NFBR Mining Supplemental EIS

1

Appendix 3

Appendix 3

NFBR Mining Supplemental EIS

NFBR Watershed Roads Analysis and the modified R1-R4 erosion model

In the 2004 NFBR Mining FEIS (2004 FEIS) two methods were used to try and estimate the 

impact of roads on water quality as it pertained to 1) inputs of sediment into streams in the 

NFBR watershed and 2) increase in the drainage network, and drainage efficiency. The first 

method used components of the Region 1-Region 4 erosion model (Potyondy 1991) to estimate 

potential contributions of sediment from logging, roads, and mining in the NFBR watershed

(USDA 2000). The model provided a qualitative comparison of potential erosion and soil loss 

generated as a result of different activities and the potential for delivery if linear distance from 

the stream channel was the only and most important factor determining delivery. This modified 

model was based on a GIS analysis, literature review, and the Region 1-WATSED (Water Yield 

and Sediment Yield) model (USDA 1991). There was no field component.

The second method was a Forest Service field-based roads inventory combined with a GIS 

analysis. All roads in the watershed were inventoried except private roads, the State Highway, 

and certain county roads. The Roads Analysis (USDA 2002) utilized GIS mapping and database 

querying to answer a series of water quality questions, and thereby obtain accurate information 

and significant data on which to stratify roads with respect to water quality risks. The result was 

a numeric value ERS (Erosion Risk Score) based on scientific judgment and information that 

resulted in a list of priorities for future road restoration and maintenance (USDA 2002). 

The driving force behind the model, and in part the Roads Analysis, was to determine the

potential for roads in the NFBR watershed to contribute to water quality degradation via through 

sediment input. The model examined the potential contribution of sediment into stream for 

roads, logging and mining based solely on linear distance from a stream channel. The Roads 

Analysis evaluated only road conditions. The results from the two methods were then linked in 

the 2004 FEIS and referenced in the Watershed and Soil Resource, Fisheries, and 

Transportation/Access sections. The results were the basis for the development and selection of 

Alternative 4. 

The water quality and sediment input conclusions in the 2004 FEIS were re-examined as part of 

this Supplement analysis. The review involved re-examining the assumptions of each method,

how the results from each method were linked, and what elements of their analysis were 

excluded from the 2004 FEIS. The conclusion of this Supplement analysis is that the 2004 FEIS

overstated the impact of roads on water quality, and that the roads in the NFBR watershed are 

not a major contributor to water quality degradation as it pertains to sediment inputs. The model 

results and the Roads Analysis conclusions were incorrectly translated from estimates of 

sediment generated by an activity (model) or potential risks of sediment delivery (model and 

Roads Analysis) into reality. Support for this conclusion is provided below in the discussion of 

the methods, the assumptions used in the methods to draw conclusions, and by considering the 

intent of each method. In addition, discussions with authors of the Model analysis (C. Bradford, 

USFS, pers. comm., 2006) and the Roads Analysis (D. Taylor, USFS, pers. comm., April 2008)

found agreement with the conclusions drawn below. 
Appendix 3 NFBR Mining Supplemental EIS

2

This discussion will be referenced in Chapter 3 of the Supplement when discussing road-water 

quality analysis and conclusion changes made from the 2004 FEIS to the Supplement in the 

Watershed and Soils Resources, Fisheries, and Transportation/Access sections. 

The Model

Bradford and Fedora (USDA 2000) used components of the Region 1-Region 4 erosion model 

(Potyondy 1991) to estimate potential contributions of sediment from logging, roads, and mining 

in the NFBR watershed. Their model was based on a GIS analysis, literature review, and the 

WATSED model. There was no field component, though the model results are later tied to the 

Roads Analysis. 

Bradford and Fedora (USDA 2000) used the following information to estimate potential tons of 

sediment that could be generated by different activities and then potentially transported and 

delivered to streams: 1) channel erosion response curves for different disturbances (Table A3-1

and A3-2) estimated sediment delivery ratios based on the linear distance between a disturbance 

and a channel (Table A3-2). Detailed discussion of the model is found in Bradford and Fedora’s 

analysis (USDA 2000, Appendix C). However, a portion of that discussion is presented here 

because it is relevant to the conclusion in this Supplement that the 2004 FEIS overstated the 

impact of roads on water quality. 

