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GEOMORPHOLOGY
Experimental evidence for hillslope
control of landscape scale
K. E. Sweeney,
1
*J. J. Roering,
1
C. Ellis
2
Landscape evolution theory suggests that climate sets the scale of landscape
dissection by modulating the competition between diffusive processes that sculpt
convex hillslopes and advective processes that carve concave valleys. However, the link
between the relative dominance of hillslope and valley transport processes and
landscape scale is difficult to demonstrate in natural landscapes due to the episodic
nature of erosion. Here, we report results from laboratory experiments combining
diffusive and advective processes in an eroding landscape. We demonstrate that
rainsplash-driven disturbances in our experiments are a robust proxy for hillslope
transport, such that increasing hillslope transport efficiency decreases drainage
density. Our experimental results demonstrate how the coupling of climate-driven
hillslope- and valley-forming processes, such as bioturbation and runoff, dictates the
scale of eroding landscapes.
Convex hillslopes and concave valleys are
ubiquitous in eroding, soil-mantled land-
scapes (1–3) (Fig. 1, A and B). These dis-
tinct landforms are produced by equally
distinct sediment transport processes: On
hillslopes, abiotic (4,5)andbiotic(6,7)distur-
banceagentsdispersesedimentdownslope,where-
as in valleys, sediment is transported by debris
flows (8)orflowingwater(9). The transition be-
tween hillslopes and valleys has long been con-
sidered a fundamental landscape scale (3,10,11),
but there is debate over what controls its style
and position. Numerical results suggest that the
hillslope-valley transition may be dictated by the
minimum runoff necessary for sediment detach-
ment or landslide initiation (11–13)orbythecom-
petition between diffusive transport on hillslopes
and advective transport in channels (14,15).
These geomorphic models predict expansion
or contraction of the valley network from changes
in climatic variables such as precipitation and
vegetation (3,12,16). Hence, rigorous testing of
controls on the hillslope-valley transition is cen-
tral to our understanding of landscape response
to environmental perturbations. Due to the slow
and episodic nature of erosion, however, field
tests are limited to comparisons of steady-state
model predictions with natural topography [e.g.,
(2)]. Such approaches rely on the assumption that
topography reflects long-term average fluxes, ig-
noring the potentially important effects of initial
conditions (17)andtemporallagsbetweenland-
scape response and climatic and tectonic forcing
(18,19).
We conducted a series of laboratory experi-
ments to determine whether the competition
between hillslope transport and valley incision
sets the spatial scale of landscapes (15). The
theoretical underpinnings of the process con-
trol on the hillslope-valley transition derive
from a statement of mass conservation, where
the rate of elevation change (dz/dt) is equal to
uplift rate (U), minus erosion due to disturbance-
driven hillslope diffusion and channel advection
by surface runoff
@z
@t¼UþDr2z−KðPAÞmSnð1Þ
where Dis hillslope diffusivity, Kis the stream
power constant, Ais drainage area, Sis slope, Pis
precipitation rate (assuming steady, uniform rain-
fall), and mand narepositiveconstants(9). In
this framework, the strength of hillslope transport
relative to channel processes can be quantified
by the landscape Péclet number (Pe), assuming
n=1(15)
Pe ¼KL2mþ1
Dð2Þ
where Lis a horizontal length scale and the
hillslope-valley transition occurs at the critical
length scale L
c
where Pe =1 (15). In plots of slope
versusdrainagearea,L
c
corresponds to a local
maximum separating convex hillslope and con-
cave valley topography (20)(Fig.1,DandE).If
this framework holds for field-scale and experi-
mental landscapes, increasing the vigor of hillslope
transport relative to valley incision (decreasing
Pe) should result in longer hillslopes (higher L
c
)
SCIENCE sciencemag.org 3JULY2015•VOL 349 ISSUE 6243 51
1
Department of Geological Sciences, University of Oregon,
1272 University of Oregon, Eugene, OR 97403-1272, USA.
2
St. Anthony Falls Laboratory and National Center for Earth-
Surface Dynamics, College of Science and Engineering,
University of Minnesota, 2 Third Avenue SE, Minneapolis, MN
55414-2125, USA.
