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Landscape evolution space and the relative importance of geomorphic processes and controls


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The concept of landscape evolution space (LES) is introduced as a tool for assessing landscapes and geomorphic systems, intended to be a systematic means for assessing the various factors that contribute to the potential for change in geomorphic systems. The LES conceptual model is based on the energy and mass available to drive and accommodate landscape evolution. An n-dimensional landscape evolution space is defined not only by spatial coordinates, but also by the availability of mass and energy. The LES is thus a space or hypervolume representing the resources available for geomorphic evolution and landscape change. An expression for LES is derived based on elevation, material density, surface area, and inputs of solar, meteoric, and biological energy and mass. Though primarily an heuristic device, the LES model can be used to address concrete problems. Two examples are given. In one, increased surface area due to topographic roughening and dissection of an incised plateau is found to only slightly offset erosional removals of mass in terms of the magnitude of the LES. In the other, sensitivity of coastal plain rivers to several impacts of sea level and climate change is explored. The LES model also leads to the concept of a geomorphological niche, representing the resources available to drive or support a specific process or suite of processes. Considerations of landscape evolution have traditionally focused on the interplay of endogenic vs. exogenic processes, uplift vs. denudation, or soil formation vs. erosion. The LES model explicitly broadens the conceptual framework of landscape evolution beyond the traditional dialectics.
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Landscape evolution space and the relative importance of geomorphic
processes and controls
Jonathan D. Phillips
Southern Landscape Systems Research Program, Department of Geography, University of Kentucky, Lexington, KY 40506-0027, USA
a b s t r a c ta r t i c l e i n f o
Article history:
Received 12 November 2008
Received in revised form 13 January 2009
Accepted 15 January 2009
Available online 27 January 2009
Landscape evolution space
Geomorphological niche
Geomorphic system
Cumberland Plateau
Climate change
The concept of landscape evolution space (LES) is introduced as a tool for assessing landscapes and geomorphic
systems, intended to be a systematic means for assessing the various factors that contribute to the potential for
change in geomorphic systems. The LES conceptual model is based on the energy and mass available to drive
and accommodate landscape evolution. An n-dimensional landscape evolution space is dened not only by
spatial coordinates, but also by the availability of mass and energy. The LES is thus a space or hypervolume
representing the resources available for geomorphic evolution and landscape change. An expression for LES is
derived based on elevation, material density, surface area, and inputs of solar, meteoric, and biological energy
and mass. Though primarily an heuristic device, the LES model can be used to address concrete problems. Two
examples are given. In one, increased surface area due to topographic roughening and dissection of an incised
plateau is found to only slightly offset erosional removals of mass in terms of the magnitude of the LES. In
the other, sensitivity of coastal plain rivers to several impacts of sea level and climate change is explored. The
LES model also leads to the concept of a geomorphological niche, representing the resources available to drive
or support a specic process or suite of processes. Considerations of landscape evolution have traditionally
focused on the interplay of endogenic vs. exogenic processes, uplift vs. denudation, or soil formation vs. erosion.
The LES model explicitly broadens the conceptual framework of landscape evolution beyond the traditional
© 2009 Elsevier B.V. All rights reserved.
1. Introduction
1.1. Landscape evolution space concept
The presence, intensity, and relative importance of geomorphic
processes and controls exhibit immense geographical variability,
associated with spatial variations in climate, tectonic setting, environ-
mental and geologic history, biological activity, human agency, and
other factors. Our perception and understanding of processes, controls,
and their relative impacts are inuenced not only by their intrinsic
real-world variability, but also by our ability to observe or measure
them, and by our conceptual frameworks and experiences. The
interpretation of layering in soils, sediments, and weathering proles,
for example, is inuenced not only by the features themselves, but
also by the training, background, and dominant paradigms of soil
science, sedimentology, archaeology, and geomorphology (Phillips
and Lorz, 2008).
In this paper the concept of landscape evolution space is introduced
as a tool for assessing landscapes and geomorphic systems. The
concept is intended to be a systematic means for assessing the various
factors that contribute to the potential for change in geomorphic
systems. Systematic application of the landscape evolution space
framework obliges consideration of all major types of energy and mass
inputs and resources, and provides a means to evaluate their relative
importance. This is important because background and experience
inuence perceptions (and thus analyses and interpretations) of, for
example, whether or not landscapes are geomorphically active. A
tectonically stable tropical plain, for instance, may appear relatively
inactive with respect to mechanical denudation and sediment
transfers, but may be extremely active with respect to chemical
weathering and bioturbation. Conversely, a cold high-altitude land-
scape may appear somewhat sterile to an earth scientist accustomed to
thick regoliths, rapid chemical weathering, and extensive bioturbation,
when in actuality sediment production by frost-shattering and mass
movements may be extensive.
In addition, some contemporary debates and controversies in
geomorphology are focused on the relative importance of particular
forcings or environmental controls. The role of biological processes vs.
abiotic factors is one example (e.g., Butler, 1995; Wilkinson and
Humphreys, 2005; Dietrich and Perron, 2006; Corenblit et al., 2008;
Phillips, 2009b). Another is the relative inuence of sea level,
tectonics, and climate on uvial systems (e.g., Blum and Tornqvist,
2000; Vandenberghe, 2002; Schumm, 2005; Blum and Aslan, 2006).
Further, conventional notions such as the primacy of sea level change
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in coastal sedimentary systems, the effectiveness of solar heating as a
weathering process, and limited chemical weathering in cold climates
are being challenged (e.g., Catuneanu, 2002; Dixon and Thorn, 2005;
McFadden et al., 2005; Turkington and Paradise, 2005; Yoshida et al.,
2007; Dixon et al., 2008; Moucha et al., 2008).
The landscape evolution space (LES) model is a tool for addressing
these issues, for comparing different sites and environments, and for
placing results and observations in a broader context. The LES
construct is an heuristic device rather than a mechanistic or predictive
model, but can be usefully applied to specic problems, as shown
below in two case studies. The LES conceptual model is also still
evolving, and is presented here in the hope that it can be expanded,
elaborated, and improved by others.
1.2. Energy and mass inputs and resources
The LES concept is based on the energy and mass available to drive
and accommodate landscape evolution. A global energy balance
approach to geomorphology was developed by Devlin (2003), and a
comprehensive survey of earth surface system energetics by Smil
(2008).Phillips (20 09b) compared biological energy inputs to
geological processes with those associated with uplift and potential-
to-kinetic energy conversions during denudation. The energetics of
soil formation was investigated by Volobuyev (1964, 1974),Rasmus-
sen et al. (2005), and Rasmussen and Taylor (2007). Together, these
papers suggest that the energy inputs to landscape evolution include
solar radiation, radiogenic heat from radioactive decay within the
earth, rotational energy, and gravity. Potential energy is stored as
landscape relief, as heat in the solid earth, and in the biosphere. Solar
energy also powers climatological and hydrological processes that
drive geomorphic change. The mass inputs are the rock mass within
the landscape, uplift of new rock mass into the unit of study, mass
uxes from other landscape units, meteoric inputs, and biomass.
