September 2010

Washington Road Sub-Basin Scale 

Effectiveness Monitoring First Sampling Event 

(2006-2008) Report

Kathy Dubé, Alice Shelly, Jenelle Black, Karen Kuzis

Cooperative Monitoring 

Evaluation & Research

CMER 08-801
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Washington State Forest Practices Adaptive Management Program

Cooperative Monitoring, Evaluation, and Research Committee (CMER)

Report

Washington Road Sub-Basin Scale Effectiveness Monitoring

First Sampling Event (2006-2008) Report

Prepared by:

Kathy Dubé, Alice Shelly, Jenelle Black, Karen Kuzis

Prepared for the

Cooperative Monitoring, Evaluation, and Research Committee (CMER)

of the

Washington State Forest Practices Board 

Adaptive Management Program

Washington State Department of Natural Resources

Olympia, Washington

May 2010 CMER 08-801
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Forest Practices Adaptive Management Program

The Washington Forest Practices Board (FPB) adopted an adaptive management program in 

concurrence with the Forests & Fish Report (FFR) and subsequent legislation. The purpose of 

this program is to: 

Provide science-based recommendations and technical information to assist the board in 

determining if and when it is necessary or advisable to adjust rules and guidance for 

aquatic resources to achieve resource goals and objectives. (Forest Practices Rules, WAC 

222-12-045)

To provide the science needed to support adaptive management, the FPB made the Cooperative 

Monitoring, Evaluation and Research Committee (CMER) a participant in the program. The 

FPB empowered CMER to conduct research, effectiveness monitoring, and validation 

monitoring in accordance with guidelines recommended in the FFR.

Disclaimer

This technical report contains scientific information from a research study designed to evaluate the 

effectiveness of the Forest Practices Rules in achieving one or more of the Forests & Fish performance goals, resource objectives, and/or performance targets. The document was prepared for 

CMER and was intended to inform and support the Forest and Fish Adaptive Management Program. 

The project is part of the Roads Rule Group Road Sub-Basin Scale Effectiveness Monitoring 

Program, and was conducted under the oversight of the Uplands Processes Scientific Advisory 

Group (UPSAG). 

This document has been reviewed by CMER and has been assessed through the Adaptive Management Program’s independent scientific peer review process. CMER has approved this document for 

distribution as an official CMER document. As a CMER document, CMER is in consensus on the 

scientific merit of the document. However, any conclusions, interpretations, or recommendations 

contained within this document are those of the authors and may not reflect the views of all CMER 

members.

Proprietary Statement

This work was developed with public funding including contracts: PSC 05-386 and PSC 08-73. As 

such it is within the public use domain. However, the concept of this work originated with the 

Washington Department of Natural Resources (WDNR) and the authors; permission must be 

obtained from the originators to use the results in the way developed herein. Use of results without 

permission of WDNR and the authors may be deemed a violation of federal statures under preview of

the Office of Research Integrity. As a public resource document, this work should be given proper 

attribution and be properly cited.
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Full Reference

Dubé, K., A. Shelly, J. Black, and K. Kuzis. 2010. Washington road sub-basin scale 

effectiveness monitoring first sampling event (2006-2008) report. Cooperative 

Monitoring, Evaluation and Research Report CMER 08-801. Washington Department of 

Natural Resources. Olympia, Washington. 

This report was prepared under contact to the Washington Department of Natural Resources as 

part of Contacts No. PSC-05-386 and PSC-08-73.

Author Contact Information

Kathy Dubé

Watershed Professionals Network

kdube@watershednet.com

Alice Shelly

TerraStat Consulting Group

alice@blarg.net

Jenelle Black

Northwest Indian Fisheries Commission

jblack@nwifc.org

Karen Kuzis

ENVIRON International Corporation

kkuzis@Environcorp.com

Acknowledgements

Many thanks to the members of the UPSAG committee and all others who reviewed various 

work products throughout both phases of this project. Your comments and thoughts are 

appreciated. Reviewers included Julie Dieu, Mark Hicks, Doug Martin, Dick Miller, Bob 

Palmquist, Nancy Sturhan, Laura Vaugeois, Curt Veldhuisen, and the Independent Science Panel 

