ArticlePDF Available

Risk Management of Sediment Stress: A Framework for Sediment Risk Management Research

September 2005
Environmental Management 36(2):175-94

Source
PubMed

Authors:

United States Environmental Protection Agency

Research related to the ecological risk management of sediment stress in watersheds is placed under a common conceptual framework in order to help promote the timely advance of decision support methods for aquatic resource managers and watershed-level planning. The proposed risk management research program relies heavily on model development and verification, and should be applied under an adaptive management approach. The framework is centered on using best management practices (BMPs), including eco-restoration. It is designed to encourage the development of numerical representations of the performance of these management options, the integration of this information into sediment transport simulation models that account for uncertainty in both input and output, and would use strategic environmental monitoring to guide sediment-related risk management decisions for mixed land use watersheds. The goal of this project was to provide a sound scientific framework based on recent state of the practice in sediment-related risk assessment and management for research and regulatory activities. As a result, shortcomings in the extant data and measurement and modeling tools were identified that can help determine future research direction. The compilation of information is beneficial to the coordination of related work being conducted within and across entities responsible for managing watershed-scale risks to aquatic ecosystems.

Conceptual linkages among anthropogenic sources of sediment stress and aquatic ecosystem health.

…

Examples of common BMP alternatives and a general continuum for the relative differences among them in characteristics related to sediment stress mitigation.

…

Conceptual diagram of a field-scale simulation model for sediment management that incorporates BMP alternatives and allows for the calculation of cost effectiveness within the context of water body recovery.

…

Primary sediment parameters to consider in a model of BMP performance, C=sediment concentration; S=settling rate; R=resuspension; D=decomposition of transportable solids; A=consolidation; H=depth; d=distance; v=velocity.

…

State of the practice and properties of existing models for simulating BMP performance. Previously cited models are referenced in Figure 3 or in the text. Arrows indicate process calculations on left are incorporated in more complex models on right.

…

Figures - uploaded by Christopher T Nietch

Content may be subject to copyright.

Content uploaded by Christopher T Nietch

Content may be subject to copyright.

PROFILE

Risk Management of Sediment Stress: A Framework

for Sediment Risk Management Research

CHRISTOPHER T. NIETCH*

U.S. EPA, Office of Research and Development

National Risk Management Research Laboratory

Water Supply Water Resources Division

Water Quality Management Branch, 26W MLK

Cincinnati, Ohio 45268, USA

MICHAEL BORST

U.S. EPA, Office of Research and Development

National Risk Management Research Laboratory

Water Supply Water Resources Division

Urban Watershed Management Branch

2890 Woodbridge Ave

Edison, New Jersey 08837, USA

JOSEPH P. SCHUBAUER-BERIGAN

U.S. EPA, Office of Research and Development

National Risk Management Research Laboratory

Land Remediation and Pollution Control Division

Aquatic Stressors Branch, 26W MLK

Cincinnati, Ohio 45268, USA

ABSTRACT / Research related to the ecological risk

management of sediment stress in watersheds is placed

under a common conceptual framework in order to help

promote the timely advance of decision support methods

for aquatic resource managers and watershed-level plan-

ning. The proposed risk management research program

relies heavily on model development and verification, and

should be applied under an adaptive management ap-

proach. The framework is centered on using best man-

agement practices (BMPs), including eco-restoration. It is

designed to encourage the development of numerical

representations of the performance of these management

options, the integration of this information into sediment

transport simulation models that account for uncertainty in

both input and output, and would use strategic environ-

mental monitoring to guide sediment-related risk man-

agement decisions for mixed land use watersheds. The

goal of this project was to provide a sound scientific

framework based on recent state of the practice in sedi-

ment-related risk assessment and management for re-

search and regulatory activities. As a result, shortcomings

in the extant data and measurement and modeling tools

were identified that can help determine future research

direction. The compilation of information is beneficial to the

coordination of related work being conducted within and

across entities responsible for managing watershed-scale

risks to aquatic ecosystems.

Nonpoint source (NPS) pollution related to sedi-

ment initiates when land use transformation causes a

change in soil erosion on hillslopes and/or alters pat-

terns of ﬂuvial sediment transport due to changes to

channel ﬂow regime. The later destabilizes channel

geomorphology producing in-stream erosion. The ero-

ded material increases the chance of bed aggradation

downstream. Therefore, the relationship between hills-

lope sediment supply and channel ﬂow controls sedi-

ment transport (Lane 1955). Sediment stress occurs as

the result of aquatic habitat disturbance in the form of

changes in bed and bank sediment composition and

light regime from high suspended solids concentrations

(a.k.a. excess turbidity). Through biological and chem-

ical feedback mechanisms, the ecological integrity of the

aquatic environment is compromised.

Stress related to sediments was the leading cause of

impaired rivers in the 1998 analysis of U.S. water

impairment patterns, with 40% of the assessed river-

miles appearing stressed due to alteration in natural

sediment processes (U.S. Environmental Protection

Agency [USEPA] 2000a). Sediments are the third

leading cause of stress for lakes, reservoirs, and ponds,

behind nutrients and metals. NPS agricultural and ur-

ban runoff and hydromodiﬁcation are the leading

sources of sediment stress. Aside from returned irri-

gation water in agricultural areas, rainfall runoff (i.e.,

stormwater) is the main mechanism for sediment stress

transfer to surface waters. These conceptual linkages

among anthropogenic activities, stress-related phe-

nomena, and ecosystem impairment are depicted in

Figure 1.

KEY WORDS: Sediment stress; Risk Management; Best manage-

ment practices; Models; Water quality protection;

Sediment transport; Erosion

Published online July 7, 2005.

*Author to whom correspondence should be addressed, email:

nietch.christopher@epa.gov

Environmental Management Vol. 36, No. 2, pp. 175–194 ª 2005 Springer Science+Business Media, Inc.

DOI: 10.1007/s00267-004-0005-1

Sediment accounts for 18% of the stress in im-

pacted water bodies under the total maximum daily

load (TMDL) program (USEPA 2000b), equating to

an annual cost estimate that ranged between $162

million and $576 million for program implementation

over 8 to 13 years. These costs do not include sedi-

ment TMDL development, which was estimated to

vary from $26,000 to more than $500,000 each

(USEPA 2001a). Additional costs include pre and post

water quality monitoring to support the development

and implementation. The United States Environ-

mental Protection Agency (USEPA) suggests, how-

ever, that these costs may be signiﬁcantly reduced

under a watershed-based risk management approach

(see Mitchell and others 1996 for reference to risk

analysis). For effective sediment risk management,

science-based strategies must be developed to deal

with the episodic and elevated sediment delivery

occurring with land use/land transformation and

chronic instability in ﬂuvial bed- and channel bank-

forms resulting from hydrological modiﬁcations with-

in watersheds.

Although erosion management research has been

active in agricultural regions since the 1930s, little of

this work has successfully transferred to dealing with

erosion processes in suburban and urban areas. In-

deed, the relative effectiveness of commonly used

management strategies (so-called BMPs or eco-resto-

ration) developed within the constraints of one land

use type may not transfer to another (e.g., riparian

buffers for rural and urban stream restoration). Eval-

uating ecological degradation within the context of

coupled sediment/ﬂow changes and subsequent geo-

morphic effects is beginning to receive recognition as

an invaluable assessment strategy (Rosgen 2001a).

However, this represents a relatively new initiative that

has been, thus far, addressed predominately by urban

stormwater management (e.g., Roads 1995). As popu-

lation grows, transportation improves, and new tech-

nologies for food production allow for spatial

concentration of crops, watershed land use becomes

more heterogeneous. Hence, risk management must

address sediment related stress within a mixed land use

context.

Figure 1. Conceptual linkages among anthropogenic sources of sediment stress and aquatic ecosystem health.

176 C. T. Nietch and others

A framework for addressing critical needs for man-

aging sediments in impacted watersheds was devel-

oped, and is presented herein, with an abbreviated

literature review to provide background on research

outlined. The framework relies heavily on model

development and veriﬁcation, is applied under an

adaptive management approach; centered on using

BMPs (including eco-restoration methods), the num-

erical representation of their performance, the inte-

gration of this information into sediment transport

simulation models, and strategic environmental moni-

toring to guide sediment risk management decisions in

mixed land use watersheds.

In the explanation of this framework, several exist-

ing soil erosion and sediment transport models are

cited. While much effort was made to provide a state-of-

the-practice picture of the ﬁeld of sediment modeling

as it relates to ecological condition, the citation of any

given model serves as an example, and is not meant to

imply any qualiﬁcation regarding its usefulness or

predictability. Even though some attention is given to

relative modeling capabilities with respect to speciﬁc

processes, this is not a model evaluation paper. Rather,

and in an integrative manner, a conceptual model for

sediment-related decision support was born as a prod-

uct of reviewing the sediment stress issue. This inte-

grative framework for sediment risk management

activities in watersheds can be used for the justiﬁcation

and direction of future modeling studies and the

coordination of related research projects and regula-

tory activities being conducted within and across

entities responsible for both risk assessment and man-

agement.

Sources of Sediment Stress

Changes in hillslope sediment load and in-stream

sediment erosion can occur simultaneously in water-

sheds to promote stressed conditions. NPS-related

anthropogenic activities affecting these natural sedi-

ment processes can be separated into two broad cate-

gories including land-based (effecting hillslope and

hydrologic loading processes) and water body-based

(effecting hydraulic and transport processes) sources.

It is popular for watershed managers to classify the

land-based sources with respect to land use, providing

linkage to broad spatial constructs with correlative so-

cial, economic, and political boundaries. General ur-

ban lands can be separated from nonurban, rural

lands, referred to here as agriculture–silviculture–rural

(ASR), based partially on the dominant pathways for

eroded sediment transporting from hillslopes to sur-

face waters. For ASR lands, hillslope sediments are

delivered to surface waters as sheet, concentrated base-

irrigation, return-drainage, tile drainage, and unsew-

ered-ditched ﬂow. Hillslope sediment loads to urban

water bodies are delivered via storm sewers and man-

made drainage channels (a.k.a. diffuse sediment pol-

lution). Although surface mining operations can be

signiﬁcant sediment sources in speciﬁc watersheds, this

activity lends itself to point source management and is

excluded here. Of the approximately 1.5 billion acres

of classiﬁed land in the United States, agricultural-re-

lated use accounts for 47%, while forested land com-

prises 20% and urban land 5% (National Resource

Conservation Services [NRCS] 1992).

Given the extent of agricultural land, it is not sur-

prising that sediment stress within it has been cited as

the leading source of water quality impairment in

streams and lakes (USEPA 2000a). Elevated hillslope

sediment loads are considered a greater contributor to

stress compared to in-stream erosion. The hillslope

sediments from agricultural lands may have associated

stressors such as nutrients from fertilizers, pesticides,

and toxics. Agricultural practices used to increase

productivity and economic returns from crop cultiva-

tion and that effect sediment yield (Tapia-Vargas and

others 2001) result in erosion rates ranging from 100

to 4000 kg Æ 10

(Novotny and Olem 1994).

Additionally, exacerbated soil erosion occurs on poorly

managed pasture, rangeland, and silviculture land that

does not maintain adequate vegetation cover to ame-

liorate rainfall erosivity.

For comparison, in urban lands the dominant hills-

lope sediment source originates from erosion of ex-

posed soil in construction areas and can reach values as

high as 50,000 kg Æ 10

(Novotny and Olem

1994). Street dirt accumulation and washoff also con-

tributes to the hillslope sediment load from impervious

surfaces after development. While the relative load

magnitude of the latter may not be as great, an altered

particle size distribution and bound toxins offer dif-

ferent, but potentially significant, mechanisms for stress

delivery to aquatic ecology. In contrast to agricultural

lands, however, and because of the overriding hydro-

logical modifications caused by imperviousness, in the

urban setting in-stream erosion is often considered as

the predominant mechanism causing sediment stress.

In fact, there are several land-based anthropogenic

activities that lead to watershed-scale hydrological

modiﬁcations that decrease rainwater inﬁltration and

depressional storage. This changes the duration and

frequency of ﬂows with geomorphic signiﬁcance (i.e.,

signiﬁcant to sediment transport) (McCuen and Mo-

glen 1988, MacRae 1996), resulting in elevated in-

stream erosion. These activities include, for example,

Risk Management of Sediment Stress 177

ditching and tiling to improve cropland drainage,

riparian buffer elimination, other wetland losses on

ASR lands, and the urban environment’s impervious

surfaces (pavement and roof-tops). The increased sur-

face runoff is represented by narrower discharge hy-

drographs (Hollis 1975). The decreased inﬁltration

reduces groundwater recharge, reducing baseﬂow

conditions (Simmons and Reynolds 1982, Booth and

Reinelt 1993). Combined, these effects produce ﬂash-

ier, less predictable channel ﬂows that upset the

established sediment equilibrium and cause geomor-

phic alterations leading to sediment stress from chan-

ges to sediment transport capacity (Booth and Jackson

1997, Trimble 1997, Ashmore and others 2000, Rosgen

2001b).

Finally, anthropogenic activities that take place

within a water body rather than on the hillslopes

draining to the water body are categorized as hydro-

modiﬁcations (USEPA 1993). These activities directly

affect in-channel sediment transport by ﬂow alteration

and/or changing sediment load along the channel

network and have been given such programmatic de-

scriptors as channelization and channel modiﬁcation,

dam construction and operation, dredging and boat-

ing, and streambank modiﬁcation and destabilization.