The energy balance according to Devlin (2003) is
Ereceived =Elost +Estored =Esolar +Egeothermal +Erotational
! "
=Eradiated +Ereflected
ð Þ +ΔEhydrologic +Ebiota +Epotential +Eheat
! " ð1Þ
represents the solar inputs; E
is the radiogenic heat
from radioactive decay within the earth, and E
is rotational
energy. Energy is stored as relief (E
), biomass (E
) and heat
). The energy associated with atmospheric processes and the
hydrologic cycle is denoted by E
Devlin (2003) reduced Eq. (1) by assuming that E
is in steady-
state and not signicantly changing, and that E
is small relative
to potential and geothermal (endogenic) energy. The latter is
reasonable because the Coriolis effect inuences the direction and
distribution, but not the energy, of uid ows (Devlin also assumed
steady-state in biological energy storage, but that assumption is not
made here). The simplied balance is then
Esolar +Egeothermal
! " =Eradiated +Ereflected
ð Þ +Ehydrologic +Epotential +Ebiota
! "
Using Mto represent mass gains or losses above a given vertical
base or reference level, and with notation analogous to Devlin (2003),
a mass balance can be presented as
Mreceived =Mlost +Mstored =ΔMuplift +Mbaselevel +Mgeomorphic +Mhydrologic +Mbiota
! "
is the mass uplifted above (or subsided below) the reference
level by tectonic or isostatic processes; M
reects changes
associated with sea level or local base level movements; M
represents gains or losses due to mass uxes; M
is the
meteoric inputs or losses; and M
the net change in biomass.
These conceptual energy and mass balances provide the basis for
dening landscape evolution space.
2. Landscape evolution space
An n-dimensional landscape evolution space is dened not only by
spatial coordinates, but also by the availability of mass and energy as
described above. The LES is a space or hypervolume representing the
resources available for geomorphic evolution and landscape change.
The total geomorphic productivity G(dened as geomorphic work,
rate of mass ux, or some other appropriate measure) is a function of
the size of the LES and the rate (r) at which geomorphic processes
convert mass and energy per unit of LES:
G=r S ð4Þ
Sdenotes the size or extent of the LES. This paper emphasizes the
extent of the LES, though Eq. (4) will be revisited later.
To dene the LES, we start with a topographic evolution space
which is a function of the total mass of material above base level. This
is consistent with potential energy of mass transfers (PE) within a
dened geomorphic system,
PE =m g h ð5Þ
Where mis the mass, gthe gravity constant, and hthe height above
the system's base level. Total potential energy in a landscape is then
PE =HρA g H =H2ρA g ð6Þ
where His the mean elevation above base level, ρis mean density
of the rock and regolith, and Ais the surface area. Base level may be
sea level or the geoid, or some locally or regionally dened reference
level. Surface area is based on actual area exposed to solar and
meteoric inputs rather than a projected plane. Thus, for example, for a
geometric space with rectangular boundaries, area would be calcu-
lated based on mean length times mean width, with the later based on
actual slope distances (i.e., straight-line walking vs. as-the-crow-ies
Eq. (6) does not account for additional inputs of matter and energy,
such as insolation and precipitation. Tectonic forcings and base level
change can be presumed to be reected by H. Absent, or indepen-
dently of, biota, inputs of solar radiation energy and moisture are
related to the surface area, so that
LES =H2ρA g ksAkpA=H2ρg kskpA3ð7Þ
Where k
and k
are parameters reecting the prevailing climatic
inputs of solar energy and precipitation with dimensions of mass
divided by time squared (M T
Biota are capable of capturing and storing solar energy which would
otherwise be reectedor dissipatedas heat. Vernadsky (1926), generally
credited with the origin of the concept of the biosphere, viewed the
biosphere as a planetary membrane for capturing and processing solar
radiation energy. Organisms, particularly vegetation, may also serve
to maximize the rates of moisture and other biogeochemical cycling
(Eagleson, 2002; Lapenis, 2002). P
is dened as that portion of
biological productivity which provides a net energy supplement to
geomorphic processesaccounting for biological weathering and mass
transport, minus any effects (such as increases in surface resistance)
which reduce the rate of geomorphic change (see Phillips, 2009b). We
then obtain
LES =H2ρg kskpA3Pgð8Þ
Potential energy, the k
Aand k
Aterms, and P
all have dimensions
of M L
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One way to assess the relative importance of various factors
dening LES is via a simple ratio comparison. Using subscripts 1, 2 to
denote the observed, modeled, or hypothesized states of the land-
scape at any two times or under any two scenarios,
ð Þ2ρ2=ρ1
ð Þ ks2 =ks1
ð Þ kp2 =kp1
! " A2=A1
ð Þ3Pg2 =Pg1
! "
In many cases, where rock mass is large relative to regolith, (ρ
)1. Further, in some circumstances k
, and P
may also be
considered constant, providing other possibilities for simplifying Eq. (9).
Two example applications are given below.
3. Fluvial dissection, mass removal, and surface roughening
3.1. Study area
The dissection of landscapes by uvial action removes mass, and
thereby, other things being equal, reduces the LES. However, incision
of low-relief plateaus by uvial networks increases the roughness and
the surface area, the effect of which is to increase the size of the LES.
With xed horizontal boundaries, Acan be changed only by changes
in relief and surface roughness. The relative importance of mass
removal and increased surface area due to dissection was investigated
for a portion of the Cumberland Plateau in Kentucky and Tennessee.
The area was chosen due to other research in progress on the Big
South Fork River and its tributaries, a portion of the drainage basin of
which is in the study area (Fig. 1).
The Cumberland Plateau is the southern portion of the Alleghany
Plateau section of the Appalachians. Within the study area the geology
consists of horizontally-bedded Paleozoic sedimentary rocks, with
little or no evidence of tectonic deformation. Sandstones comprise
the ridgetops and most of the higher elevation units, with shales,
limestone, and coal beds occurring at lower elevations. No uplift or
other neotectonic activity has been proposed or demonstrated in the
area, and 1:24,000 scale geological maps of the area show no mapped
faults. The review of Wheeler and Crone (2001) of known and
suggested Quaternary faulting in the midcontinental U.S. west of the
Appalachians does not indicate any activity in the Cumberland Plateau
region of Kentucky and Tennessee. Thus any late Cenozoic uplift which
is occurring must be isostatically driven.
The Big South Fork (sometimes called the Big South Fork of the
Cumberland River) is a tributary of the Cumberland River, which
drains to the Ohio River. Streams of the study area began the most
Fig. 1. Shaded relief map of the study area in the Big South Fork area, Tennessee and Kentucky, showing the strongly dissected topography in the Cumberland Plateau region.
81J.D. Phillips / Geomorphology 109 (2009) 7985
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recent episode of incision about 1.5 Ma, in response to glacially-driven
reorganization of the Ohio River drainage system (Andrews, 2004;
Anthony and Granger, 2007). Topography is typical of a dissected
plateau, with topographically accordant ridgetops and peaks, and
deeply incised stream valleys with steep hillslopes.
3.2. Methods
Mass removal was calculated relative to the surface represented by
the current ridgelines and peaks. A digital elevation model (DEM)
with a horizontal resolution of 10 m was obtained from the U.S.
Geological Survey and a surface plot was produced. An imaginary
plane resting on top of the surface (imagine a at board supported by
the highest peaks and ridges; Fig. 2) was the reference surface for
calculating mean removal as the elevation difference between the
reference level and the actual terrain. Base level was taken as the
elevation of the Big South Fork as it exits the study area. Thus (in the
framework of Eq. (9)), H
is the elevation of the upper reference
surface minus base level elevation, and
H2=hHbaselevel ð10Þ
where his the local elevation. Any isostatic compensation for mass
removal should affect the entire approximately 920 km
study area
equally, and is thus not included in comparing the current surface to
the ridgetop reference plane.