Review committee members. Jenelle Black performed the site selection process. Thanks also to 

the field crews who drove and walked all those road miles: Scott Hotchkiss, Pete Malinak, Matt 

Rourke, Jesse Saunders, Dan Thomas, and Brett Winterowd, and to Ted Hitzroth for GIS 

support. 
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ABSTRACT

New Forest Practice Rules for forest roads under Washington Department of Natural Resources 

(WDNR) jurisdiction were adopted in Washington State in 2001. Implementation of the road 

rules for existing roads is planned over a 15-year time horizon through the completion of Road 

Maintenance and Abandonment Plans (RMAP). The objectives of the Road Sub-Basin Scale 

Effectiveness Monitoring Program are: 

• to determine if the road characteristics that affect runoff and sediment delivery to streams 

are improving through time as RMAP are implemented between 2001 and 2016; and

• to determine the extent to which roads on lands subject to WDNR forest practice rules 

meet the FFR performance targets. 

Characteristics of forest roads in a total of 60 random four-square-mile sample units across the 

state were inventoried between 2006 and 2008, five to seven years after the forest practice rules 

were adopted. This is the first sample event planned for the Road Sub-Basin Scale Effectiveness 

Monitoring Program, and provides the first look at the current status of forest roads. 

A high percentage of roads in the sample units across the state were reported to either have 

RMAP work complete, or already be up to current road rule standards, with over half of the 

sample units reported to have at least 85 percent of road length meeting standards. An average 

of 11 percent of the road network was hydrologically connected and assumed to deliver water 

and sediment to streams or wetlands. Across the state, 62 percent of the sample units met the 

Forests & Fish Report (FFR) hydrology performance target (miles of delivering road/miles of 

stream) and 88 percent of the units met the FFR sediment performance target (tons of delivered 

sediment/year/miles of stream). 

Statewide, no relationship was found between length of road delivering in a sample unit and 

percent of roads in the unit reported to be up to standards; however, a statistically significant 

decreasing relationship was found between sediment delivery in the sample unit and percent of 

roads in the unit reported to be up to standards. These findings suggest that, while there may be 

locations where there is higher hydrologic connectivity or sediment input from roads, many 

roads show decreasing sediment inputs as they are brought up to standards. 

Approximately ninety-five percent of the land sampled was owned by large industrial forest 

owners and state/local governments. The study was intended and designed to incorporate land 

owned by small forest landowners, but due to the sample site criteria and layout and their

fragmented ownership patterns, little of that ownership type was able to be incorporated. 

Development of a companion study specifically designed to obtain access to and evaluate small 

forest ownerships could be pursued in order to characterize those lands.

It is recommended that the monitoring project continue with next planned monitoring period 

(planned interval of 5 years) to evaluate the expectation that, in general, roads conditions 

improve and they meet the performance metrics as they are brought up to FFR standards.
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WASHINGTON ROAD SUB-BASIN SCALE EFFECTIVENESS MONITORING

FIRST SAMPLING EVENT REPORT (2006-2008)

1 Introduction............................................................................................................................1

1.1 Literature Summary.........................................................................................................1

2 Monitoring Objectives............................................................................................................2

3 Methods .................................................................................................................................5

3.1 Project Coordination and Meetings..................................................................................5

3.2 Field Protocol Development ............................................................................................6

3.3 Quality Assurance/Quality Control Program....................................................................7

3.4 Sample Units...................................................................................................................7

3.4.1 Sampling Frame .....................................................................................................7

3.4.2 Sample Size and Unit Area.....................................................................................8

3.4.3 Site Selection .......................................................................................................10

3.5 Landowner Contacts......................................................................................................12

3.6 Field Sampling ..............................................................................................................12

3.7 Database Development ..................................................................................................16

3.8 Calculation of Monitoring Measures..............................................................................16

3.8.1 Statistical Analysis...............................................................................................19

4 Results and Discussion .........................................................................................................20

4.1 Crew Variability Test ....................................................................................................20

4.2 Sample Units.................................................................................................................22