*Corresponding author. E-mail: kristin.e.sweeney@gmail.com
Fig. 1. Characteristic morphology of eroding landscapes. Photographs of eroding landscapes.
(A) Painted Hills unit of John Day Fossil Beds National Monument, Oregon. (B) Gabilan Mesa, Cal-
ifornia. (C) Laboratory landscape from this study with no hillslope diffusion, and associated plots
of local slope versus drainage area, calculated with steepest descent algorithm (Dto F). Pictures
in (A) and (C) taken by the author (K.E.S.); (B) from Google Earth. Topographic data to generate
slope-area plots from (D) field surveys; (E) Lidar data from National Center for Airborne Laser
Mapping; and (F) this study. Gray vertical bars in (D) to (F) demarcate the inferred hillslope-valley
transition (34).
RESEARCH |REPORTS
on July 2, 2015www.sciencemag.orgDownloaded from on July 2, 2015www.sciencemag.orgDownloaded from on July 2, 2015www.sciencemag.orgDownloaded from
and a contraction of the valley network (i.e., a
decrease in drainage density).
Experimental landscapes bridge the gap in
complexity between numerical models and nat-
ural landscapes (21) by enabling us to control the
confounding influences of tectonics, climate, and
lithology and observe surface evolution through
time. As previously noted [e.g., (21)], a complete
dynamical scaling of erosional landscapes in the
laboratory is typically intractable due to shallow
water depths, large grain sizes relative to the
size of the experiment, and other considerations.
Nonetheless, past landscape experiments have
successfully demonstrated the topographic man-
ifestation of changing uplift rate (22,23), precipi-
tation rate (24), and precipitation patterns (25).
In these experiments, however, erosion was ex-
clusively driven by surface runoff (e.g., Fig. 1, C
and F), intentionally excluding the representa-
tion of diffusive hillslope processes (22)andhence
precluding tests for the role of hillslope transport
in setting landscape scale.
Following Eq. 1, we created an experimental
system that distilled landscape evolution into
three essential ingredients: base-level fall (uplift),
surface runoff (channel advection), and sediment
disturbance via rainsplash (hillslope diffusion)
(Fig. 2). Our experiments in the eXperimental
Landscape Model (XLM) at the St. Anthony Falls
Laboratory systematically varied the strength
of disturbance-driven transport relative to sur-
face runoff (changing Pe) for steady, uniform
uplift. The XLM consists of a 0.5 by 0.5 by 0.3 m
3
flume with two parallel sliding walls, each con-
nected to a voltage-controlled dc motor to sim-
ulaterelativeuplift(Fig.2A).Theexperimental
substrate was crystalline silica (median grain
size = 30 mm) mixed with 33% water to increase
cohesion and reduce infiltration (Fig. 2C). We
began each experiment by filling the XLM with
sediment and allowing it to settle for ~24 hours
to homogenize moisture content. Topographic
data at 0.5 mm vertical accuracy were collected
at regular time intervals on a 0.5 by 0.5 mm
grid using a laser scanner.
Sediment transport in our experiments was
driven by two distinct rainfall systems: the mister,
a rotating ring fitted with 42 misting nozzles, and
the drip box, a polyvinyl chloride constant head
tank fitted with 625 blunt needles of 0.3 mm in-
terior diameter arranged in a 2 by 2 cm grid
(Fig. 2B). The fine drops produced by the mister
lack sufficient energy to disturb sediment on im-
pact and instead result only in surface runoff. By
contrast, the 2.8 mm diameter drops from the
drip box are sufficiently energetic to create rain-
splash and craters on the experiment surface that
result in sediment transport. We used four fans
mounted on the corners of the experiment to
generate turbulence and randomize drop loca-
tion during drip box rainfall. Importantly, sed-
iment transport due to drip box rainfall consists
of both hillslope diffusion from the cumulative
effect of drop impacts and nonnegligible advec-
tive transport due to the subsequent runoff of the
drops. Thus, we expect that changing the relative
contribution of rainsplash results in a change in
both hillslope and channel transport efficiency
(Dand K, respectively).