Changes in surface area were calculated using a number of sample
transects across the study area, comparing the horizontal distance
) to the cumulative slope distance, D
(that is, as-the-crow-
ies distance compared to distance covered by walking the same
path). This comparison is based on an assumption of an initially
relatively smooth surface where D
. With A
taken to be an
original at surface and A
the current surface, change in surface area
was then estimated as
A1=A2=Dhoriz =Dslope ð11Þ
All DEM analyses were conducted using RiverTools
(Rivix, Inc.).
Soil thicknesses are minimal in the study area (generally b0.5 m
except in valley bottoms) and unknown for the pre-incision surface.
However, as they are in any case small compared to rock mass above
the local base level, it was assumed that ρ
1. Quaternary climate
changes indicate that k
, and P
have no doubt changed during the
plateau dissection. However, for purposes of isolating the relative
inuence of mass removal and topographic roughening (increase of A),
they are neglected in this example. Then, for this problem,
ð Þ2A2=A1
ð Þ3ð12Þ
3.3. Results
Minimum local base level elevation is about 220 masl, the mean
elevation of the slightly tilted upper reference surface is about 504 m,
and the mean elevation of the study area is about 410 m. Fluvial
dissection has removed a third of the mass above the local base
level, and H
=0.666. The surface area has increased by nearly 3%
=1.084, indicating that the increased surface area has
increased the landscape evolution space by about 8%. However, this is
more than offset by the decrease in H, which has decreased LES by
more than half [(H
=0.444]. Thus results in the study area
suggest that surface roughening and the associated increase in surface
area only slightly offsets the effects of mass removal with respect
to LES.
4. Sea level, climate, and coastal plain rivers
The relative importance of sea level and climate (as well as
tectonics, human agency, and other factors) in determining the forms
and process regimes of coastal plain rivers has long been a source of
controversy. The coastal plain of Texas is no exception. Notwithstand-
ing debates and uncertainties about the pace and timing of sea level
changes, and of Quaternary climate variations, several recent efforts
have been made to untangle the inuence of climate and sea-level on
observed features of alluvial valleys in the region (e.g., Morton et al.,
1996; Blum and Price,1998; Otvos, 2005; Blum and Aslan, 2006; Sylvia
and Galloway, 2006; Phillips and Slattery, 2008; Taha and Anderson,
2008; Phillips, 2009a).
Climate change, both in general and in southeast Texas, inuences
uvial systems chiey via the discharge regime and sediment supply,
both directly via precipitation, temperature, and the water balance,
and indirectly via vegetation. Climate is thus reected in the k
, and
components of the LES model.
The most obvious inuence of sea level is via H, as rising or falling
sea level directly increases or decreases mass above base level. On
low-relief coastal plains, sea level changes may also lead to signicant
inundation or exposure of land areas, thus changing the surface area
if interest is restricted to the subaerial landscape. This is not to deny
the signicance of submarine processes; an LES-based analysis of an
Fig. 2. Vertically-exaggerated surface plot of the study area shown in Fig. 1. The upper reference surface is an imaginary plane resting atop the high points, and mass removal and
surface roughness are calculated relative to the reference surface.
82 J.D. Phillips / Geomorphology 109 (2009) 7985
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estuarine and/or marine geomorphic system, could for example,
incorporate sea level rise in terms of increases in the geographic
boundaries of the LES.
4.1. Study area
For this illustration, characteristics of the Texas Coastal Plain in the
general vicinity of the lower Brazos River, southwest of Houston, are
used. The study area (Fig. 3) has a humid subtropical climate, and the
topography ranges from virtually at in the coastal marshes to gently
rolling. The case study is limited to the lower coastal plain, where
valleys are cut into late Quaternary material. Recent reviews of
debates about the Quaternary geologic framework and sea level
history of the region are provided by Blum et al. (2002),Rodriguez
et al. (2004), and Otvos (2005). More detailed information on the
lower Brazos River area is given by Sylvia and Galloway (2006),
Phillips (2007a, 2009a) and Taha and Anderson (2008).
4.2. Methods
The outer coastal plain in the lowermost Brazos River basin is
generally about 70 km wide, with a mean elevation of 6.2 m above sea
level. The mean coast-parallel slope gradient is about 0.0003. Thus,
per meter of coastline, there are about 434,400 m
above sea level.
These values were used to determine effects of sea level rise using a
simple bathtubmodel, which involves inundating existing topo-
graphy without accounting for morphological changes in response to
changing base levels. Estimates were made on a per-unit-length of
coastline basis, with the distance of retreat calculated as sea level rise
divided by mean coastal plain slope gradient. The loss of mass above
sea level is calculated from sea level rise over the width of the coastal
Potential changes in climate-related forcings were based on
scenarios of increased temperature, decreased precipitation, and
both decreased and increased biological productivity (with an
emphasis on increases) relative to 20th century norms in the lower
Brazos River area (mean annual precipitation of 1320 mm; mean
annual temperature 20.3 °C). It was assumed that changes in k
and k
are directly proportional to changes in temperature and precipitation,
respectively. Temperature increases of up to 6 °C and precipitation
decreases of as much as 600 mm were considered. P
was assumed
proportional to net primary productivity (NPP), which is inuenced
by temperature, moisture, and atmospheric CO
Fig. 3. Shaded topographic map of the coastal plain in the lower Brazos River area, Texas, derived from a digital elevation model with 30-m horizontal resolution.
Fig. 4. LES ratios associated with surface area (A
and mass above base level (H
for sea level rise up to 3 m.
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Climate and crop yield models predict temperature increases,
precipitation decreases, and slight decreases to larger increases in
crop yields (assumed related to NPP) for Texas. The NPP/crop yield
increases are due to longer growing seasons and fertilization/stimulus
effects of increased atmospheric CO
4.3. Results
The mass component of LES (decreased H) was more sensitive to
higher sea levels than area, with increasing disparities at larger values
of sea level rise (Fig. 4). The (A
term ranged from 0.986 (1.4%
decrease) with a sea level rise of 0.1 m to 0.63 (37% decrease) with a
rise of 3 m. The height above base level term (H
ranged from
0.968 (3.2% decrease) to 0.266 (74.4%) over the same span of sea level
rise values.
The solar input term (k
), based on temperature changes,
varied from a 1% rise (1.01) associated with a temperature increase of
0.2 °C to an increase of nearly 30% (1.296) with a 6 °C warming. A
precipitation decline of 20 mm year
yielded a k
value of 0.985
(1.5% fall), ranging down to k
= 0.545 (45.5%) with precipitation
decreased by 600 mm. These are shown in Fig. 5, along with changes
in P
ranging from a 10% decline (P
=0.9) to a nearly 50%
increase (P
The LES model can be used to examine changes in LES with any
particular climate and sea level scenario. For instance, a sea level rise of
0.5 m, 3 °C warming, precipitation decline of 300 mm year
, and P
increase of 15% leadsto a decrease in LES (LES
= 0.802). The most
important factor in that decline is the decrease in precipitation,
delivered to a smaller area [(k
=(0.773)(0.930)= 0.72].
The model could also be manipulated to evaluate potential effects of
increased mass input via deposition associated with rising sea level.
