Jones, Jamie L
Knudsen, Keith L
2017
Liquefaction potential as a result of HayWired earthquake scenario mainshock (April 18, 2018) shaking in Alameda and Santa Clara Counties, San Francisco Bay area, California
Raster Digital Data Set
USGS Scientific Investigations Report
2017-5013
https://doi.org/10.5066/F74X5610
Jones, Jamie L.
Knudsen, Keith L.
Wein, Anne
20170418
HayWired scenario mainshock—liquefaction probability modeling
Publication (Other)
USGS Scientific Investigations Report
2017-5013-A-E
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/sir20175013
These data are a geospatial representation of liquefaction potential for the HayWired earthquake scenario, a magnitude 7.0 earthquake occurring on the Hayward Fault on April 18, 2018, with an epicenter in the city of Oakland, CA. These data are the product of an analysis that created a detailed liquefaction probability map covering the northern Santa Clara County and western Alameda County areas. The approach of Holzer, Noce, and Bennett (U.S. Geological Survey) was used to produce the data; Holzer, Noce, and Bennett used the liquefaction potential index parameter as an indicator for liquefaction hazard in their mapping of a smaller part of northern Santa Clara County and western Alameda County.
These raster .IMG data were developed and are intended for use in GIS applications such as ESRI's ArcGIS software suite.
These data support the following publication:
Jones, J.L., Knudsen, K.L., and Wein, Anne, 2017, HayWired scenario mainshock—Liquefaction probability mapping, in Detweiler, S.T., and Wein, Anne, eds., The HayWired earthquake scenario—Earthquake hazards: U.S. Geological Survey Scientific Investigations Report 2017-5013–A–E, 18 p., https://doi.org/10.3133/sir20175013.
These data were collected in support of the Science Application for Risk Reduction (SAFRR) project's HayWired earthquake scenario.
Appropriate use may include future work related to research using the HayWired earthquake scenario as its earthquake source.
Please note that this dataset is based on scenario earthquake shaking data and does not represent any known future earthquake activity. These data are for educational and training purposes only.
20180418
publication date
None planned
-122.347063492
-121.740235191
37.906255291
37.246679003
USGS Thesaurus
liquefaction
earthquakes
hazards
None
HayWired
USGS Metadata Identifier
USGS:58b6f375e4b01ccd54ff8155
Common geographic areas
California
None
San Francisco Bay area
None. Please see 'Distribution Info' for details.
None. Users are advised to read the data set's metadata thoroughly to understand appropriate use and data limitations.
U.S. Geological Survey, PACIFIC REGION
Jamie L Jones
Geographer
mailing address
Mail Stop 531, 345 Middlefield Road
Menlo Park
CA
94025
650-329-4125
650-329-4722
jamiejones@usgs.gov
Tom Holzer and Thomas Noce (U.S. Geological Survey, USGS) were consulted on application of their methods to the HayWired scenario mainshock and expanded geographical area. Amandine Dhellemmes (USGS) ran the preliminary analysis, explained differences in results from using the HayWired scenario compared to previously-used scenarios, and helped to identify geologic units that were not accounted for in the extended region.
Environment as of Metadata Creation: Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.4.1 (Build 5686) Service Pack N/A (Build N/A)
Using ArcGIS 10.3.1 visualization methods and local expert opinion, data in this release were visually compared with existing liquefaction susceptibility data (Witter and others, 2006, available at https://pubs.usgs.gov/of/2006/1037/) and previous records of liquefaction events in the region (Knudsen and others, 2000, available at http://pubs.usgs.gov/of/2000/of00-444/) to verify the accuracy of the data produced. Several iterations of the analysis were completed in response to the above checks. All data fall within a range of 0 (no probability of liquefaction) to 1 (100 percent probability of liquefaction).
These data are presented as a continuous raster .IMG file with values ranging from 0 to 1, with 0 representing no chance of the liquefaction potential index (LPI) exceeding 5 and 1 representing a 100 percent chance of LPI exceeding 5. No overlapping data were found during or following the analysis. Areas classified as water in the input surficial geology dataset were masked out in order to remove inaccurate artifacts of the GIS process used to create the raster.
Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
A formal accuracy assessment of the horizontal positional information in the data set has not been conducted.
A formal accuracy assessment of the vertical positional information in the data set has either not been conducted, or is not applicable.