The predicted soil erosion curves for management activities (Table A3-1) were obtained from the 

WATSED model documentation. The erosion response curves data used came from three 

sources: 

1) the WATSED model, 

2) values estimated by van der Zweep (1999) based on professional judgment, and 

3) values estimated by Kennedy (1997) to be 17% of unsurfaced roads (USDA 2000).

“Soil detachment and sediment transport are two components used by the R1-R4 model for the 

prediction of sediment yield from a watershed. Soil detachment component, or soil erosion, 

predicts how much soil is moved from its original location. The amount that detached sediment 

moves downhill or downstream is predicted by a sediment transport component (USDA 2000, 

p. C-2). 
NFBR Mining Supplemental EIS

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Appendix 3

Table A3-1.

Erosion Response Curves for North Fork Burnt River non-point sources 

(USDA 2000, Table C.1)

Proposed activity Predicted Soil Loss (tons/sq. mile/yr)

Year 1 Year 

2

Year 

3

Year 4 Year 5 Year 6 Year 7

Road construction 112750 9817 8160 6875 5100 4450 4080

Temp Road construction 212750 6375 3188 1594 797 398 0

Closed Road (Level 1) 22040 2040 2040 2040 2040 2040 2040

Reopen closed road 24080 3060 2550 2295 2168 2104 2040

Open Native Surface Road 

(Level 2) 1

4080 4080 4080 4080 4080 4080 4080

Open Aggregate Surfaced 

road (Level 3) 2

694 694 694 694 694 694 694

Logging (tractor) 1352 187 144 92 42 21 0

Logging (cable) 1221 110 55 0 0 0 0

Wildfire (high intensity ) 1550 468 275 138 83 44 17

Wildfire (moderate 

intensity) 2

225 234 138 69 42 22 8

Wildfire (low intensity, 

prescribed natural fire) 1

10 0 0 0 0 0 0

Road obliteration 212750 6375 0 0 0 0 0

Subsoiling 2525 278 137 0 0 0 0

Note: there is no value for mining disturbance

1 WATSED

2 Values estimated by van der Zweep (1999) based on professional judgement

3 Values estimated to be 17% of unsurfaced roads (Kennedy 1997)

According to the model, the volume of predicted soil loss assigned to open and closed native 

surface roads is an order of magnitude greater than logging, or low to moderate intensity 

wildfire. It is four times (closed road) and eight times (open road) as great as that estimated for a 

high intensity wildlife. Therefore, even if roads were rare in a watershed and logging or 

wildfires common and widespread, roads would still be weighted heavily as a source of sediment 

generation that could potentially be transported and delivered to a stream.

The model then used only the linear distance between a disturbance and a channel to determine 

the amount of sediment potentially delivered to a channel (sediment delivery ratio) due to lack 

of other information (Table A3-2). However, as clearly stated by Bradford and Fedora (USDA 

2000) and in a review of riparian buffer articles by Belt et al (1992), distance is only one factor 

that determines the amount of sediment delivered to a stream, and it is often not the most 

important one. Therefore, the sediment delivery ratios presented in Table A3-2 represent 

maximum values possible under a highly simplified landscape. The context of the model results 

– maximum values possible under a highly simplified landscape – were lost in the FEIS and 

appeared instead as actual delivery. 
Appendix 3 NFBR Mining Supplemental EIS

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“The distance that sediment gets transported before getting deposited depends on 

numerous characteristics including slope gradient, surface roughness, vegetation and 

litter cover. Delivery ratios predict the ratio of detached sediment that actually leaves a 

particular watershed. Sediment delivery ratios in WATSED were based on land type 

and slope position and the values varied from 1% on ridge tops to 80% on stream 

bottoms. 

Land type databases have not been developed on the Wallowa-Whitman National 

Forest, so an alternative method using existing data was developed to estimate sediment 

yield based on the distance of the disturbance to the nearest stream (USDA 2000, p. C2).” 

Table A3-2.

Estimated sediment delivery ratios (van der Zweep 1999) 

(Bradford and Fedora 2000, Table C.2)

Distance from stream channel 

(meters)

Delivery ratio (%)

0 – 50 30

51 – 100 20

100 – 150 10

> 150 1

Tables A3-1 (predicted soil loss) and A3-2 (estimated sediment delivery ratios) were used to 

estimate tons of sediment that might make it to the stream from a given activity (Equation 1). 

