CAN RAPID ASSESSMENT PROTOCOLS BE USED TO JUDGE SEDIMENT

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JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
Vol. 51, No. 2
AMERICAN WATER RESOURCES ASSOCIATION
April 2015
CAN RAPID ASSESSMENT PROTOCOLS BE USED TO JUDGE SEDIMENT
IMPAIRMENT IN GRAVEL-BED STREAMS? A COMMENTARY1
Thomas E. Lisle, John M. Buffington, Peter R. Wilcock, and Kristin Bunte2
ABSTRACT: Land management agencies commonly use rapid assessments to evaluate the impairment of
gravel-bed streams by sediment inputs from anthropogenic sources. We question whether rapid assessment can
be used to reliably judge sediment impairment at a site or in a region. Beyond the challenges of repeatable and
accurate sampling, we argue that a single metric or protocol is unlikely to reveal causative relations because
channel condition can result from multiple pathways, processes, and background controls. To address these concerns, a contextual analysis is needed to link affected resources, causal factors, and site history to reliably identify human influences. Contextual analysis is equivalent in principle to cumulative effects and watershed
analyses and has a rich history, but has gradually been replaced by rapid assessment methods. Although the
approaches differ, rapid assessment and contextual analysis are complementary and can be implemented in a
two-tiered approach in which rapid assessment provides a coarse (first-tier) analysis to identify sites that
deserve deeper contextual assessment (second-tier). Contextual analysis is particularly appropriate for site-specific studies that should be tailored to local conditions. A balance between rapid assessment and contextual
analysis is needed to provide the most effective information for management decisions.
(KEY TERMS: rapid assessment; sediment impairment; contextual analysis; gravel-bed channels.)
Lisle, Thomas E., John M. Buffington, Peter R. Wilcock, and Kristin Bunte, 2015. Can Rapid Assessment Protocols Be Used to Judge Sediment Impairment in Gravel-Bed Streams? A Commentary. Journal of the American
Water Resources Association (JAWRA) 51(2): 373-387. DOI: 10.1111/jawr.12255
ment impairment is difficult to assess because sediment is an intrinsic part of river systems and is
controlled by both natural and human factors. An
assessment of impairment requires not only identification of excess instream sediment storage, but evidence that the condition is due to human disturbance
rather than natural conditions and their variability.
It also requires one or more metrics that reliably indicate change, which may then be compared to suitable
standards or historical conditions to evaluate impact.
INTRODUCTION
Sediment impairment is the degradation of channel conditions by human activities that alter the
volume and/or the particle size of sediment in the
channel. A stream impairment of broad concern, for
example, is the accumulation of fine-sediment (commonly sand and finer material) in coarse-grained
river beds, which can degrade instream habitat. Sedi-
1
Paper No. JAWRA-13-0174-P of the Journal of the American Water Resources Association (JAWRA). Received August 19, 2013; accepted
July 30, 2014. © 2014 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the
USA. Discussions are open until six months from print publication.
2
Research Hydrologist (Lisle), Pacific Southwest Research Station, U.S. Forest Service, 1700 Bayview Drive, Arcata, California 95521;
Research Geomorphologist (Buffington), Rocky Mountain Research Station, U.S. Forest Service, Boise, Idaho 83702; Professor (Wilcock),
Department of Watershed Sciences, Utah State University, Logan, Utah 84322; and Research Scientist (Bunte), Department of Civil and
Environmental Engineering, Colorado State University, Fort Collins, Colorado 80523 (E-Mail/Lisle: thomas.lisle@gmail.com).
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ments). Similarly, Bunte et al. (2009, 2012) demonstrate that the percentage of fine material (<5.6 mm)
determined from rapid protocols can differ by a factor
of 2 relative to detailed sampling.
Uncertainty in rapidly measured values can work
against the basic goal of change detection and may
preclude the detection of all but the most extreme
conditions (i.e., least vs. most disturbed; e.g., figures
7 and 8 of Kaufmann et al., 2008). Moreover, rapid
assessment protocols frequently employ random sampling of sites (e.g., Stevens and Olsen, 2002, 2004)
that may not capture the underlying spatial variability of physical conditions, human disturbances, and
channel responses, nor is such sampling amenable to
elucidating pathways of disturbance and response.
An important challenge facing rapid assessment
programs is an essential tension that lies at the heart
of many environmental monitoring and assessment
programs: to sample extensively at a few locations or
to sample rapidly at many. There is no general resolution to this dilemma because the tradeoff between
intensive and extensive monitoring protocols depends
on the objective of the monitoring and the variability
of the quantities measured. However, the standard
that must always be addressed — one that supersedes logistic and cost considerations — is that the
information collected must be sufficient to answer the
questions asked. The question addressed in this study
is, can we judge sediment impairment accurately and
meaningfully with rapid assessments? Although we
recognize the compelling reasons that motivate a
rapid assessment approach, we question whether the
approach is sufficient to the task. We contend that
rapid assessments have limited value due to their
demonstrated uncertainty and to the fact that they
do not directly link cause and effect in a way that
allows land managers to develop defensible sediment
mitigation or remediation plans. We argue that rapid
assessment may be effective if used in combination
with analyses that accommodate watershed and historical context.
In this study, we examine the metrics available for
judging sediment impairment and discuss the available standards and references used for comparison
and evaluation. We then evaluate the ability of rapid
assessments to judge sediment impairment at two
different spatial scales:
Federal programs in the United States (U.S.),
such as the Environmental Protection Agency’s
Environmental Monitoring and Assessment Program
(EMAP) (Kaufmann et al., 1999; USEPA, 2004; Stoddard et al., 2005; Peck et al., 2006), the Forest Service’s Aquatic and Riparian Effectiveness Monitoring
Program (AREMP) (Reeves et al., 2004; Lanigan
et al., 2014), and the PACFISH INFISH Biological
Opinion monitoring program (PIBO) (Kershner et al.,
2004; E.K. Archer, R.A. Scully, R. Henderson, B.B.
