TY - JOUR
T1 - Identifying autogenic sedimentation in fluvial-deltaic stratigraphy
T2 - Evaluating the effect of outcrop-quality data on the compensation statistic
AU - Trampush, S. M.
AU - Hajek, E. A.
AU - Straub, K. M.
AU - Chamberlin, E. P.
N1 - Funding Information:
This work was in part supported by NSF grant EAR-1024710 to Hajek and NSF grant EAR-1024443 to Straub. Additional grants to Trampush include AAPG Grants-in-Aid, Harold J. Funkhouser Memorial Grant (2014); Shell Research Facilitation Award (2014–2015); Chesapeake Energy Scholarship (2015); and Marathon Alumni Centennial Graduate Fellowship (2015/2016). We would like to thank Evan Greenberg and Rachel Seidner for their assistance in the field while collecting the Sego and Ferron Sandstone data sets. We would also like to thank Vamsi Ganti, Janok Bhattacharya, and Gary Hampson for their thoughtful reviews. Data for the experiment TD-1-1 can be found at https://sen.ncsa.illinois.edu/acr/#collection?uri=tag:cet.ncsa.uiuc.edu, 2008:/bean/Collection/5A2390DB-5C8E-4393-BEE1-C7C3D2DEF644. Stratigraphic and terrestrial lidar data for the case studies can be found at https://scholarsphere.psu.edu/collections/5999n353w for the Ferris Formation, https://scholarsphere.psu.edu/collections/7s75dc52b for the lower Williams Fork Formation, https://scholarsphere.psu.edu/collections/xk81jk48h for the lower Sego Sandstone, and https://scholarsphere.psu.edu/collections/x346d576t for the upper Ferron Sandstone. Details of our analyses can be found in the supporting information. Code we used to calculate CV and bin CV values can be found at https://scholarsphere.psu.edu/collections/bn999687g.
Publisher Copyright:
©2016. American Geophysical Union. All Rights Reserved.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Stratigraphy preserves an extensive record of Earth-surface dynamics acting over a range of scales in a variety of environments. To take advantage of this record, we first must distinguish depositional patterns that arise due to intrinsic (i.e., autogenic) landscape dynamics from sedimentation that results from changes in climate, tectonic, or eustatic boundary conditions. The compensation statistic is a quantitative tool that has been used to estimate scales and patterns of autogenic sedimentation in experimental deposits; it has been applied to a few outcrop studies, but its sensitivity to data limitations common in natural deposits remains unconstrained. To explore how the compensation statistic may be applied to outcrop data, we evaluate the sensitivity of the tool to stratigraphic data sets limited in extent and resolution by subsampling an autogenic experimental deposit to create pseudo-outcrop-scale data sets. Results show that for data sets more than 3 times thicker than a characteristic depositional element (e.g., channel or lobe), the compensation statistics that can be used reliably constrain the maximum scale of autogenic sedimentation even for low-resolution data sets. Additionally, we show that autogenic sedimentation patterns may be characterized as persistent, random, or compensational using the compensation statistic when data sets are high resolution. We demonstrate how these measurements can be applied to natural data sets with comparative case studies of two fluvial and two deltaic outcrops. These case studies show how the compensation statistic can provide insight into what controls the maximum scale of autogenic sedimentation in different systems and how landscape dynamics can produce organized sedimentation patterns over long time scales.
AB - Stratigraphy preserves an extensive record of Earth-surface dynamics acting over a range of scales in a variety of environments. To take advantage of this record, we first must distinguish depositional patterns that arise due to intrinsic (i.e., autogenic) landscape dynamics from sedimentation that results from changes in climate, tectonic, or eustatic boundary conditions. The compensation statistic is a quantitative tool that has been used to estimate scales and patterns of autogenic sedimentation in experimental deposits; it has been applied to a few outcrop studies, but its sensitivity to data limitations common in natural deposits remains unconstrained. To explore how the compensation statistic may be applied to outcrop data, we evaluate the sensitivity of the tool to stratigraphic data sets limited in extent and resolution by subsampling an autogenic experimental deposit to create pseudo-outcrop-scale data sets. Results show that for data sets more than 3 times thicker than a characteristic depositional element (e.g., channel or lobe), the compensation statistics that can be used reliably constrain the maximum scale of autogenic sedimentation even for low-resolution data sets. Additionally, we show that autogenic sedimentation patterns may be characterized as persistent, random, or compensational using the compensation statistic when data sets are high resolution. We demonstrate how these measurements can be applied to natural data sets with comparative case studies of two fluvial and two deltaic outcrops. These case studies show how the compensation statistic can provide insight into what controls the maximum scale of autogenic sedimentation in different systems and how landscape dynamics can produce organized sedimentation patterns over long time scales.
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U2 - 10.1002/2016JF004067
DO - 10.1002/2016JF004067
M3 - Article
AN - SCOPUS:85013073524
VL - 122
SP - 91
EP - 113
JO - Journal of Geophysical Research: Earth Surface
JF - Journal of Geophysical Research: Earth Surface
SN - 2169-9003
IS - 1
ER -