide hazards in the ProjectArea were identified as low, moderate and high and were re-classed into ranked values of 0, 1 and 2,respectively. As shown on Figure 5a, the combined mine points were used to extract ranked values fromthe ranked landslide dataset using the ArcMap Extract Multi Values to Points Tool. PrioritizingBrownfields within areas of higher landsliding potential is more likely to reduce downstream loads ofdisturbed eroded mercury containing sediments.
3.3 Earthquake Ground Motion Impact Ranking
Figure 6 presents estimated ground motion values (Peak Ground Acceleration, PGA) based on theMaximum Considered Earthquake in the Project Area. Similarly to Landslide hazard, Earthquake groundmotion is a potential indicator of mercury mine site contamination risk because naturally occurringmercury containing minerals and contaminated mine debris could be mobilized in an earthquake andrelease these materials to the environment. The ground motion PGA values were grouped into values of0.2-0.4g, 0.4-0.6g and >0.6g and re-classed into ranked values of 1, 2 and 3, respectively. As shown onFigure 6a, the combined mine points were used to extract ranked values from the ranked ground motiondataset using the ArcMap Extract Multi Values to Points Tool. Prioritizing Brownfields within areas ofhigher intensity ground motion is more likely to reduce loads of air borne mercury laden dusts duringearthquakes and reduce downstream loads of eroded mercury containing sediments from earthquakeinduced landsliding or ground failures.
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3.4 Mercury Impaired Waters Impact Ranking
Figure 7 presents the location of water bodies impaired by mercury as listed in the 2010 Clean Water ActSection 303(d) list. This analysis is intended to evaluate risk factor to listed waterbodies from mine sites,such as potential to worsen their condition from other factors. This impact however, could also becorrelated to the mine site. The evaluation of the impacts was based on a straight line distance from themine locations to the nearest impaired waterbody using the ArcMap Near Function of the ProximityTool. The distances were grouped into classes based on distances of 2 miles. The distances were re-classed into ranked values offrom 5 to 0, respectively, and shown on Figure 7a. Prioritizing Brownfields located in areas based ondistance to existing impaired waters is more likely to reduce the potential of continued impairment fromloads of eroded mercury containing sediments.
3.5 Soil Loss Impact Ranking
We adapted the Revised Universal Soil Loss Equation (RUSLE) to estimate annual soil loss in order toapproximate the potential water quality impacts due to soil erosion from a mine site. The data wereobtained from the State Water Resources Control Boards GIS datasets for the factors used in the RULSEequation. Annual soil loss is an indication of the potential impact from rain induced sediment, frommercury containing minerology as well as erosion from mine sites to streams, RUSLE is composed of sixfactors that are used to calculate an estimated loss of top soil due to rainfall erosion. The RUSLEequation is:
A = R x K x L x S x C x P
Where,A Estimated soil loss in tons per acre per yearR Rainfall ErosivityK Soil ErosivityL Length of the slopeS Steepness of the slopeC Crop coefficientP Practice coefficient
The crop coefficient and the practice coefficient are conservatively taken as 1 for this evaluation.Combining the GIS data for R, K and LS provides an estimated soil loss in tons/acre-yr which is presentedon Figure 8. Soil losses in the Project Area were grouped by an equal statistical distribution and then re-classed into ranked values of from 5 to 0, with 5 being the highest potential soil loss. The combinedmine points were used to extract ranked values from the ranked soil loss dataset using the ArcMapExtract Multi Values to Points Tool. The soil loss ranked values are presented on Figure 8a. Prioritizing
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Brownfields with higher sediment erosion potential is more likely to reduce downstream loads oferoded mercury containing sediments.