Equation 1: 

Predicted soil loss (tons/sq. mi/yr) x Disturbance area (sq. miles) within a given sediment 

delivery zone x estimated sediment delivery ratio (%) = sediment delivered to stream (tons/yr)

As stated earlier, the distance that sediment gets transported before being deposited depends on 

numerous characteristics including slope gradient, surface roughness, vegetation and litter cover 

in the buffer strip and fillslope, as well as distance from a stream (Belt et al. 1992) and distance 

travelled. The distance will also travel will also vary depending on if water moves as 

channelized versus sheet flow. 

The type and density of vegetation or obstructions on the fill slope can greatly reduce sediment 

movement via sheet flow off the fill slope. Burroughs and King (1985) compared sediment 

yields from treated fill slopes and the yields from fill slopes with a loose soil surface. They 

found that dense grass planted on a section of fill slope at a 67% slope reduced sediment yield by 

97%, a wood fiber mulch reduced sediment yield by 91%, and a slash windrow reduced sediment 

yield by 87%. Trapping of sediment transported via sheet flow would be enhanced even further 

as slope decreased. Wright et al. (1982) examined soil losses after a prescribed burn in a 

grassland/shrub area with some oak and juniper. They found that soil losses and changes in 

water quality were not serious on 20% or less slopes, but that adverse effects lasted for 15 to 

more than 30 months on slopes 37 to 61%. They also found that soil loss rates stabilized when a 

combination of live vegetation and ground cover reached 64 to 72% during normal to wet years,
NFBR Mining Supplemental EIS

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Appendix 3

or 53 to 60% during dry years. And an experimental study of the effects of changing percentages 

of vegetation cover on sediment yields (no fire component) found that sediment yields decreased 

rapidly on 10% slopes as live vegetative cover increased from 15 to 43% (Rogers and Schumm 

1991). The Burroughs and King (1985) study also showed the impact of increasing storm 

duration on sediment yields as a function of ground cover. As storm durations increased, so did 

sediment yields. However, the same pattern remained of decreasing sediment yields with 

increasing live vegetative cover.

Channelized flow is limited to cross-drains, culverts, drainage ditches along the inside of the 

road bed and in the vicinity of a stream crossing, and road ruts and rills. Because these features 

are restricted in space, their impact is localized. Therefore, the values generated by the model 

represent a maximum value that could be generated and might be delivered to a stream if 

1) distance was the only factor influencing delivery, 

2) the predicted soil loss values were appropriate for roads built in the 1970s through the 

1980s, and 

3) the fillslopes and intervening topography between the base of the fillslope and the stream 

were unvegetated. 

Belt et al. (1992) stated in their review of the studies evaluating the effectiveness of buffer strips 

in reducing sediment inputs into streams that “Road construction [emphasis added] is generally 

recognized as the largest single source of sediment because the removal of vegetation and 

construction of cut and fill slopes initially exposes large areas of erodible surface (p. 15).” 

However, Belt et al. (1992) also indentified fillslope cover and the role of slope and topography 

in reducing sediment movement. The roads in the NFBR watershed have been in place since the 

1970s and 1980s and the fillslopes have become vegetated.

Field work conducted for this Supplement by the Whitman District hydrologist found no 

evidence to support the model’s results that large volumes of sediment were being delivered to 

the stream. Evidence for channelized or diffuse flow originating off the road fillslope and 

crossing the valley floors was absent. NFBR watershed roads in close proximity to stream 

channels were separated from the streams by zones with moderate to high ground cover and 

micro-topography, and it was common for the streams to be lined with old placer mining tailings. 

Fillslopes have become vegetated with a mix of trees, litter and grasses, thereby effectively 

trapping the sediment that exits the road as sheetwash. These features have effectively limited

the amount of road sediment that could be delivered to NFBR streams.

Location of potential sediment inputs from roads into channels in the NFBR area are restricted to 

road-stream intersections, fords, or failed road drainage features where flow is concentrated.