Roper, and J.D. Heitke, “2012 Sampling Protocol for
Stream Channel Attributes”, unpublished manual.
PIBO-EMP, PACFISH/INFISH Biological Opinion
Effectiveness Monitoring Program for Streams and
Riparian Areas, Logan, Utah, http://www.fs.fed.us/
biology/resources/pubs/feu/pibo/pibo_stream_sampling_
protocol_2012.pdf, accessed March 2014), evaluate
physical conditions and their temporal trends in
stream channels in first- to third-order basins at
regional and national scales. An important element of
these programs is assessing sediment-related impacts
on channel stability and on instream and riparian
habitat. Regulatory and administrative requirements
compel the evaluation of many streams as well as a
regional assessment of stream health.
The large number of sites to be monitored inevitably strains the resources available for monitoring,
such that each of these programs has developed rapid
assessment protocols that are designed to be efficient,
repeatable, and widely applicable. Rapid assessments
devote a day or less at each site to provide a snapshot
of particular stream conditions at each site which,
taken together, can be used to develop an assessment
for an entire region. Changes over time are assessed
with a resampling plan in which a few sites are visited annually and others are revisited over longer
intervals. Another part of the strategy is to base the
assessment on a small number of parameters measured at each site. Given limited agency time and
personnel, the rapid assessment strategy is to trade
precision, accuracy, and detail at any site for a large
number of sample sites to overcome the statistical
demands of variability in a large geographic area.
By their nature, rapid methods may be expected to
provide a coarse assessment that is less precise and
accurate relative to more detailed monitoring (Roper
et al., 2002, 2008, 2010; Whitacre et al., 2007; Bunte
et al., 2009, 2012). For example, Roper et al. (2010)
report substantial uncertainty in rapidly measured
sediment metrics (coefficients of variation ranging
from about 30 to 70% within monitoring groups for
measurements of median grain size and percent
fines) and widely varying levels of accuracy (coefficients of determination ranging from 0.07 to 0.92 for
correlating rapidly measured sediment metrics with
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1. Can rapid assessment be used to accurately judge
sediment impairment in a region? Are the origins
and manifestations of sediment impacts in a
variety of watersheds so similar that a single
metric or protocol can diagnose human influences
on a variety of channel resources in all of them?
If so, can meaningful deviations be detected
given precision, accuracy, and sample size?
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We focus on gravel-bed rivers because of their habitat value for many threatened and endangered aquatic
and riparian species (the management of which frequently drives sediment monitoring programs) and
because most sediment metrics have been developed
for this channel type. Critiques of rapid assessment
protocols and evaluations of their accuracy and precision are reported elsewhere (e.g., Roper et al., 2002,
2008, 2010; Whitacre et al., 2007; Bunte et al., 2009,
2012). Here, we focus on the ability of rapid assessments to provide adequate information to identify sediment impairment and link it to its causes and
possible remediation. We recognize that not all impairments of stream condition are influenced by sediment,
but we suggest that some of our commentary is relevant to assessments of those impairments as well.
SEDIMENT IMPAIRMENT: DEFINITION
AND CONTROLS
Because a stream’s sediment composition can
depend on both natural and anthropogenic factors, it
is important to begin by carefully defining the terms
of the problem. Sediment impairment can be defined
simply as harm to stream resources as a result of
anthropogenic changes in the sediment transport
regime. Any definition of harm requires standards
and references with which to judge important deviations from the norm as specified by laws and regulations. For example, the Clean Water Act defines
impairment as (1) “A classification of poor water quality for a surface water body,” or (2) “Detrimental
effect on the biological or physical integrity of a water
body caused by an impact that prevents attainment
of the designated use” (USC, 1972). To implement
these broad definitions, specific metrics are needed
to indicate and quantify impairment. Furthermore,
taken together, these definitions highlight the fact
that the severity of impairment depends not only on
the magnitude of change in sediment (as judged by
one or more reliable metrics) but also on the sensitivity of the resource affected.
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Because sediment is a natural part of stream systems, identification of sediment sources, pathways,
and sinks is particularly important to distinguish
between natural and anthropogenic influence. Sediment delivery to channels is complex, often localized,
and episodic. Changes in sediment composition may
be triggered by pulses in sediment supply produced
by a range of geomorphic events, including floods (De
Jong, 1992; Nolan and Janda, 1995), debris flows
(Benda and Dunne, 1987; Benda, 1990; Berger et al.,
2010), landslides (Perkins, 1989; Sutherland et al.,
2002), and wildfire (Klock and Helvey, 1976; Megahan, 1983; Robichaud and Brown, 1999; Legleiter
et al., 2003; Eaton et al., 2010; Goode et al., 2012).
The factors controlling the magnitude, frequency, and
location of these events may be natural, anthropogenic, or both. Identification of sediment sources and
supply rates is insufficient, however, because the
downstream influence of sediment pulses can be
strongly mediated by in-channel and near-channel
storage (Benda and Dunne, 1997; Lisle, 2008). Evaluation of any stream reach requires an understanding
of the routing of sediment from its sources.
The range of aquatic resources that may be
impacted by sediment, as well as the complex mix of
natural and human factors that influence sediment
supply and storage, indicates that a judgment of sediment impairment must consider a wide range of
interactions. For example, different aquatic resources
(e.g., fisheries, water supply, and recreation) may be
impacted by sediment. The condition and vulnerability of these resources, in turn, can depend on a variety of factors (e.g., stream temperature, channel
morphology, and riparian vegetation) which themselves depend on both sediment and nonsediment
controls (e.g., the magnitude and frequency of floods
and drought, the availability of large woody debris).