We ran five experiments, varying the time of
drip box rainfall (i.e., predominantly diffusive
transport) from 0 to 100% of total experiment
runtime (Fig. 3 and table S1) (26)andholding
base-level fall and water flux from the mister
and the drip box constant. During the experi-
ment, we alternated between drip box rainfall and
mister rainfall over 10-min periods (table S1); the
fans used for drip box rainfall prevented simulta-
neous operation. We continued each experiment
until we reached flux steady state such that the
spatially averaged erosion rate was equal to the
rate of base-level fall (figs S1 and S2). Each ex-
periment ran for 10 to 15 hours, encompassing
60 to 90 intervals of drip box and/or mister
rainfall.
The steady-state topography of our experiments
(Fig. 3, A to F) demonstrates how increasing the
relative dominance of rainsplash disturbance af-
fects landscape morphology. Qualitatively, land-
scapes formed by a higher percentage of drip box
rainfall (Fig. 3E) appear smoother, with wider,
more broadly spaced valleys and extensive un-
channelized areas. In contrast, landscapes with
more surface runoff transport (Fig. 3A), equivalent
to past experimental landscapes (24,27), are
52 3JULY2015•VOL 349 ISSUE 6243 sciencemag.org SCIENCE
Fig. 2. Experimental setup. (A) Schematic profile of experimental apparatus (XLM). Line arrows show
direction of sediment movement. (B) Photograph of misting ring and drip box looking from below.
(C) Photograph of sediment surface during 100% drip run.
Fig. 3. Steady-state topography and hillslope
morphology. (Ato E) Hillshades of experimental
topography for (A) 0% drip, (B) 18% drip, (C) 33%
drip, (D) 66% drip, and (E) 100% drip overlain with
channel networks (blue) and locations of hillslope
profiles (red). Topography is 475.5 mm wide in plan-
view. (F) Elevation profiles of hillslopes marked by
red lines in (A) to (E). Vertical and horizontal length
scales are equal.
RESEARCH |REPORTS
densely dissected. As the relative percentage of
rainsplash increases, hillslope transects increase
in both length and topographic curvature (Fig.
3F), confirming that our experimental procedure
can be used to adjust hillslope transport efficiency.
Hillslope relief in our experiments is approxi-
mately 10 to 20% of total landscape relief, a sim-
ilar value to natural landscapes (28).
To test the expected relationship between
Péclet number and landscape scale (15)(Eq.2),
we used steady-state relationships between land-
scape morphology and sediment transport laws
to independently calculate Dand K. This ap-
proach is often not possible in natural landscapes
and thus extends our theoretical understanding
beyond the slope-area plots shown in Fig. 1, D to
F. Specifically, we used the approach of (28)to
calculate D, which uses average hillslope length
and gradient, thereby avoiding the stochastic
imprint of individual raindrop impacts that can
obscure local metrics of hillslope form, such as
curvature. The following relationship relates
mean hillslope gradient (S) to hillslope length
(L
h
), critical slope (S
c
), erosion rate (E, equal to
Uat steady state), and hillslope diffusivity (D)
S
Sc
¼1
E*ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1þðE*Þ2
q−
ln 1
21þffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1þðE*Þ2
q
−1ð3Þ
where E*=E(2L
h
/KS)(28). To calculate Kand
mforthestreampowermodel,weusedthepre-
diction of Eq. 1 that local steady-state channel slope
is a power-law function of drainage area (29):
S¼U
KPm
1
n
A
−m
=
nð4Þ
To quantify hillslope length and gradient, we
mapped the channel network by explicitly iden-
tifying channel forms (28–31) (fig. S3), then traced
hillslopes beginning at hilltop pixels by follow-
ing paths of steepest descent to the nearest chan-
nel (28) (fig. S3). We take S
c
to be sufficiently large
(table S1) that Eq. 3 approximates linear diffu-
sion. As the proportion of rainsplash transport
increases, Dcalculated from Eq. 3 also increases
(table S1), confirming that the morphologic trend
of individual hillslope transects (Fig. 3F) reflects
increasing hillslope transport efficiency.