Hydromodiﬁcation has traditionally been regulated

through state environmental ofﬁces or the Corps of

Engineers. Compared to the indirect effects of land use

practices on surface waters, the uncertainty in manag-

ing these activities is not as great. Hence, future risk

management research should focus primarily on the

sources deriving from land use change.

Due to the episodic nature of excess sediment

loading, usually occurring during rain events, eroded

material is often added in ‘‘slugs’’ to a receiving

channel. After large loading events these slugs of sed-

iment can take long periods to travel downstream,

progressing in a staggered manner during rain events.

This phenomenon adds a legacy component to iden-

tifying the source of sediment stress. Hence, the par-

ticular source of sediment stress relative to a speciﬁc

location in a receiving-water may have occurred much

earlier pending the location of the identiﬁed impact

relative to the source and the interim climatic condi-

tions. This legacy effect adds to the difﬁculty in iden-

tifying sources of sediment stress for management.

Effects of Sediment Stress

Sediment stress can be broadly classiﬁed as a change

in sediment load coming from somewhere (hillslopes

and/or channel beds and banks) within a watershed at

sometime, it has an explicit spatial reference within a

drainage network (e.g., impacted stream reach, lake, or

estuary) and negatively affects aquatic ecology. The

ecological effects of sediment stress are manifest most

commonly as decreased biotic integrity due to distur-

bance or loss of habitat and/or changes to water clarity

(i.e., excess turbidity) (Figure 1). A non-biotic-related

effect that needs mention and has important implica-

tions to the socioeconomics of watershed management

is that of sedimentation in managed impoundments.

This results in increased filling rates and difficulties for

the extraction of drinking or irrigation water (Ackers

and Thompson 1987). However, future research re-

lated to sediment risk analysis currently places

emphasis on the less certain ecological effects.

Channel-bed scour and -bank erosion directly affect

the loss of habitat used during the different life stages

of ﬁsh, invertebrates, algae, amphibians, or birds

(Platts and others 1983, Rinne 1988, Pitlick and Van

Steeter 1998). Severe bank erosion widens channels

and may remove the shading effect of overhanging

vegetation on stream temperature regulation. Sub-

sequent indirect effects occur upon deposition of this

eroded/suspended sediment, resulting in the clogging

of interstitial spaces between substrate elements of the

streambed (increasing embeddedness) (Berkman and

Rabeni 1987). The habitat loss results from an overall

reduction in streambed heterogeneity, disrupting via-

ble spawning grounds for important species such as

salmon. Benthic invertebrates are also affected (Wil-

liams and Feltmate 1992), which alters the food web

and can eventually result in an overall decline in ﬁsh

diversity and abundance (Peterson and others 1992).

The excess sedimentation can change important bed-

water column biochemical exchanges with ecological

feedback.

Concomitant to sediment-related habitat losses is

the direct effect of excess turbidity on aquatic biota.

High suspended solids concentrations caused by in-

creased hillslope sediment load or channel erosion/

resuspension can affect predation success of secondary

consumers and cause irritation to the mucosa lining

the gills of these and other aquatic organisms (Och-

umba 1990, Ewing 1991). Excess turbidity also alters

patterns of primary production by affecting light

availability for photosynthesis. Changes in turbidity can

shift conditions for phytoplankton and other aquatic

ﬂora from nutrient- to light-limited (Pennock and

Sharp 1994), which can affect dissolved oxygen

dynamics and net stream metabolism. Excess turbidity

is thought to play a major role along with nutrient

overenrichment in the loss of sea grasses in Chesa-

peake Bay through this mechanism (Short and Wyllie-

Echeverria 1996).

178 C. T. Nietch and others

The overall effect of excess turbidity on primary

production can be complex. For example, it has been

suggested that controlling sediment to decrease tur-

bidity in areas of the Hudson River may result in a

switch to a nutrient-stimulated algal bloom problem as

light limitation decreases (Howarth and others 1991).

Finally, excess turbidity may alter the nutrient/toxin

biogeochemistry of aquatic ecosystems by affecting

dynamics of adsorption and desorption, cycling, and

microbial metabolism. Excess turbidity, in general,

tends to be transient in streams while becoming

chronic in the more quiescent waters of reservoirs,

lakes, and estuaries where suspended solids from

multiple sources concentrate and transport is reduced.

Perspectives for Sediment Stress Management

To date, a substantial effort has been placed toward

managing sediment stress in impacted watersheds. For

example, in agricultural lands, conservation tillage

(Mueller and others 1981) has signiﬁcantly decreased

estimated soil erosion since 1982 (NRCS 2003) and has

been reported to play a major role in improving the

water quality of Lake Erie (WET 2001). Other exam-

ples include maintaining streamside vegetation buffers

to reduce the impact of clear cutting on water yield and

sediment ﬂux in lands under silviculture (Arthur and

others 1998). Implementing a suite of rangeland

BMPs, such as exclusion zones, resulted in a 49%

reduction in turbidity in one watershed: Morro Bay,

California (Lombardo and others 2000).

Similarly, erosion and sediment control has been a

focus of risk management researchers in urban areas

for sometime. For example, as early as 1970, the

Department of the Interior began urging states to give

special attention to urban soil erosion and sediment

control in their compliance efforts by providing guid-

ance to local governments on implementing urban

sedimentation control programs (NACRF 1970). Work

done by the USEPA, the state of Maryland, and in

cooperation with the Departments of Transportation

and Agriculture culminated in publication of an

audiovisual sediment control-training program in 1976

to provide guidance for new development projects

(Mills and others 1976). However, the effective imple-

mentation of such guidance into practice by the land

development community has been slow coming. For

example, Paterson (1994) found that nearly 25% of

commonly prescribed construction-site BMPs had not

actually been implemented in a survey conducted in

North Carolina. Those plans that are followed are of-

ten carried out ineffectively (Barret and others 1995).

Attempts have been made to alleviate this issue, by

attending to the simulation of construction site erosion

for BMP design purposes and by considering the

inclusion of this process in large-scale stormwater

management models (e.g. Huber and Dickinson 1988).

However, large uncertainties in the simulated output

remain, currently making these tools impractical for

erosion planning and implementation programs.

Erosion control practices, in general, can come with

considerable economic impact. One statistic suggests

that for every $50 spent on erosion control at construc-

tion sites, taxpayers could save $500 spent on down-

stream dredging costs (Pennsylvania Department of

Environment Protection [PDEP] 1998), while Chang

and others (1994) estimated a national $42 million de-

crease in net cropland returns for the coastal zone

drainage basin resulting from proposed regulations for

enhanced erosion management. The alternative cost

beneﬁt to coastal ﬁsheries, in this case, although very

difﬁcult to estimate, was not mentioned. The discrep-

ancy in these cost–beneﬁt relationships highlights the

need for more effective ecological risk analysis.

Sediment Risk Management Research

The ﬁeld of NPS sediment-related risk management

can be represented by an iterative, self-reinforcing

information ﬂow scheme designed for achieving

appropriate risk management decisions, which will be

explained in the context of providing an organizing

framework for ongoing, planned, and future research

(Figure 2). The prescribed research supports imple-

mentation of USEPA’s stormwater regulation, specifi-

cally, Phase II rules of the national pollution discharge

elimination (NPDES) program under the Clean Water

Act, including the options to specifically address

stormwater discharges from construction sites (USEPA

2004) and the source water protection provisions un-

der the amended Safe Drinking Water Act. Addition-

ally, the research conducted under the framework

supports the USEPA mission under goal 2 (clean safe

water), goal 8 (sound science), and the implementa-

tion phase of the TMDL program for water bodies

impaired by sediments.

The primary question a sediment risk management

research program in watersheds is designed to address

is, ‘‘What is required for quantitative and effective wa-

tershed management of sediment stress?’’ To answer

appropriately, an understanding is needed of the nat-

ural dynamics of sediment in water bodies in relations

to ecological integrity, how these dynamics change

under different ﬂow regimes, and how various man-

agement strategies affect a given level of stress on a

watershed-wide basis. The last category of work pre-

Risk Management of Sediment Stress 179

cisely distinguishes sediment risk management from

risk assessment. Where risk assessment science works to

establish technically sound sediment criteria designed

to answer the question, ‘‘How much sediment in a

body of water is too much?’’ risk management science

develops methods for watershed planners to achieve

and maintain the desired sediment criteria for func-

tional aquatic ecosystems. The framework (Figure 2)

integrates the products of risk assessment and man-

agement science for developing decision support tools.

Based on the review of the literature, four stages are

envisioned to be necessary for quantitative watershed

risk management planning. In succession, they provide

a research framework that promotes the development

of decision support tools: (1) the ability to quantify

sources of sediment stress in space and time, (2)

determination of the best management practice and

location to reduce or remove the stressor sources (3)

linking the source descriptions with BMP performance

over multiple scales for simulation and decision sup-

port, and (4) evaluation of decisions and development

of the ability to adapt to future changes in both the

physical and the socioeconomic structure of a wa-

tershed. A scientiﬁc approach to accomplishing these

steps is to develop and evaluate sediment simulation

models over multiple scales and the accompanying

uncertainty in their output to help guide management

decisions. Overall, risk management research should

strive to develop techniques and approaches to allow

community-based planners to select cost-effective

solutions to restore and protect receiving water quality

from sediment stress in mixed land use watersheds

within a predictable time.

Allocation of Sediment Sources in Space and

Time

The ﬁrst step in developing a sediment stress man-

agement plan is to allocate sediment loads among

sources in a watershed. To allocate sediment stress

among the possible sources, models for (1) hillslope

soil erosion and overland transport to water bodies

(sediment loading models), (2) sediment fate and

transport within water bodies as they relate to changes

in ﬂow regime and sediment supply, and (3) spacio-

temporally linked loading and channel sediment

transport models for simulation have to be developed

and/or evaluated. Example of such models are pro-

vided in Figures 3A, B, and C, respectively.

Before reviewing the contextual aspects of extant

models it is important to consider the interaction be-

tween climatic conditions and spatially explicit sedi-

mentary characteristics as primary environmental

factors controlling sediment processes in watersheds.

On a continental scale this interaction supersedes

anthropogenic effects on erosion and transport pro-

cesses and, therefore constrains the lower bound of a

condition of sediment stress. Applying the ecoregional

concept to account for this higher-order factor in

determining relevant levels for management appears

promising (see Omernick 1995). For example, Simon

and others (2004) using extant sediment monitoring

data demonstrated the use of the ﬂow that occurs, on

average, every 1.5 years (Q

1.5

) as a measure of effective

discharge for suspended-sediment transport. Applying

the Q

1.5

concept at the level III ecoregion scale pro-

duced sediment ‘‘reference’’ values spanning four or-

ders of magnitude. National regulatory authorities

recognize that water quality standards and the gener-

alized models for allocating sediment stress to develop

plans for meeting those standards must account for

these regional differences in climate and sedimentary

characteristics. Such differences alone may drive future

decisions about sediment management and need to be

accounted for in the data input to stressor source

allocation exercises.

Another modeling issue to consider before

embarking on sediment source allocation exercises is

akin to what has been described as the uniqueness of

place issue in hydrological modeling (Beven 2000).

Management plans directed at the watershed scale

Figure 2. Framework for sediment risk management re-

search and development of a decision support system within

an adaptive management context.

180 C. T. Nietch and others

have to deal with the unique characteristics afforded by

the watershed in question. Presently, due to limitations

in measurement technology, it is nearly impossible to

capture this uniqueness of place in process-level mod-

els. What follows then is calibration of a model with

observed data and that subsequent predictions must be

associated with uncertainty. This is the approach lar-

gely adopted by the TMDL program in the United

States, in which the output uncertainty with respect to

maximum load is qualitatively associated with a margin

of safety factor. Beven and others (2001) offer an ap-

proach to dealing with this uncertainty that places

emphasis on data availability and making predictions

based on a conditioning structure that rejects invali-

dated models. Currently, however, this remains a the-

oretical exercise in the environmental management

community. It is important for sediment source allo-

cation practitioners to realize that the uniqueness of

speciﬁc watersheds in question in terms of both phys-

iography and the characteristics of the observational

water quality monitoring program (i.e., action and

time) equates to large uncertainties in model output.

Hence, the sedimentary components of watershed

loading models need to be reviewed in light of these

higher order ecoregional differences and the smaller

scale, immeasurable details that promote high uncer-

tainty in model outputs. For example, while landscape

indices based on topography, vegetation, or soil may

Figure 3. Examples of models and formulations that may be useful for sediment source allocation and simulating water quality-

related processes. A) Sediment loading models. B) Sediment transport models. C) Spacio-temporally linked loading and

transport models. Arrows indicate process calculations on left are incorporated in more complex models on right. Models listed

more than once are only referenced once. Models reviewed as part of previous work are referenced under that work.

Risk Management of Sediment Stress 181

give important indications of differences in hydrologi-

cal and sedimentary variables at the ecoregional scale,

they may not specify the parameter values necessary for

process-level modeling to distinguish the relative

magnitudes of hillslope vs. stream bank erosion at the

watershed scale. Yet models that offer process-level

descriptions are desirable when causal linkages are re-

quired to support management strategies.