However, both stream crossing and cross-drains are limited in the area. Therefore, the use of 

estimated sediment delivery ratios based on solely on a linear distance from a stream does not 

reflect conditions in the NFBR watershed, and overstates tons delivered to the streams in this 

area. In addition, the erosion response curves (Table A3-1) of predicted soil loss are likely high 

for this area because the majority of NFBR Forest Service roads were built in the 1970s and 
Appendix 3 NFBR Mining Supplemental EIS

6

1980s (2004 FEIS, Chapter III, p. 69) and bare ground is limited to the cutslope and the road 

beds. 

Stream Bank Conditions

While sediment is indeed entering the NFBR streams, field work in Fall 2006 and Fall 2007 by 

the Whitman District hydrologist found that the source of the majority of the sediment is from 

eroding stream banks. Field observations found vertical banks composed of fine sediment 

overlying gravels, or stream banks composed of old placer tailings devoid of stabilizing riparian 

vegetation. Blocks of stream bank were observed in the stream and the abundance of 

unvegetated, vertical stream banks indicated that instream erosion is an ongoing process. Unlike 

roads, stream banks have no features that can prevent the delivery of sediment from an eroding 

stream bank into the stream. In contrast, the sediment delivery potential from roads, logging, 

and mining is minimized or eliminated by topography, ground cover, placer tailings along stream 

banks, and/or stable, vegetated road fillslopes and stable road beds. Therefore, though the model 

indicates that roads have the highest potential to contribute sediment to streams, this is only 

when roads are 1) compared to logging, and mining and 2) when distance from a stream is the 

only parameter considered. 

The conclusions of this Supplement, with respect to the relative contribution of sediment into 

streams from roads, mining, and logging compared to stream bank and bed erosion, is in 

agreement with the final conclusions of Bradford and Fedora (2002) found in the Fisheries 

section of the FEIS (Ch. III, p. 54-55). They concluded that the majority of the sediment 

entering the streams was coming from channel erosion and background soil erosion. 

“Sediment yields resulting from mining, roads, and timber harvest are 

approximately 5 tons/sq. mile/year [based on model]. This [5 tons/sq. mile/year 

from all three human activities] represents approximately 2.3% of the average 

annual yield contributed to the reservoir [based on a 1991 Bureau of Reclamation 

study]. The remainder of the sediment budget [97.7%] must come from channel 

erosion and background soil erosion (Bradford and Fedora, 2000) (emphasis 

added).”

It is important to keep in mind that this 5 tons/sq. mile/year estimate was intended for 

comparison purposes only. It does not reflect current conditions. Sediment inputs into the 

reservoir are episodic in nature and volumes would vary as a function of timing and location of 

land uses, type of disturbance, and climatic events. Watershed vegetation conditions have 

improved greatly since the reservoir was built and soil disturbances from road building, logging 

and mining are much less than historically occurred. 

Roads Analysis

The second method used to access potential inputs of sediment into streams from roads was the 

NFBR Watershed Roads Analysis completed in 2002. This analysis combined field inventory 

and reconnaissance with a GIS analysis which evaluated questions related to water quality 

threats on each individual road in the watershed, excluding private roads, the State Highway, and 

certain County roads. 711 miles of Forest Service roads were inventoried out of the 747 miles of 
NFBR Mining Supplemental EIS

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Appendix 3

road identified in GIS in the NFBR watershed. The road inventory qualitatively rated Forest 

Service road conditions as good, fair, poor, bad, or very bad, based on evidence of road erosion 

and sediment transport (USDA 2002, Figure 4.1, pp. 15-16). Roads rated poor, bad, or very bad 

were selected out of the total roads and then subjected to a GIS analysis to obtain road-related 

information and data. The GIS analysis overlaid various parameters (Table A3-3) selected to 

capture the potential for a road to generate and deliver that sediment to a channel. The 

information and data were rated, prioritized and quantified to obtain an Erosion Risk Score 

(ERS). The ERS was then used to identify a list of priorities for future restoration and 

maintenance (USDA 2002).

Table A3-3

Parameters used in the GIS analysis of the roads that had rated poor, bad, or very bad and 

the information sought

Parameters examined Information provided

Soil erosivity Sediment generation potential

Road surface type Sediment generation potential

Landslide areas Sediment generation potential and 

possible mechanism for sediment delivery 

to stream

Current road conditions Sediment generation potential and 

delivery potential (i.e. are ruts or rills 

present?)