Furthermore, a range of human activities can either
directly (e.g., channelization, water storage) or indirectly (e.g., roads, dams, grazing) change the supply,
transport capacity, and storage of sediment. Consequently, an assessment of sediment impairment
requires an understanding of the full suite of these
linkages.
The lag time between sediment inputs and stream
response can vary from days to centuries, depending
on the quantity, grain size, and location of the sediment input. Channel change at any one location may
well reflect the combined influence of multiple
watershed disturbances. Spatial variability, process
interactions, and variable lag times all conspire to
make it difficult to link current stream conditions to
a particular cause or causes. Although stream monitoring (whether rapid or detailed) can tell the current
state of the local system, it cannot explain its cause.
This link between cause and effect is crucial because
2. Can rapid assessment be used to accurately judge
sediment impairment at a particular site? Given
that site-specific projects (e.g., watershed and
channel restoration) are commonly evaluated
and monitored using some of the same metrics
as rapid assessments, can we sacrifice some precision and accuracy and use rapid assessment
protocols to adequately judge impairment at individual sites with different resources, causal pathways, and environmental issues?
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difficulty of measuring sediment load, most sediment
metrics do not measure load directly but use measures of channel condition that might register variations in load. These include channel dimensions
(width, depth, or width:depth ratio), channel planform
(e.g., meandering, braided), and bed texture (bed-surface particle size and concentration of fine sediment).
it is necessary for any explanation of degradation and
for developing plans for remediation.
In practice, a determination of sediment impairment is based on deviation of an indicator from a
desired condition or reference value (Stoddard et al.,
2006) and evidence that links such a deviation to
human causes (e.g., Reeves et al., 2004). Metrics of
sediment impairment have been correlated with
watershed disturbances that are believed to cause
increased sediment loading, such as road density or
absence of riparian trees (e.g., Kaufmann et al., 2009;
Al-Chokhachy et al., 2010). Correlation is not causation, of course, and the wide range of potential interactions and lags linking stream channels to their
watersheds suggests that assessment of sediment
impairment must depend additionally on context.
This context includes intrinsic watershed features
such as geology, relief, and climate, the pattern,
intensity, location, and timing of human disturbance,
and recent changes in process variables such as
streamflow, water temperature, and pollution.
As much as problems associated with accuracy and
uncertainty in rapid assessments, it is the challenge
of connecting cause and effect that causes us to have
concerns about using rapid assessment for judging
sediment impairment. Without explanation accounting for context, it is not possible to reliably demonstrate sediment impairment, describe its cause, and
develop defensible remediation plans that address the
root causes of impairment. We suggest that rapid
assessment protocols can be combined with contextual analysis to provide the necessary confirmation
and guidance for the task.
Channel Geometry
Increases in channel width or width:depth ratio are
commonly associated with increases in bed-material
load (Lyons and Beschta, 1983; Schumm, 1985), but
sediment load cannot be interpreted from width by
itself because other factors (depth, slope, grain size,
bank strength, vegetation) mutually adjust to the
imposed flow and sediment load (Dietrich et al., 1989;
Eaton et al., 2004; Buffington, 2012). Without a generally applicable reference for channel width, and by
extension, channel planform, assessing sediment
impacts using channel width or width:depth ratio is
inconclusive. Moreover, decreases in width or width:
depth ratio can signal either an increase or decrease
in sediment supply. For example, both narrowing and
widening of stream channels has been observed below
dams (Williams and Wolman, 1984). In addition,
channel incision by gullying, debris-flow scour, or erosion of debris-jam deposits can increase downstream
sediment load, triggering local channel response that
is not indicative of general channel condition.
Bed-Material Texture and Bed Mobility
Adjustments among sediment supply, bed-material
texture, and the boundary shear stress exerted by
flow in gravel-bed channels provide a basis for evaluating sediment influences, while avoiding some of the
factors complicating variations in channel morphology. Gravel-bed streams usually contain a wide range
of bed-material sizes, including a fraction of fine sediment (mostly sand). Increases in sediment supply can
affect the grain-size distribution and mobility of the
bed surface in various ways, depending on the volume (rate) and texture of the input sediment. For
example, flume, numerical experiments, and field studies suggest that an increase in the rate of sediment
supply can fine the bed surface, rendering it more
mobile (Dietrich et al., 1989; Buffington and Montgomery, 1999b; Lisle et al., 2000; Pitlick et al., 2008).
However, supplied sediment may also be finer than
the river bed. Large inputs of sand not only directly
increase transport rates of sand but also mobilize the
gravel fraction (Iseya and Ikeda, 1987; Wilcock et al.,
2001; Curran and Wilcock, 2005; Venditti et al.,
SEDIMENT METRICS
Sediment load (the volume and particle size of sediment transported by a channel) is a primary influence
on channel condition, but it is difficult to measure
(Bunte and MacDonald, 1999). Sediment transport
measurements are impractical for rapid assessments,
and quantification of stored sediment available for
transport (an element of sediment supply) is complicated by the fact that alluvial channels are formed in
the sediment that they transport and store. Changes
in the supply of sediment can be expected to alter the
channel as it adjusts to transport the imposed
sediment load, although the magnitude and pace of
channel adjustments can be difficult to judge
(Schumm, 1985; Dietrich et al., 1989; Lisle et al.,
1993; Buffington and Montgomery, 1999b; Wilcock
and DeTemple, 2005; Eaton and Church, 2009; Pryor
et al., 2011; Buffington, 2012). Because of the
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2010). Changes in bed grain size depend on a balance
among the existing bed-material size, the sediment
supply rate and texture, the flow, and the transport
capacity of the stream channel (Wilcock, 2001) such
that different sediment metrics may be needed to
monitor the effects of different sediment supply
scenarios.