Models that simulate hillslope erosion and sediment

yield focus on sediment derived from soil material

detached during an erosion event. Sediment load in

this sense is akin to sediment yield as it applies to

agricultural ﬁelds. It refers to the sediment received by

a water body, entering at its edge, perpendicular to the

channel ﬂow, and is the difference between soil loss

and net deposition during overland transport. Sedi-

ment deposition may happen anywhere downslope of

the point of erosion and occurs when the transport

capacity of the ﬂow is less than the sediment available

for transport. Water quality loading models used to

simulate soil erosion and sediment yield have ac-

counted for processes that occur in all but the domi-

nant stream and river channels. When coupled with

ﬂow routing algorithms, hillslope erosion models can

simulate the inﬂuent sediment loads for BMP design.

The most widely used erosion model is the universal

soil loss equation (USLE) (Wischmeier and Smith

1978), which was later revised (RUSLE; Renard and

others 1993). These statistically based, lumped-param-

eter models were originally developed to predict long-

term average soil erosion over a total agricultural ﬁeld.

To compute sediment yield, a sediment delivery ratio is

needed to account for net deposition. Neglecting the

temporal and spatial limitations of the RUSLE/USLE

has resulted in frequent misuse (e.g., Nagle and others

1999) and has raised questions over the applications

for erosion estimation (Hearing and others 2000,

Trimble and Crosson 2000). Despite the known short-

comings, the RUSLE/USLE serve as the basis for sim-

ulating sediment loads in several widely used ﬁeld and

watershed scale-loading models used in both ASR and

urban watersheds (Figure 3A).

Process-based soil erosion models address rill and

interill erosion separately, consider concentrated ﬂow

erosion, and relate sediment deposition and detach-

ment to transport capacity (Figure 3A). With the in-

creased complexity afforded to the process-based

algorithms, watershed-scale simulations become highly

uncertain. WEPP, for example, is applicable to areas

that range 10

to 10

(i.e., several hundred acres)

for agricultural fields. Similarities and differences

among the examples provided in Figure 3 and other

erosion models can be ascertained from reviews pro-

vided by the United States Department of Agriculture

(USDA) (1995) and Shoemaker (1997).

The washoff of solids from impervious surfaces in

urban areas and the effects of management in the form

of street cleaning are represented empirically in both

ﬁeld- and watershed-scale sediment loading models

(Figure 3A). Deletic and others (1997) provided a

process-based washoff model, yet it does not appear

that this, or similar algorithm, has been incorporated

into a large-scale model. Likewise, simulation of sedi-

ment load from construction areas is poorly repre-

sented in existing models.

Computational complexity of in-channel sediment

fate and transport models, on the other hand, derives

from the requisite of adequate description of ﬂow

mechanics in water bodies of different size. In models

of this type, sediment transport equations, of which

there are many, are combined with ﬂow routing and

dynamic solutions for channel change. Single channels

that are cross-sectionally mixed can be represented in

one dimension. While two dimensions in the horizon-

tal or vertical are required for well-mixed, shallow lakes

and estuaries or deep and narrow water bodies,

respectively. Three-dimensional models are used in

complex meandering rivers or large reservoirs. Exam-

ples are given in Figure 3B and were reviewed by Tetra

Tech (2000) for applications specific to contaminated

sediment impact mitigation.

The distance an eroded soil, channel bank, or bed

particle travels depends on the sediment transport

capacity of the ﬂow. It is modeled based on the

threshold point for incipient motion. Variables affect-

ing incipient motion are particle diameter, particle

speciﬁc weight, ﬂuid speciﬁc weight, ﬂuid density,

particle density, and kinematic viscosity. Sediment

transport formulas (Figure 3B) serve as the backbone

for particle transport in many models used to simulate

noncohesive particles larger than 20 lm in diameter.

Smaller, cohesive particles are subject to the van der

Waals attractive forces and double-layer repulsive for-

ces, Bui (2000) provided a review of cohesive sediment

transport in streams. Several existing modeling pack-

ages include both cohesive and noncohesive sediment

simulation options. Transport of sediment slugs deliv-

ered in periodic pulses has been simulated with a wave

model (Bartley and Rutherford 2004). Although this

model was used in this case to evaluate geomorphic

recovery potential of streams disturbed by sediment

slugs, this effect cannot be investigated explicitly in

common water quality models.

With respect to bank erosion, there are energy-

based indices of speciﬁc stream power that are used to

predict channel response to land use changes and hy-

182 C. T. Nietch and others

dromodiﬁcations (Yang and others 1998). However, to

be applicable to TMDL development and subsequent

BMP planning, more emphasis may need to be placed

on the magnitude of sediment moved during bank

erosion and its ultimate fate. Empirical/statistical

models describe the relative magnitude of bank ero-

sion from simple indices of bank stability (Figure 3B).

More process-based approaches attempt to deal with

the near bank velocity field and have been discussed by

Darby (1998). Examples that might prove useful to

sediment source allocation provided in Figure 3B were

collated from a review (FEMA 1999).

To date, there are few established models or mod-

eling packages containing modules that address both

hillslope and in-channel sediment transport processes

and that may he useful for risk management (Fig-

ure 3C). Most, for example, do not explicitly address

bank erosion. A notable exception is AnnAGNPS

(Yuan and others 2001), which links an agricultural-

specific loading model with a stream network channel

evolution model. Key shortcomings, however, are that

no such model includes algorithms for quantifying the

legacy effects of sediment slug movement or has been

applied within a mixed land use context to specifically

address sediment stress.

Determining the Best Management Practice

Traditionally, BMP design standards emphasized

ﬂood control and/or sediment removal to protect

channel structure and impoundment storage capacity.

Current USEPA regulations rely heavily on a combi-

nation of similar BMP designs to mitigate the effects of

NPS pollution on the ecological integrity of the water

body. This has produced a need for a revaluation of

BMP design standards. Stream restoration, revegeta-

tion of channel banks, and wetland reclamation tech-

niques are currently used by various land planning

entities to mitigate the effects of land use changes on

NPS pollution and water quality (see FISRWG 1998, for

example). These practices are considered collectively

as eco-restoration options and are included with the

suite of BMP options that watershed planners may

choose. Hence, the performance of eco-restoration

options also needs to be evaluated with respect to

management of sediment stress (Figure 4).

BMPs fall along a continuum of structural intensity

relative to engineering design, with the more struc-

turally intensive usually located in space nearer to the

watershed outlet. Lower- and nonstructural methods

are implemented more upstream and/or nearer to the

watershed divide. BMPs exhibit considerable differ-

ence in the availability and quality of mathematical

models developed to simulate their performance rela-

tive to sediment stress control and that could be used

for decision support. BMPs have different response

times in terms of both the ability of watershed man-

agers to implement the practice given socioeconomic

constraints and their ability to estimate the relative

time lag before improvements are observed post

implementation. There are also inherent differences

among BMP types in the relative magnitude of sedi-

ment stress reduction that may be achieved regardless

of the quality of the individual BMP unit designs. Al-

though to a lesser degree of certainty, differences in

terms of relative cost effectiveness can also be dis-

cerned.

Figure 4 provides common BMP examples and

explicates general qualitative differences among them

with respect to the aforementioned characteristics. For

example, nonstructural alternatives listed at the far left

in Figure 4 are considered relatively more cost effective

but require extended periods to implement, given

socioeconomic constraints. During the long periods

required to turn education into practice and policy,

the practical option, at this point in time (and for the

Figure 4. Examples of

common BMP alternatives and

a general continuum for the

relative differences among

them in characteristics related

to sediment stress mitigation.

Risk Management of Sediment Stress 183

last few decades), seems to be intercepting or amelio-

rating persistent sediment stress with structural BMP

alternatives.

To address the current issues with respect to the

protection and preservation of water quality, several

BMP guidance manuals have been compiled at both

the state and the federal levels to help developers and

municipal ofﬁcials choose among management strate-

gies for surface runoff and sediment control (e.g., Mills

and others 1976, USEPA 1993, MDE 2000, ASCE 2001).

Although these manuals provide some design guidance

and quantitative performance measures, the general-

izations therein represent cursory estimates of mass

sediment removal efﬁciencies and do not quantitatively

address the effects of discharge control on in-channel

sediment transport. The breadth of reported removals

is so broad it makes the results nearly meaningless for

serious engineering design. For example, reported

removals for total suspended solids in ponds and wet-

lands and swales range from 10% to 100% (Nietch and

others 2001, Yu and others 2001, respectively).

Much of the existing design guidance has been

developed under single event hydrologic simulations

directed at controlling ﬂoods produced by heavy rains.

Under this large-storm design standard, much of the

runoff associated with smaller events passes through

structural BMPs ‘‘untreated’’ (Claytor and Schueler

1996, Pitt 2002). Furthermore, there has been little

work to quantitatively link BMP performance with

surface water quality, let alone ecology, in the post-

implementation phase of any given practice.

The pattern of land use, development, and acquisi-

tion predicates that BMPs are implemented on the

ﬁeld scale (one to several hundred acres). Linking a

sediment source-loading allocation model for small

catchments (e.g., ﬁeld-scale models in Figure 3) to a

BMP performance model is a practical formula for

planning and making ﬁeld-scale sediment manage-

ment decisions. A conceptualization of such a model-

ing system is provide in Figure 5. This calls for a more

process-based approach rather than empirical rules of

thumb to achieve water quality targets. Examples of

this approach include work by Heitz and others (2000)

and Pitt (2002) that reports on the sizing of wet ponds

for water quality control. The sizing of constructed

wetlands to enhance performance has also received

much attention (Somes and Wong 1997, Tilley and

Brown 1998, Persson and others 1999, Kadlec 2000,

Walker 2001). Numerical simulation of the perfor-

mance of more temporary controls such as those used

at construction sites has received less attention. There

is a growing consensus that new BMP design evalua-

tions should use continuous simulation of hydrologic

and sediment fate.

Complex algorithms that describe performance

under continuous simulation, however, may preclude

their use by nontechnical decision makers. Translating

these models to simpler spreadsheet and graphic tools

without increasing outcome uncertainty has consider-

able regulatory advantage, both increasing the likeli-

hood of successful designs and expediting permit

review. As an example, a simple technique by Akan and

Antoun (1994) for preliminary sizing of detention ba-

sins was based on predetermined solutions to the res-

ervoir-routing equation. Similar strategies could be

explored for BMPs designed for sediment control in

mixed land use watersheds.

For a BMP to be commonly installed not only must

it have technical worth, but also it must be cost effec-

tive. It is more difﬁcult to generalize relative cost dif-

ferences among BMP alternatives because BMP

installation is a constrained-optimization problem. Al-

though the ability to estimate BMP construction cost

exists (Brown and Schueler 2000, Raghavan and others

2001, Heaney and others 2002), operation and main-

tenance costs are less certain. Cost effectiveness ex-

pressed as $/ton of stressor removed or similar

Figure 5. Conceptual diagram of a field-scale simulation

model for sediment management that incorporates BMP

alternatives and allows for the calculation of cost effectiveness

within the context of water body recovery.

184 C. T. Nietch and others

parameter must become part of sediment management

models in the future in order that they be useful for

decision support (e.g., cost blocks in Figure 5).

Factors affecting a BMP’s performance with respect

to sediment control and that may be considered in a

simulation model include particle size distribution,

ﬂow velocity, which is reﬂected in detention storage

time and overﬂow rate, particle shape, particle density,

turbulence levels, and sediment concentrations (Fig-

ure 6). What differs among BMP alternatives are the

boundary conditions, flow depths, overflow rates, and

the surface roughness that reflect deflections in flow.

Figure 7 provides examples of BMP alternatives and

their speciﬁc numerical representation that have re-

ceived attention with respect to process-based perfor-

mance modeling. The event-based nature of loads to

BMPs precludes the assumption of steady state. For

basin-type BMPs both reactor- and hydrodynamic-

based models have been used. Reactor models use

dead storage and short-circuiting to explain nonideal

behavior. Hydrodynamic models, to varying degrees,

can be used to identify areas in the basin where short-

circuiting, dead zones, resuspension, and sedimenta-

tion occur. The more advanced alternatives (e.g.,

Walker, 2001) allow for a more detailed analysis of

basin shape and other design features. Computational

ﬂuid dynamic models solve turbulent equations of

motion and continuity to simulate impoundment

hydrodynamics.

Other widely applied management practices for

sediment control, including some low-structural and

semipermanent alternatives, have received more-lim-

ited operational attention with respect to process

modeling. Figure 7 shows options that have received

numerical attention in modeling packages used for

management. For example, the stand-alone riparian

ecosystem management model (REMM) developed by

the USDA quantifies the water quality benefits of

riparian buffers (Lowrance and others 2000). Perfor-

Figure 6. Primary sediment

parameters to consider in a

model of BMP performance,

C=sediment concentration;

S=settling rate; R=resuspension;

D=decomposition of

transportable solids;

A=consolidation; H=depth;

d=distance; v=velocity.

Figure 7. State of the practice and properties of existing

models for simulating BMP performance. Previously cited

models are referenced in Figure 3 or in the text. Arrows in-

dicate process calculations on left are incorporated in more

complex models on right.

Risk Management of Sediment Stress 185

mance formulations for some semipermanent options

take into account mechanical filtration within the

porous media and reduced transport capacity behind

the structures. Appropriate simulation of the effec-

tiveness of low impact development (LID) techniques

(Figure 4) needs considerably more attention before

the potential benefits can be compared to other alter-

natives (Strecker 2001). Currently, there appears to be

no numerical guideline in the literature for how to

simulate the effects of nonstructural alternatives on

sediment stress. In the near term, a likely approach

would be to promote case studies in experimental

watersheds where nonstructural BMPs are used exclu-

sively, and their effectiveness can manifest a posteriori

as reductions in unit area sediment or hydrologic

loading coefficients.