5. Discussion
Traditionally, considerations of landscape evolution have focused
on the interplay of opposing forces or trends, such as endogenic vs.
exogenic processes, uplift vs. denudation, or soil formation vs. erosion.
Energy considerations have, by and large, been restricted to conver-
sion of potential to kinetic energy associated with mass transfers from
higher to lower elevations. One motivation for the landscape evolution
space concept is to propose a heuristic device which explicitly
broadens the conceptual framework of landscape evolution beyond
the dialectics outlined above. A secondary aim was to bring additional
attention to the role of solar and biological energy in geomorphology.
The LES concept is, like landscapes themselves, still evolving. Many
aws and shortcomings undoubtedly exist in the LES model outlined
above. However, these may be viewed as opportunities for enhance-
ments, improvements, and adaptations. A few of these are outlined
5.1. Productivity and geomorphological niches
We return now to geomorphic productivity (Eq. (4)), reecting the
actual rates and magnitudes of geomorphic activity, as opposed to the
LES alone, which reects potentials. The rate (r) at which geomorphic
processes convert mass and energy per unit of LES varies with
different processes, materials, and environments within a landscape.
We can therefore expand Eq. (4) to
G=r S =XGi=XriSið13Þ
where the LES is divided into i=1, 2,..., Ncomponents where specic
relationships exist between processes and portions of the resource
If the components iare based on particular processes or process
regimes, then the components of S
would be dened relative to the
processes in question, and S
can be interpreted as the geomorpholo-
gical niche for process i, representing the mass and energy resources
inuencing the process. This is analogous to the ecological niche
concept, where the niche is a hypervolume representing the resources
and habitat elements associated with a given species.
Exploration of landscape evolution in terms of these geomorphic
niches could provide new insights, and would explicitly incorporate
the rate (r) as well as the LES (S) factors, and in much greater detail
than the broad-brush illustrations in this paper.
More generally, incorporation of r-factors allows an expanded
variation on Eq. (9):
ð Þ½ $ H2=H1
ð Þ2ρ2=ρ1
ð Þ ks2 =ks1
ð Þ kp2 =kp1
! " A2=A1
ð Þ3Pg2 =Pg1
! "
5.2. Climate and biotic factors
The LES model presented here represents climate inputs as simple
linear functions of surface area (the k
and k
factors). More
sophisticated representations are possible, and presumably desirable
in cases where solar energy and climate factors are of particular
interest. With respect to biotic effects, gross or net primary
productivity is probably a good indicator of the biological energy
inputs potentially available for geomorphic processes, but the
biologically relevant fraction of this is unquestionably both highly
variable and poorly understood at present (Phillips, 2009b).
5.3. Topographic factors
Topography is denoted in the current version of the LES model by
Hand A. Topographic changes relevant to the landscape evolution
potential (S, as opposed to r) are probably reasonably well
represented. However, topographic changes often result in changes
in slope gradients which may profoundly impact gravity-driven
processes. Changes in surface area may also inuence weathering
rates via surface exposure, independently of the k
and k
Other feedbacks may also be relevant, such as fracturing due to
lithostatic pressure release during landscape dissection.
5.4. Over-simplication?
In general, the LES model is highly simplied, but a word of caution
is in order with respect to LES elaborations. The temptation is always
present to introduce more factors and more complex representations.
However, increasing size and complexity does not always improve the
Fig. 5. LES ratios for solar energy/temperature (k
), precipitation (k
), and
biological (P
) energy inputs over the range of climate and productivity changes
considered (x-axis). The horizontal (x-) axis represents temperature increases of 0.1 °C
to 6.0 °C; precipitation decreases of 10 to 600 mm; and biological productivity changes
ranging from +10 to 48%.
84 J.D. Phillips / Geomorphology 109 (2009) 7985
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appropriateness and performance of models, even if the higher costs
and difculties of implementation are ignored. Simpler models geared
toward capturing essential behaviors and phenomenologies may in
many cases represent geomorphic system behavior better than larger
and more complex models (Werner, 1995; Phillips, 1999; Hergarten,
2002). Further, model expansion may actually reduce the generality of
the model and its results and implications (Beven, 2000; Sivakumar,
2004; Phillips, 2007b).
In many cases, geomorphic changes and responses, and landscape
evolution, may be dominated by a handful of the often vast number of
(potentially) relevant processes and controls. Efforts to identify and
focus on these dominant processes and controls may be more fruitful
than increasing the number and sophistication of components of LES-
based models.
6. Conclusions
The landscape evolution space concept attempts to account for all
major energy and mass resources which dene the potential for
landscape evolution, and the resources available to drive and support
geomorphic processes. Despite its origin as an essentially heuristic
model, LES can be used to address concrete problems, such as those
illustrated in the case studies. The LES model is particularly well suited
to confront issues regarding the relative importance of various
controls or forcings on geomorphic evolution. It is also intended as a
framework to allow for a systematic consideration of the major energy
and mass components of earth surface systems.
In the Big South Fork river basin, the LES was applied to investigate
changes in LES associated with uvial dissection; specically the
relative importance of mass removal by denudation vs. increased
surface area due to topographic roughening. Results indicate that
surface roughening and the associated increase in surface area only
slightly offsets the effects of mass removal with respect to LES.
The Texas coastal plain case study illustrated the use of the LES to
assess the relative inuences of predicted climate changes and sea
level rise under various scenarios. For instance, a sea level rise of
0.5 m, 3 °C warming, precipitation decline of 300 mm year
, and
biological productivity increase of 15% would result in a 20% decrease
in LES. The most important factor in that decline is the decrease in
precipitation, delivered to a smaller surface area.
Andrews, W.M., Jr., 2004. Geologic controls on Plio-Pleistocene drainage evolution of
the Kentucky River in central Kentucky. PhD dissertation, University of Kentucky,
Lexington, 213 pp.
Anthony, D.M., Granger, D.E., 2007. A new chronology for the age of Appalachian
erosional surfaces determined by cosmogenic nuclides in cave sediments. Earth
Surface Processes and Landforms 32, 874887.
Beven, K.J., 2000. Uniqueness of place and process representations in hydrological
modeling. Hydrology and Earth System Sciences 4, 203213.
Blum,M.D., Aslan, A., 2006. Signaturesof climate vs. sea-level change withinincised valley-
ll successions: Quaternary examples from the Texas Coastal Plain. Sedimentary
Geology 190,177211.
Blum, M.D., Price, D.M., 1998. Quaternaryalluvial plain construction in response to glacio-
eustatic and climatic controls, Texas Gulf Coastal Plain. In: Shanley, K., McCabe, P.
(Eds.), Relative Role of Eustasy, Climate, and Tectonism in Continental Rocks. SEPM
Spec. Publ., vol. 59. Society for Sedimentary Geology, Tulsa, OK, pp. 3148.
Blum, M.D., Tornqvist, T.E., 2000. Fluvial response to climate and sea-level change:
a review and look forward. Sedimentology 47 (suppl. 1), 248.
Blum, M.D., Carter, A.E., Zayac, T., Goble, R., 2002. Middle Holocene sea-level and
evolution of the Gulf of Mexico coast (USA). Journal of Coastal Research Special
Issue 36, 6580.
Butler, D.R., 1995. Zoogeomorphology. Animals as Geomorphic Agents. Cambridge
University Press, New York. 239 pp.
Catuneanu, O., 2002. Sequence stratigraphy of clastic systems: concepts, merits, and
pitfalls. Journal of African Earth Sciences 35, 143.