U.S. Geological Survey
20170111
Shakemap ushaywiredm7.05_se X,Y,Z text grid file
Raster Digital Data Set
Reston, VA
U.S. Geological Survey
https://earthquake.usgs.gov/scenarios/eventpage/ushaywiredm7.05_se#shakemap
Digital and/or Hardcopy Resources
20180418
publication date
PGA shaking data
Source information used in support of the development of the data set.
Holzer, T.L., Noce, T.E., and Bennett, M.J.
2008
Liquefaction hazard maps for three earthquake scenarios for the communities of San Jose, Campbell, Cupertino, Los Altos, Los Gatos, Milpitas, Mountain View, Palo Alto, Santa Clara, Saratoga, and Sunnyvale, Northern Santa Clara County, California
Publication (Journal Article)
Reston, VA
U.S. Geological Survey
https://pubs.usgs.gov/of/2008/1270/
Digital and/or Hardcopy Resources
2008
publication date
Holzer and others, 2008
Source information used in support of the development of the data set.
Holzer, T.L., Noce, T.E., and Bennett, M.J.
2010
Predicted liquefaction in the greater Oakland area and northern Santa Clara Valley during a repeat of the 1868 Hayward Fault (M 6.7-7.0) earthquake
Publication (Journal Article)
Sacramento, CA
Proceedings of the Third Conference on Earthquake Hazards in the Eastern San Francisco Bay Area
https://pubs.er.usgs.gov/publication/70041523
Digital and/or Hardcopy Resources
2010
publication date
Holzer and others, 2010
Source information used in support of the development of the data set.
Holzer, T.L., Noce, T.E., and Bennett, M.J.
20110201
Liquefaction probability curves for surficial geologic deposits
Publication (Journal Article)
Denver, CO
Environmental and Engineering Geoscience
https://pubs.er.usgs.gov/publication/70041657
Digital and/or Hardcopy Resources
2011
publication date
Holzer and others, 2011
Source information used in support of the development of the data set.
Witter, R.C., Knudsen, K.L., Sowers, J.M., Wentworth, C.M., Koehler, R.D., and Randolph, C.E.
2006
Maps of Quaternary Deposits and Liquefaction Susceptibility in the Central San Francisco Bay Region, California
Vector Digital Data Set
Reston, VA
U.S. Geological Survey
https://pubs.usgs.gov/of/2006/1037/
Digital and/or Hardcopy Resources
2006
publication date
Surficial geology units for liquefaction modeling estimates
Source information used in support of the development of the data set.
McCrink, T.
2014
Depth to groundwater contours for Alameda and Santa Clara counties, San Francisco Bay area, California
Vector Digital Data Set
Sacramento, CA
California Geological Survey
Digital and/or Hardcopy Resources
2014
publication date
Groundwater contours used to identify liquefaction potential in Santa Clara County, CA.
Source information used in support of the development of the data set.
Knudsen, K.L., Sowers, J.M., Witter, R.C., Wentworth, C.M., and Helley, E.J.
2000
Preliminary maps of Quaternary deposits and liquefaction susceptibility, nine-county San Francisco Bay region, California—a digital database
Vector Digital Data Set
Reston, VA
U.S. Geological Survey
http://pubs.usgs.gov/of/2000/of00-444/
Digital and/or Hardcopy Resources
1838
1999
observed
Knudsen and others, 2000
Source information used in support of the development of the data set.
1) Assign surficial geology types in study area to one of three liquefaction classes: low, high, or not assessed.
Using a combination of expert input and liquefaction class assignments as completed by Holzer and others (2008, 2010), the surficial geology types in the western Alameda and Santa Clara Valley areas were assigned to the appropriate liquefaction class. Selection was completed using ESRI ArcMap 10.3.1.
2016
2) Create a regular grid of points spaced 50 meters apart for the entire study area.
Using ESRI ArcMap 10.3.1, a fishnet with each point spaced 50 meters from the surrounding points was generated. 50 meters was used for the grid spacing in order to be consistent with the earlier work that established the methodology (Holzer and others, 2008, 2010). Any points not co-located spatially with a surficial geology type from the Witter and others (2006) data and the study area extent were removed in order to reduce processing time. Points located on inland waterbodies were not removed, but points located on the San Francisco Bay were.
2016
3) Determine for each point what the surface geology unit is, then assign the corresponding liquefaction probability constants.
Using a spatial join in ArcMap 10.3.1, the details of the surface geology were assigned to each remaining point in the fishnet. A set of three constants (available in Holzer and others, 2011) was assigned to each point based on the following: the region in which the point was located (western Oakland or Santa Clara Valley), the groundwater depth at the point's location (above 10 feet or below 10 feet; below 10 feet only applies in Santa Clara Valley), and the surface geology type at the point's location (please refer to associated publication for details on the specific surface geology types assigned to different sets of liquefaction probability constants).