Most BMP design guidance has not considered po-

tential in-channel sediment transport effects (Moglen

and McCuen 1988, Roesner and others 2001). Pitt

(2002) suggested that water could be discharged from

detention facilities at ﬂow rates below receiving water

incipient motion threshold velocity, cautioning, how-

ever, that the identiﬁcation of this threshold would be.

difﬁcult and site speciﬁc. Integrating geomorphic

indices such as this into sediment loading/BMP per-

formance models represents a signiﬁcant challenge.

Bledsoe and others (2001) developed an erosion in-

dex, similar to the approach suggested by MacRae

(1993), that compares the pre and post development

erosive power of stream ﬂows under different man-

agement scenarios. Findings suggest that designs based

on sediment transport capacity may inadvertently re-

sult in channel instability and substrate changes unless

the approach considers the frequency distribution of

subbankfull ﬂows, the capacity to transport heteroge-

neous bed and bank materials, and potential shifts in

inﬂowing sediment loads (Bledsoe 2001).

Decisions Support Systems for

Watershed-Scale Management

The above prescription for sediment management

appears practical at a ﬁeld scale where BMPs are

implemented and given the current state of the prac-

tice. However, to address problems in a larger wa-

tershed context both statistical and theoretical issues

related to determining appropriate model inputs and

scaling of model outputs arise. These modeling issues

represent a signiﬁcant challenge for risk management

and deﬁne the relevant research necessary to support

the development of a decision support system (DSS)

for sediment-related water resource applications. A

DSS for watershed sediment stress management should

be (1) integrated with a geographic information system

(GIS) so that multiple BMP projects, landscape char-

acteristics, and receiving waters of interest can be ref-

erenced and spatially correlated; (2) ﬂexible enough to

handle the interactions between BMP processes and

diverse hydrological and sedimentary conditions de-

ﬁned at both the larger ecoregional scale and

the smaller watershed-speciﬁc scale; 3) applicable over

a broad temporal scale to incorporate future changes

in land use management and simulate extended sedi-

ment transport processes such as the movement of

legacy sediment slugs; and 4) capable of exploring

multiple options or management scenarios using heu-

ristic techniques.

First, a geographic information system provides a

spatially explicit, integrating framework that can store,

process, and display the large amount of data required

for watershed studies. Models such as SWAT, SWMM,

HSPF, STORM, and AGNPS, for example, have been

designed to incorporate data from GIS databases

(Shoemaker 1997). The Better Assessment Science

Integrating point and Non-point Systems (BASINS)

represents a platform where pollutant-loading models

and GIS technologies are integrated so that hydrologic

monitoring, modeling, and assessment may be-accom-

plished in one setting, centralized around a common

reference data set (USEPA 2001b). These examples

integrate rainfall/runoff with sediment load and

transport with varying degrees of spatial and temporal

complexity to assess their impact on water quality and

have been reviewed (Shoemaker 1997).

Few of the GIS-integrated models receive spatially

explicit BMP input, however. Geographically referenc-

ing site-level BMP projects is a prerequisite for applying

risk management options and studying their effects at

watershed scales. For example, it has been shown that

improper placement of BMP designs can result in

additive hydrologic stress if considerations are not ex-

tend beyond the scale of the small catchment (Pitt

2002). Project-level BMP designs accumulate across

space as watersheds develop. Yet, nationally, this type of

geographic data for addition to GIS is relatively rare.

The effects of watershed management plans cannot be

projected if the input data on BMP location, let alone

type, do not exist for linkage to water quality moni-

toring points. Presently, modeling sediment transport

at the scale of watersheds has produced poor results

because of the uncertainty involved in quantifying in-

put variables (DeRoo 1998).

Second, models integrated within the DSS are used

ﬁrst to allocate sediment loads from the various sour-

ces. Regional and watershed-speciﬁc spatial scaling ef-

fects in relation to output uncertainty were mentioned

186 C. T. Nietch and others

previously. With respect to the latter, there are com-

plex computational issues that arise when projections

from the ﬁeld scale (<0.5 km

) to the watershed scale

(one to several hundred square kilometers) are at-

tempted. These include error propagation during

lengthened model execution relative to the temporal

domain and masked effects due to averaging when

aggregating distributed processes to simplify spatial

complexity (Clemen 1998, Schumann and others

2000).

Another factor attributing to model output uncer-

tainty is related to the numerical representations of

BMP performance in watershed-scale water quality

models. These have not been adequately evaluated and

are most often represented by fractional reductions in

land use–speciﬁc loading coefﬁcients, with no consid-

eration given to differences in BMP design, let alone

geographical placement. The uncertainty associated

with incorporating more process-level descriptions of

BMP performance has yet to be considered. Models

that can simulate multiple BMPs positioned across

watershed space and at the same time describe uncer-

tainty in unique hydrological and sedimentary condi-

tions are now only in the conceptual phase of

development (e.g., Lai and others 2003). It is unknown

if output uncertainty levels from models with more

process-based BMP descriptions will be useful in

developing watershed management implementation

plans.

Third, as watersheds develop and land use changes

different management methods are implemented.

Being able to track these changes over time and sim-

ulate the integrated results of new hydrologic and

sediment transport alterations with the legacy effects of

past sediment loading events represent the temporal

issues involved in DSS development. These have largely

gone unattended at this time due to research lags in

landscape-level data for input of key sediment pro-

cesses such as bank erosion and slug movement. A

need surfaces for simulating the nonlinearity in

uncertainty that results at the larger scale when a

combination of BMPs is placed throughout a wa-

tershed. Understanding tradeoffs involved in both

spatial and temporal scaling of BMP performance for

watershed planning is essential.

Finally, adding the capability of posing ‘‘what if ’’

questions within a watershed management plan is

considered prerequisite by many watershed practitio-

ners for any fully functional DSS. However, this adds

to the already large output uncertainty. The manner

in which different management scenarios are input

into the system and the utility of the output may range

from conducting multiple runs with different BMPs to

complex optimization routines such as are provided

by linear programming or genetic algorithms that

predict all possible outcomes from a breadth of op-

tions. This capability, for example, would allow a user

to explore alternatives to balance economic and water

quality objectives by spatially optimizing site-speciﬁc

practices (Randhir and others 1999). Achieving this

goal for NPS pollution phenomena at watershed

scales, given the plethora of interacting factors, is both

intellectually and computationally exorbitant at the

moment.

Watershed-scale modeling packages, once devel-

oped and tested, can be used as TMDL templates for

sediments and ultimately should provide decision

support allowing defensible choices between structural

and nonstructural management alternatives. Examples

exist that allow interactive evaluation of the economic

and environmental attributes of agroecosystems at the

watershed scale under different management actions,

e.g., WAMADSS (Fulcher and others 1996), or that

were designed similarly to help watershed managers

identify their water quality problems and select

appropriate BMPs, e.g., WATERSHEDSS (Osmond and

others 1995). The USEPA has developed an interactive

web-based modeling tool for sediment TMDL calcula-

tions (CEAM 2001). In these examples, BMP selection

criteria remain fairly qualitative, however. The model

for urban stormwater improvement conceptualization

(MUSIC), on the other hand, provides a suite of tools

that allow urban design engineers to formulate and

evaluate alternative drainage management strategies in

a more quantitative fashion (CRCCH 2001). No such

system has been conceived to explicitly address sedi-

ment stress allocation and risk management in com-

bination or at the scales required for watershed-scale

implementation. Model development and evaluation at

this scale require substantial ﬁnancial support and

collaboration among a diverse group of watershed

managers, economists, engineers, and natural scien-

tists.

Monitoring for Adaptive Sediment Risk

Management

After selecting and implementing a sediment man-

agement plan, managers need an adequate method to

measure the effectiveness of the choices. The concep-

tual aspects and linkages among information required

for this decision-making and evaluating process are

shown in Figure 2. Ideally, the subsequent effectiveness

of management decisions would be ascertained by

monitoring the ecologic integrity of the water body in

question.

Risk Management of Sediment Stress 187

No matter how detailed and successful a DSS may

simulate sediment stress and the effects of manage-

ment, there will always be response uncertainty in the

simulated outcome. As discussed, this uncertainty has a

physical nature (e.g., climate) and also is, in part,

attributable to the role socioeconomic values play in

the decision-making process. All management pre-

scriptions are, effectively, working hypotheses that, if

tested, are employed under the socioeconomic frame-

work blanketing the physical watershed. A sediment

management plan should be developed, implemented,

and evaluated within a programmatic structure that

recognizes the uncertainties not only in the natural

systems and sciences but also in societal and political

realities. With this comes the need to maintain com-

munication and collaboration among scientists, man-

agers, and the public to ensure appropriate use,

interpretation of model outputs, and the ability to

determine when model reevaluation is necessary.

The iterative process of adaptive management pro-

vides an approach for dealing with the uncertainty in

project success by using scientiﬁc principles of

hypothesis testing and model building. Two aspects

central to this management approach are (1) a col-

laborative programmatic organizational structure

developed within the context of using the DSS that

encourages continuous learning and (2) appropriate

pre- and post-implementation monitoring programs to

test the effectiveness of the actions. In this light,

watershed plans implemented within an adaptive

management framework can be viewed as ﬁeld exper-

iments, or, more speciﬁcally, demonstrations of BMP

effectiveness related to sediment stress.

A beneﬁt of incorporating collaborative learning

into watershed management planning is establishing

up-front commitment from project stakeholders

(Bentrup 2001). The USEPA’s Regional Vulnerability

Assessment (ReVA) and Multimedia Integrated Mod-

eling System (MIMS) programs, for example, provide

venues for making such collaborative linkages and

partnerships (Smith 2000, Fine and others 2002,

respectively). Initial identiﬁcation and explanation of

the outcome uncertainty, promoted by these programs,

allow for the needed buy-in for subsequent assessment

and monitoring programs. For effective monitoring,

planners must seriously consider costs, personnel, and

future commitment.

A large hurdle for monitoring to overcome is the

temporal and spatial variability of watershed-scale

characteristics, such as annual sediment loads, that

respond at different rates and make it very difﬁcult to

detect changes within time spans that allow for pro-

grammatic adjustment. Some have suggested that even

10 to 20 years of post-implementation monitoring may

prove insufﬁcient. Not only do most political leaders,

whose turnover time is typically 4 to 8 years, not allow

for such extended periods to gather supporting evi-

dence, but also, to understand the success or failure of

a given management prescription, monitoring must

occur over two spatiotemporal scales, which greatly

increases costs, These include (1) the ﬁeld scale over a

representative part of the life history of the prescribed

BMP and (2) the watershed scale to assess the com-

bined effects of multiple BMPs on meeting established

sediment criteria for the impacted water body (Fig-

ure 2).

From a scientiﬁc standpoint, if a given plan proves

unsuccessful within the expected recovery period, it

may be due to poor performance of the chosen BMP,

inappropriate BMP selection, the right BMP being

placed ineffectively, the aggregated effects of multiple

BMPs being improperly scaled, or some combination

thereof. Post-implementation monitoring activities as-

sess whether the watershed meets the water quality

criteria for sediment. If the answer is no, then a second

question follows to address whether the BMPs are

working as expected. The answer in this case is pro-

vided by comparing the BMP performance model

predictions to ﬁeld observations taken as a part of the

monitoring plan. This requires BMP-speciﬁc monitor-

ing. A joint project funded by the American Society of

Civil Engineers (ASCE) and USEPA has recently pro-

duced a guidance manual for BMP-speciﬁc monitoring

intended to improve the state of the practice (Clary

and others 2001). Additional method development is

required to expedite BMP ﬁeld performance evalua-

tions to reduce the substantial ﬁeld-related costs.

BMP-speciﬁc monitoring helps determine the sou-

rce of the project failure. If the chosen BMP(s) is not

working, then the ﬁeld-scale simulation model is

revisited to determine if inadequacies exist in the

mechanistic representation or if the unit design was

faulty. If, however, observed and predicted parameters

are within expected range, then project failure may be

a function of inadequacies in the spatial scaling, poor

optimization, or inadequate estimation of the time lag

for the receiving water body to show measurable

recovery. Determining the effectiveness of risk man-

agement decisions forces a feedback loop in the deci-

sion-making process and is a primary feature of the

adaptive management approach (Figure 2).

Prerequisites to the success of a monitoring plan are

cost-effective and technically sound methods for sedi-

ment parameter estimation. Unfortunately, this is not a

moot point, as indicated in a synopsis of technical is-

sues for monitoring sediment conducted by the United

188 C. T. Nietch and others

States Geological Survey (USGS) (Bent and others

2001), which highlights several problems with current

sediment sampling methods. Updated sediment sam-

pling protocols have been proposed and evaluated

(Thomas and Lewis 1995, Ryan and Troendle 1997,

Sichingabula 1998, Gray and others 2000) but not

necessarily adopted.

Newer techniques such as remote sensing of chan-

ges in turbidity or stream morphology may provide an

innovative and effective means to manage sediment in

the future (Moll 1988, Nellis and others 1998, Stojlc

and others 1998). Optical sensors and acoustic tech-

niques are undergoing reﬁnement to replace tradi-

tional turbidity meters and grab sampling methods for

better assessment of in situ levels of suspended solids

(Schoellhamer 2001, Pathak and others 2002). Chro-

nological sediment dating techniques to develop bud-

gets and maps of soil redistribution and trace

suspended solids in streams may prove useful to risk

management (Mabit and others 1999, Bonniwell and

others 1999). These innovative techniques are often

cost prohibitive. Hence, actual ﬁeld trials or modeling

simulations, which provide an evaluation of current

monitoring methods, standard indicators, and guid-

ance for their use, are required. The continual meth-

ods development feeds back to reinforce modeling

efforts by expediting evaluation and veriﬁcation of

model outputs and reﬁning uncertainty estimates.