Corenblit, D., Gurnell, A.M., Steiger, J., Tabacchi, E., 2008. Reciprocal adjustments
between landforms and living organisms: extended geomorphic evolutionary
insights. Catena 73, 261273.
Devlin, J.F., 2003. Rationalizing geomorphology with an energy balance. Journal of
Geoscience Education 51, 398409.
Dietrich, W.E., Perron, J.T., 2006. The search for a topographic signature of life. Nature
439, 411418.
Dixon, J.C., Thorn, C.E., 2005. Chemical weathering and landscape development in
midlatitude alpine environments. Geomorphology 67, 127145.
Dixon, J.C., Thorn, C.E., Darmody, R.G., 2008. Spatial scale and chemical weathering in
Karkevagge: inuences on landscape evolution. Zeitschrift für Geomorphologie 52,
Eagleson, P.S., 2002. Ecohydrology: Darwinian Expression of Vegetation Form and
Function. Cambridge University Press, New York. 443 pp.
Hergarten, S., 2002. Self-Organized Complexity in Earth Systems. Springer, Berlin.
Lapenis, A.G., 2002. Directed evolution of the biosphere: biogeochemical selection or
Gaia? Professional Geographer 54, 379391.
McFadden, L.D., Eppes, M.C., Gillespie, A.R., Hallet, B., 2005. Physical weathering in and
landscapes due to diurnal variation in the direction of solar heating. Geological
Society of America Bulletin 117, 161173.
Morton, R.A., Blum, M.D., White, W.A., 1996. Valley lls of incised coastal plain rivers,
southeastern Texas. Transactions of the Gulf Coast Association of Geological Societies
46, 321331.
Moucha, R., Forte, A.M., Mitrovica, J.X., Rowley, D.B., Quere, S., Simmons, N.A., Grand, S.P.,
2008. Dynamic topography and long-term sea-level variations: there is no such
thing as a stable continental platform. Earth and Planetary Science Letters 271,
Otvos, E.G., 2005. Numerical chronology of Pleistocene coastal plain and valley
development; extensive aggradation during glacial low sea-levels. Quaternary
International 135, 91113.
Phillips, J.D., 1999. Earth Surface Systems. Complexity, Order, and Scale. Blackwell,
Oxford, UK. 180 pp.
Phillips, J.D., 2007a. Perfection and complexity in the lower Brazos River. Geomorphology
91, 364377.
Phillips, J.D., 2007b. The perfect landscape. Geomorphology 84, 159169.
Phillips, J.D., 2009a. Avulsion regimes in southeast Texas rivers. Earth Surface Processes
and Landforms 34, 7587.
Phillips, J.D., 2009b. Biological Energy in Landscape Evolution. American Journal of
Science 309, 271290.
Phillips, J.D., Lorz, C., 2008. Origins and implications of soil layering. Earth-Science
Reviews 89, 144155.
Phillips, J.D., Slattery, M.C., 2008. Antecedent alluvial morphology and sea level controls
on formprocess transition zones in the lower Trinity River, Texas. River Research
and Applications 24, 293309.
Rasmussen, C., Taylor,N.J., 20 07. Applying a quantitative pedogenic energy model across
a range of environmental gradients. Soil Science Society of America Journal 71,
Rasmussen, C., Southard, R.J., Horwath, W.R., 2005. Modeling energy inputs to predict
pedogenic environments using regional environmental databases. Soil Science
Society of America Journal 69, 12661274.
Rodriguez, A.B., Anderson, J.B., Siringan, F.P., Taviani, M., 2004. Holocene evolution of
the east Texas coast and inner continental shelf: along-strike variability in coastal
retreat rates. Journal of Sedimentary Research 74, 405421.
Schumm, S.A., 2005. River Variability and Complexity. Cambridge University Press, New
York. 220 pp.
Sivakumar, B., 2004. Dominant processes concept in hydrology: moving forward.
Hydrological Processes 18, 23492353.
Smil, V., 2008. Energy in Nature and Society. General Energetics of Complex Systems.
MIT Press, Cambridge, MA. 480 pp.
Sylvia, D.A., Galloway, W.E., 2006. Morphology and stratigraphy of the late Quaternary
lower Brazos valley: implications for paleoclimate, discharge, and sediment delivery.
Sedimentary Geology 190, 159175.
Taha, Z.P., Anderson, J.B., 2008. The inuence of valley aggradation and listric normal
faulting on styles of river avulsion: a case study of the Brazos River, Texas, USA.
Geomorphology 95, 429448.
Turkington, A.V., Paradise, T.R., 2005. Sandstone weathering: a century of research and
innovation. Geomorphology 67, 229253.
Vandenberghe, J., 2002. The relation between climate and river processes, landforms,
and deposits during the Quaternary. Quaternary International 91, 1723.
Vernadsky, V.I., 1926. The Biosphere: New York, Nevramont, 20 0 p. (1998 edition
translated from Russian by Langmuir, D.B., edited by McMenamin, M.A.S. and
Margulis, L.).
Volobuyev, V.R., 1964. Ecology of soils. Israel Program for Scientic Translation,
Jerusalem. 260 pp. (translated by A. Gourevich).
Volobuyev, V.R., 1974. Main concepts of soil ecology. Geoderma 12, 2733.
Werner, B.T., 1995. Eolian dunes: computer simulation and attractor interpretation.
Geology 23, 11071110.
Wheeler, R.L., Crone, A.J., 2001. Known and suggested Quaternary faulting in the mid-
continent United States. Engineering Geology 62, 5178.
Wilkinson, M.T., Humphreys, G.H., 2005. Exploring pedogenesis via nuclide-based soil
production rates and OSL-based bioturbation rates. Australian Journal of Soil
Research 43, 767779.
Yoshida, S., Steel, R.J., Dalrymple, R.W., 2007. Changes in depositional processes
an ingredient in a new generation of sequencestratigraphic models. Journal of
Sedimentary Research 77, 447460.
85J.D. Phillips / Geomorphology 109 (2009) 7985
... Phillips (2015) developed an individualistic concept of landscape evolution (ICLE), broadly analogous to Gleason's (1939) individualistic concept of plant associations in ecology. The ICLE is based on three propositions: (1) landscapes have positive evolution space (Phillips, 2009) -mass, energy, space, and time sufficient to allow for geomorphic evolution to occur; (2) every landform can change or evolve; and (3) the environment within and encompassing any landscape is variable (at a variety of temporal scales). The environment exerts selection pressure so that only some landforms are able to be formed and to persist. ...
... The changes in productivity and diversity of an ecological system can be interpreted with respect to the partitioning of these resources (Cochran et al., 2016;Lapenis, 2002;Phillips, 2008). A broadly analogous landscape evolution space can be defined based on available mass and energy resources for geomorphic processes, again modified by the development of the landscape itself (Phillips, 2009;Rósa and Novák, 2011). ...
... However, these are constrained by general laws, which allow some possibilities and forbid others, and determine that some of the allowable options are more or less probable. Similarly, place characteristics constrain the possibilities, by defining the resource or evolution space (Phillips, 2008(Phillips, , 2009) in which development can occur. Law-governed processes acting on a geographically constrained template result in environmental transformations, and a new (continually evolving) set of singular place characteristics. ...
