2.3. HAZ: Hazards

In this panel the user can define or simulate hazards over a region. The user can select the type of hazard, such as Earthquakes and Hurricanes, from the Hazard Selection combo box, as shown on the top of Fig. 2.3.1. As the user selects between the different hazard applications, the main panel will change to reflect the inputs for each application.


Fig. 2.3.1 Hazard input panel.

2.3.1. User-specified Ground Motions

The User-specified Ground Motion application loads the results of an Earthquake Scenario Simulation that was run previously. The User-specified Earthquakes application input pane is given in Fig. As seen in the figure, the user is required to input the file path to the EventGrid.csv file in the Event File Listing Motions Field. If the ground motions are not in the same folder as the EventGrid.csv file, then the user needs to input the directory path to the folder containing the ground motions. Users also need to specify the units of the ground motion field. Both ground shaking (See Example E1-E4) and ground failure (See Example E5 and E14) can be analyzed in the current version.


Fig. User-defined earthquakes input panel.

2.3.2. User-specified Hurricane

The User-specified Hurricane application works similar to the User-specified Ground Motion application. It loads the results of an Hurricane Scenario Simulation that was run previously. The User-specified Hurricane application input pane is similar to Fig. As seen in the figure, the user is required to input the file path to the EventGrid.csv file in the Event File Listing Hurricane Field. If the hurricane files are not in the same folder as the EventGrid.csv file, then the user needs to input the directory path to the folder containing the hurricane stations. Users also need to specify the units of the hurricane hazard input fields.

2.3.3. ShakeMap Earthquake Scenarios

The ShakeMap Earthquake Scenario application provides the functionality to import a USGS ShakeMap earthquake hazard. The ShakeMap Earthquake Scenario application input pane is given in Fig. As seen in the figure, the user is required to input a path to a folder on the user’s computer that contains the ShakeMap data. At a minimum, the folder must contain a grid.xml file (e.g., downloaded from this page) that provides the ground motion intensity measures, e.g., PGA, PGV, over a geographical grid. To visualize the PGA contours or rupture in the GIS window, a user can also provide the cont_pga.json file, or rupture.json file, respectively. Note that more than one ShakeMap can be input. However, the ShakeMap that is selected in the List of ShakeMaps tree in Fig., is the one that is employed in the subsequent analysis. The user also has the option to select the type of intensity measure they want from the ShakeMap grid.


Fig. ShakeMap input panel.

After a ShakeMap is loaded, it will appear in the list of ShakeMaps shown above in Fig. Users can see the grid, contours, etc., ShakeMap visuals by going to the VIZ pane, as highlighted in Fig. below.


Fig. ShakeMap visualization.


R2D will create one .csv file containing the ground motion intensity measures at each grid point in the grid.xml file. The files will be stored in a similar format as the ground motion files used in the User-specified Ground Motion application. As shown in Fig., the number of grid point is usually large (sometimes over 10 thousand). Although creating such a number of .csv files is fast in Unix-like operating systems, it may be particular slow (around 5 minutes for 10,000 grid points) on a Windows machine. As a result, consider trimming or subsampling the grid.xml file downloaded from USGS’s ShakeMap website, if fast computation is desired for testing or debugging purposes.

2.3.4. Raster Defined Hazard

The Raster Defined Hazard Widget allows for the import of raster files to represent hazard intensities. The Raster Defined Hazard Widget input pane is given in Fig.

  1. To load a raster file, click on the Browse button next to the input file box, and then select the raster file in the dialog that will appear.

  2. Next, select the event type in the Event Type Dropdown, shown in the Fig., e.g., Hurricane or Earthquake.

  3. You then need to specify the coordinate reference system (CRS) that was used to create the raster so that the raster will appear in the correct geographic location. Upon import, a default CRS will be assigned, which will be the CRS that is currently used by the main map.

  4. Depending on the number of bands in your raster, the equivalent number of Unit Selection Dropdowns will appear. For each raster band, you need to provide the corresponding units.


Fig. Raster hazard input pane.


When the Raster Defined Hazard Widget is employed in an analysis, for each asset, the raster will be sampled at the asset location to determine the hazard intensity level. A set of .csv files in the SimCenter event format (EventGrid.csv) will be created where each grid point corresponds to the location of an asset. As a result, the corresponding Mapping Application in HTA (Hazard to Asset Mapping) should be set to Site Specified.

2.3.5. Regional Site Response

Site response analysis is commonly performed to analyze the propagation of seismic wave through soil. As shown in Fig., one-dimensional response analyses, as a simplified method, assume that all boundaries are horizontal and that the response of a soil deposit is predominately caused by SH-waves propagating vertically from the underlying bedrock. Ground surface response is usually the major output from these analyses, together with profile plots such as peak horizontal acceleration along the soil profile. When liquefiable soils are presenting, maximum shear strain and excess pore pressure ratio plots are also important.


Fig. Schematic figure for site response analysis (courtesy of Pedro Arduino)

Regional Site Response consists of four major functionalities for site response analysis, each of which is encapsulated in a specific widget:


Fig. Graphic user interface of Regional Site Response

  1. Site information widget: three options for defining a set of sites for soil response analysis: (1) Single Location, (2) Grid of Locations, and (3) Scattering Locations. Users can manually define or select a rectangular grid on map using the Grid of Locations. In addition, users can upload a csv site file using the Scattering Locations. The minimum attributes are: Station ID column, Longitude and Latitude columns. Users can add extra columns for soil properties or modeling paramters; alternatively, users could use the Site Data tool widget to generate needed attributes.

  2. Site data toolbox widget: three Vs30 data sources are available: (1) Wills et al., 2015 ([Wills2015]), (2) Thompson et al., 2018 ([Thompson2018]), and (3) Heath et al., 2020 ([Heath2020]). There are two data sources of bedrock depth: (1) SoilGrid250 ([Hengl2017]) and (2) National Crustal Model ([Boyd2020]). Three soil model types will be available: (1) Elastic isotropic, (2) Multiaxial Cyclic plasticity, and (3) User. After selecting the desired data sources and model type, a new site information csv site file will be generated and loaded by clicking the Fetch Site Data button.

  3. Soil model widget: a soil modeling script is expected, which will be used to create numerical models from the site information csv and run simulations.

  4. Input motion widget: a EventGrid.csv csv file along with a directory including ground motion acceleration time history files are expected. Note that the units of the time history and scaling factor should also be provided by users.


Wills, C. J., Gutierrez, C. I., Perez, F. G., & Branum, D. M. (2015). A next generation VS 30 map for California based on geology and topography. Bulletin of the Seismological Society of America, 105(6), 3083-3091.


Thompson, E.M., 2018, An Updated Vs30 Map for California with Geologic and Topographic Constraints: U.S. Geological Survey data release.


Heath, D. C., Wald, D. J., Worden, C. B., Thompson, E. M., & Smoczyk, G. M. (2020). A global hybrid VS30 map with a topographic slope–based default and regional map insets. Earthquake Spectra, 36(3), 1570–1584.


Hengl T, Mendes de Jesus J, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, Blagotić A, et al. (2017) SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12(2): e0169748.


Boyd, O.S., 2020, Calibration of the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2020–1052, 23 p., https://doi.org/10.3133/ofr20201052.