Conclusions

Present uncertainties in sediment source allocation

models, BMP performance estimation, watershed scal-

ing, and in situ sediment monitoring constrain the

characterization of the changing sedimentary status of

a watershed. This makes it difﬁcult to recommend and

implement management strategies and assess their

relative effectiveness on water quality improvement

beyond a conceptual basis. Focusing on watersheds,

and the accompanying space and time scales, within a

framework that integrates water quality assessment and

related management strategies helps to show linkages

among speciﬁc projects. The framework can be used as

a guide for the direction of future research related to

sediment stress. Reducing the high uncertainty in

sediment stress risk management will be better realized

if new research (1) takes advantage of existing models,

(2) evaluates these models based on controlled

experiments and case studies designed to address is-

sues related to spatial and temporal scaling with link-

age to ecological assessments, and (3) uses appropriate

sampling methods in conjunction with model simula-

tions and stakeholder collaboration to evaluate and

eventually track the effectiveness of management

decisions.

Acknowledgments

The authors wish to thank Carl Enﬁeld, Evan Fan,

Dan Sullivan, and Richard Field of the USEPA, Na-

tional Risk Management Research Laboratory, and Bill

Barﬁeld, Oklahoma State University, for providing

written reviews and comments on early versions of the

manuscript. Their input was invaluable in shaping the

conceptual framework for risk management research

presented herein. Additionally, the refereed comments

of John Gray and Craig Goodwin were helpful in

improving the content of the manuscript. Any opinions

expressed in this paper are those of the authors and do

not, necessarily, reﬂect the ofﬁcial positions and poli-

cies of the USEPA. Any mention of products or trade

names does not constitute recommendation for use by

the USEPA.

Literature Cited

Ackers, P., and G. Thompson. 1987. Reservoir sedimentation

and influence of flushing,. Pages 845–861 in C. R. Thorne J.

C. Bathhurst and R.D. Hey (eds.), Sediment transfer in

gravel bed rivers. John Wiley & Sons, New York.

Akan, A.O., and E. N. Antoun. 1994. Runoff detention for

flood volume or erosion control. Journal of Irrigation and

Drainage Engineering 120:168–178.

American Society of Civil Engineers. 2001. Guide for best

management practice (BMP) selection in urban developed

areas. Urban Water Infrastructure Management Commit-

tee’s Task Committee for Evaluating Best Management

Practices, ASCE, Reston, Virginia 51 pp.

Arthur, M. A., G. B. Coltharp, and D. L. Brown. 1998. Effects

of best management practices on forest streamwater quality

in astern Kentucky. Journal of the American Water Resources

Association 34:481–496.

Ashmoore, P., F. M. Conly, D. deBoer, Y. Martin, E. Petticrew,

and A. Roy. 2000. Recent (1995–1998) Canadian research

on contemporary processes of river erosion and sedimen-

tation, and river mechanics. Hydrological Processes 14:1687–

1706.

Barfield, B. J., J. C. Hayes, A. W. Fogle, and K.A. Kranzler.

1996. The SEDIMOT III model of watershed hydrology and

sedimentology. Pages IX –54-61 in Proceedings of the sixth

federal interagency sedimentation conference, 10–14

March, 1996. Las Vegas, Nevada.

Barret, M. E., J. E. Kearney, T. G. McCoy, J. F. Malina, R. J.

Charbenau, and G. H. Ward. 1995. An evaluation of the use

and effectiveness of temporary sediment controls. Techni-

cal Report CRWR 261. Center for Research in Water Re-

sources. University of Texas, Austin.

Bartley, R., and I. Rutherford. 2005. Re-evaluation of the wave

model as a tool for quantifying the geomorphic recovery

Risk Management of Sediment Stress 189

potential of streams disturbed by sediment slugs.

Geomorphology 64:221–242.

Bent, G. C., J. R. Gray, K. P. Smith, and G. D. Glysson. 2001. A

synopsis of technical issues for monitoring sediment in

highway and urban runoff. Open-File Report 00-497. U.S.

Geological Survey, Denver, Colorado.

Bentrup, G. 2001. Evaluation of a collaborative model, A case

study analysis of watershed planning in the intermountain

west. Environmental Management 27:739–748.

Berkman, H. E., and C. F. Rabeni. 1987. Effect of siltation on

stream fish communities. Environmental Biology of Fishes

18:285–294.

Beven, K., and A. Musy, and C. Higy. 2001. Tribune libre:

uniqueness of place and time. Journal of Water Science

14:525–533.

Bingner, R., V. Justice, and F.D. Theurer. 2004. AGNPS Web

site. U.S. Department of Agriculture, Oxford, Mississippi.

Available at: http://msa.ars.usda.gov/ms/oxford/nsl/AG

NPS.html.

Bledsoe, B. P. 2001. Relationships of stream responses to

hydrologic changes. Pages 127–144 in B.Urbonas (ed.),

Proceedings linking stormwater BMP designs and perfor-

mance to receiving water impacts mitigation, 19–24 August

2001. Snowmass Village, Colorado.

Bledsoe, B. P., R. Anderson, B. McCaig, A. Flores, and

C. Watson. 2001. Modeling package for assessing the po-

tential effects of hydrologic change on stream form and

integrity. In D. F. Hayes (ed.), Proceeding of the wetlands

engineering and river restoration conference, 27–31 Au-

gust 2001. Reno, Nevada. CD-ROM.

Bonniwell, E. C., G. Matisoff, and P. J. Whiting. 1999. Deter-

mining the times and distances of particle transit in a

mountain stream using fallout radionuclides. Geomorphology

27:75–92.

Booth, D. B., and C. R. Jackson. 1997. Urbanization of aquatic

systems: Degradation thresholds, stormwater detention,

and limits of mitigation. Journal of the American Water Re-

sources Association 22:1–19.

Booth, D. B., and L. E. Reinelt. 1993. Consequences of

urbanization on aquatic systems: Measured effects, degra-

dation thresholds, and corrective strategies. Pages 545–550

in Proceedings of Watershed 93, 21–24 March 1993. Alex-

andria, Virginia.

Borah, D. K., and P. K. Bordoloi. 1989. Stream erosion and

bed evolution model. Pages 848– in S. Wang (ed.), Sedi-

ment transport modeling. ASCE, New York, 848 pp.

Brown, W., and T.Schueler.2000.Theeconomicsofstormwater

treatment: An update. Technical Note 90 from Watershed

Protection Techniques 2(4):395–499. in T. R. SchuelerH. K. and

Holland (eds..), The practice of watershed protection.

Center for Watershed Protection, Ellicott City, Maryland.

Bui, T. 2000. Cohesive sediment transport in natural streams:

state of knowledge. Page 268 in R. H. Hotchkiss and M.

Glade (eds.), Proceedings of the joint conference on the

water resources engineering and water resources planning

and management divisions, ASCE, 30 July–2 August 2000.

Minneapolis, Minnesota. CD-ROM.

Center for Exposure Assessment Modeling. 2001. TMDL

USLE. U.S. Environmental Protection Agency, Office of

Research and Development, Athens, Georgia. Available at:

http://www.epa.gov/ceampubl/swater/usle/index.htm.

Chang, C., J. D. Atwood, K. Alt, and B. A. McCarl. 1994.

Economic impacts of erosion management measures in

coastal drainage basins. Journal of Soil and Water Conservation

49:606–611.

Cheng, M., L. S. Coffman, Y. Zhang, J. Riverson, and J. Zhen.

BMP model for low impact development. Pages 1–12 in

G. Haves Sehlke D. F. and K. Stevens (eds.), Proceedings

of the 2004 world water and environmental resources

congress, 27 June–1 July 2004. Salt Lake City, Utah.

Clary, J., J. Kelly, J. O’Brien, J. Jones, and M. Quigley. 2001.

National stonnwater best management practices database:

A key tool to help communities meet Phase II stormwater J

requirements. Stormwater 2:44–52.

Claytor, R., and T. Schueler. 1996. Design of stormwater

filtering systems. Ellicott City, Maryland.

Clemen, T. 1998. The use of scale information for integrating

simulation models into environmental information sys-

tems,. Ecological Modeling 108:107–113.

Cooperative Research Centre for Catchment Hydrology.

2001. MUSIC: Model for urban stormwater improvement

conceptualization, pilot version, training manual. Monash

University, Australia. Available at: http://www.catch-

ment.crc.org.au/toolkit/music/.

Darby, S. E 1998. Modeling width adjustment in straight

alluvial channels. Hydrological Processes 12:1299–1321.

Deletic, A., C. Maksimovic, and M. Ivetic. 1997. Modeling of

storm washoff of suspended solids from impervious sur-

faces. Journal of Hydraulic Research 35:99–118.

DeRoo, A. P. J. 1998. Modeling runoff and sediment transport

in catchments using GIS,. Hydrological Processes 12:905–922.

Dewey, R., R. Flindall, and D. Crichton. 2000. Hydrodynamic

modeling of a stormwater pond for optimal sizing and

effectiveness. Pages 263–282 in W. James (ed.), Applied

modeling of urban water systems, monograph 8. CHI,

Guelph, Ontario, Canada.

Duan, G., L. Li, and S. S. Y. Wang. 1998. Two dimensional

bank erosion model for non-cohesive bank materials. Pages

1398–1403 in Proceedings of the international water re-

sources engineering conference, ASCE, 3–7 August 1998.

Memphis, Tennessee.

Einstein, H.A. 1950. The bed load function for sediment

transportation in open channel flow Technical Bulletin No.

1026. U.S. Department of Agriculture, Washington, DC, 70

pp.

Engelund, F., and E. Hansen. 1967. A monograph on sedi-

ment transport in alluvial streams. Teknisk Forlag, Tech-

nical Press, Copenhagen, Denmark, 62 pp.

Ewing, M. S 1991. Turbidity control and fisheries enhance-

ment in a bottomland hardwood backwater system in

Louisiana (USA). Regulated Rivers 6:87–99.

Federal Interagency Stream Restoration Work Group. 1998.

Stream corridor restoration: Principles, processes, and

practice. National Engineering Handbook, part (NEH)

653, 483 pp.

Federal Emergency Management Agency. 1999. Riverine

erosion hazard areas: mapping feasibility study. FEMA,

190 C. T. Nietch and others

Report to Congress. Available at: http://www.fema.gov/

fhm/dl_river.shtm.

Fine, S. S., S. C. Howard, A. M. Eyth, D. A. Herington, K. J.

Castleton. 2002. The EPA multimedia integrated modeling

system software suite. In Proceedings of the second federal

interagency hydrologic modeling conference, 28 July–1

August 2002. Las Vegas, Nevada, Available at: http://

www.epa.gov/asmdnerl/mims/publications/mims.PDF.

Fulchar, C., T. Prato, and Y. Zhou. 1996. Watershed man-

agement decision support system. Pages 790–793 in Pro-

ceedings of Watershed 96: Moving ahead together, 8–12

June 1996. Baltimore, Maryland.

Gray, J. R., G. D. Glysson, L. M. Turcios, and G. E. Schwarz.

2000. Comparability of suspended-sediment concentration

and total suspended solids data. U.S. Geological Survey

Water-Resources Investigations Report 00–4191. Reston,

Virginia. Available at: http://water.usgs.gov/osw/pubs/

WRIR00–4191.pdf.

Hayes, J. C., B. J. Barfield, and R. I. Barnhisel. 1984. Perfor-

mance of grass filters under laboratory and field condi-

tions. Transactions of the American Society of Civil Engineers

27:1321–1331.

Hayter, E. J., M. A. Bergs, R. Gu, S. C. McCutcheon, S. J.

Smith, and H. J. Whiteley. 1998. HSCTM-2, a finite ele-

ment model for depth-averaged hydrodynamics, sediment

and contaminant transport. U.S. Environmental Protec-

tion Agency, Athens, Georgia. Available at: http://

www.epa.gov/ceampubl/swater/hsctm2d/index.htm.

Heaney, J. P., D. Sample, and L. Wright. 2002. Costs of urban

stormwater control. EPA600-R-021. U.S. Environmental

Protection Agency, Office of Research and Development,

Edison, New Jersey, 113 pp.

Heitz, F., S. Khosrowpanah, and J. Nelson. 2000. Sizing of

surface water runoff detention ponds for water quality

improvement. Journal of the American Water Resources Associ-

ation 36:541–548.

Hollis, G. E 1975. Effect of urbanization on floods of different

recurrence interval. Water Resources Research 11:431–435.

Howarth, R. W., J. R. Fruci, and D. Sherman. 1991. Inputs of

sediment and carbon to an estuarine ecosystem: Influence

of land use. Ecological Applications 1:21–37.

Huber, W. C., and R. E. Dickinson. 1988. Storm water man-

agement model version 4: User’s manual. EPA 6000/3–88/

001a. U.S. Environmental Protection Agency, Athens,

Georgia, 493 pp.

Jia, Y., and S. S. Y. Wang. 2001. The application of the en-

hanced CCHE2D model to study the alluvial channel

migration process. Journal of Hydraulic Research 39:469–480.

