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An Evaluation of Techniques for Measuring Substrate Embeddedness

by Traci Sylte and Craig Fischenich

The degree to which fine sediments surround coarse substrates on the surface of a streambed is referred to as embeddedness. Although the term and its measurement were initially developed to address habitat space for juvenile steelhead trout, embeddedness measures have been used to assess fish spawning and macroinvertebrate habitat, as well as substrate mobility.  Embeddedness continues to be used as an indicator of water quality.

No publication provides a comprehensive description of embeddedness, and the sampling methodology is far from standardized. The information presented here is derived from a technical note (ERDC TN-EMRRP-SR-36) produced by the authors under the U.S. Army Corps of Engineers Ecosystem Management and Restoration Research Program.  The technical note documents definitions and usage of the term “embeddedness,” describes the development of embeddedness measurement, summarizes the existing literature, and provides guidelines for the application of measurement techniques.

The character of stream substrates is important to both physical and biological stream functions. In its simplest expression, increased embeddedness, or the intrusion of fines into a coarse streambed, decreases the living space between particles and limits the available area and cover for small fish, macroinvertebrates, and periphyton.

Definitions of Embeddedness

Many definitions of embeddedness exist in the literature. The following is a brief summary; others exist in the source document:

  “the degree to which cobble larger than 45-mm diameter is embedded in sand (Kelley and Dettman, 1980).

 -  “the degree that the larger particles  (e.g., boulder, rubble, gravel) are surrounded or covered by fine sediment” (Platts et al., 1983; Fitzpatrick et al., 1998).

  -  “the amount of fine sediment that is deposited in the interstices between larger stream substrate particles” (Burns, 1984; Burns and Edwards, 1985).

 -  “the extent to which larger particles are buried by fine sediment” (MacDonald et al., 1991).

 -  “the ‘depth to embeddedness’ is the distance from the top of the rocks on the bed surface down to the top of the layer of fines in which the cobbles are embedded” (Osmundson and Scheer, 1998).

Embeddedness measures the degree to which larger particles are covered with finer particles – a length term representing a volume of fines surrounding coarser substrates, which is often placed in a relative proportion to rock height in the plane of embeddedness (Fig. 1). Moreover, “fines” are commonly not defined even though the nature and degree of impact depend upon the size and the character of the sediments filling interstitial voids.  Misconceptions arise because embeddedness is conceptually appealing as an index of impact even though a precise consistent definition is lacking.

  Schematic representation of embeddedness  

              Figure 1. Schematic representation of embeddedness.

Embeddedness Measurement Methods

Klamt (1976) and Kelley and Dettman (1980) originally introduced the concept of embeddedness.  Klamt estimated the degree to which key rocks or dominant rocks in streams were embedded by using 25, 50, and 75 percent embeddedness levels. Kelley and Dettman focused on juvenile steelhead rearing habitat and quantified the depth of sand particles surrounding cobble-sized substrate in glide, glide/riffle, and riffle habitat units.

Several methods have since been developed to measure or characterize embeddedness and are summarized in Table 1.  Some of these rely on visual estimation while others measure and compute embeddedness as a percent.  Recommended sample sizes range from as few as 15 to as many as 400 particles.  Sampling may occur at locations that meet specific fish habitat criteria or span entire stream reaches.  Because of this diversity in technique, comparing embeddedness values from one application to another is ill advised.






Platts et al.;

Bain & Stevenson


General sample design guidance; no specifics for embeddedness

Thalweg or mid-channel

5 embeddedness classes:0-5, 5-25, 25-50, 50-75, 75-100%

U.S. Environmental Protection Agency EMAP

Kaufmann et al. (1999)



5 estimates at 11 cross-sections

10-cm sampling area at 0, 25, 50, 75, and 100% of cross-sectional wetted width

U.S. Geological

Survey NAWQA

Fitzpatrick et al. (1998)


3 transects;5 gravel to boulder sized substrates examined at each

Not specified

Nearest 10 percent of embedded depth per particle is averaged


Burns & Edwards


100-400 individual particle depending on desired standard deviation from the mean

Specific fish habitat depth and velocity criteria

Random 60-cm hoop toss into area meeting depth/velocity criteria; hoops tossed until sample particle number is attained 



Statistically determined; typically 20 random hoops;

3 hoops/transect typically result in @100  samples/transect

Bank to bank transects spanning a reach length of  @20 times average stream width

Focused on stream-related questions; improved statistics by averaging individuals within the hoop and then averaging the transect

U.S. Fish & Wildlife Service

Osmundson et al. (1998)


20 measurements/site

Minimum of 1 run and riffle/site; specific depth and velocity criteria wading parallel to shoreline

Measure depth to embeddedness (DTE); 20 DTE are divided by median rock width of the site and then averaged for the reach

Table 1. Summary of embeddedness methods.