4.2.1 Sample Unit Selection and Rejection....................................................................24

4.2.2 Sample Unit Results.............................................................................................25

4.3 Monitoring Questions and Measures..............................................................................30

4.3.1 Monitoring Question 1 .........................................................................................33

4.3.2 Monitoring Question 2 .........................................................................................45

4.3.3 Monitoring Question 3 .........................................................................................48

4.3.4 Monitoring Question 4 .........................................................................................52

4.3.5 Monitoring Question 5 .........................................................................................54

4.3.6 Monitoring Question 6 .........................................................................................54

4.4 New Roads Evaluation ..................................................................................................59

5 Summary and Recommendations for Future Sample Events .................................................60

6 References............................................................................................................................62

LIST OF FIGURES

Figure 1(a) and 1(b). Change in the Mean Power and P-value for (a) RSED and (b) RLEN as the 

Area of Each Sample Unit from Phase I was Increased. ............................................9

Figure 2. Sample Unit/Quarter Section Selection Process (from Raines et al. 2005)..................10

Figure 3. Example Road Segments...........................................................................................13

Figure 4. Length Delivering and Sediment Production by Surveyor for 2006 and 2008 Tests. ..21
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Figure 5. Location of Road Monitoring Sample Units. .............................................................23

Figure 6. Un-weighted Road Length Delivering in Sample Unit vs. Road Density....................28

Figure 7. Estimated Sediment Delivered to Streams in Sample Unit vs. Road Density..............28

Figure 8. Un-weighted vs. Weighted Road Length Delivering for the Sample Units. ................29

Figure 9. Length of Road by Sediment Yield Category in Each Sample Unit Showing Overall 

Variability Among Sites. ........................................................................................30

Figure 10. MQ1.1 Total Road Length Delivering to Streams per Unit Area. .............................33

Figure 11. MQ1.2 Percent of Road Network Draining to Streams.............................................34

Figure 12. MQ1.3 Percent of Delivering Road Network by Surfacing. .....................................36

Figure 13. MQ1.4 Percent of Road Network by Traffic Level. .................................................38

Figure 14. MQ1.5 Percent of Road Network by Cutslope Cover Category................................40

Figure 15. MQ1.6 Percent of Drainage Points by Connectivity Class........................................42

Figure 16. MQ1.7 Percent of Delivering Road Length by Rutting Category. ............................44

Figure 17. H2b1 Road Surfacing Index.....................................................................................45

Figure 18. H2b2 Road Traffic Index.........................................................................................46

Figure 19. H2b3 Cutslope Cover Index.....................................................................................47

Figure 20. H2b4 Miles of Delivering Road with Ruts Interfering with Drainage.......................48

Figure 21. MQ3.1 Miles of Delivering Road per Mile of Stream (FFR Hydrology Performance 

Measure).................................................................................................................49

Figure 22. MQ3.1 Cumulative Percent of Sample Units, Miles of Delivering Road per Mile of 

Stream (RLEN).......................................................................................................50

Figure 23. MQ3.1 Sediment Delivered/Year per Mile of Stream (FFR Sediment Performance 

Measure).................................................................................................................51

Figure 24. MQ3.1 Cumulative Percent of Sample Units, Tons of Delivered Sediment per Mile of 

Stream (RSED).......................................................................................................52

Figure 25. MQ4.1 Miles of Delivering Road per Mile of Stream Divided by Regional 

Performance Target. ...............................................................................................53

Figure 26. MQ4.2 Sediment Delivered/Year per Mile of Stream Divided by Regional 

Performance Target. ...............................................................................................54

Figure 27. Percent of Sample Units with Percent of Roads Reported to be up to FFR Road 

Standard .................................................................................................................55

Figure 28. Miles of Delivering Road/Miles of Stream (MQ3.1) Expressed as Percent of Regional 

Target vs. Percent of Road Miles in Sample Unit Reported to be up to Standards. ..56

Figure 29. Tons of Delivered Sediment/Miles of Stream (MQ3.2) Expressed as Percent of 

Regional Target vs. Percent of Road Miles in Sample Unit Reported to be up to 

Standards................................................................................................................56