Several metrics have been proposed for gravel-bed
rivers that relate the volume (or rate) of sediment
supply to the degree of textural fining relative to a
reference grain size. Each of these metrics is an index
of bed mobility and transport rate, which, in turn, is
a measure of bed-load supply, if one assumes a quasiequilibrium state in which the channel has adjusted
to its supply. For example, Dietrich et al. (1989) propose that the degree of bed surface armoring and consequent bed mobility is related to the upstream
supply of bed material. They parameterize bed mobility in a dimensionless term q*, which is the bed-load
transport rate of the surface material normalized by
that of the load, and relate q* to equilibrium transport rates from flume studies. Values of q* range
from 0 to 1 (high to low bed-material supplies, respectively), with the reference grain size defined as the
median grain size (D50) of the load, which can be
approximated by that of the subsurface material when
bed-load transport observations are not available.
Another family of metrics that relate bed-material
size to sediment load is based on the concept of a
threshold channel in which the channel is assumed
to have a near-bankfull threshold for bed-material
entrainment. The reference grain size is typically
defined as the D50 of the bed surface and is predicted
by rearranging the Shields (1936) equation to solve
for the D50 that can be mobilized by the bankfull flow
(Dietrich et al., 1996; Olsen et al., 1997; Power et al.,
1998; Buffington and Montgomery, 1999a, b; Kappesser, 2002; Kaufmann et al., 2008, 2009). The difference between the predicted and observed D50 is a
measure of bed mobility at bankfull flow and can be
related to equilibrium transport rates (and thus bedmaterial supply) if boundary shear stress is corrected
for channel roughness (Buffington and Montgomery,
1999a). Similarly, Kaufmann et al. (2008) use the
ratio of observed to predicted grain size as an index
of sediment load, assuming a bankfull threshold
channel.
The threshold channel approach is limited to a certain class of rivers. It is a useful approximation of
mobility in gravel- and cobble-bed rivers (typically
plane-bed and pool-riffle channels), which have been
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shown to have, on average, a near-bankfull threshold
for motion (Leopold et al., 1964; Li et al., 1976;
Parker, 1978; Andrews, 1984; Buffington and Montgomery, 1999a; Buffington, 2012), although bed
mobility is only loosely associated with channel type
(Bunte et al., 2010, 2013). However, the approach is
inappropriate for both sand- and boulder-bed rivers
(dune-ripple, step-pool, and cascade morphologies),
because bed mobility in those channels generally does
not exhibit a bankfull threshold (Buffington and
Montgomery, 1999a; Bunte et al., 2010, 2013; Buffington, 2012). For example, the bankfull shear stress
in sand-bed channels can be more than 100 times the
critical shear stress (Dade and Friend, 1998; Parker
et al., 2003; Church, 2006; Buffington, 2012), indicating a high degree of transport at bankfull stage. Similarly, at bankfull stage, the mobility of the median
grain size systematically increases with channel slope
in coarse-grained rivers and outpaces slope-dependent increases in the critical Shields stress (Buffington, 2012), suggesting mobility at stages less than
bankfull in steeper channels or the need to correct
boundary shear stress for systematic increases in
roughness with greater slope (i.e., smaller values of
both the width-to-depth ratio and relative submergence) (Buffington and Montgomery, 2001; Buffington, 2012). Consequently, bankfull threshold grain
sizes predicted for sand- and boulder-bed rivers will
provide inappropriate references and metrics for
assessing sediment impairment. Furthermore, it
should be recognized that the notion of a bankfull
threshold channel is a simplifying construct based on
the central tendency among many rivers. Natural,
unimpacted gravel, and cobble rivers may have an
entrainment threshold at flows smaller or larger than
bankfull, depending on a range of variables including the rate and size of supplied sediment, the
flow regime, and the valley slope and confinement
(Mueller et al., 2005).
Although the threshold channel approach is limited in terms of basin-wide application, it may be
particularly relevant for assessing sediment impacts
in salmon-bearing streams because anadromous salmonids generally prefer gravel- and cobble-bed rivers
in which they can excavate redds (Montgomery et al.,
1999). In contrast, the q* approach may be more
robust in terms of application; it was developed for
gravel-bed rivers, but is not limited to threshold
channels.
There is a correlation between grain size and channel roughness (e.g., energy dissipation due to banks,
bars, wood, downstream changes in channel geometry; Buffington and Montgomery, 1999a), such that it
is important that the above metrics use boundary
shear stress corrected for roughness to avoid a false
indication of sediment loading (Buffington and Mont-
Textural Metrics Related to the Volume of BedMaterial Supply
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1992; Paola and Seal, 1995; Lisle and Hilton, 1999;
Dietrich et al., 2005).
Inferring watershed sediment supply from the concentration of fine sediment on streambeds is problematic. First, the abundance of fine material in
streambeds may not be sensitive to sediment inputs if
the inputs contain low concentrations of sand (Lisle
and Hilton, 1999; Montgomery and MacDonald,
2002), such that the fines are transported predominately in suspension over an armored bed. Second,
form roughness (e.g., large woody debris, boulders,
bars) can force variations in sand abundance independent of sediment load by creating wakes, eddies, and
pools where sand can deposit (Buffington and Montgomery, 1999a) and zones of high shear stress (e.g.,
riffles) where sand is winnowed. More intensive sampling can help overcome problems of heterogeneity
within a given channel reach, but variations in channel structure between sites complicate the establishment of a standard reference for sand concentration.
Spatial variation in fine-sediment concentrations
in gravel beds poses challenges to the precision and
repeatability of measurements and the comparison to
a meaningful reference. High variation in channel
texture requires intensive, unbiased sampling to
obtain reach-mean values of adequate precision, even
if surface sampling is restricted to certain areas of
the channel such as pool tails (Bunte et al., 2012).
The rapid assessment protocols used by EMAP,
AREMP, and PIBO all measure the percent of fine
sediment on the easily identifiable, but laterally variable wetted part of the bed surface, neglecting deposits of fines along the dry portions of the banks.