Burns (1984) and Burns and Edwards (1985) essentially developed the embeddedness measurement method commonly employed. Skille and King (1989) later advanced the technique to apply it to stream analysis beyond fish habitat and strengthened its statistical rigor. However, this work has not been published.

Burns (1984) used embeddedness to refer to the proportion of a large individual particle that was surrounded by fine sediment. The size of large particles considered was 4.5 to 30.0 cm in greatest diameter, and fine sediment was defined as particles less than 6.3 mm diameter. Burns and Edwards (1985) calculated the proportion by dividing the embedded depth (De) by the total depth (Dt) of the particle lying perpendicular to the plane of embeddedness (Fig. 1). Burns used a 60-cm-diameter steel hoop to define particles in the substrate to be measured, a 30-cm-transparent ruler to measure particle dimensions, and a float and a stopwatch to measure water velocity.

Embeddedness Application Limits

In 1988, Forest Service fisheries biologists and hydrologists united to review embeddedness literature, share experiences, and refine methods. Results of the standardization effort, found only in agency correspondence documentation, identify several important application limitations.

·     Cobble embeddedness exhibits high spatial and temporal variability in both natural and disturbed streams. Sampling must be intensive to detect changes.

·     Cobble embeddedness should be a measured parameter. However, visual assessments may provide information adequate for characterization purposes.

·     Embeddedness measurements are most applicable in granitic watersheds or other geologies where sand is an important component of the annual sediment load and substrate.

·     Cobble embeddedness is best applied to streams where embeddedness is suspected or known to limit salmonid rearing.

·     Repeat monitoring must be conducted at the same site because of high instream variability.

·     Application of the method in streams less than 20 feet wide may destroy sites for future monitoring(Fig. 2)

·     Cobble embeddedness is most appropriate for stream-to-stream comparisons of similar reaches or for measuring temporal changes in the same reach.

                Typical disturbance of the streambed

Figure 2. Typical disturbance of the streambed.

Kramer (1989) identified several additional limitations to the embeddedness methodology and concluded that the techniques developed by Burns (1984) and Skille and King (1989) failed to accurately portray the true nature of temporal sediment changes in a channel. Kramer simulated conditions where fine sediment levels were increased and found that percent embeddedness actually decreased with increasing fine materials in some situations. This occurs because rocks that become 100 percent embedded are no longer measured; i.e., the total rock count is reduced and calculated percent embeddedness of the sample decreased (Fig. 3).

Example of simulated increases in embeddedness that might result from adding fines from level t1 to t3 that actually results in a reduction in the calculated embeddedness percentage

Figure 3.  Example of simulated increases in embeddedness that might result from adding fines from level t1 to t3 that actually results in a reduction in the calculated embeddedness percentage.

Relation of Embeddedness to Management Activities

The ability of embeddedness to detect changes due to land management activities is unclear and results have rarely been published in peer reviewed literature.  Burns (1984) sampled embeddedness in 19 tributaries of the South Fork of the Salmon River with varying levels of development. He found that streams with more development had statistically significant higher mean embeddedness than undeveloped or partially developed streams. Partially developed and undeveloped streams were not significantly different from each other. Munther and Frank (1986) quantified conditions in Montana streams and found significant differences in only four of eight pairings of habitat units between developed and undeveloped streams.  Potyondy (1993) in one of the most rigorous of all embeddedness studies summarized the results of cobble embeddedness analyses conducted on 120 streams in the Idaho Batholith on the Boise National Forest (Potyondy 1988) using the Burns (1984) measurement methodology.  Potyondy found no statistical differences among streams in watersheds with various degrees of land-disturbing impacts from timber harvest, road construction, grazing, and mining. Stream embeddedness levels appeared to be more closely related to estimated natural sediment yields related to geology rather than to management activities occurring in the watersheds.