3.6 Wetlands Impact Ranking
Figure 9 presents the location of wetlands based on the National Wetland Inventory developed by theU.S. Fish and Wildlife Service. This ranking evaluates the risk to wetlands from mine sites, and iscorrelated with listed species, and in some cases with water quality impaired streams. Wetlands areimportant ecologically, and are efficient natural converters of mercury to methylmercury, which is muchmore bioavailable and toxic. The evaluation of the impacts was based on a straight line distance fromthe mine locations to the nearest wetland feature using the ArcMap Near Function of the ProximityTool. The distances were grouped into classes based on distances of 2 miles. The distances were re-classed into rankedvalues of from 5 to 0, respectively, and shown on Figure 9a. Prioritizing Brownfields located in areasbased on distance to wetlands is more likely to reduce the impact to wetlands from loads of erodedmercury containing sediments.
3.7 Population Density Impact Ranking
Figure 11 presents the total (human) population per block based on the 2010 US Census data. Theblocks were grouped by total population according to natural data breaks and re-classed into rankedfrom 0 to 6 with 6 having the highest population density. As shown on Figure 11a, the combined minepoints were used to extract ranked values from the population density dataset using the ArcMap ExtractMulti Values to Points Tool. The method used may have introduced some biased grouping due to thearea of the population being defined by artificial irregular blocks inherent to the Census data. A minemay be located in a low population block but be adjacent to a high population block, and this would notbe reflected in a higher ranking. Prioritizing Brownfields located in areas based on the total humanpopulation is more likely to reduce the impact of potential mercury exposure to the number of humanreceptors.
3.8 Threatened and Endangered Species Impact Ranking
Figure 13 presents the location of documented observations of federally-listed Threatened andEndangered Species from the California Natural Diversity Database (CNDDB) developed by the CaliforniaDepartment of Fish and Wildlife. The standard federal lists of species are not specifically related toobservations and largely rely on potential habitat. The approach provided here is the most accuratemeans of identifying risks to federally listed species in occupied habitat. The evaluation of the impactswas based on a straight line distance from the mine locations to the nearest Threatened andEndangered Species feature using the ArcMap Near Function of the Proximity Tool. The distances weregrouped into classes based on distances of 2 miles. The distances were re-classed into ranked values of from 5 to 0,respectively and shown on Figure 13a. Prioritizing Brownfields located in areas based on distance to
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threatened and endangered species is more likely to reduce the potential impacts to existing stressedhabitat.
3.9 Streams and Rivers Impact Ranking
Figure 14 presents the location of streams, rivers, canals and artificial flowpaths obtained from the USGSNational Hydrography Dataset. This impact analysis is intended to capture the most dominant means ofmercury transport in the watershed. The evaluation of the impacts was based on a straight line distancefrom the mine locations to the nearest flowline using the ArcMap Near Function of the Proximity Tool.The distances were grouped into classes based on distances of
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Category 4: Community Benefit Factors. How well the cleaned up site would address localvalues.
Category 5: Environmental Benefit Factors. How well the cleaned up site would provideecological benefits.
These criteria will be quantified and sorted by respondent class (citizens, tribes, local agency staff,developers, and others) to understand similarities and differences of responses to the criteria, and theirrelevant metrics. These categories/criteria are described in Attachment B Mine Ranking Synthesis.Site-specific scoring will be done following the scoring sheet in Attachment C Draft Site Scoring Sheet.