Figure 30. Sample Unit Maps Showing Difference in Delivery Between Units with Ridgetop 

Roads (left) and Midslope/Valley Bottom Roads (right)..........................................58

LIST OF TABLES

Table 1. FFR Sediment Performance Targets for Roads .............................................................3

Table 2. Monitoring Questions/Hypotheses and Measures..........................................................5

Table 3. Data Collected on Delivering Road Segments.............................................................14

Table 4. Methods Used to Compute Monitoring Measures and Statistics..................................16
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Table 5. Potential Study Unit Rejection Reasons and Rates......................................................24

Table 6. Summary of Data Collected by Sample Unit...............................................................26

Table 7. Mean, Median and Standard Deviation of Monitoring Measures by Region and State.31

Table 8. Summary of New Roads by Sample Unit ....................................................................60

LIST OF APPENDICES

Appendix A. Meeting Minutes

Appendix B. QAPP (available electronically on CD)

Appendix C. QA/QC Report (available electronically on CD)

 Management Visit Memos

 Replicate Survey Memos

 Crew Variability Assessment Report

 Third Party Report

Appendix D. Field Protocol (available electronically on CD)
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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1 Introduction

The Washington Department of Natural Resources (WDNR) implemented new Forest Practice 

Rules for forest roads under WDNR jurisdiction in 2001. The 2001 road rules were developed in 

the wake of the Forests & Fish Report (FFR) and are designed to improve many aspects of the 

road network by reducing the occurrence of road landslides, culvert plugging, and road surface 

erosion, and by eliminating barriers to fish passage. The resource objectives for roads include 

sub-basin scale performance targets for surface sediment and water diversion to the stream 

network associated with forest roads (Raines et al. 2005). The resource objectives and 

performance targets for road hydrologic connectivity to the stream network and sediment input 

to streams are linked because runoff is required to transport sediment from roads to streams. By 

limiting the delivery of sediment and excess water to streams, the road rules will help to protect 

water quality and aquatic resources. Implementation of the road rules for existing roads is 

planned over a 15-year time horizon through implementation of Road Maintenance and 

Abandonment Plans (RMAP) that concludes in 2016. After that time, all roads will be required 

to be maintained to forest practice rule standards. 

As part of the Cooperative Monitoring, Evaluation, and Research (CMER) Committee mission, a 

number of different monitoring programs have been developed to evaluate the Forest Practice 

Rules. Monitoring projects are grouped by ‘Rule Group’ (roads, riparian, etc.) and include 

effectiveness and validation monitoring at several different scales (FY 2010 CMER WORK 

PLAN p.12). The Road Sub-Basin Scale Effectiveness Monitoring Project (Raines et al. 2005) 

was designed to determine the degree to which forest roads under the jurisdiction of Washington 

Forest Practices Rules are meeting the road surface erosion and hydrologic connectivity resource 

objectives. This monitoring project has been set up to document current road characteristics 

related to runoff and surface erosion from roads within randomly-selected four-square-mile 

sample units of forest land. Sample units are planned to be re-surveyed three times through 2016 

to determine if road conditions are either meeting targets or improving with respect to surface 

erosion and hydrologic connectivity. This is a voluntary study relying on the cooperation of 

landowners and does not evaluate landowner compliance with the Forest Practices Rules.

This report describes the first data collection effort, conducted from 2006 to 2008. It includes 

the field protocols, quality assurance plan, and analysis of data collected during the first 

sampling effort. Trends in road performance can not be evaluated until after future revisits to 

these (and/or other) sample units.

1.1 Literature Summary

There is a large network of unpaved forest roads in Washington State that provides access to 

private and state-owned timberlands. While these roads provide many positive benefits, they can 

also be sources of runoff and sediment that have the potential to affect aquatic habitat and water 

quality where the roads are hydrologically connected to streams or wetlands. Because the 

documentation for the Washington Road Surface Erosion Manual (Dubé et. al 2004, Appendix 

A) provides a detailed narrative of past research, the following discussion is limited to a brief 

summary. 
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The characteristics of a road and where it is constructed on the landscape control how much 

sediment is produced and whether or not this sediment is delivered to a waterbody. Road 

characteristics that have a major influence on erosion rates include:

