Group A, Poster #071, Earthquake Geology
Comparison of mapped fault locations based on geomorphic mapping from remote-sensing datasets
Poster Image:
Poster Presentation
2023 SCEC Annual Meeting, Poster #071, SCEC Contribution #13215 VIEW PDF
natural model is impacted by their experience and people with similar experiences can interpret areas differently.
To evaluate the effect of epistemic uncertainty on mapped active fault trace locations, 23 mappers of varying experience levels produced fault maps from pre-rupture topography and imagery. Mappers include 4 undergraduate students, 11 graduate students, 2 postdocs, and 3 mid- and 3 senior-level professional consulting geologists. They used a systematic approach to map faults based on geomorphology.
We compared the pre-rupture fault maps to published coseismic ruptures. We evaluated the 1) percentage of coseismic ruptures predicted by the mapped faults, 2) percentage of the mapped faults that ruptured, 3) distribution of the mapped faults around coseismic ruptures, and 4) impact of data type and a geologic map. We found surprisingly small improvement by experience level in the portion of ruptures predicted and mapped faults that ruptured. Less experienced mappers misinterpreted geomorphology and mapped incorrect faults. No participant group outperformed the others except for one mapping area where consultants were better. For rupture locations near geomorphic features, we found that consultants best predicted the rupture location and the undergraduate students mapped with the highest error.
Mappers of all experience levels were most successful with the high-resolution topography. Aerial imagery was of little use in areas with high vegetation and anthropogenic activity. Adding a geologic map did not result in better maps.
Our analyses demonstrate that fault mapping is a challenging endeavor, regardless of expertise. Epistemic uncertainty must be accounted for when creating and applying active fault maps, especially for surface rupture hazard assessments.
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To evaluate the effect of epistemic uncertainty on mapped active fault trace locations, 23 mappers of varying experience levels produced fault maps from pre-rupture topography and imagery. Mappers include 4 undergraduate students, 11 graduate students, 2 postdocs, and 3 mid- and 3 senior-level professional consulting geologists. They used a systematic approach to map faults based on geomorphology.
We compared the pre-rupture fault maps to published coseismic ruptures. We evaluated the 1) percentage of coseismic ruptures predicted by the mapped faults, 2) percentage of the mapped faults that ruptured, 3) distribution of the mapped faults around coseismic ruptures, and 4) impact of data type and a geologic map. We found surprisingly small improvement by experience level in the portion of ruptures predicted and mapped faults that ruptured. Less experienced mappers misinterpreted geomorphology and mapped incorrect faults. No participant group outperformed the others except for one mapping area where consultants were better. For rupture locations near geomorphic features, we found that consultants best predicted the rupture location and the undergraduate students mapped with the highest error.
Mappers of all experience levels were most successful with the high-resolution topography. Aerial imagery was of little use in areas with high vegetation and anthropogenic activity. Adding a geologic map did not result in better maps.
Our analyses demonstrate that fault mapping is a challenging endeavor, regardless of expertise. Epistemic uncertainty must be accounted for when creating and applying active fault maps, especially for surface rupture hazard assessments.
SHOW MORE
Citation: Zuckerman, M. G., Scott, C. P., Arrowsmith, R., Adam, R. N., Madugo, C. M., Koehler, R. D., & Kottke, A. R. (2023, 09). Comparison of mapped fault locations based on geomorphic mapping from remote-sensing datasets. Poster Presentation at 2023 SCEC Annual Meeting.
Keywords: tectonic geomorphology, fault mapping
Relevant SCEC Themes:
Risk to Distributed Infrastructure
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