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ounties, California
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SGS M
ineral Resources
Data S
ystemBS
K Project E
1601201S0
1428
7M
iles.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\Watersheds_Counties\F3b usgs mines.mxd
By: M
BC
Date S
aved: 5/5/2016
Coordinate S
ystem:
NA
D 1983 2011 S
tatePlane C
alifornia II FIPS
0402 Ft US
P
rojection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference: U
SG
S M
ineral Resources D
ata System
, 2005, http://m
rdata.usgs.gov/mrds/
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L, Ordnance S
urvey, Esri
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rownsfield C
oalitionC
olusa, Lake, Solanoand Yolo C
ounties, California
Figure 3cC
ompiled M
ine Data
BSK P
roject E1601201S
014
287
Miles
.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\Watersheds_Counties\F3c all mines.mxd
By: M
BC
Date S
aved: 5/5/2016
Coordinate S
ystem:
NA
D 1983 2011 S
tatePlane C
alifornia II FIPS
0402 Ft US
P
rojection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference: U
SG
S M
ineral Resources D
ata System
, 2005, http://m
rdata.usgs.gov/mrds/
1 inch = 14 miles
-
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: Esri, H
ER
E, DeLorm
e, Intermap, increm
ent P Corp., G
EBC
O, U
SGS, FAO
, NPS
, NR
CAN
, GeoBase, IG
N, K
adaster NL, O
rdnance Survey, Esri
Japan, ME
TI, Esri China (H
ong Kong), sw
isstopo, Mapm
yIndia, O
penStreetM
ap contributors, and the GIS
User C
omm
unity
LegendC
ounty Boundary
Watershed B
oundary
Geology
Rock Types
alluviumlandslideVolcanics andesite; dacite; rhyoliteS
edimentary R
ocks, mudstone; sandstone; siltstone
Metam
orphics blueschist; greenstonem
elangeserpentinite
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 4R
ock Type Map
BS
K P
roject E1601201S
014
287
Miles
.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\Watersheds_Counties\F4a geologic_map.mxd
By: MB
C
Date Saved: 5/5/2016
Coordinate S
ystem:
NAD
1983 2011 StateP
lane California II FIP
S 0402 Ft US
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference: C
alifornia geologic map data, U
SG
S O
pen-File Report 2005-1305,
http://mrdata.usgs.gov/geology/state/state.php?state=C
A1 inch = 14 m
iles
-
(
((
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((((
((
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((((((
((((
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: Esri, H
ER
E, DeLorm
e, Intermap, increm
ent P Corp., G
EBC
O, U
SGS, FAO
, NPS
, NR
CAN
, GeoBase, IG
N, K
adaster NL, O
rdnance Survey, Esri
Japan, ME
TI, Esri China (H
ong Kong), sw
isstopo, Mapm
yIndia, O
penStreetM
ap contributors, and the GIS
User C
omm
unity
LegendC
ounty Boundary
Watershed B
oundaryM
ines Ranked by R
ock Types(
0 - Other R
ock Types!(
1 - Melange
!(2 - Serpentinite
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 4aM
ines Ranked by R
ock TypeB
SK
Project E
1601201S0
1428
7M
iles.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\Watersheds_Counties\Ranking\F4a geologic_map.mxd
By: MB
C
Date Saved: 7/21/2016
Coordinate S
ystem:
NAD
1983 2011 StateP
lane California II FIP
S 0402 Ft US
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference: C
alifornia geologic map data, U
SG
S O
pen-File Report 2005-1305,
http://mrdata.usgs.gov/geology/state/state.php?state=C
A1 inch = 14 m
iles
-
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: E
sri, HE
RE
, DeLorm
e, Intermap, increm
ent P Corp., G
EB
CO
, US
GS
, FAO
, NP
S, N
RC
AN
, GeoB
ase, IGN
, Kadaster N
L, Ordnance S
urvey, Esri
Japan, ME
TI, Esri C
hina (Hong K
ong), swisstopo, M
apmyIndia,
OpenS
treetMap contributors, and the G
IS U
ser Com
munity
LegendC
ounty Boundary
Watershed B
oundary
Landslide Hazard
Landslide IncidenceLow
- Less than 1.5% of A