Nine axioms for interpreting landscapes from a geoscience perspective are presented, and illustrated via a case study. The axioms are the self-evident portions of several key theoretical frameworks: multiple causality; the law–place–history triad; individualism; evolution space; selection principles; and place as historically contingent process. Reading of natural landscapes is approached from a perspective of place formation. Six of the axioms relate to processes or phenomena: (1) spatial structuring and differentiation processes occur due to fluxes of mass, energy, and information; (2) some structures and patterns associated with those fluxes are preferentially preserved and enhanced; (3) coalescence occurs as structuring and selection solidify portions of space into zones (places) that are internally defined or linked by mass or energy fluxes or other functional relationships, and/or characterized by distinctive internal similarity of traits; (4) landscapes have unique, individualistic aspects, but development is bounded by an evolution space defined by applicable laws and available energy, matter, and space resources; (5) mutual adjustments occur between process and form (pattern, structure), and among environmental archetypes, historical imprinting, and environmental transformations; and (6) place formation is canalized (constrained) between clock-resetting events. The other three axioms recognize that Earth surface systems are always changing or subject to change; that some place formation processes are reversible; and that all the relevant phenomena may manifest across a range of spatial and temporal scales. The axioms are applied to a study of soil landscape evolution in central Kentucky, USA.
... Additional forces depend on the case study setting and may include the force that flowing water or blowing wind exerts on a substrate, the force that a flowing glacier exerts on bedrock through scouring, or the uplifting force for an entire orogen (cf. Phillips, 2009). Material properties of relevance to Figure 3, depending on geomorphic setting, on spatial scale and on model complexity may include, for example, bulk density, cohesion, shape, wetness, size, lithology, or crustal elasticity. ...
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This chapter reviews quantitative modeling of landscape evolution. Quantitative modeling is contrasted with conceptual or physical modeling, and four categories of model studies are presented. Procedural studies focus on model experimentation. Descriptive studies use models to learn about landscapes in general. Postdictive and predictive try to correctly simulate the evolution of real landscapes, respectively in the past (with calibration) or in the future (with calibrated models). After classification of 322 landscape evolution studies in these categories, we find that descriptive studies are most common, and predictive studies are least common. Procedural studies have focused on production methods for digital landscapes, spatial resolution effects, the role of sinks and depressions and calculation schemes for flow routing. Descriptive studies focused mainly on surface-tectonic interactions, sensitivity to external forcing, and the definition of crucial field observations from model results. Postdictive and predictive studies operate mainly in time-forward mode and are increasingly validated using independent data. Overall, landscape evolution modeling has progressed to the extent that non-experts are able to easily use modern models, and are commonly used in inversion schemes to obtain the most likely (set of) inputs to produce known topographies. This development will likely continue, with more attention for interactions with ecology and soils over short (ca, ma) timescales, and with climate over long (Ma) timescales.
... Changes in productivity and diversity of an ecological system can be interpreted in terms of partitioning of these resources (Cochran et al., 2016;Lapenis, 2002;Phillips, 2008). An analogous geomorphological landscape evolution space can be defined based on available energy and mass available for geomorphic processes, again modifiable by external factors as well as the development of the landscape itself (Phillips, 2009;Rósa and Nov ak, 2011;Lisenby et al., 2018). ...
This chapter focuses on the (not necessarily final) destination of landscape evolution—the attractors that landscapes may move toward and the goal functions that govern these trajectories. Single-outcome concepts posit that landscape systems move toward a single self-perpetuating state. These include notions of progression toward climax or mature forms, stable equilibrium conditions, or self-organized critical states. Multi-outcome models include notions of alternative stable states, nonequilibrium systems, and unstable attractors. As they evolve, landscapes have plasticity defined by their degrees of freedom, and constraints imposed by limits on energy, matter, and geographical space. These can be described using concepts of a multidimensional resource or landscape evolution space. Goal functions for landscape evolution are generally based on increasing fitness, often assessed in terms of optimality hypotheses, which systems strive toward maximizing or minimizing some aspect of energy and/or mass flux. Many of these are directly or indirectly related to the least action principle and maximum entropy production. Apparent goal functions can generally be explained on the basis of emergent phenomena. Landscape systems cannot aspire to anything in a literal sense, and there exist no laws that dictate trends toward the optimal states. However, if these optimal states are associated with advantages in the formation, survival, and replication of landscape components, then trends toward the optima will frequently be observed. Emergence and general principles of selection can tie together the majority of the concepts of attractors and goal functions in landscape evolution.
... Human intervention on the surface has become a geological factor, which is indicated by the fact that 'artificial ground', a category used for decades on British geological maps, has recently been categorized into a series of 'domains ' (ford et al. 2010). In densely populated regions the rate of human modified surface development far exceeds that of natural processes; however, it may also be important to distinguish areas affected by higher and lower grades of human geomorphological influence in these cases (gares et al. 1994;cendero et al. 2001;PhIllIPs 2009). ...
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The degree of human geomorphological impact was estimated as a ratio of natural geomorphological processes and geomorphological processes triggered or facilitated by humankind. A typical Central European cultural landscape of diverse land use and relief was considered as a pilot area. Based on topography maps and landforms the natural material fluxes were calculated. By overlapping historical maps, modern maps and remotely sensed data, the duration and extent of different land use types were mapped, and were assigned to each landscape unit. Anthropogenic material fluxes were calculated for the land use types identified. Dividing the summarized anthropogenic material fluxes by natural ones, the anthropic geomorphological transformation ratio (r AG) was estimated. The value of r AG is independent of the efficiency and intensity of processes; it merely expresses the relation of effectiveness between human induced and natural processes. Since the calculated index is based on estimated values and there is, at least theoretically, no upper limit, the term 'hemeromorphy' was introduced and the values were classified in corresponding 'hemeromorphy' categories. For the smallest landscape units with the same degree of 'hemeromorphy' the term 'hemeromorphotop' was applied. This interpretation makes the comparison of landscape units possible according to their anthropogeomorphological transformation, independently of the intensity and quality of their geomorphological processes. Zusammenfassung: Der Grad der geomorphologischen Einflüsse des Menschen wird als Verhältnis zwischen natürlichen geo-morphologischen Prozessen und durch den Menschen ausgelöste oder begünstigte geomorphologischen Prozessen betrachtet. Eine typische mitteleuropäische Kulturlandschaft mit vielfältiger Landnutzung und Relief wird als Modellgebiet betrachtet. Auf der Grundlage topographischer Karten und Landformen werden zunächst die natürlichen Stoffflüsse berechnet. Durch die Über-lagerung von historischen Karten, aktuellen Karten und Fernerkundungsdaten werden Dauer und Ausmaß der verschiedenen Landnutzungstypen kartiert und den einzelnen Landschaftseinheiten zugeordnet. Für die identifizierten Landnutzungstypen wer-den die anthropogenen Materialflüsse berechnet. Durch die Division der zusammengefassten anthropogenen Materialflüsse durch die natürlichen Materialflüsse wird das anthropogene geomorphologische Transformationsverhältnis (r AG) geschätzt. Der Wert der r AG ist unabhängig von der Effizienz und Intensität der Prozesse; er drückt lediglich das Verhältnis der Effektivität zwischen menschlich induzierten und natürlichen Prozessen aus. Da dem berechneten Index geschätzte Werte zugrunde liegen und es, zumindest theoretisch, keine obere Grenze gibt, wird der Begriff 'Hemeromorphie' eingeführt und die Werte in entsprechende 'Hemeromorphie' Klassen eingeteilt. Für die kleinsten Landschaftseinheiten gleichen 'Hemeromorphie' Grads wird der Begriff 'Hemeromorphotop' verwendet. Die Interpretation ermöglicht den Vergleich von Landschaftseinheiten entsprechend ihrer anth-ropo-geomorphologischen Transformation, unabhängig von der Intensität und Qualität der geomorphologischen Prozesse.