Riparian Habitat Conservation Area 

(RHCA)

Sediment delivery potential 

Number of stream crossing (actual and 

adjusted number based on length of road in 

the RHCA)

Sediment delivery potential

Topography Sediment delivery potential

The Roads Analysis was intended as a screening tool to assist in stratifying roads. An ERS of 

Extreme, Severe, or Serious was meant only to indicate potential for sediment generation or 

sediment delivery into a channel, not actual generation or delivery. “The accumulation of data 

generated through answering these questions was rated, prioritized and quantified to obtain a 

numeric value based on scientific judgment and information that resulted in a list of priorities for 

future restoration and maintenance (USDA 2002, p.17).” 

A road inside an RHCA was weighted very heavily in the generation of an ERS. Therefore, 

three points regarding how GIS used RHCAs in its analysis need to be made in order to 

understand how the ERS would have been skewed. 

The first point is one of clarification. RHCA buffer widths vary depending on flow and 

presence/absence of fish. A fish-bearing perennial or fish-bearing intermittent stream is given a 

300-foot buffer on each side of the channel. A non-fish bearing, intermittent stream in a nonpriority watershed such as the NFBR is given a 50-foot buffer. A non-fish bearing, perennial 
Appendix 3 NFBR Mining Supplemental EIS

8

stream is given a 150-foot buffer. The Roads Analysis (USDA 2002), however, did not make a 

distinction between the type, and therefore width, of the RHCA buffer. Thus a road that was 75 

feet from a stream would be inside the RHCA if along a perennial, fish-bearing stream, but 

outside the RHCA buffer if along a non-fish bearing intermittent stream. In this way, the Roads 

Analysis (USDA 2002) differs significantly from the modified R1-R4 model (USDA2000) which 

used fixed distances from a stream without regard to RHCA classification. The ability to link the 

two methods is thus compromised. 

The second point has to do with how RHCAs were used to rate road connectivity to the streams,

or the likelihood that a road could deliver sediment to a stream. The GIS analysis determined 

the number of times a road crossed a channel and the length of road that was inside an RHCA. 

The number of stream crossings was then increased as a function of the length of road inside an 

RHCA. The variable buffer widths again provide a complication in the assessment as shown in 

the following example: 

Road 1 is two miles long and is within 250 feet of a perennial fish-bearing stream (300-foot RHCA 

buffer) for its entire length. It has one stream crossing. Road 1 would end up with a RHCA Interaction 

factor of 21. Road 2 is also two miles long but is within 100 feet of an intermittent non-fish bearing 

stream (50-foot RHCA buffer). It has 10 stream crossings. Road 2 would end up with a lower RHCA 

Interaction factor (11) despite the fact that actual road-stream connection is higher for Road 2. 

Finally, the third point is the Road Connectivity Percentage calculation. This calculation looks 

at the length of road inside an RHCA compared to its total length -- the higher the percentage of 

road/total road length along inside the RHCA the higher the RHCA Significance Index. Using 

the above example, Road 1 would end up with an RHCA Significance Index of 9 because more 

than 56% is within the RHCA. Road 2 would end up with an RHCA Significance Index of 0 

because none of its length is within an RHCA. The result of using the RHCA buffer without 

regard to actual distance is that the Roads Analysis overstated the potential for sediment delivery 

for some roads and understated the delivery potential for others. Therefore, road work on those

roads that ended up with an ERS of Extreme, Severe, or Serious does not automatically translate 

into a measurable improvement in water quality if the roads were not actually delivering 

sediment.

Conclusions

Three components need to be examined when assessing whether sediment generated by a 

disturbance may present a water quality problem. 

1. The amount of sediment generated and its spatial location with respect to a stream 

channel. 

2. The amount of that sediment that is transported off-site. 

3. The amount of that sediment that is actually delivered to a stream channel. 

Activity type determines the amount of sediment generated, and ground conditions and weather 

determine the amount and distance a sediment particle is transported from its original site. Site 

conditions between the activity and the channel, along with the timing of weather conditions
NFBR Mining Supplemental EIS

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Appendix 3

with respect to the disturbance, will determine the amount and timing of sediment delivered to a 

stream channel. 

Studies examining the amount of road sediment moved during a weather event are limited. 