Johnson, B. E., P. Y. Julien, D. K. Molnar, and C. Watson.

2000. The two-dimensional upland erosion model

CASC2D-SED. Journal of the American Water Resources Associ-

ation 36:31–42.

Kadlec, R. H 1994. Detention and mixing in free water wet-

lands,. Ecological Engineering 3:345–380.

Kadlec, R. H 2000. The inadequacy of first-order treatment

wetland models. Ecological Engineering 15:105–119.

Kipkie, C. W., and W. James. 2000. Feasibility of permeable

pavement option in SWMM for long-term continuous

modeling. Pages 303–324 in W. James (ed.), Applied

modeling of urban water systems, monograph 8. CHI,

Guelph, Ontario, Canada.

Lai, F., C. Fan, L. Shoemaker, and R. Field. 2003. Development

of a decision-support framework for placement of BMPs in

urban watersheds. In Proceedings of national TMDL science

and policy 2003 specialty conference, Water Environment

Federation, 16–19 November 2003. Chicago, Illinois.

Lane, E. W. 1955. The importance of fluvial geomorphology

in hydraulic engineering. Proceedings of the American Society of

Civil Engineers 81:1–17.

Langendoen, E. J. 2000. CONCEPTS—Conservational chan-

nel evolution and pollutant transport system: stream

corridor version 1.0. Research Report No. 16. U.S.

Department of Agriculture, Oxford, Mississippi. Available

at: http://msa.ars.usda.gov/ms/oxford/nsl/agnps/Con-

cepts/manual/Cover.html.

Lindley, M. R., B. J. Barfield, and B. N. Wilson. 1995. Surface

impoundment element model description. In USDA

Water Erosion Prediction Project (WEPP). NSERL

Report No. 10, West Lafayette, Indiana. Available at:

http://topsoil.nserl.purdue.edu/nserlweb/weppmain/

docs/chap14.pdf.

Lombardo, L. K., G. L. Grabow, J. Spooner, D. E. Line, D. L.

Osmond, and G. D. Jennings. 2000. Section 319 nonpoint

source national monitoring program successes and rec-

ommendations. NCSU Water Quality Group. North Caro-

lina State University, Raleigh.

Lowrance, R., L. S. Altier, R. G. Williams, S. P. Inamdar, J. M.

Sheridan, D. Bosch, R. K. Hubbard, and D. L. Thomas.

2000. REMM: The riparian ecosystem management model.

Journal of Soil and Water Conservation 55:27–34.

Mabit, L., C. Bernard, M. R. Laverdiere, and S. Wicherek.

1999. Assessment of soil erosion in a small agricultural ba-

sin of the St. Lawrence River watershed. Hydrobiologia 410:263–

268.

MacRae, C. R. 1993. An alternative design approach for the

control of stream erosion potential in urbanizingwatersheds.

Pages 405–410 in J. Marsalek and H. Torno (eds.), Proceed-

ings of the sixth international conference on urban storm

drainage, 12–17 September 1993. Niagara Falls, Canada.

MacRae, C. R. 1996. Experience from morphological research

on Canadian streams: Is the control of the two-year fre-

quency runoff event the best basis for stream channel

protection? Pages 144–162 in L. A. Roesner (eds.), Effects

of watershed development and management of aquatic

ecosystems, 4–9 August 1996. Snowbird, Utah.

Marsalik, P. M., W. E. Watt, J. Marsalek, and B. C. Anderson.

2000. Winter flow dynamics of an on-stream stormwater

management pond. Water Quality Research Journal of Canada

35:505–523.

Maryland Department of the Environment. 2000. Maryland

stormwater design manual, Volumes I and II. MDE,

Annapolis, Maryland. Available at: http://www.mde.state.

md.us/Programs/WaterPrograms/SedimentandStrom-

water_design/index.asp.

McCuen, R. H., and G. E. Moglen. 1988. Multicriterion

stormwater management methods,. Journal of Water Research

and Planning 114:414–431.

Risk Management of Sediment Stress 191

Meyer-Peter, E., and R. Muller. 1948. Formulas for bed-load

transport. Pages 39–64 in Proceedings of the second

meeting International Association for Hydraulic Research,

7–9 June 1948. Stockholm, Sweden.

Mills, T. R., M. A. Nawrocki, G. Squire, H. T. Hopkins, and M.

L. Clar. 1976. Erosion and sediment control audiovisual

training program instructor’s workbook. EPA-600/8–76–

001b. U.S. Environmental Protection Agency, Washington,

DC, 354 pp.

Mitchell, D. F., D. Galya, B. Ruffle, and J. A. Bleiler. 1996. The

use of risk analysis in watershed planning activities. Pages

411–416 in Proceedings of Watershed 96’: Moving ahead

together, 8–12 June 1996. Baltimore, Maryland.

Moglen, G. E., and R. H. McCuen. 1988. Effects of detention

basins on in-stream sediment movement. Journal of Hydrol-

ogy 104:129–139.

Moll, J. R. 1988. Monitoring of suspended sediments in the

Jatiluhur Reservoir using satellite images. Pages 1403–1404

in Proceedings of the international geoscience and remote

sensing symposium, 13–16 September 1988, Volume II.

Edinburgh, Scotland.

Morgan, R. P. C., J. N. Quinton, R. E. Smith, G. Govers, J. W.

A. Poesen, K. Auerswald, G. Chisci, D. Torri, and M. E.

Styczen. 1998. The European soil erosion model (EURO-

SEM): a process-based approach for predicting sediment

transport from fields and small catchments. Earth Surface

Processes and Landforms 23:527–544.

Mosselman, E. 1992. Mathematical modeling of morpholog-

ical processes in rivers with erodible cohesive banks. Ph.D.

dissertation. Delft University of Technology, Delft, the

Netherlands.

Mueller, D. H., T. C. Daniel, and R. C Wendt. 1981. Conser-

vation tillage: Best management practice for nonpoint

runoff. Environmental Management 5:33–53.

Munoz-Carpena, R., J. E. Parsons, and J. W. Gilliam. 1999.

Modeling hydrology and sediment transport in vegetative

filter strips. Journal of Hydrology 214:111–129.

Nagle, G. N., T. J. Fahey, and J. P. Lassoie. 1999. Management

of sedimentation in tropical watersheds. Environmental

Management 23:441–452.

National Association of Counties Research Foundation. 1970.

Urban soil erosion and sediment control. U.S. Department

of the Interior, Washington, DC.

National Resource Conservation Service. 1992. Broad land

cover/use, by state: table and map. Products 2445 and

5150, National Resource Inventory. U.S. Department of

Agriculture, Washington, DC.

National Resource Conservation Service, 2003. 2001. annual

NRI—Soil erosion. National Resource Inventory. U.S.

Department of Agriculture, Washington, DC.

Nearing, M. A., M. J. Ro

mkens, L. D. Norton, D. E. Stott,

F. E. Rhoton, J. M. Laflen, D. C. Flanagan, C. V. Alonso,

R. L. Binger, S. M. Dabney, O. C. Doering, C. H. Huang,

K. C. McGregor, and A. Simon. 2000. Measurements and

models of soil loss rates,. Science 290:1300–1301.

Nellis, M. D., J. A. Harrington, and J. Wu. 1998. Remote

sensing of temporal and spatial variations in pool size,

suspended sediment, turbidity, and secchi depth in Tuttle

Creek Reservior, Kansas: 1993. Geomorphology 21:281–293.

Newman, T. L., T. A. Omer, and E. D. Driscoll. 2000. SWMM

storage-treatment for analysis/design of extended-deten-

tion ponds. Pages 283–302 in W. James (eds.), Applied

modeling of urban water systems, monograph 8. CHI,

Guelph, Ontario, Canada.

Nietch, C. T., M. Borst, and M. L. O’Shea. 2001. Stormwater

treatment: Ponds vs. constructed wetlands. Pages 524–528

in B. Urbonas (eds.), Proceedings linking stormwater BMP

designas and performance to receiving water impacts mit-

igation, 19–24 August 2001. Snowmass Village, Colorado.

Novotny, V., and H. Olem. 1994. Water quality: Prevention,

identification, and management of diffuse pollution. John

Wiley and Sons, New York, 888 pp.

Ochumba, P. B. O 1990. Massive fish kills within the Nyanza

Gulf of Lake Victoria, Kenya. Hydrobiohgia 208:93–99.

Omernik, J. M. 1995. Ecoregions: a framework for environ-

mental management. Pages 49–62 in W. Davis and

T. Simon (eds.), Biological assessment and criteria: Tools

for water resource planning and decision making. Lewis,

Chelsea, Michigan.

Osmond, D. L., D. E. Line, J. A. Gale, R. W. Gannon, C. B.

Knott, K. A. Bartenhagen, M. H. Turner, S. W. Coffey,

J. Spooner, J. Wells, J. C. Walker, L. L. Hargrove, M. A.

Foster, P. D. Robillard, and D. W. Lehning. 1995.

WATERSHEDSS: Water, Soil and Hydro-Environmental

Decision Support System. Available at: http://h2osp-

arc.wq.ncsu.edu.

Paterson, R. G 1994. Construction practices: the good, the

bad, and the ugly. Watershed Protection Techniques 1:95–99.

Pathak, A. G., R. R. Chaudhury, J. Lengricht, and K. U. Graw.

2002. Acoustic measurements of suspended sediments in

estuaries. 10 in Proceedings of the international confer-

ence on hydraulic measurement & experimental methods,

28 July–1 August 2002. Estes Park, Colorado. CD-ROM.

Pennock, J.R., and J. H. Sharp. 1994. Temporal alternation

between light- and nutrient-limitation of phytoplankton

production in a coastal plain estuary. Marine Ecology Progress

Series 111:275–288.

Pennsylvania Department of Environmental Protection. 1998.

Fact sheet: Controlling accelerated soil erosion and

preventing sediment pollution. 3630-FS-DEP1841, PDEP,

Harrisburg, Pennsylvania. Available at: http://www.

dep.state.pa.us/dep/subject/pubs/water/wqm/FS1841.doc.

Persson, J. 2000. The hydraulic performance of ponds of

various layouts. Urban Water 2:243–250.

Persson, J., N. L. G. Somes, and T. H. F. Wong. 1999.

Hydraulic efficiency of constructed wetlands and ponds.

Water Science and Technology 40:291–300.

Peterson, N. P., A. Henry, and T. P. Quinn. 1992. Assessment

of cumulative effects on salmonid habitat: Some suggested

parameters and target condition. TFW-F3-92-001. Wash-

ington Department of Natural Resources, Olympia, 75 pp.

Pitlick, J., and M. M. Van Steeter. 1998. Geomorphology and

endangered fish habitats of the upper Colorado River: 2.

Linking sediment transport to habitat maintenance. Water

Resources Research 34:303–316.

Pitt, R. 2001. Watershed-scale models and some unique as-

pects and uses of SLAMM, the source loading and man-

agement model. Technical seminar documentation. U.S.

192 C. T. Nietch and others

Environmental Protection Agency, Edison, New Jersey, 62

pp.

Pitt, R. 2002. The design and use of detention facilities for

stormwater management using DETPOND. University

of Alabama, Birmingham, Available at: http://unix.eng.ua.

edu/rpitt/SLAMMDETPOND/WinDetpond/WinDETP

OND%20guide%20and20documentation.pdf.

Pitt, R., and J. Voorhees. 2002. SLAMM: The source loading

and management model. Pages 79–101 in R. D. Field

Sullivan (eds.), Wet-weather flow in the urban watershed:

Technology and management. CRC Press, Boca Raton,

Florida.

Platts, W. S., W. F. Megahan, and G. W. Minshall. 1983.

Methods for evaluating stream, riparian, and biotic condi-

tions. General Technical Report. INT-138. U.S. Forest

Service, Ogden, Utah, 70 pp.

Prince George’s County. 1999. Low-impact development de-

sign strategies: An integrated design approach. PGC, Lar-

go, Maryland, 150 pp.

Raghavan, R., R. N. Koustas, and S. L. Liao. 2001. Cost

estimating for best management practices (BMPs). Pages

539–543 in Proceedings linking stormwater BMP designs

and performance to receiving water impacts mitigation,

B. Urbonas (ed.), 19–24 August 2001. Snowmass Village,

Colorado.

Randhir, T. O., J. G. Lee, and B. Engel. 2000. Multiple criteria

dynamic spatial optimization to manage water quality on a

watershed scale. Transactions of the American Society, of Civil

Engineers 43:291–299.

Renard, K. G., G. R. Foster, G. A. Weesies, D. K. McCool, and

D. C. Yoder. 1993. Predicting soil erosion by water: A guide

to conservation planning with the revised universal soil loss

equation RUSLE. Agriculture Handbook No. 703. U.S.

Department of Agriculture, Tucson, Arizona, 404 pp.

Rinne, J. 1988. Effects of livestock grazing exclosure on

aquatic macroinvertebrates in a mountain stream, New

Mexico. Great Basin Naturalist 48:146–153.

Roads, B. L. 1995. Stream power: a unifying theme for

urban fluvial geomorphology. Pages 65–75 in E. Herricks

(ed.), Stormwater runoff and receiving systems: Impact,

monitoring, and assessment. CRC Press, Boca Raton,

Florida.

Roesner, L. A., B. P. Bledsoe, and R. W. Brashear. 2001. Are

best-management-practice criteria really environmentally

friendly? Journal of Water Resources and Planning 127:150–

154.