EMAP uses a visual estimate of particle-size class at
five points along 21 transects spanning the reach;
AREMP and PIBO protocols use grid counts on the
tails of the first 10 pools in a reach.
Temporal trends are best evaluated by repeating
the same field protocols (e.g., surface grid counts, surface pebble counts, and volumetric samples) at a particular site during every visit. However, measuring at
precisely the same point, transect, or area can introduce false variability if morphological changes cause
shifts in the depositional environment. For example,
a location that is a pool tail one year may become a
riffle crest the next. This can be partially offset by
sampling pool tails wherever they exist in a reach
from year to year, but the definition of a pool tail or
other morphological unit can be uncertain and influenced by the presence or absence of fines, thereby
introducing bias. Even if bias and spurious variation
can be reduced by careful selection of sampling sites,
channel heterogeneity (e.g., due to sharp bends or
large wood debris) can force variations in fine-sediment abundance between reaches independent of sediment load. For example, the bed surfaces of simple
gomery, 1999b; Kaufmann et al., 2008; Rickenmann
and Recking, 2011). Precise estimates of boundary
shear stress and characteristic grain size are necessary because small differences in these values can
correspond to large differences in particle entrainment, transport rate, and associated estimates of sediment loading (Buffington and Montgomery, 1999b).
These requirements may preclude determination of
the above metrics from rapid assessment protocols
because rapidly measured channel characteristics can
have large uncertainty due to the limited number of
samples, observer bias, and methodological differences between assessment protocols (Roper et al.,
2002, 2008, 2010; Whitacre et al., 2007; Bunte et al.,
2009, 2012).
Sediment metrics based on bed mobility relate sediment supply to transport capacity. Consequently,
these metrics are sensitive to changes in both bedmaterial supply and shear stress (Buffington and
Montgomery, 1999b), which may confound interpretation of sediment impairment from streambed texture.
Furthermore, the above metrics describe textural
response to altered rates (or volume) of bed-material
supply, but do not specifically address the supply of
fine sediment, which may be particularly detrimental
to aquatic habitats and characteristic of certain types
of anthropogenic disturbance (e.g., roads, grazing).
Textural Metrics Related to Fine-Sediment Loading
The abundance of fine sediment on the bed surface
is commonly the basis for metrics of sediment impairment. Fine sediment is often transported and locally
deposited at moderate flows that are unable to transport gravel (Jackson and Beschta, 1982; Bathurst,
1987; Beschta, 1987; Carling, 1988; Ashworth and
Ferguson, 1989; Wilcock, 1998; Hassan and Church,
2001; Wilcock et al., 2001). Because fine sediment is
commonly abundant in eroded soil mantles and its
residence time in streambeds is shorter than that of
the gravel framework, it can be a sensitive indicator
of sediment impact from watershed disturbances.
Moreover, fine material has a strong influence on
stream biota (Bjornn et al., 1977; Chapman, 1988;
Suttle et al., 2004; Cover et al., 2008). Fine sediment
is distributed nonuniformly over the surface and in
the subsurface of natural gravel-bed channels. Local
hydraulic conditions winnow fine sediment from some
areas of the bed and deposit it in others, commonly
forming patches of fine sediment in pools and eddies,
among large woody debris, and on the downstream
end of bars. Large supplies of fine sediment also create sandy patches on the bed surface and result in
reach-averaged bed-material size distributions having
distinct modes of sand and gravel (Lisle and Madej,
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STANDARDS AND REFERENCES
Judging sediment impairment involves comparing
values of one or more sediment metrics against a
standard or reference, which can take one of several
forms (Stoddard et al., 2006). All types of reference
have strengths and weaknesses, and the use of more
than one may improve the quality of site assessment
(Lisle et al., 2007).
An ecological threshold is a standard marking the
onset of harm to a resource that is measured or
indexed by the metric. Ecological thresholds can provide precise standards for harm. There are some
thresholds for sediment [e.g., the concentration of fine
sediment in salmonid egg pockets (e.g., Milan et al.,
2000)], but their values differ between affected
resources. In contrast to chemical pollutants, for
example, the mere presence of sediment is neither
indicative nor necessarily harmful, but rather influences factors that are important to aquatic ecosystems, such as hyporheic flow, dissolved oxygen,
turbidity, water temperature, and riparian vegetation.
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A pristine reference is the central tendency or
range of natural variability of sites that have experienced little human disturbance. Although local
human influence may be slight, the history of natural
disturbances (Reeves et al., 1995) and the influence of
background conditions (Lisle et al., 2007) can cause
the range of pristine conditions to overlap with those
where human impacts are significant (Lisle, 2002;
Diehl and Wolfe, 2010) and to exceed ecological
thresholds (Diehl and Wolfe, 2010).
A regional central tendency is the mean, median,
range, or some part of the frequency distribution of
values of an assessed metric. Regional central tendencies
provide
straightforward
comparisons
between a value at a given site and those from a
sample of sites in the same domain and can motivate a deeper analysis to explain significant deviations. Comparisons outside the domain are seldom
valid, so variations in regional conditions can only
be evaluated for the same region over time. The
regional approach offers a sliding scale that
accounts for differences between regions and avoids
imposing unrealistic goals based on absolute standards. However, if conditions are generally degraded
within a region, references and standards drawn
from the observed population of values may be poor
targets, and care should be taken to distinguish
“least disturbed” vs. “best attainable” conditions
when evaluating sediment impairment (Stoddard
et al., 2006).
Valid comparisons between measured sites and
regional central tendencies or pristine references
require comparing channels of the same general type
and using sediment metrics appropriate for that channel type. This enhances the sensitivity of the metric to
environmental influences while reducing spurious
variations between channels due to differences in
channel type and applicability of the metric (use in a
channel type for which the metric was intended).
Stratification of sites according to the background
factors that influence values of the metric can also
strengthen interpretations of regional variation.