To calculate the advective process parameters
(Eq. 4), we extracted slope and steepest-descent
drainage area data along networks defined by a
minimum drainage area of 250 mm
2
(larger than
the drainage area of channel initiation) and fit
power-law relationships to plots of slope versus
drainage area (29). Following (15,22), we assume
that n= 1 and use the intercept and slope of the
power-law fits to calculate mand Kfor each ex-
periment. Whereas mis relatively invariant for all
our experiments, Ktends to increase with the
fra ction of drip box transport, indicating that post-
impact rainfall runoff contributes to advective as
well as diffusive transport in our experiments.
Given that both Dand Kchange in our ex-
periments, we calculated Pe values (Eq. 2) for
each of our experiments to quantify how diffu-
sive and advective processes contribute to the
observed transition from smooth and weakly
channelized landscapes (100% drip box, Fig. 3A)
to highly dissected terrain (mist only, 0% drip
box, Fig. 3E). We calculated Pe for each exper-
iment (Eq. 2) by assuming that n= 1 and taking
the length scale Lto be the horizontal distance
fromthemaindividetotheoutlet(256mm).
Our results show that landscape Pe value increases
with the fraction of drip box transport, demon-
strating that an increase in hillslope transport
efficiency, D, is the dominant result of increasing
rainsplash frequency. Figure 4 reveals a positive
relationship between Pe and drainage density,
which is inversely related to hillslope length or
L
c
,suchthatincreasingPe in our experiments
results in higher drainage density (i.e., shorter
hillslopes). This finding is consistent with theo-
retical predictions for coupled hillslope-channel
process controls on the scale of landscape dis-
section (14,15).
In our experiments, hillslope transport im-
parts a first-order control on landscape scale,
emphasizing the need to establish functional
relationships between climate variables and
hillslope process rates and mechanisms for real
landscapes. Although climate change scenarios
typically focus on the influence of vegetation and
rainfall on overland flow and channel hydraulics
(3,12), climate controls on the vigor of hillslope
transport (e.g., 32,33) can drive changes in land-
scape form. Robust linkages between transport
processes and topography, as discussed here, are
an important component of interpreting plane-
tary surfaces as well as decoding paleolandscapes
and sedimentary deposits.
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ACKNO WLED GMEN TS
This work was supported by a National Science Foundation
grant (EAR 1252177) to J.J.R. and C.E. We thank D. Furbish and
A. Singh for fruitful discussions, S. Grieve and M. Hurst for
assistance with the calculation of hillslope metrics, and the
technical staff of St. Anthony Falls Laboratory for support during
experiments. All authors designed the experiments and wrote
the manuscript, C.E. built and troubleshot the experimental
apparatus, and K.E.S. conducted the experiments and analyzed
the data. Comments from two anonymous reviewers greatly
improved the manuscript. Topographic data are available from
the National Center for Earth Dynamics Data Repository at
https://repository.nced.umn.edu.
SUPPLEMENTARY MATERIALS
www.sciencemag.org/content/349/6243/51/suppl/DC1
Materials and Methods
Figs. S1 to S3
Table S1
References (35)
3 March 2015; accepted 26 May 2015
10.1126/science.aab0017
SCIENCE sciencemag.org 3JULY2015•VOL 349 ISSUE 6243 53
Fig. 4. Effect of landscape Péclet num-
ber on landscape scale. Landscape
Péclet number for each experiment (circle,
0% drip; square, 18% drip; diamond,
33% drip; triangle, 66% drip; plus sign,
100% drip) versus drainage density of
GeoNet-derived drainage networks.
RESEARCH |REPORTS
DOI: 10.1126/science.aab0017
, 51 (2015);349 Science et al.K. E. Sweeney
Experimental evidence for hillslope control of landscape scale
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