... The structure of a soil cover is determined by realization of a number of major regularities of the soil geography including the lithogenic differentiation, lateral geochemical links between its components, as well as the historical-chronological diversity of the soil cover (Dyakonov et al., 2012;Gennadiev and Smirnova, 2012). The position within the landscape, hypsometric levels along the gradient and the lateral constituent of the migration processes represent the factors regulating the landscape evolution (Phillips, 2009). ...
The ‘catena concept’, along with previously proposed meanings of this term, has recently acquired a soil evolutionary content. The prospects of wider special and chronological study of dated pedotopocatenas include the possibility of a more detailed analysis of the mutual dependence of soil-geomorphological relationships through distinguishing relatively homogeneous climatic stages of pedogenesis and denudation. With this purpose, the present study comprised earthen defensive constructions, which, within the ‘rampart/ditch’ system, combine erosive, trans-accumulative catenas and accumulators of pedolithosediments. The goal was to develop a system of the most information-rich pedogenetic indicators to reconstruct the dynamics of erosion-accumulative processes on the basis of dated earthen defensive constructions of a historical period (using the example of a frontier rampart within a ditch from the mid-17th century). Soil samples were collected within the limits of the erosion and trans-accumulative catenas, as well as in the closing alignment of the ditch (over the vertical profile in eight strata of pedosediments of up to 1m high). The granulometric composition, concentration of macroelements and trace elements (25 metals and oxides) in soils and in particles with sizes<1 mm, and the fractional composition of the humus were analysed in soil samples taken from different points in the catena and along the profile of the pedosediments. For the reconstruction of the humidity conditions over 3.5 centuries based on dendrochronological data, the cross-relation approach was applied. This allowed us to represent the chronostratigraphy of pedosediments as stages differing in the rate of accumulation processes. The system of soil indicators in pedosediments including the percentage of particles 0.001–0.005mm and>0.01mm in size, the content of organic carbon and its qualitative composition, the sum of the elements accumulated in the soil (P, Ca, K, Mg, Mn, Cu), as well as the geochemical ratios which reflect the processes of leaching, can serve as palaeogeographic tracers of the climatic variability at the level of intra-secular changes under forest-steppe conditions. The history of the formation of pedosediments over 3.5 centuries in the forest-steppe zone of Eastern Europe comprises two wet periods (1890–1935, 1976–2013) when the average annual rates of pedosedimentogenesis were similar (2.80–2.85mmyr−1) and two periods of geomorphological ‘lull’ and a xeromorphic climatic condition span (1821–1890 and 1666–1741). These periods correspond to diminution of the average rate of accumulation of sediments down to 2.47mmyr−1. The results of the present study suggest the need for purposeful research and wide inclusion of dated sites of the anthropogenic relief formation with flow-geochemical series over the topographic gradient into studies of soil–geomorphologic interrelations and calibration of mathematic models of natural processes using on-site data.
... In this topographic state space, topography and resilience properties can be compared simultaneously. Geomorphologists have employed analogous approaches, like morphospace, phase space, or evolution space (Inkpen and Petley 2001;Phillips 2009;Baas and Nield 2010;Inkpen and Hall 2016;Phillips 2018b). Any single landscape should be capable of being located within a larger state space derived from multiple landscapes or else expand the boundaries of this state space if it has not been encountered before. ...
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We compared two biogeomorphic models that postulate how vegetation is intertwined in the response and recovery of barrier island dunes. Each model was developed in a separate coastal region using different methods. Both relied on simple elevational representations of topography. By comparing topographies among more islands of these two regions and by linking multiple representations of topographic pattern to resistance and resilience, we provide a synthesis that shows the validity of both models and the consequences of reifying one over the other. Using airborne LiDAR, topographic metrics based on point, patch, and gradient representations of topography were derived for fifty-two sites across eleven islands along the Georgia Bight and Virginia. These seventeen metrics were categorized in terms of resistance and resilience to disturbance from storm-forced high water levels and overwash. Resistance refers to intrinsic properties that directly counter expressions of power from disturbance. Resilience refers to the degrees of freedom to adjust and adapt to disturbance. Using a cross-scale data modeling approach, these data were visualized as topographic state space using multidimensional scaling. In this state space, similarity in topography as well as resistance and resilience were inferred through a site's position along low-dimension axes representing geomorphic resistance and high-dimension axes representing the spatial landscape properties of biogeomorphic resilience. The two models overlap in how they account for barrier dune resistance and resilience along the U.S. south Atlantic coast. Islands of the Georgia Bight have a propensity for higher resistance and resilience. The Virginia islands have lower resistance and resilience. Key Words: barrier islands, biogeomorphology, cross-scale structure, dunes, resilience.
... Also, discrete values of stream power and shear stress can be compared to local geomorphic thresholds of adjustment by deriving them from total energy curves (Costa and O'Connor, 1995). In addition, the total energy of disturbance events can be compared with energy values derived from the geomorphic work accomplished by hydrological, ecological, biological, climatological, and pedological processes that contribute to landscape evolution and denudation (Devlin, 2003;Rasmussen et al., 2005Rasmussen et al., , 2011Phillips, 2009aPhillips, , 2009c. ...
Geomorphic effectiveness has been an influential concept in geomorphology since its introduction by Reds Wolman and John Miller in 1960. It provided a much needed framework to assess the significance of an event by comparing event magnitude to the resultant geomorphic effects. Initially, this concept was applied primarily in river channels, under the linear assumption that geomorphic responses to similarly sized flood events will be consistent. Numerous authors have since attempted to quantify a direct, proportional relationship between event magnitude and different forms of geomorphic response in a variety of geomorphic settings. In doing so, these investigations applied an array of metrics that were difficult to compare across different spatiotemporal scales, and physiographic and geomorphic environments. Critically, the emergence of other geomorphic concepts such as sensitivity, connectivity, thresholds, and recovery has shown that relationships between causes (events) and geomorphic effects (responses) are often complex and non-linear. This article is protected by copyright. All rights reserved.
Theoretical and practical issues in geomorphology have not been adequately addressed due to a lack of formalization and digital representation of spatial and temporal concepts, given the limitations associated with modern-day geographic information systems (GIS). Rapid advancements in geospatial technologies have resulted in new sensors and large volumes of geospatial data that have yet to be fully exploited given a variety of computational issues. Computational limitations involving storage, preprocessing, analysis, and modeling pose significant problems for Earth scientists. Consequently, advanced cyberinfrastructure is required to address geospatial data-science issues involving communication, representation, computation, information production, decision-making, and geovisualization. We identify and discuss important aspects of exploiting advances in cyberinfrastructure that involve computational scalability, artificial intelligence, and uncertainty characterization and analysis for addressing issues in the Earth sciences. Such developments can be termed cyber geographic information science and systems (cyberGIS). We discuss this important topic by addressing the significant overlap of concepts in GIS and geomorphology that can be formalized, digitally represented, implemented, and evaluated with cyberGIS. We then introduce the fundamentals of cyberinfrastructure and cyberGIS, including a discussion of the utilization of artificial intelligence and deep learning. We finally provide one case study demonstrating operational cyberGIS capabilities.