A temporal benchmark compares observations at
the same site over time and is the basis for trend
monitoring. This well-proven referencing gives unambiguous trends in conditions, provided sampling is
adequate. Although an ecological threshold may be
lacking, time trends can establish whether conditions
are becoming more or less favorable. Temporal
benchmarks are applicable to both site and regional
assessments. However, lag times between sedimentgenerating disturbance (e.g., wildfire, road construction) and increased sediment loads in channels vary
widely between systems and can be as long as decades (Madej and Ozaki, 1996) or centuries. This can
make it difficult to establish background conditions
channels tend to maintain less fine sediment than
those of complex channels (Buffington and Montgomery, 1999a). These problems exist whether finesediment concentration is measured on the bed
surface or subsurface.
A fine-sediment parameter that can overcome the
problem of spatial variation of fine-sediment concentration in a reach (due to heterogeneity of surface
textures, hydraulic conditions, and channel structure)
is the fraction of pool volume filled with fine
sediment, or V* (Lisle and Hilton, 1992, 1999). A
flow-dependent scouring mechanism simultaneously
controls the volume of fines and the residual pool volume (that below the riffle crest) in each pool. Thus,
the ratio V* appears to be independent of pool size,
as well as local hydraulic conditions, e.g., gradient
(Lisle and Hilton, 1999). Variation in a reach can be
further minimized by selecting pools without large
wood or other complex roughness elements that tend
to trap fines. The remainder of the influences on V*
are sand supply rates and factors that characterize
background watershed conditions (e.g., geology, flow
regime), which can confound interpretations of variations in V* across geologic provinces (Sable and Wohl,
2006). The time required to measure V*, whose standard error can be computed on-site, typically exceeds
the time limitations of rapid assessments (a day or
less), depending on acceptable error (Hilton and Lisle,
1993).
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Such complexities and uncertainties can be
addressed through contextual analysis, which examines site history, physiography, and process linkages
to elucidate causes for the current channel condition.
Regarding sediment impairment, a contextual analysis would aim to explicitly link human activity to a
sediment-related condition of a channel. Common
examples of contextual analyses are cumulative
effects analyses (Reid and Dunne, 1996; Reid, 1998)
and watershed analyses (Montgomery et al., 1995;
USDA, 1995; Shilling et al., 2005), although these are
not limited to sediment-related issues. By evaluating
both cause and effect, a contextual analysis can
ask “How did it get this way” and can identify the
origins of sediment impairment, potentially guiding
management to improved outcomes. As a watershed
approach, it focuses on hillslopes and channel networks, as well as channel condition, and can be
adapted for a number of resources. The approach
does not rely on a formal or fixed protocol, but rather
employs a bottom-up inquiry into factors leading to
conditions at a site and/or a top-down inquiry into
the propagation of apparent watershed disturbances
downslope and downstream to affected sites. The goal
is to use the weight of the evidence to identify
the most important, site-specific cause-and-effect
mechanisms.
Some rapid assessments provide contextual analysis, but they are typically limited. The relative bed
stability index (RBS; Kaufmann et al., 1999, 2008,
2009), which is defined as the ratio of the geometric
mean surface particle size (Dgm) to the median grain
size predicted to be mobile at bankfull flow (D*cbf) in
a threshold channel, is an example of an analytical
reference approach that is correlated with basin disturbance. RBS was developed for regional assessments as an element within EMAP, but may be
applicable to site evaluations of sediment impairment
if more precise parameter measurements are conducted (Kaufmann et al., 2008). In regional applications, anthropogenic disturbance is quantified by a
combination of a riparian condition index, which is
evaluated at the stream measurement site using a
variety of visual scores and road density, which is
calculated from road coverage provided by the U.S.
Census Bureau (Kaufmann et al., 1999; USEPA,
2004; Peck et al., 2006; Kaufmann et al., 2008, 2009).
Disturbance category correlates weakly with values
of RBS and varies with basin lithology (Kaufmann
et al., 2008, 2009). However, evaluation of sources of
variation in RBS is reduced to categories of disturbance, rather than evaluation of watershed-specific
types of disturbance and process pathways. Furthermore, cause and effect are not directly established,
but only linked through correlation. Hence, the
approach provides limited contextual analysis and is
(Grant and Wolffe, 1991) or to detect a disturbance in
the watershed in time to remedy the problem before
it impacts the stream, unless monitoring extends
beyond the channel to the watershed (L.M. Reid and
M.J. Furniss, “On the Use of Regional Channel-Based
Indicators for Monitoring,” unpublished report,
USDA Forest Service, Redwood Sciences Laboratory,
Arcata, California, 1998).
An analytical reference is a theoretical value determined from relatively simple physical models that is
based on first principles of watershed and channel
processes (Dietrich et al., 1996; Power et al., 1998).
Deviations from predicted values can be used to
explore influences of factors not included in the
model. For example, observed values of surface D50
that are finer than those predicted by the threshold
channel model (an analytical reference) could reveal
influences of sediment supply or channel roughness
(Buffington and Montgomery, 1999a, b), whereas values of D50 coarser than predicted could reveal the
presence of lag material from landslides or rock falls.
Analytical references must be limited to the channel
type for which the theory applies. In general, the simplification involved in an analytical reference is so
severe that it is most appropriately used as a starting
point (e.g., a hypothesis to be tested) from which comparisons with field observations might motivate
further study. Comparison with an analytical reference alone is not sufficient to judge impairment.
CONTEXTUAL ANALYSIS
None of the reference types outlined above point
to the specific cause for a deviation from the reference, so comparison between observation and reference alone cannot be used to conclusively identify
impairment or its cause. An observed channel condition can result from multiple pathways and processes that may be human-caused or natural
(Table 1). For example, a streambed can become
finer by channel widening caused by trampled
banks, by decreased peak flows and reduced transport capacity downstream of a diversion, or by
increased sediment supply from debris flows. An
observation of finer bed material does not point to a
specific cause, nor does it necessarily indicate
impairment because either human or natural causes
may be involved. Moreover, a particular channel
reach may be fine grained due to a direct local disturbance (e.g., suction dredging, bank trampling,
and logging slash) rather than cumulative effects of
basin-scale disturbance, and therefore not representative of watershed condition.