2016
4) Determine for each point what the PGA value is.
Using raster tools in ArcMap 10.3.1, each point was assigned a PGA value (values in g, acceleration due to gravity). The PGA data used for this assessment are available as a USGS scenario ShakeMap from https://earthquake.usgs.gov/scenarios/eventpage/ushaywiredm7.05_se#shakemap. The PGA data (which are at an initial spatial resolution of one minute, or approximately 1.6 square kilometers) were downscaled to 50-meter resolution prior to extracting so as to be consistent with the fishnet spacing. Downscaling was done by converting the existing PGA raster to point (each point is the centroid of a pixel in the raster) and then using the new point file as an input to create a finer-resolution raster. Nearest neighbor interpolation was used to create the new downscaled raster in order to prevent the minimum and maximum values in the original raster from changing in the new output raster.
Please note that because our analysis makes use of a relatively fine 50-m grid, and the original ShakeMap PGA values are a much coarser grid, we interpolated between the provided PGA values. Use of shaking maps generated by other Hayward Fault earthquake scenarios would likely result in a different depiction of liquefaction hazard; for example, shaking in San Francisco might be greater for other scenario earthquakes.
2016
5) Calculate the liquefaction probability for each point based on its PGA value and liquefaction probability constants.
In Holzer and others (2008, 2010, 2011), a formula was provided to calculate the liquefaction potential for a point. The following steps were used to calculate the liquefaction potential in ArcMap 10.3.1: (1) divide the PGA value for the location by the earthquake event's MSF value (in this case, the value is 1.17 for an earthquake of moment magnitude 7.05); (2) divide the result of step 1 by the second liquefaction constant; (3) raise the result to the power of the third liquefaction constant and add one to the result; (4) divide the first liquefaction constant by the result of step 3. The final liquefaction probability values will not exceed 1.
An example using PGA of 0.82, MSF of 1.17, first liquefaction constant of 0.7826, second liquefaction constant of 0.2315, and third liquefaction constant of -4.6645 follows:
(1) 0.82000/1.17000 = 0.70085
(2) 0.70085/0.23150 = 3.02743
(3) 1+(3.02743^-4.6645) = 1.00570
(4) 0.78260/1.00570 = 0.77816
2016
6) Convert the point grid into a raster using the final liquefaction probability value to produce the final liquefaction probability raster.
The final point dataset, with the newly-calculated liquefaction potential values, was processed using the raster tools in ArcMap 10.3.1 to convert the points to a raster. Inverse distance weighted interpolation was used to convert the data to raster; due to the raster resolution matching the final raster output cell size, the minimum and maximum values were not modified as a result of the interpolation method.
2016
Raster
Grid Cell
1453
1057
1
Universal Transverse Mercator
10
0.9996
-123.0
0.0
500000.0
0.0
row and column
50.0
50.0
Meter
D_North_American_1983
GRS_1980
6378137.0
298.257222101
Attribute Table
Table containing attribute information associated with the data set.
Producer defined
Value
Probability of liquefaction potential index exceeding 5. This corresponds to the likelihood that liquefaction will occur as a result of shaking caused by the HayWired earthquake scenario mainshock.
Producer defined
0
0.78145951032639
The entity and attribute information provided here describes the tabular data associated with the data set. Please review the detailed descriptions that are provided (the individual attribute descriptions) for information on the values that appear as fields/table entries of the data set.
The entity and attribute information was generated by the individual and/or agency identified as the originator of the data set. Please review the rest of the metadata record for additional details and information.
U.S. Geological Survey - ScienceBase
mailing address
Denver Federal Center, Building 810, Mail Stop 302
Denver
CO
80225
1-888-275-8747
sciencebase@usgs.gov
This dataset has been approved for release and publication by the U.S. Geological Survey (USGS). Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and/or contained herein.
Raster Digital Data Set
https://doi.org/10.5066/F74X5610
None. Please check sources, scale, accuracy, currentness and other available information. Please confirm that you are using the most recent copy of both data and metadata. Acknowledgement of the USGS would be appreciated.
20200818
Jamie L Jones
U.S. Geological Survey, PACIFIC REGION
Geographer
mailing address
Mail Stop 531, 345 Middlefield Road
Menlo Park
CA
94025
650-329-4125
650-329-4722
jamiejones@usgs.gov
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998