The fault awareness areas show
areas where there may be a surface fault rupture hazard. Surface fault rupture
is the permanent breaking, ripping, buckling or warping of the ground on or
near the line where a fault meets the ground surface, as a result of movement
on the fault. It is different from earthquake shaking.
This dataset has been compiled
from individual district fault datasets and reports developed for Environment
Canterbury by GNS Science between 2009 and 2019: Kaikoura (2015, updated 2018),
Hurunui (2012), Waimakariri (2013, updated 2019), Selwyn (2013), Ashburton
(2009), Timaru (2017), Mackenzie (2010), Waimate (2017) and Waitaki (2017).
There is no dataset for Christchurch City as there are no known earthquake faults
at the ground surface in the Christchurch City or Banks Peninsula area.
This dataset has been created
as recommended in Barrell, et al, 2015, Guidelines for using regional-scale
earthquake fault information in Canterbury. GNS Science Consultancy Report
2014/211. A 125m or 250m buffer was placed around the mapped fault traces to
create this polygon dataset, depending on how certain the fault is, and how
well expressed it is at the ground surface. Definite (well expressed and
moderately expressed) fault and monocline records and likely (well expressed
and moderately expressed) fault and monocline records have a 125m buffer,
recognising that the mapped location of the fault is fairly well constrained
and is reasonably close the actual location. All other faults and monocline
records have a 250m buffer, recognising that the mapped location is not as well
constrained. See Barrell, et al, 2015 for a full description of the method used
to create this polygon dataset, and recommended actions for each type of area.
More detailed fault avoidance
zone mapping has been undertaken for several faults in Kaikoura, as well as the
Hanmer Fault (Hurunui District), Ashley Fault (Waimakariri District), Greendale
Fault (Selwyn District) and the Ostler Fault (Mackenzie District). These areas
have been clipped out of this dataset and the more detailed datasets should be
referred to in these areas.