Landscape evolution often occurs over long-time scales that do not allow for direct observation and measurement. This chapter reviews approaches for observing, inferring, and reconstructing evolutionary trajectories. These include direct observation and monitoring (e.g., observatories), simulation models, and historical reconstruction. The latter encompasses documentary evidence, dating techniques, paleoenvironmental indicators, and inferential methods such as space-for-time substitutions and contemporary inferential indicators.
The Earth had liquid water oceans for most of its history, has a highly mobile crust, and a dynamically convecting interior. Its surface has been constantly driven by the movement of the interior causing the periodic conglomeration and separation of continental landmasses, the opening and closing of oceans, and the construction and destruction of mountain ranges. Such globally dynamic geomorphology profoundly impacted the global climate and thus biological evolution in general, and specifically human habitation patterns and the development of civilization. Given that as a species we have been shaped and affected by (and now, ourselves, shape) the patterns and intensity of surface geological processes – geomorphic processes – it is hard to overemphasize the importance of geomorphology as a discipline that offers environmental insights significant to our continued well-being as Earth inhabitants. New emerging techniques and approaches to landscape analyses using remote sensing on a planetary scale offer additional significant advantages for unification of regional geomorphological insights into an emerging global science (Baker, 1986; Short and Blair, 1986; Church, 2010). Such knowledge will most likely be even more important as we try to cope with and mitigate the effects of global climate change on society.
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This book provides a theory to overcome the problem of identifying the principles behind the interdependence of different aspects of nature. Climate, vegetation, geology, landforms, soils, hydrology, and other environmental factors are all linked. Many scientists agree that there must be some general principles about the way in which earth surface systems operate, and about the ways in which the interactions of the biosphere, lithosphere, hydrosphere, and atmosphere manifest themselves. Yet there may be inherent limits on our ability to understand and isolate these interactions using traditional reductionist science. The argument of this book is that the simultaneous presence of order and chaos reflects fundamental, common properties of earth surface processes and systems. It shows how and why this is the case, with examples ranging from evolutionary and geological times scales to microscale examinations of process mechanics.
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This paper addresses the problem of uniqueness of catchment areas in relation to model representations of flow processes. The uniqueness of field measurements as a limitation on model representations is discussed. The treatment of uniqueness as a residual from a modelled relationship may conceal information about the uniqueness of catchments, while the treatment of uniqueness as a set of parameter values within a particular model structure is problematic due to the equifinality of model structures and parameter sets. The analysis suggests that a fully reductionist approach to describe the uniqueness of individual catchment areas by the aggregation of descriptions of small scale behaviour will be impossible given current measurement technologies. A suggested strategy for the representation of uniqueness of place as a fuzzy mapping of the landscape into a model space is suggested. This will lead to a quantification of the uncertainty in predictions of any particular location in a way that allows a conditioning of the mapping on the basis of the available data. This process can incorporate a hypothesis testing approach to model evaluation but the problem of multiple behavioural models may provide an ultimate limitation on the realism of process representations: not on the principle of realism but on the possibility of unambiguous process representations.
An energy balance shows that geomorphological processes are driven by an energy source more powerful than the geological processes that raise the continents. In addition, energy fluxes for the entire Earth are calculated from several energy sources including enery from the Sun, Esolar, geothermal energy, Egeothermal, based primarily on heat production from radiogenic sources, energy in the hydrologic cycle, Ehydrologic, based on energy stored as latent heat in water vapor, and energy required to maintain continental uplift rates, Epotential. The Epotential term is estimated from the hypsometric curve for the Earth's continents and the crustal roots according to Airy's model of isostasy. It is shown that Esolar > Ehydrologic, Egeothermal > Epotential and Ehydrologic > Epotential. The preceding calculations are presented in a format that illustrates the development and application of mathematical equations for geological problems. These examples provide instructors with material to illustrate the use of graphs, algebra and integral calculus in a geological context. All steps are explained assuming only basic knowledge from the reader.
The Texas Gulf Coastal Plain consists of a series of low-gradient, fan-shaped alluvial plains emanating from each major river valley. The majority of alluvial plain surfaces have been mapped as Pleistocene Beaumont Formation or younger unnamed strata, and interpreted to represent eustatically-controlled deposition during the oxygen isotope stage 5 and modern interglacial highstands. Reevaluation of preexisting data combined with reexamination of Beaumont and younger strata of the Colorado River suggests the stratigraphic and geochronologic framework needs revision, and processes of alluvial plain deposition are more complex than previous interpretations have inferred. As a result, Beaumont and younger strata provide an opportunity to examine alluvial plain construction within a sequence-stratigraphic framework and discuss some key characteristics and the heirarchal nature of eustatically-controlled versus climatically-controlled components of alluvial plain depositional sequences. Mapping from satellite imagery, field documentation of geomorphic and stratigraphic relationships, consideration of the stratigraphic significance of surface and buried soils, and a number of radiocarbon and thermoluminescence ages suggests that Beaumont and younger alluvia] plains consist of multiple cross-cutting and/or superimposed valley fills of widely varying age, and may represent the last 300–400 ky or more. Valley fills become partitioned by initial lowering of sea-level below interglacial highstand positions, when channels rapidly incise and valley axes become fixed in place as they extend across the subaerially-exposed shelf. While shorelines remain basinward of highstand positions, the remainder of the alluvial plain is characterized by non-deposition and soil development. During this time, multiple episodes of lateral migration, aggradation, degradation, and/or flood-plain abandonment with soil formation occur within incised and extended valleys in response to climatic controls on discharge and sediment supply. This creates a composite basal valley fill unconformity, as well as multiple smaller-scale allostratigraphic units within the valley fill. With late stages of transgression and highstand valleys fill at paces set by upstream controls on sediment delivery. As valley filling nears completion, veneers of flood basin sediments spread laterally, which buries soils developed on downdip margins of the alluvial plain. Complete valley filling during highstand is one of several processes that promotes avulsion, with relocation of valley axes before the next sea-level fall, such that successive 100–ky valley fills have a distributary pattern, and successive increments of geologic time occur lateral to each other.
The earth’s surface is shaped by a variety of processes; beside gravity-driven mass movements, erosion by water, wind, and glaciers are the most important examples. Fluvial erosion is ubiquitous in many climates; river networks can be considered as the backbone of the landscape. Thus, understanding the evolution of drainage networks has been a major challenge in geomorphology.
This volume reviews biogeomorphic effects in terms of animals eroding, transporting and/or causing the deposition of rock, soil and unconsolidated sediments. It is divided into nine chapters, the first being an introduction. The second looks at the geomorphic influence of terrestrial and aquatic invertebrates. Next the geomorphic role of ectothermic vertebrates (fish, amphibians and reptiles) is reviewed. Birds are covered next, as agents of erosion, transportation and erosion (nest building, mound building, vegetation removal). The specific activities of digging for food and catching of food are examined in Chapter five. Chapter six discusses the processes of trampling, wallowing and geophagy (by mammals). Mammalian burrowing is covered in the next chapter. The influence of beavers is reviewed in chapter eight: beaver species and morphology; distribution; dam building; the beaver pond environment and associated geomorphic influences; sedimentation and sedimentation rates in beaver ponds; and dam failure and its effects. The final chapter consists of concluding remarks. -S.R.Harris