Current Application

Few field projects currently use the Burns-Skille-King method. In the late 1980s and early 1990s, the method was widely used by the Payette, Boise, Nez Perce, Clearwater, Helena, Deerlodge, Bitterroot, and Lolo National Forests. We conducted a brief literature review of the current use of embeddedness in the United States and found that embeddedness remains a common monitoring technique in at least 17 states and is present as a water quality criterion where legal implications, such as Total Maximum Daily Load (TMDL) issues, may ensue.

Although embeddedness is still widely used as a substrate measurement, certain negative aspects are apparent. These include the following:

·     Significant differences exist in methodologies.

·     Published guidance fails to provide the appropriate detail needed for field application.

·     Fundamental defects exist such that a change in approach is necessary.

Without additional research addressing the reliability of embeddedness outputs from the various methods, use of embeddedness as standards and guidelines or to link embeddedness to biologic criteria currently appears highly questionable.


Bain, M. B., and Stevenson, N. J., eds. (1999). Aquatic habitat assessment: Common methods. American Fisheries Society, Bethesda, MD.

Burns, D. C. (1984). An inventory of embeddedness of salmonid habitat in the South Fork Salmon River drainage, Idaho, Unpublished paper, USDA Forest Service, Payette National Forest, McCall, ID.

Burns, D. C., and Edwards, R. E. (1985). Embeddedness of salmonid habitat of selected streams on the Payette National Forest, USDA Forest Service, Payette National Forest, McCall, ID.

Fitzpatrick, F. A., Waite, I. R., D’Arconte, P. J., Meador, M. R., Maupin, M. A., and Gurtz, M. E. (1998). Revised Methods for Characterizing Stream Habitat in the National Water-Quality Assessment Program, Water-Resources Investigations Report 98-4052, U.S. Geological Survey, Raleigh, NC.

Kaufmann, P. R, Levine, P., Robison, E. G., Seeliger, C., and Peck, D. V. (1999). Quantifying Physical Habitat in Wadeable Streams, EPA/620/R-99/003. U.S. Environmental Protection Agency, Washington, DC.

Kelley, D. W., and Dettman, D. H. (1980). Relationships between streamflow, rearing habitat, substrate conditions, and juvenile steelhead populations in Lagunitas Creek, Marine County, 1979, Unpublished Report, Marine County Water District, CA.

Klamt, R. R. (1976). The effects of coarse granitic sand on the distribution and abundance of salmonids in the central Idaho Batholith, M.S. thesis, University of Idaho, Moscow.

Kramer, R. (1989). Evaluation and revision of the hoop method for monitoring embeddedness, Unpublished Report, Lolo National Forest, Missoula, MT.

MacDonald. L. H., Smart, A. S., and Wissmar, R. C. (1991). Monitoring guidelines to evaluate effects of forestry activities on streams in the Pacific Northwest and Alaska, EPA/910/9-91-001, United States Environmental Protection Agency, Water Division, Seattle, WA.

Osmundson, D. B., and Scheer, B. K. (1998). Monitoring cobble-gravel embeddedness in the streambed of the upper Colorado River, 1996-1997, Final Report, U.S. Fish and Wildlife Service, Grand Junction, CO.

Platts, W. S., Megahan, W. F., and Minshall, W. G. (1983). Methods for evaluating stream, riparian, and biotic conditions, General Technical Report INT-138, USDA Forest Service, Rocky Mountain Research Station. Ogden, UT.

Potyondy, J. P. (1988). Boise National Forest cobble embeddedness baseline inventory: Results and relationship to management activities, Unpublished Report, Boise NF, Boise, ID.

Potyondy, J. P. (1993). Relationship of fish habitat condition to management activities on granitic watersheds in Central Idaho, Hydrological Science and Technology 8(1-4), 117-122.

Skille, J., and King, J. (1989). Proposed cobble embeddedness sampling procedure, Unpublished draft, Idaho Department of Health and Welfare, Division of Environmental Quality, and USDA Forest Service, Intermountain Research Station, Boise, ID.


Traci Sylte is a Hydrologist, Lolo National   Forest, Missoula, MT;; (406) 329-3896.

Craig Fischenich is a Research Civil Engineer, US Army Engineers, Research and Development Center, Vicksburg, MS;; (601) 634-3449.

For more information about embeddedness see: Sylte, T. L., and Fischenich, J. C. (2002).

"Techniques for measuring substrate embeddedness,” EMRRP Technical Notes Collection (ERDC TN-EMRRP-SR-36), U.S. Army Engineer Research and Development Center,  icksburg, MS.  Available online at:


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