Rosgen, D. L. 2001a. A hierarchical river stability/watershed-

based sediment assessment methodology. Wildland

Hydrology, Pagosa Springs, Colorado. Available at: http://

www.wildlandhydrology.com/assets/A_HIERARCHICAL_

RIVER_ TABILITY.pdf.

Rosgen, D. L. 2001b. A practical method of computing

streambank erosion rate. Wildland Hydrology, Pagosa

Springs, Colorado. Available at: http://www.wildlandhy-

drology.com/assets/Streambank_erosion_paper.pdf.

Ryan, S. E., and C.W. Troendle. 1997. Measuring bedload in

coarse-grained channels: procedures, problems, and rec-

ommendations. Pages 949–958 in J. J. Warwick (eds.),

Proceedings water resources education, training, and

practice: Opportunities for the next century, 29 June–3 July

1997. Keystone, Colorado.

Sartor, J., and G. Boyd. 1972. Water pollution aspects of street

surface contaminants. EPA-R2-72-081. U.S. Environmental

Protection Agency, Washington, DC, 242 pp.

Schoellhamer, D. H. 2001. Continuous monitoring of sus-

pended sediment in rivers by use of optical sensors. Pages

III-160–168 in III-Proceedings of the Seventh Federal In-

teragency Sedimentation Conference, 25–29 March 2001.

Reno, Neveda.

Schumann, A. H., R. Funke, and G. A. Schultz. 2000. Appli-

cation of a geographic information system for conceptual

rainfall-runoff modeling. Journal of Hydrology 240:45–61.

Shoemaker, L. 1997. Compendium of tools for watershed

assessment and TMDL development, EPA841-B-97-006. U.S.

Environmental Protection Agency, Washington, DC, 118

pp.

Short, F. T., and S. Wyllie-Echeverria. 1996. Natural and hu-

man-induced disturbance of seagrasses. Environmental Con-

servation 23:17–27.

Sichingabula, H. M 1998. Factors controlling variations in

suspended sediment concentration for single-valued sedi-

ment rating curves, Fraser River, British Columbia, Can-

ada,. Hydrological Processes 12:1869–1894.

Simmons, D. L., and R. J. Reynolds. 1982. Effects of urbani-

zation on base flow of selected south-shore streams, Long

Island, New York. Water Resources Bulletin 18:797–805.

Simon, A., W. J. Wolfe, and A. Molinas. 1991. Mass wasting

algorithms in an alluvial channel model. Pages 8-22–8-29 in

Proceedings of the 5th annual conference, 18–21 March

1991. Las Vegas, Nevada.

Simon, A., W. Dickerson, and A. Heins. 2004. Suspended-sed-

iment transport rates at the 1.5-year recurrence interval for

ecoregions of the United States: transport conditions at the

bankfull and effective discharge? Geomorphology 58:243–262.

Smith, E. R 2000. An overview of EPA’s Regional Vulnerability

Assessment (ReVA) Program. Environmental Monitoring and

Assessment 64:9–15.

Smith, R. E., D. C. Goodrich, and J. N. Quinton. 1995. Dy-

namic, distributed simulation of watershed erosion: The

KINEROS2 and EUROSEM models. Journal of Soil and Water

Conservation 50:517–520.

Somes, N. L. G., and T. H. F. Wong. 1997. Designing outlet

characteristics for optimal wetland performance. Water

Science and Technology 36:235–240.

Stojlc, M., J. Chandler, P. Ashmore, and J. Luce. 1998. The

assessment of sediment transport rates by automated digital

photogrammetry. Photogrammetric Engineering and Remote

Sensing 64:387–395.

Strecker, E. W. 2001. Low-impact development (LID)—Do we

know if it is low? Or is it really lower? Pages 210–222 in

B. Urbonas (ed.), Proceedings linking stormwater BMP

designs and performance to receiving water impacts miti-

gation, 19–24 August 2001. Snowmass Village, Colorado.

Tapia-Vargas, M., M. Tiscareno-Lopez, J. J. Stone, J. L. Oro-

peza-Mota, and M. Velazquez-Valle. 2001. Tillage system

effects on runoff and sediment yield in hillslope agricul-

ture. Field Crops Research 69:173–182.

Risk Management of Sediment Stress 193

Tetra Tech, Inc. 2000. Overview of sediment- contaminant

transport and fate models for use in making site-specific

contaminated sediment remedial action decisions. Pre-

pared for U.S. EPA, Office of Emergency Response and

Remediation, Washington, DC.

Thomas, R.B., and J. Lewis. 1995. An evaluation of flow-

stratified sampling for estimating suspended sediment

loads. Journal of Hydrology 170:27–45.

Tilley, D. R., and M. T. Brown. 1998. Wetland networks for

stormwater management in subtropical urban watersheds.

Ecological Engineering 10:131–158.

Trimble, S. W 1997. Contribution of stream channel erosion

to sediment yield from an urbanizing watershed. Science

278:1444.

Trimble, S. W., and P. Crosson. 2000. Measurements and

models of soil loss rates. Science 290:1301.

U.S. Army Corps of Engineers. 1993. HEC-6, scour and

deposition in rivers and reservoirs, user’s manual, AD-A316

120, USACE. Available at: http://www.hec.usace.army.mil/

software/legacysoftware/hec6/hec6-documentation.html.

U.S. Department of Agriculture. 1995. Appendix 8. Similari-

ties of WEPP with other models that might be used for

erosion computations. In WEPP User Requirements,

NSERL Report 11, Lafayette, Indiana, Available at: http://

topsoil.nserl.purdue.edu/nserlweb/weppmain/jhtml/adv-

dis.html.

U.S. Environmental Protection Agency. 1993. Guidance

specifying management measures for nonpoint pollution

in coastal waters. EPA840-B-92-002. USEPA, Washington,

DC, 828 pp.

U.S. Environmental Protection Agency. 2000a. The quality of

our nation’s waters, A summary of the National Water

Quality Inventory: 1998 report to Congress. EPA841-S-001.

USEPA, Office of Water, Washington, DC, 18 pp.

U.S. Environmental Protection Agency. 2000b. Overview of

current total maximum daily load—TMDL—program and

regulations, EPA841-F-00-009. Office of Water, Washing-

ton, DC.

U.S. Environmental Protection Agency. 2001a. The national

costs of the total maximum daily load program (draft re-

port). Support document 2. EPA841-D-01-005. Office of

Water, Washington, DC. Available at: http://www.epa.gov/

owow/tmdl/coststudy/costsupp2.pdf.

U.S. Environmental Protection Agency. 2001b. Better assess-

ment science integrating point and non-point sources,

BASINS, version 3.0, user’s manual. EPA-68-C-98-010.

Office of Water, Washington, DC, 348 pp.

U.S Environmental Protection Agency. 2004. Effluent guide-

lines, construction and development, fact sheet—final ac-

tion, non-regulatory option. EPA 82l-F-04-001. Office of

Water, Washington, DC. Available at: http://www.epa.gov/

waterscience/guide/construction/finalaction-fs.htm.

Vieira, D. A., and W. Wu. 2002. One-dimensional channel

network model CCHE1D version 3.0: User’s manual. Report

NCCHE-TR-2002-2. University of Mississippi, Oxford. avail-

able at: http://hydra.che.olemiss.edu/content/software/

eche1d/usersmanual.pdf.

Walker, D. J 2001. Modeling sedimentation processes in a

constructed stormwater wetland. Science of the Total Envi-

ronment 266:61–68.

Water, Environment and Technology Research Notes. 2001.

Conservation tillage helps clean waterways. Water Environ-

ment and Technology July:14.

Werner, T. M., and R. H. Kadlec. 2000a. Stochastic simulation

of partially-mixed, event-driven treatment wetlands. Ecolog-

ical Engineering 14:253–267.

Werner, T. M., and R. H. Kadlec. 2000b. Wetland residence

time distribution modeling. Ecological Engineering 15:77–90.

Wicks, J. M., and J. C. Bathurst. 1996. SHESED: A physically

based, distributed erosion and sediment yield component

for the SHE hydrological modeling system. Journal of

Hydrology 175:213–238.

Williams, J. R 1975. Sediment routing for agricultural water-

sheds. Water Resources Bulletin 11:956–947.

Williams, S., and B. Feltmate. 1992. Aquatic insects. CAB

International, Wallingford, UK, 360 pp.

Wilson, B.N., and B. J. Barfield. 1985. Modeling sediment

detention ponds using reactor theory and advection-diffu-

sion concepts. Water Resources Research 21:523–532.

Wischmeier, W. H., and D. D. Smith. 1978. Predicting rainfall

erosion losses—A guide to conservation planning. Agri-

cultural Handbook No. 537. U.S. Department of Agricul-

ture, Washington, DC, 85 pp.

Wong T. H. F., H. P. Duncun. T. D. Fletcher. and G. A. Jen-

kins. 2001. A unified approach to modeling urban storm-

water treatment. Pages 319–327 in Proceedings of the

second South Pacific stormwater conference, 27–29 June

2001. Aukland, New Zealand.

Yang, C. T. 1972. Unit stream power and sediment transport.

Proceedings of American Society of Civil Engineers 98:1805–1826.

Yang, C.T., M. A. Trevin

o, and F. J. M Simo

es. 1998. User’s

manual for GSTARS 2.0, Generalized Stream Tube Model

for Alluvial River Simulation. Bureau of Reclamation,

Technical Service Center, Denver, Colorado.

Yu, S. L., J. T. Kuo, E. A. Fassman, and H. Pan. 2001. Field test

of grassed-swale performance in removing runoff pollution.

Journal of Water Resources Planning and Management 127:168–

171.

Yuan, Y., R. L. Bingner, and S. Dabney. 2001. Evaluation of

agricultural BMPs for sediment reduction using AnnA-

GNPS. Pages 275–280 in Proceedings of water quality

monitoring and modeling, AWRA, 30 April–2 May 2001.

San Antonio, Texas.

Zhang, Y., and E. J. Langendoen. 1998. An introduction to

BEAMS (bed and bank erosion analysis model for streams).

Technical Report No. CCHE-TR-98-2. University of Missis-

sippi, Oxford.

194 C. T. Nietch and others

Framework for Developing Suspended and Bedded Sediments (SABS) Water Quality Criteria

Technical Report

Full-text available

May 2006

Suspended and bedded sediments (SABS) occur naturally in all types of waterbodies. In appropriate amounts, sediments are essential to aquatic ecosystems (e.g., in appropriate amounts, SABS can contribute to essential habitat for aquatic species’ growth and reproduction). However, imbalanced sediment supply has repeatedly ranked high as a major cause of waterbody impairment (U.S. EPA 2003a). The quantity and characteristics of SABS can affect the physical, chemical, and biological integrity of streams, lakes, rivers, estuaries, wetlands, and coastal waters. Excessive SABS (and in some cases, insufficient SABS) can impair waterbody uses such as navigation, recreation, and drinking water filtration. An imbalanced sediment supply resulting from human activities impacts ecological integrity at several scales and trophic levels. In 2003, the U.S. EPA Office of Science and Technology (OST) within the Office of Water (OW) issued a document titled “Strategy for water quality standards and criteria: setting priorities to strengthen the foundation for protecting and restoring the Nation’s waters” (U.S. EPA 2003a). After a wide-ranging review of the existing water quality standards and criteria programs within the context of all clean water programs and after extensive discussions with Water Quality Standards stakeholders, U.S. EPA identified 10 priorities for improving the quality of the Nation’s waters. Development of SABS criteria was among the top priorities. The U.S. EPA developed this document in support of states, tribes and territories’ efforts to establish SABS criteria that protect the ecological integrity and beneficial uses of water resources, which are major goals of the Clean Water Act (CWA). This Framework describes a process that states, tribes, and territories can use to develop SABS criteria to support water quality standards and protect designated uses. The Framework is intended to provide a consistent, defensible process for developing SABS criteria that also allows flexibility for regional and local application and interpretation. The major chapters of the Framework include both programmatic and technical elements. The programmatic elements section contains discussions of resources, integration with state programs, and implementation of criteria and standards. The technical elements section provides analytical methods for SABS criteria development. Examples are provided to illustrate how the Framework can be applied. Neither the process nor the methods are meant to be mandatory.

