Site Models#
This section is used to specify where the hazard will be computed. Two options are available:
The first option is to define a polygon (usually a rectangle) and a distance (in km) to be used to discretize the polygon area. The polygon is defined by a list of longitude-latitude tuples.
An example is provided below:
[geometry]
region = 10.0 43.0, 12.0 43.0, 12.0 46.0, 10.0 46.0
region_grid_spacing = 10.0
The second option allows the definition of a number of sites where the hazard will be computed. Each site is specified in terms of a longitude, latitude tuple. Optionally, if the user wants to consider the elevation of the sites, a value of depth [km] can also be specified, where positive values indicate below sea level, and negative values indicate above sea level (i.e. the topographic surface). If no value of depth is given for a site, it is assumed to be zero. An example is provided below:
[geometry]
sites = 10.0 43.0, 12.0 43.0, 12.0 46.0, 10.0 46.0
If the list of sites is too long the user can specify the name of a csv file as shown below:
[geometry]
sites_csv = <name_of_the_csv_file>
The format of the csv file containing the list of sites is a sequence of points (one per row) specified in terms of the longitude, latitude tuple. Depth values are again optional. An example is provided below:
179.0,90.0
178.0,89.0
177.0,88.0
The complete list of valid site parameters that can go into a site model .csv file are listed here. Currently, the work in documentation to describe this input parameters more explicitly, and to provide short descriptions of each valid site parameter and where they are needed is in progress:
# dtype of each valid site parameter
site_param_dt = {
'sids': numpy.uint32,
'site_id': numpy.uint32,
'lon': numpy.float64,
'lat': numpy.float64,
'depth': numpy.float64,
'vs30': numpy.float64,
'kappa0': numpy.float64,
'vs30measured': bool,
'z1pt0': numpy.float64,
'z2pt5': numpy.float64,
'siteclass': (numpy.string_, 1),
'geohash': (numpy.string_, 6),
'z1pt4': numpy.float64,
'backarc': numpy.uint8, # 0=forearc,1=backarc,2=alongarc
'xvf': numpy.float64,
'soiltype': numpy.uint32,
'bas': bool,
# Parameters for site amplification
'ampcode': ampcode_dt,
'ec8': (numpy.string_, 1),
'ec8_p18': (numpy.string_, 2),
'h800': numpy.float64,
'geology': (numpy.string_, 20),
'amplfactor': numpy.float64,
'ch_ampl03': numpy.float64,
'ch_ampl06': numpy.float64,
'ch_phis2s03': numpy.float64,
'ch_phis2s06': numpy.float64,
'ch_phiss03': numpy.float64,
'ch_phiss06': numpy.float64,
'fpeak': numpy.float64,
# Fundamental period and and amplitude of HVRSR spectra
'THV': numpy.float64,
'PHV': numpy.float64,
# parameters for secondary perils
'friction_mid': numpy.float64,
'cohesion_mid': numpy.float64,
'saturation': numpy.float64,
'dry_density': numpy.float64,
'Fs': numpy.float64,
'crit_accel': numpy.float64,
'unit': (numpy.string_, 5),
'liq_susc_cat': (numpy.string_, 2),
'dw': numpy.float64,
'yield_acceleration': numpy.float64,
'slope': numpy.float64,
'relief': numpy.float64,
'gwd': numpy.float64,
'cti': numpy.float64,
'dc': numpy.float64,
'dr': numpy.float64,
'dwb': numpy.float64,
'zwb': numpy.float64,
'tri': numpy.float64,
'hwater': numpy.float64,
'precip': numpy.float64,
# parameters for YoudEtAl2002
'freeface_ratio': numpy.float64,
'T_15': numpy.float64,
'D50_15': numpy.float64,
'F_15': numpy.float64,
'T_eq': numpy.float64,
# other parameters
'custom_site_id': (numpy.string_, 8),
'region': numpy.uint32,
'in_cshm': bool # used in mcverry
}
The custom_site_id
#
Since engine v3.13, it is possible to assign 6-character ASCII strings as unique identifiers for the sites (8-characters
since engine v3.15). This can be convenient in various situations, especially when splitting a calculation in geographic
regions. The way to enable it is to add a field called custom_site_id
to the site model file, which must be unique
for each site.
The hazard curve and ground motion field exporters have been modified to export the custom_site_id
instead of the
site_id
(if present).
We used this feature to split the ESHM20 model in two parts (Northern Europe and Southern Europe). Then creating the
full hazard map was as trivial as joining the generated CSV files. Without the custom_site_id
the site IDs would
overlap, thus making impossible to join the outputs.
A geohash string (see https://en.wikipedia.org/wiki/Geohash) makes a good custom_site_id
since it can enable the
unique identification of all potential sites across the globe.