However, a review of the literature on surface erosion after wildfires found that an increase in 

sediment inputs as a result of a wildfire will be temporary with recovery to pre-fire levels about 

three years after a low-severity wildfire, and 7 to 14 years after a moderate or high-severity 

wildfire, respectively (Robichaud et al. 2000,) and that ground cover was key to stabilizing and 

reducing soil loss (Wright et al. 1982). Wright et al. (1982) examined soil losses after a 

prescribed burn in a grassland/shrub area with some oak and juniper. They found that soil losses 

and changes in water quality were not serious on 20% or less slopes, but that adverse effects 

lasted for 15 to more than 30 months on slopes 37 to 61%. They also found that soil loss rates 

stabilized when a combination of live vegetation and ground cover reached 64 to 72% during 

normal to wet years, or 53 to 60% during dry years. Wright et al. (1982) found significant 

reduction in soil losses 3 months after seeding, and soil loss rates reached pretreatment levels in 

6 months. On the unseeded slopes, it took 15 to 18 months before soil loss rates decreased 

significantly, and 33 to 42 months to reach pretreatment levels. And an experimental study of 

the effects of changing percentages of vegetation cover on sediment yields (no fire component) 

found that sediment yields decreased rapidly on 10% slopes as live vegetative cover increased 

from 15 to 43% (Rogers and Schumm 1991). Their study also showed the impact of increasing 

storm duration on sediment yields as a function of ground cover. As storm durations increased 

so did sediment yields. However, the same pattern remained of decreasing sediment yields with 

increasing live vegetative cover.

The Roads Analysis (USDA 2002) and the modified R1-R4 model results cannot be linked

because the two methods used different techniques to determine potential for sediment delivery. 

The variability in methods with no factors in common resulted in different conclusions for the 

same road. The modified R1-R4 model used a straight linear distance between a disturbance and 

a stream channel to determine potential sediment delivery ratio. The Roads Analysis used the 

variable Riparian Habitat Conservation Areas (RHCA) to define the distance relationship 

without noting actual distances, and adjusted road connectivity based on whether a road was 

inside/outside an RHCA. Roads in the Roads Analysis that were of equal distance from a 

stream, but in different RHCA buffer zones, ended up with very different ratings, while the same

roads in the modified R1-R4 model ended up with the same sediment delivery ratio. 

Sediment is entering the NFBR streams, but field work in Fall 2006 and Fall 2007 by the 

Whitman District hydrologist found that the bulk of it is coming from the stream banks. There is 

sufficient complexity in ground conditions between roads and stream channels to effectively trap 

road sediments that exit the road as sheet flow. While many of the roads parallel drainages, the 

numbers of actual fords or road-stream channel crossings are few. The study of forest roads in 

the western Cascades found that nearly 60% of all roads in their study area were hydrologically 

integrated with the stream systems (Wemple 1994; Wemple et al. 1996). This number was used 

in the 2004 FEIS (Chapter III, p. 15) to estimate percent increase in drainage efficiency (Chapter 

III, p. 15, Table III-6). Sixty percent is likely high for the NFBR watershed because the 

landscape is drier, the topography less steep, tributaries, and therefore ditch relief culverts, much 

fewer than the western Cascades. 
Appendix 3 NFBR Mining Supplemental EIS

10

The conclusion of this Supplement that 60% connectivity between roads and streams 

overestimates conditions on the NFBR watershed is based on a review of Wemple et al (1996). 

In this study the authors noted that the key factor in determining drainage network extension is 

the number of culverts which deliver water to a stream. Therefore, as the number of stream 

crossings decreases, so does the connectivity of the roads to the streams and the amount of 

drainage network extension.

The importance of channel and stream bank erosion was noted by Bradford and Fedora (USDA 

2000, p. C-4), but could not be factored into the model. The statement that the vast majority of 

sediment is generated from other activities and from channel and stream bank erosion (Bradford 

USDA 2000, C-4) was mentioned only once in the 2004 FEIS (Chapter III, p. 54) though bank 

erosion is mentioned three other times in other places (Chapter III, pp. 13, 41, 151). The result 

is that the importance of bank erosion as a source of sediment input into streams is lost in the 

presentation and interpretation of the model results. 

In conclusion, the assumptions in the two methods, their very different approaches, and absence 

of parameters in common, often resulted in the same road having different impacts. The 

assumptions and approaches prevent their results from being linked. Based on the above 

discussion, it is therefore, the conclusion of this Supplement that sediment contribution from 

roads into streams was overstated and does not reflect current conditions.