rea Involved M
oderate - 15% - 1.5%
of Area Involved
High - G
reater than 15% of A
rea Involved
Westside B
rownsfield C
oalitionC
olusa, Lake, Solanoand Yolo C
ounties, California
Figure 5Landslide H
azard Map
BSK P
roject E1601201S
014
287
Miles
.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\F5 landslide_map.mxd
By: M
BC
Date S
aved: 3/29/2016
Coordinate S
ystem:
NA
D 1983 2011 S
tatePlane C
alifornia II FIPS
0402 Ft US
P
rojection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Source: A
dapted from U
SG
S Landslide Incidence M
ap, 1978 http://pubs.usgs.gov/pp/p1183/figures/m
ap.jpg1 inch = 14 m
iles
-
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!(!(!(!(!(!(
!(!(!(!(
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: Esri, H
ER
E, DeLorm
e, Intermap, increm
ent P Corp., G
EBC
O, U
SGS, FAO
, NPS
, NR
CAN
, GeoBase, IG
N, K
adaster NL, O
rdnance Survey, Esri
Japan, ME
TI, Esri China (H
ong Kong), sw
isstopo, Mapm
yIndia, O
penStreetM
ap contributors, and the GIS
User C
omm
unity
LegendW
atershed Boundary
County B
oundaryM
ines Ranked by Landslide H
azard(
0 - Low!(
1 - Moderate
!(2 - H
igh
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 5aM
ines Ranked by Landslide H
azardB
SK
Project E
1601201S0
1428
7M
iles.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\Watersheds_Counties\Ranking\F5 landslide_map.mxd
By: MB
C
Date Saved: 7/21/2016
Coordinate S
ystem:
NAD
1983 2011 StateP
lane California II FIP
S 0402 Ft US
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Source: Adapted from
US
GS
Landslide Incidence Map, 1978
http://pubs.usgs.gov/pp/p1183/figures/map.jpg
1 inch = 14 miles
-
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
0.7 g
0.6 g0.5 g
0.4 g
0.3 g
0.8 g
0.7 g
0.6 g
0.5 g
0.4 g
0.3 g
0.8 g
0.7 g
0.7 g0.6 g
0.8 g
0.7 g0.6 g
0.4 g
0.3 g
0.2 g
0.8 g
0.2 g
0.8 g
0.7 g
0.6 g
Sources: E
sri, HE
RE
, DeLorm
e, Intermap, increm
ent P Corp., G
EB
CO
, US
GS
, FAO
, NP
S, N
RC
AN
, GeoB
ase, IGN
, Kadaster N
L, Ordnance S
urvey, Esri
Japan, ME
TI, Esri C
hina (Hong K
ong), swisstopo, M
apmyIndia,
OpenS
treetMap contributors, and the G
IS U
ser Com
munity
LegendW
atershed BoundaryM
aximum
Considered Earthquake G
eometric M
ean (MC
Eg)PG
A (g)0.06 - 0.20.3 - 0.40.5 - 0.60.7 - 0.80.9 - 1
Westside B
rownsfield C
oalitionC
olusa, Lake, Solanoand Yolo C
ounties, California
Figure 6Earthquake G
round Motion (PG
A)BS
K Project E
1601201S0
1428
7M
iles.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\F6 Fault_map.mxd
By: M
BC
Date S
aved: 5/5/2016
Coordinate S
ystem:
NA
D 1983 2011 S
tatePlane C
alifornia II FIPS
0402 Ft US
P
rojection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Source: A
dapted from gridded data from
Figures 22-1, 22-2, and 22-7 of the 2010 A
SC
E-7 S
tandard, prepared by US
GS
1 inch = 14 miles
-
!(
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!( !(!(
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!( !(!(
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!( !(!(!(!(
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!( !(!( !(
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!( !(!( !(!(!( !(!( !(!(
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!(!(!(!(!(
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!( !(!( !(!(
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!( !( !(!(!(
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!(!(!(!(!(!(
!(!( !(!(!(!(
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!(!(!(!(!(!(
!( !(!(!( !(
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!(
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!(!( !(!(
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!( !(!(
!( !(!(!(
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Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
0.7 g
0.6 g0.5 g