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TABLE 1. Causal Linkages between Human or Natural Disturbance, Geomorphic Response, and Channel Change.
Human Cause
Natural Cause
Geomorphic Response
Logging, roads, urban development,
vegetation conversion, grazing,
off-road vehicles (ORVs) dam removal,
climate change
Water diversion, climate change
Grazing, ORV traffic
Gravel mining, ORV traffic, suction
dredging, grazing
Impoundments, grade control
structures
Habitat structures, logging slash
Wildfire, landslides, debris flows,
large floods, channel migration
Forest growth, stream capture
Meander migration
Intensive salmon spawning
Increased total sediment
input
Increased fine sediment
input
Decreased flow
Channel widening
Armor layer disturbance
Log jams, tributary deltas,
landslide deposits
Woody debris
Deposition from backwater
effects
Increased form roughness
Dams, watershed rehabilitation,
gravel mining
Gravel injections, hillslope disturbance
Decreased sediment input
Transbasin diversion, flow releases
Stream cleaning, channelization
Watershed recovery, debris flows,
log jams
Debris flows, landslides, tributary
inputs
Large runoff events
Scour by large floods
Causes for increased sediment
input (see above)
Grazing, dewatering of riparian
vegetation
Logging, development, roads,
channelization, climate change
Causes for increased sediment
input (see above)
Succession from sod to forest,
increased meandering
Wildfire, large floods, change in
flow regime
Increased sediment input
Causes for decreased sediment input
(see above), stream cleaning
Disturbance of fine-grained soils and
bedrock
Peak flow reduction below dams, finesediment inputs (see cause above)
Grazing, impacts leading to increased
runoff, removal of large wood from
channels
Causes for decreased sediment
input (see above), scour of wood
Volcanic ash eruptions
Channel incision from decreased
sediment input or roughness
Increased suspended sediment
to build banks
Riparian encroachment
Channelization, stream cleaning
Causes for increased sediment
input (see above)
Grazing, removal of woody riparian
vegetation, desiccation of riparian
vegetation by water withdrawals
Debris flows and floods
Causes for increased sediment
input (see above)
Bank erosion by floods, natural loss
of riparian vegetation
Loss of scour elements
Increased sediment input
Habitat structures, logging debris,
blowdown of riparian buffers
Causes for decreased sediment
input (see above)
Suction dredging
Wood inputs, debris flows and
landslides
Causes for decreased sediment
input (see above)
Gain in scour elements
Fine-sediment inputs (see
cause above), reduced peak flows
Steep landscapes with fine-grained,
cohesive sediments
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Finer surface grain
size
Coarser surface
grain size
Inputs of coarse sediment
Increased flow
Decreased form roughness
Channel widening
Weakening banks
Increased peak flow
Channel narrowing
Gullying
Decreased pool
frequency and/or
volume
Channel widening
Decreased sediment input
Increased pool
frequency and/or
volume
Direct effects
best viewed a first-order estimate of the causal linkages for measured sediment impairment, as recognized by Kaufmann et al. (2008). Moreover, the
riparian and watershed indices may not be independent of channel type. For example, absence of
large-diameter riparian trees (an indicator of human
disturbance in the EMAP approach) is a common
phenomenon for streams passing through fields and
meadows, and may have little to do with recent
watershed disturbances.
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JUDGING SEDIMENT IMPAIRMENT
Regional Assessments
Whether or not to incorporate contextual analysis
in a regional assessment of sediment impairment has
a strong influence on sampling strategy, interpretation of results, and the degree of uncertainty of judgments. The absence of a contextual analysis in a
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establish baselines from which to design site-specific
monitoring of recognized stressors and sensitive
channel metrics, without the need to revisit the
analysis in detail later. Moreover, lengthening the
schedule may hold little risk for trend monitoring,
since significant changes from one year to the next
are unlikely given long lag times of sediment routing
in drainage basins and long recurrence intervals
between geomorphic events that can trigger large
sediment inputs (e.g., flooding or post-fire debris
flows). According to this strategy, sites in AREMP
and PIBO are revisited on a rotating schedule spanning five years (Henderson et al., 2004; Gallo et al.,
2005). An impediment to using a contextual analysis
can be an access to information and observations of
basin conditions, particularly in locations with mixed
public/private ownership.
Although rapid assessment and contextual analysis
differ in approach, they can be combined in a complementary, two-tiered strategy for assessing sediment
impairment. For example, rapid assessments can be
used as a coarse (first-tier) analysis to identify sites
that deserve a deeper contextual assessment (secondtier analysis), provided that uncertainties of the rapid
protocol are such that change and degree of impairment can actually be detected. This strategy would
streamline contextual analyses by targeting their use
in specific locations, thereby optimizing the utility of
a large sample of sites (rapid assessments) and
strengthening regional interpretations of trends
through contextual analysis. Some land management
agencies implement such multilevel approaches, in
which rapid assessments may be followed by detailed
studies (e.g., Peck et al., 2006; Csiki, 2010).
regional assessment of sediment impairment imposes
a weak link between human disturbance and
resource impairment and reflects a shift in management strategy from watershed analyses advocated in
the 1990s to status-and-trend monitoring that is currently in use by management agencies in the U.S.
