Emergence of patterns in the geologic record and what those patterns can tell us about Earth surface processes Rina Schumer Rina Schumer Desert Research Institute, Reno NV, USA Desert Research Institute, Reno NV, USA Hydrologic Synthesis Reverse Site Visit – August 20, 2009
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Emergence of patterns in the geologic record and what those patterns can tell us about Earth surface processes Rina Schumer Desert Research Institute,
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Emergence of patterns in the geologic recordand what those patterns can tell us about Earth surface processes
Rina SchumerRina Schumer
Desert Research Institute, Reno NV, USADesert Research Institute, Reno NV, USA
Hydrologic Synthesis Reverse Site Visit – August 20, 2009
Stochastic Transport and Emergent Scaling in Earth-Surface Processes (STRESS)
Hydrosphere/ Biosphere
Water Cycle
Dynamics
Hillslopes
How can we improve predictability?
Transport of water/sediment/biota over heterogeneous surfaces
Synthesis subgroup #5
Synthesis (Carpenter et al., 2009 - BioScience)
Sustained, intense interaction among individuals with ready access to data:
•mine existing data from new perspectives that allow novel analyses
•develop and use new analytical/computation/modeling tools that may lead to greater insights
•bring theoreticians, empiricists, modelers, practitioners together to formulate new approaches to existing questions
•integrate science with education and real-world problems
solute transport in groundwater flow systems
1990’s
solute transport in
streams~2000
STRESSworking group
2007-2009
flow through heterogeneous
hillslopes
bedform deformation
gravel transport
slope-dependent soil
transport
non-local transport on
hillslopes
sediment transport in
sand bed rivers
sediment accumulation
rates
landslide geometry and debris
mobilization
hillslope evolution
depositional fluvial profiles
transport on river networks
Timeline showing use of heavy-tailed stochastic
processes in modeling Earth surface systems
Results of Synthesis“acceleration of innovation”
Introduction
•Geology records the “noisiness" of sediment transport, as seen in wide range of sizes of sedimentary bodies
intermittency at many scales
•Describe nature and pace of landscape evolution by separating random transport from forcing mechanisms (glacial cycles,tectonics,etc)
•Need to estimate deposition rate
Modified from Sadler 1999
hiatus
Influence of transport fluctuations on stratigraphy
thickness
time intervalobsR
1( )S t
2( )S t
“Sadler Effect”
accumulation rate = thickness/time
1,000 yr. hiatus
1,000 yr. hiatus
50 yr. hiatus2,000 yr. hiatus
40,000 yr. hiatus
1,000 yr. hiatus10 yr. hiatus
1,000 yr. hiatus
500 yr. hiatus
100 yr. hiatus
-3/4
0
1
2
3
4
5
6
7
-1
-2
-3
-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8
LOG (Time interval, t ) [yr]
LO
G (A
cc
um
ula
tion
rate
) [m
m/y
r]
-1/5
ShorelineShelfDeltaContinental RiseAbyssal Plain
measured deposition rate depends on measurement interval
0
1
2
3
4
5
6
7
-1
-2
-3
-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8
LOG (Time interval, t ) [yr]
LO
G (A
cc
um
ula
tion
rate
) [m
m/y
r]
-3/4
accumulation rate = thickness/time
1,000 yr. hiatus
1,000 yr. hiatus
50 yr. hiatus2,000 yr. hiatus
40,000 yr. hiatus
1,000 yr. hiatus10 yr. hiatus
1,000 yr. hiatus
500 yr. hiatus
100 yr. hiatus
-1/5
ShorelineShelfDeltaContinental RiseAbyssal Plain
“Sadler Effect” measured deposition rate depends on measurement interval
0
1
2
3
4
5
6
7
-1
-2
-3
-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8
LOG (Time interval, t ) [yr]
LO
G (A
cc
um
ula
tion
rate
) [m
m/y
r]
-3/4
accumulation rate = thickness/time
1,000 yr. hiatus
1,000 yr. hiatus
50 yr. hiatus2,000 yr. hiatus
40,000 yr. hiatus
1,000 yr. hiatus10 yr. hiatus
1,000 yr. hiatus
500 yr. hiatus
100 yr. hiatus
-1/5
ShorelineShelfDeltaContinental RiseAbyssal Plain
“Sadler Effect” measured deposition rate depends on measurement interval
0
1
2
3
4
5
6
7
-1
-2
-3
-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8
LOG (Time interval, t ) [yr]
LO
G (A
cc
um
ula
tion
rate
) [m
m/y
r]
-3/4
accumulation rate = thickness/time
1,000 yr. hiatus
1,000 yr. hiatus
50 yr. hiatus2,000 yr. hiatus
40,000 yr. hiatus
1,000 yr. hiatus10 yr. hiatus
1,000 yr. hiatus
500 yr. hiatus
100 yr. hiatus
>350 references to Sadler(1981) !
-1/5
ShorelineShelfDeltaContinental RiseAbyssal Plain
“Sadler Effect” measured deposition rate depends on measurement interval
“Sadler Effect”
1. Strong correlation between sample age and measurement interval Young samples small interval Old samples long intervalsNo constant sampling intervals
2. Greater probability of encountering a long hiatus in a longer interval:
Eastern Alps volumetric erosion rates estimated from surrounding basin accumulation rates (adapted from
Kuhlemann et al. 2001)
Measurement bias or…..climate change?
Same patterns seen in rate measurements for
•subsidence•erosion•incision•evolution!
Synthesis (Carpenter, et al. BioScience)
Sustained, intense interaction among individuals with ready access to data:
mine existing data from new perspectives that allow novel analyses
develop and use new analytical/computation/modeling tools that may lead to greater insights
bring theoreticians, empiricists, modelers, practitioners together to formulate new approaches to existing questions
integrate science with education and real-world problems
References
Hay, W.W., J.L. Sloan, and C.N. Wold (1988). Mass/Age distribution and composition of sediments on the ocean floor and the global rate of sediment subduction. J. Geophys. Res., 93(B12), 14933-14940.
Molnar, P. (2004) Late Cenozoic increase in accumulation rates of terrestrial sediment: How might climate change have affected erosion rates?, Annual Review of Earth and Planetary Sciences, 32, 67-89.
Pelletier, J.D. (2007) Cantor set model of eolian dust deposits on desert alluvial fan terraces, Geology, 35, 439-442.
Plotnick, R.E. (1986) A fractal model for the distribution of stratigraphic hiatuses, J. Geology, 94(6), 885-890.
Sadler, P.M. (1981) Sediment accumulation rates and the completeness of stratigraphic sections, J. Geology, 89(5), 569-584.
Sadler, P.M. (1999) The influence of hiatuses on sediment accumulation rates, GeoRes. Forum, 5, 15-40.