0.4 g
0.3 g
0.8 g
0.7 g
0.6 g
0.5 g
0.4 g
0.3 g
0.8 g
0.7 g
0.7 g0.6 g
0.8 g
0.7 g0.6 g
0.4 g
0.3 g
0.2 g
0.8 g
0.2 g
0.8 g
0.7 g
0.6 g
Sources: Esri, H
ER
E, DeLorm
e, Intermap, increm
ent P Corp., G
EBC
O, U
SGS, FAO
, NPS
, NR
CAN
, GeoBase, IG
N, K
adaster NL, O
rdnance Survey, Esri
Japan, ME
TI, Esri China (H
ong Kong), sw
isstopo, Mapm
yIndia, O
penStreetM
ap contributors, and the GIS
User C
omm
unity
LegendW
atershed Boundary
County B
oundaryC
ontours of Peak G
round Acceleration (g)
Mines R
anked by Earthquake Ground M
otion!(
1 - 0.2g to 0.4g!(
2 - 0.4g to 0.6g!(
3 - >0.6g
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 6aM
ines Ranked by
Earthquake G
round Motion (P
GA
)B
SK
Project E
1601201S0
1428
7M
iles.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\Watersheds_Counties\Ranking\F6a ground motion.mxd
By: MB
C
Date Saved: 7/21/2016
Coordinate S
ystem:
NAD
1983 2011 StateP
lane California II FIP
S 0402 Ft US
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Source: Adapted from
gridded data from Figures 22-1, 22-2, and 22-7 of the 2010
AS
CE-7 S
tandard, prepared by US
GS
1 inch = 14 miles
-
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: Esri, DeLorm
e, NAV
TEQ
, TomTom
, Intermap, increm
ent P Corp., G
EB
CO
, US
GS, FA
O, N
PS
, NR
CAN
, GeoBase, IG
N, Kadaster N
L, Ordnance
Survey, Esri Japan, METI, Esri C
hina (Hong K
ong), swisstopo, and the G
IS U
ser Com
munity
LegendC
ounty Boundary
Watershed B
oundary 303(d) M
ercury Impaired W
aters (Stream
/River)
303(d) Mercury Im
paired Waters (Lakes/R
eservoir)
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 7a2010 C
lean Water A
ct Section 303(d)
Impaired W
atersB
SK
Project E
1601201S0
1428
7M
iles.
Document Path: C:\GIS\E1601201S - Westside Brownfield\Watersheds_Counties\F7 Impaired_streams.mxd
By: MB
C
Date S
aved: 5/7/2016
Coordinate System
: N
AD 1983 2011 S
tatePlane C
alifornia II FIPS 0402 Ft U
S
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference:
http://ww
w.w
aterboards.ca.gov/water_issues/program
s/tmdl/integrated2010.shtm
l1 inch = 14 m
iles
-
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: Esri, DeLorm
e, NAV
TEQ
, TomTom
, Intermap, increm
ent P Corp., G
EB
CO
, US
GS
, FAO, N
PS, N
RC
AN
, GeoB
ase, IGN
, Kadaster N
L, Ordnance
Survey, Esri Japan, METI, Esri C
hina (Hong K
ong), swisstopo, and the G
IS User C
omm
unity
LegendC
ounty Boundary
Watershed B
oundary 303(d) M
ercury Impaired W
aters (Stream
/River)
303(d) Mercury Im
paired Waters (Lakes/R
eservoir)R
ank by Distance to M
ercury Impaired W
aterbody0 - > 2 m
iles1 - 1 to 2 m
iles2 - 2000 feet to 1 m
ile3 - 500 to 2000 feet4 - 100 to 500 feet5 - < 100 feet
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 7aM
ine to Mercury Im
paired Waterbody
Ranked by D
istanceB
SK
Project E
1601201S0
1428
7M
iles.
Document Path: C:\GIS\E1601201S - Westside Brownfield\Watersheds_Counties\Ranking\F7a Impaired_streams.mxd
By: MB
C
Date S
aved: 7/24/2016
Coordinate System
: N
AD 1983 2011 S
tatePlane C
alifornia II FIPS 0402 Ft U
S
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference:
http://ww
w.w
aterboards.ca.gov/water_issues/program
s/tmdl/integrated2010.shtm
l1 inch = 14 m
iles
-
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: Esri, DeLorm
e, NAV
TEQ
, TomTom
, Intermap, increm
ent P Corp., G
EB
CO
, US
GS, FA
O, N
PS
, NR
CAN
, GeoBase, IG
N, Kadaster N
L, Ordnance
Survey, Esri Japan, METI, Esri C
hina (Hong K
ong), swisstopo, and the G
IS U
ser Com
munity
LegendC
ounty Boundary
Watershed B
oundaryR
USLE Estim
ated Soil Loss (tons/acre, one year)0 - 2021 - 4041 - 6061 - 8081 - 100101 - 120121 - 140141 - 160161 - 180181 - 200>200
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 8R
US
LE E
stimated S
oil LossB
SK
Project E
1601201S0
1428
7M
iles.