Some compensation can be gained by screening or
stratifying regional values by characteristics of channels and valleys (classification, drainage area or
order, confinement) and basins (climate, geology,
physiography). Screening for some human influences
such as dams can be used to avoid competing effects
on channel response variables (Table 1), and sampling can be designed to target sensitive resources
(e.g., fish habitat) to reduce the number of linkages
between human activities and impacts. These selection criteria can help constrain the possible pathways
between human impacts and channel response. The
time that would otherwise be devoted to a contextual
analysis can be spent on measuring more sites and
conducting replication. However, the necessary
assumption that human activity is responsible for
variations in channel condition is difficult to test
without the explanatory information provided by
contextual analyses.
Regional sediment metrics can be used to assess
status (good vs. poor) and trend (increasing, decreasing, no change) of the associated resource. However,
because causal pathways of disturbance are not
established, land managers and policy makers cannot defensibly use this information to prescribe
specific treatments or level of effort. Hence, rapid
assessments and their resultant status-and-trend
values provide an initial assessment, akin to a canary in a coal mine, but provide little or no causeand-effect understanding needed for remediation.
The purpose of contextual analysis is specifically to
identify causes and pathways for sediment impairment, such that appropriate remedies can be developed. Site- and basin-specific courses of action could
then be integrated to inform regional programs and
policies for addressing the identified sediment
conditions.
Inclusion of contextual analysis in an assessment
of sediment impairment establishes the linkages
between human disturbance and channel condition
and between channel condition and resource viability, and thereby allows judgment of sediment impairment at each site independently of others, but
requires more detailed measurements and a deeper
analysis at each site than is afforded by rapid assessments. Assuming fixed resources for monitoring,
the cost of more time devoted to each site is fewer
sites visited in a region or a longer time between
successive visits. However, contextual analyses can
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Assessments at Individual Study Sites
At the site scale, there are even greater needs
and opportunities to use a contextual analysis to
design a monitoring program and interpret its
results. Contextual analysis is particularly useful for
selecting monitoring parameters and protocols appropriate to local conditions, providing increased flexibility compared to the fixed metrics used in rapid
regional assessments. Although consistent monitoring, over time, can demonstrate change at a site,
contextual analysis is needed to identify causal relations and the most appropriate monitoring metrics.
Monitoring with a contextual analysis at any scale
can go beyond judging sediment impairment by providing constructive answers to essential management
questions: (1) How did it get this way? (2) What is
the trajectory of change? (3) How can management
affect the trajectory?
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Extensive stream monitoring in the western U.S.
is undertaken to establish status and trends for
threatened and endangered salmonids and their ecosystems. The methodology uses rapid assessment protocols to monitor a large number of sites. Although
there are compelling reasons to use a repeatable, efficient, and quick monitoring protocol, we question
whether the approach is sufficient. The question we
address in this study is: can we judge sediment
impairment accurately and meaningfully with rapid
assessments? We contend that rapid assessments, on
their own, have limited value due to their demonstrated uncertainty and to the fact that they do not
directly link cause and effect in a way that allows
land managers to develop defensible sediment mitigation or remediation plans.
(1) Can rapid assessment be used to accurately
judge sediment impairment in a region? Rapid assessments allow a large number of sites to be sampled
across a region. If conducted for a sufficient length of
time, consistent monitoring of this type can indicate
change. However, such monitoring cannot conclusively indicate sediment impairment because the variability in natural stream conditions is large and the
same stream condition may be caused by different
drivers. More important, an indication of channel
condition cannot provide information on the cause of
that condition, providing little defensible basis for
taking corrective action. An analysis of cause and
effect, termed here contextual analysis, is needed to
interpret monitoring results and guide future action.
Broad correlations between, for example, land use
and stream sediment grain size are too weak to
provide explanation or guidance.
Rapid assessment monitoring and contextual
analysis are different approaches, but complement
each other well. Rapid assessment can indicate
change (if repeat samples are collected) and can be
used to find sites that deviate from expected conditions. These sites can then become a focus for closer
analysis. Contextual analysis can provide a basis for
evaluating monitoring results and guiding the selection of monitoring variables. But the main purpose of
contextual analysis is to link cause and effect such
that the reasons for impairment can be determined
and appropriate remedial actions taken.
Contextual analysis may compete for resources
with rapid assessment monitoring. A balance between
the two is needed to provide information that is reliable, empirical, understood, and actionable. Rapid
assessment and contextual analysis can be combined
in a two-tiered effort that capitalizes on the strengths
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GRAVEL-BED STREAMS? A COMMENTARY
of each approach (large sample size vs. in-depth
analysis of cause and effect).
(2) Can rapid assessment be used to accurately
judge sediment impairment at a particular site?
Assessment and remediation for projects at individual
sites often provide sufficient resources and time such
that monitoring can be more detailed and tailored to
local conditions. The strong constraints of a regionally fixed protocol are appropriately relaxed to make
observations most appropriate to the problem at
hand. Contextual analysis plays a key role in determining how human influences on the watershed scale
may influence local channel processes. Such an
approach will be much more valuable to a manager
than a rapid judgment of whether or not the resource
is impaired. Due to their large uncertainty, rapid
assessment protocols are rarely appropriate at the
site scale for judging sediment impairment, requiring
refinement of techniques for site analysis (Kaufmann
et al., 2009). Much more valuable information can be
gained by designing an assessment that suits the
targeted watershed and can expand the scope beyond
sediment impairment.
CONCLUSIONS
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ACKNOWLEDGMENTS
John Potyondy encouraged the authors to write this manuscript
and provided constructive comments for an earlier draft. Additional
comments from three anonymous reviewers further improved the
manuscript. Funding comes, in part, from the U.S. Forest Service
Stream Systems Technology Center.
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JOURNAL
OF THE
AMERICAN WATER RESOURCES ASSOCIATION
CAN RAPID ASSESSMENT PROTOCOLS BE USED
TO
JUDGE SEDIMENT IMPAIRMENT
OF THE
AMERICAN WATER RESOURCES ASSOCIATION
GRAVEL-BED STREAMS? A COMMENTARY
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