Landscape changes and watershed erosion in Prince George's County, Maryland

Article

Full-text available

May 2024
RIVER RES APPL

James Stribling

This study evaluated erosion rates and sediment production in streams, and factors potentially influencing them throughout the Anacostia, Patuxent, and Potomac (non-Anacostia) River watersheds within Prince George's County, Maryland, US. As part of the County's watershed-scale biological monitoring program, from approx. 1999 to 2008, permanent monuments were established to allow measurement of stream channel cross-sectional (XS) area. The intent of this study was to characterize the intensity and spatial distribution of fluvial geomorphic instability across the county and use the results to target and plan stormwater management and stream restoration actions. For this study, 78 stream locations were re-surveyed in 2020, representing a time lapse of from 12 to 21 years. Data collected included XS dimensions, modified Wolman 100-particle pebble counts, and reach-specific soil bulk density. Land use/land cover data were compiled from the National Land Cover Dataset (NLCD), precipitation from the National Weather Service Center for Environmental Information (NCEI), and soils from the Natural Resources Conservation Service Web Soil Survey (NRCS/WSS). We calculated percent change in XS area, rates of erosion, sediment yield, and assigned geomorphic classifications, and interpreted them in the context of spatial positions relative to changes in land cover characteristics. Sediment yields among the 78 reaches exhibited a combination of those undergoing enlarge-ment/erosion (67.9%), reduction/deposition (25.6%), and the remaining 6.4% with essentially no change over the period of record. Of the top 20 most geomorphically active reaches surveyed in the County, 12 are in the Anacostia River basin, with the other scattered among the Patuxent River and Potomac River basins. K E Y W O R D S erosion, fluvial geomorphology, physical habitat, prioritization, restoration, stormwater

Conservation management practices: Success story of the HOG Creek and Sturgeon River watersheds, Ontario, Canada

Article

Full-text available

May 2016

The soil erosion from agricultural watersheds can be reduced by implementation of conservation management practices. In this study, the effectiveness of most popular agricultural best management practices (BMPs) for reducing sediment loads within Hog Creek and Sturgeon River watersheds in Ontario was investigated using measurement of the shift in the sediment rating curves from pre-BMP (1989 to 1993) to post-BMP (2004 to 2008) implementation periods. The data from the water quality monitoring program for the Hog Creek and the Sturgeon River watersheds over this decade of extensive conservation management program implementation showed significant reductions in the sediment loads of 49% for Hog Creek and 41% for the Sturgeon River. The results showed that the most widely adopted BMPs that greatly influenced the overall removal in sediment loads were stream bank fencing, no-till farming, and vegetative buffer strips. Overall, the outcome of the study recommends these promising practices to protect and improve receiving water quality. The practical novel technique presented in this study for quantification of the overall long-term water quality benefits of conservation management practices can be an integral part of an adaptive strategy for a watershed-scale BMP implementation program.

A review of the potential effects of suspended sediment on fishes: potential dredging-related physiological, behavioral, and transgenerational implications

Article

Full-text available

Jul 2015

The long-term effects of sediment exposure on aquatic organisms are poorly understood, yet it is critical for determining threshold effects and exposure limits to mitigate potential impacts with regard to population dynamics. In this paper, we present the current state of knowledge to help consolidate the breadth of information regarding total suspended solids (TSS) thresholds for aquatic species, as well as identify areas where data are lacking. More specifically, we provide the state of the science related to TSS effects on freshwater and estuarine fish including short-term (i.e., physiology and behavior) and long-term effects. Our research indicated that little attention has been given to examining long-term effects, e.g., transgenerational effects, from suspended sediments (SS) on fish populations. Understanding transgenerational effects is paramount to developing and predicting the links between fish condition, survival, populations, and communities. Survival of a local fish population to high sediment loads often translates into short-term physiological and behavioral effects; however, the ramifications of such exposure events are rarely tracked across generations. The majority of studies involving SS effects on fish have focused on exposure and mortality rates of affected fish, deposited eggs, or larvae. We developed a conceptual model that highlighted the interactions between sediment dynamics and fish populations. The model can assist in the formulation of more quantitative-based approaches for modeling these interactions. Future research efforts should focus on developing an understanding of whether environmental disturbances, e.g., dredging, may lead to epigenetic changes that may lead to cascade population effects, and if so, under what circumstances.

Optimal Allocation of Stormwater Pollution Control Technologies in a Watershed

Thesis

Full-text available

Dec 2006

In recent decades, more than 90 percent of urban growth in the United States has taken place in the suburbs. The phenomenon, referred to as urban sprawl, has led to long-term degradation of environmental quality. Best Management Practices (BMPs) serve as novel effective technologies to reduce the movement of pollutants from land into surface or ground waters, in order to achieve water quality protection within natural and economic limitations. Four types of BMPs are discussed in this study—Pond, Wetland, Infiltration, and Filtering Systems. Each has different installation requirements, costs, and pollutant removal efficiency. The purpose of this research is to find out the minimum-cost combinations of these four technologies, with a focus on total suspended sediments (TSS), in order to achieve TMDL (Total Maximum Daily Loads) and EQS (Environmental Quality) standards. The methodology uses three major models: Spatial Model, Watershed Model, and Economic Model. These models provide suitability analyses for potential residential developments and BMP technology installations, stormwater and pollutant simulations, and minimum cost optimization procedure. The results of this research will provide a practical reference for decision making about the balance between the urban development and environment protection. It can further provide EPA with economic assessment information regarding existing TMDL and EQS standards.

Assessment of Watershed Nutrient Loads and Effectiveness of Best Management Practices

Thesis

Full-text available

Jun 2018

Research on Implementation Model of Enterprises Risk Management

Article

Jun 2013

Risks bring about opportunities as well as challenges to the enterprises. If corporations expect to achieve the fixed goal,they have to maximize the effectiveness of assets, and minimize risks at the same time. That's why companies must identify and assess all the significant risks, take response measures and ensure sustainable development by building an increasingly sophisticated risk management system.

Monitoring, modeling, and emergent toxicology in the east fork Watershed: Developing a test bed for water quality management.

Article

Jan 2008

Overarching objectives for the development of the East Fork Watershed Test Bed in Southwestern Ohio include, 1) providing research infrastructure for integrating risk assessment and management research on the scale of large multi-use watershed (i.e., 1295 km2). 2) focus on process-level understanding of ecotoxicology and fate/transport for emerging contaminants and stressful mixtures for linking stressor dynamics to instream ecology. And 3) developing and maintaining long-term continuity in base analytics for ecosystem structure and function useful for meta-analyses and continual testing of new indicators of stress-response, monitoring technologies, and modeling functions. The key components proposed as requisite for a watershed test bed are described here along with an example of how they have been combined to address a pertinent question related to water quality management.

The use of 7Be and 210Pbxs to differentiate fine suspended sediment sources in South Slough, Oregon

Article

Apr 2007
ESTUAR COAST

Suspended sediment was collected in the South Slough, National Estuarine Research Reserve, Oregon, over 8 tidal cycles during and following a single runoff event. The sediment was analyzed for its radionuclide signature to determine the relative contributions of different sources of sediment to the efflux from the estuary. Suspended sediment in the estuary is a mixture of sediment from three potential sources: the river system, Coos Bay, and the estuarine bed. Each source material has a distinctive 7Be: 210Pbxs ratio. The ratios of the source sediments decreased in magnitude in the following order: riverine > bay > bed. The ratios of the suspended sediment collected within a subsection of the South Slough estuary reflected the relative mixture of the source areas. The 7Be:210Pbxs ratios provided a means of not only differentiating between resuspended bed sediment and freshly delivered sediment from both the river system and Coos Bay, but also calculating the relative amount of resuspended bed sediment in the suspended sediment collected in the estuary. The sampled subsection of the South Slough estuary was a net sink of sediment during a 100-h sampling period associated with the runoff event, but the radionuclide analysis suggests that approximately 39% of the sediment efflux was resuspended bed sediment.

Effects of forest management on water resources in Canada: A research review

Article

Dec 2009

Although forestry practices commonly occur at the stand level, watersheds are used as the study unit for hydrological and water quality issues. Watersheds are natural or artificial drainages on which all precipitation and emanating spring discharges collect and flow to a common outlet. To establish a cause-and-effect relationship of ecosystem response to disturbance, it is essential to determine watershed level impact by removing biases that could occur at smaller scales. However, since the hydrologie cycle is driven by numerous processes that occur at smaller scales (e.g., évapotranspiration and snow melt), stand-level research is also vital in understanding responses at the watershed scale. More than 25 research watersheds in Canada have been used to examine the hydrologic and water quality impacts of forestry practices. Research has shown that effects of forest management on hydrology and water quality are highly variable in both magnitude and duration. Factors such as topography, sub-surface geology, forest type, watershed composition and extent of harvest all play a part, and are difficult to separate. Although a common goal in hydrological research is to transfer information gained at one scale of study to larger or smaller scales, or to transfer knowledge from one region to another, the field of forest watershed research is rife with scaling issues and uncertainty in transferability. The watershed research community is moving toward embracing these challenges. For example, several watershed research projects in Canada are incorporating information about stand-level processes in simulation models. Watershed studies should be conducted in the ecozones in which the results will be applied for forest management. There is a need for continued and increased collection of field data at established research watersheds and at new research sites. When evaluating priorities for new research watersheds, explicit consideration should be given to processes of regional significance, e.g., fog drip in the Maritimes; permafrost in the Boreal Cordillera; and large-scale harvesting and fire disturbance occurring in the Boreal Shield and Boreal Plains.

The uniqueness of place, action and time

Article

Full-text available

Jan 2001

Hydraulics Efficiency of Constructed Wetlands and Ponds

Article

Aug 1999

Constructed ponds and wetlands are widely used in urban design to serve a number of functions including stormwater management. The design of constructed wetlands for stormwater management involves a number of multi-disciplinary inputs. Fundamental to their sustainable operation are the proper control of the hydrologic regime of the wetland and optimal flow hydrodynamics within the wetland. Many ofthe problems encountered in constructed wetlands can be minimised or avoided by good engineering design principles. Poor wetland hydrodynamics are often identified as a major contributor to wetland management problems. Ponds and wetlands with a high hydraulic efficiency are expected to promote full utilisation ofthe available detention storage and near plug flow conditions. The shape and layout of urban ponds and wetlands are often varied to suit the landscape and to satisfy aesthetic requirements as an urban water feature. These can be achieved while maintaining an effective stormwater treatment outcome if steps are taken to ensure that the hydrodynamic behaviour of the system is not severely compromised. A consistent measure is required to allow the effects of design features to be evaluated against this criterion. This paper introduces a new measure for hydraulic efficiency that combines existing measures of flow uniformity and effective volume. Case studies are presented on the use of this measure to assess the effects of different pond and wetland shapes, locations of inlet and outlet, botanical layouts and basin morphology on the flow hydrodynamics.

Designing outlet characteristics for optimal wetland performance

Article

Oct 1997

Central to the hydrological and botanical design of constructed wetlands for stormwater quality management is the proper control of their hydrologic regime. The hydrologic regime, defined as the probabilistic distribution of inundation depth in the wetland, reflects the inherent variability of storm inflows to the wetland and is directly influenced by the discharge characteristics of the outlet structure of the wetland. The influence of three typical outlet structures on the hydrologic regime of a hypothetical wetland was investigated using a continuous simulation approach. The three outlet types investigated were that of a culvert, a riser and a siphon. Simulations found that all three devices provides equally effective control of the ability of the wetland to capture and detain storm runoff but can have different influence on the hydrologic regime of the wetland. The siphon-controlled wetland was found to exhibit a more even distribution of inundation depth compared to the other two outlet types.

The European Soil Erosion Model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments

Article

Jun 1998
EARTH SURF PROC LAND

The European Soil Erosion Model (EUROSEM) is a dynamic distributed model, able to simulate sediment transport, erosion and deposition over the land surface by rill and interill processes in single storms for both individual fields and small catchments. Model output includes total runoff, total soil loss, the storm hydrograph and storm sediment graph. Compared with other erosion models, EUROSEM has explicit simulation of interill and rill flow; plant cover effects on interception and rainfall energy; rock fragment (stoniness) effects on infiltration, flow velocity and splash erosion; and changes in the shape and size of rill channels as a result of erosion and deposition. The transport capacity of runoff is modelled using relationships based on over 500 experimental observations of shallow surface flows. EUROSEM can be applied to smooth slope planes without rills, rilled surfaces and surfaces with furrows. Examples are given of model output and of the unique capabilities of dynamic erosion modelling in general. © 1998 John Wiley & Sons, Ltd.

Construction practices: The good, the bad, and the ugly

Article

Jan 1994

R.G. Paterson

Costs of urban stormwater control

Article

Jan 2000

Methods for evaluating stream, riparian, and biotic conditions

Article

Jan 1983

Develops a standard way of measuring stream, riparian, and biotic conditions and evaluates the validity of the measurements recommended. Accuracy and precision of most measurements are defined. This report will be of value to those persons documenting, monitoring, or predicting stream conditions and their biotic resources, especially those related to impacts from land uses. -Authors

Economic impacts of erosion management measures in coastal drainage basins

Article

Jan 1994

Measurements and models of soil loss rates - Response

Article

Nov 2000

Modelling width adjustment in straight alluvial channels

Article

Jun 1998

Stephen E. Darby

Many existing numerical alluvial channel models are limited because they are unable to account for adjustments of channel width through time. In this paper, the basis for modelling width adjustment in straight river channels is discussed. Features and capabilities of selected models are discussed in terms of advances made in representing the physical processes and mechanisms involved in width adjustment, and in terms of approaches used to characterize initial and boundary conditions accurately. Validation and verification studies of existing width adjustment models are also considered. Existing models have, for the most part, not yet been subjected to rigorous evaluation of their numerical robustness, accuracy in replicating analytical solutions, accuracy in replicating laboratory data or their ability to simulate field situations. In part, these limitations reflect the lack of available detailed laboratory and field data sets required to evaluate complex models. The potential of width adjustment models for use as tools for the investigation of river channel dynamics is briefly described using two examples. (C) 1998 John Wiley & Sons, Ltd.

Risk Management of Sediment Stress: A Framework for Sediment Risk Management Research

Abstract and Figures

Recommended publications

Decision Support for Sustainable Management of Grazing Lands. A.D. Shulman and R.J. Price (eds), Cas...

An Exploratory Study on the Relative Weightings being put Upon Environmental Outcomes by Waikato Far...

A POSSIBLE APPROACH FOR ADDRESSING NEGLECTED HUMAN FACTORS ISSUES OF SYSTEMS ENGINEERING

De la gestion des cadres à la gestion des ressources intellectuelles