Document Path: C:\GIS\E1601201S - Westside Brownfield\Watersheds_Counties\F8 estimated soil loss.mxd
By: MB
C
Date S
aved: 5/8/2016
Coordinate System
: N
AD 1983 2011 S
tatePlane C
alifornia II FIPS 0402 Ft U
S
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference:
1 inch = 14 miles
-
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: Esri, H
ER
E, DeLorm
e, Intermap, increm
ent P Corp., G
EBC
O, U
SGS, FAO
, NPS
, NR
CAN
, GeoBase, IG
N, K
adaster NL, O
rdnance Survey, Esri
Japan, ME
TI, Esri China (H
ong Kong), sw
isstopo, Mapm
yIndia, O
penStreetM
ap contributors, and the GIS
User C
omm
unity
LegendC
ounty Boundary
Watershed B
oundaryR
anked RU
SLE Soil Loss0 - 0 -401 - 40 - 802 - 80 - 1203 - 120 - 1604 - 160 - 2005 - >200
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 8aM
ines Ranked by R
US
LEE
stimated S
oil LossB
SK
Project E
1601201S0
1428
7M
iles.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\Watersheds_Counties\Ranking\F8 estimated soil loss.mxd
By: MB
C
Date Saved: 10/4/2016
Coordinate S
ystem:
NAD
1983 2011 StateP
lane California II FIP
S 0402 Ft US
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference:
1 inch = 14 miles
-
Lake County
Colusa C
ounty
Yolo County
Napa C
ounty
Solano County
Upper C
ache
Upper Putah
Sources: Esri, H
ER
E, DeLorm
e, Intermap, increm
ent P Corp., G
EBC
O, U
SGS, FAO
, NPS
, NR
CAN
, GeoBase, IG
N, K
adaster NL, O
rdnance Survey, Esri
Japan, ME
TI, Esri China (H
ong Kong), sw
isstopo, Mapm
yIndia, O
penStreetM
ap contributors, and the GIS
User C
omm
unity
LegendW
atershed Boundary
County B
oundaryW
etland TypeEstuarine and M
arine Deepw
aterEstuarine and M
arine Wetland
Freshwater Em
ergent Wetland
Freshwater Forested/Shrub W
etlandFreshw
ater PondLakeR
iverineO
ther
Westside B
rownsfield C
oalitionC
olusa, Lake, Solano
and Yolo Counties, C
alifornia
Figure 9N
ational Wetland Inventory
BS
K P
roject E1601201S
014
287
Miles
.
Document Path: T:\GIS-Files\Project-Files\E1601201S - Westside Brownfield\Watersheds_Counties\F9 NWI2.mxd
By: MB
C
Date Saved: 5/8/2016
Coordinate S
ystem:
NAD
1983 2011 StateP
lane California II FIP
S 0402 Ft US
Projection: Lambert C
onformal C
onicD
atum: N
AD
1983 2011U
nits: Foot US
Reference: N
ational Wetland Inventory, U
.S. Fish and W
ildlife Service
1 inch = 14 miles
-
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!( !(!(
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!((
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(
!( !( !(!(
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!( !((((
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!( !(!(!(!(
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!( !( !(!(!(
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!( !(!(
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!( !(!( !(
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!(!(!(!( !( !(!( !(!(!(!(
!( !(!( !(!(
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!(!(!(
!( !(!(
!( !(!(
!( !(!(
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!(!(!( !( !( !(!(!( !(!( !(!(!(!( !(
!( !(!(!(
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!( !(!(
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!(!(!(!( !( !(!( !( !(!(
!( !(!(
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!( !( !(!(
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!( !(!( !(!( !(
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