• Road segment length – longer lengths have more erosion (Mills et al. 2003)

• Road gradient – steeper roads have more erosion (Luce and Black 1999)

• Surfacing type and durability – surfacing with durable gravel or vegetation reduces 

erosion (Meyers 2007, Coe 2006, Mills et al. 2003, Foltz 1996, Burroughs and King 

1989, Kochenderfer and Helvey 1987, Swift 1984, Reid and Dunne 1984)

• Traffic use – higher use, particularly during precipitation events, produces more erosion 

(Mills et al. 2003, Foltz 1996, Reid and Dunne 1984, Sullivan and Duncan 1981)

• Grading and rut development – rutting produces more erosion; disturbance from grading 

temporarily increases erosion (Meyers 2007, Sugden and Woods 2007, Foltz and 

Burroughs 1990, Burroughs and King 1989)

• Interception of cutbank sub-surface flow by the road ditch – more interception results in 

ditch erosion (MacDonald et al. 2001)

Factors that influence the delivery of sediment to streams include:

• Distance between runoff point and waterbody – shorter distances result in more delivery 

(Brake et al. 1997, Megahan and Ketcheson 1996, Swift 1985, Trimble and Sartz 1957)

• Hillslope gradient and number of obstructions between road and waterbody – steeper 

gradient hillside and/or fewer obstructions results in more delivery (Brake et al. 1997, 

Megahan and Ketcheson 1996)

• Volume of flow and erosion from road segment – higher runoff and/or erosion volumes 

results in delivery at greater distances (Ketcheson and Megahan 1996)

The present monitoring project collected information on all the road conditions that have a major 

influence on erosion as well as indicators of hydrologic connectivity between the road and a 

stream or wetland. 

2 Monitoring Objectives

The Road Sub-Basin Scale Effectiveness Monitoring Project was developed by members of 

CMER to determine if road characteristics that affect runoff and sediment delivery to streams are 

improving through time and the extent to which roads meet the FFR performance targets 

(Table 1). Details of the monitoring design are in Raines et al. (2005). 
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Table 1. FFR Sediment Performance Targets for Roads 

Measure

Performance Target

New Roads Existing Roads

Road sediment delivered to streams Virtually none

RLEN - Ratio of road length delivering to 

streams/total stream length (mile/mile)

Not to exceed:

 East of Crest 0.08-0.12

 Coast (Spruce) 0.15-0.25

 West of Crest 0.15-0.25

RSED - Ratio of road sediment production 

delivered to streams/total stream length 

(tons/yr/mile)

Not to exceed:

 East of Crest 1-3

 Coast (Spruce) 6-10

 West of Crest 2-6

(Source: Forests & Fish Report, Schedule L-1, June 2000)

The performance targets for road hydrologic connectivity to streams (RLEN) and surface 

sediment delivery (RSED) were developed in 2000 to supplement qualitative road standards 

identified in the Forests & Fish Report (Table 1). Target values were derived from sediment 

production estimates for forest road networks across Washington inventoried as part of 

Watershed Analyses done during the 1990s. Watershed analysts compiled road sediment 

delivery within sub-basins of similar scale to this study, each of which was given an aquatic 

hazard rating of Low, Moderate or High. The ranges bracketed by the RLEN and RSED targets 

correspond to sub-basins rated Low hazard and the lower values rated Moderate hazard. The 

group chose to document the targets by a ‘range’ rather than a single value because they felt the 

scientific information available to quantify aquatic sensitivity to sediment was insufficient to 

support a single threshold value. Separate targets were developed for the western and eastern 

sides of the Cascades and the coastal zone to reflect differing precipitation rates and channel 

densities. Although sub-basins where road metrics are within the local target range are expected 

to have acceptably low impact levels, the target development group recommended initiating 

further sediment-sensitivity studies to evaluate and possibly refine the target values. Readers 

should also be aware that although road evaluation methods for this monitoring study are similar 

to those used for Watershed Analysis, there have been numerous minor changes to 

methodologies since target development that have changed road sediment estimates.

The FFR performance target for new roads, virtually no sediment delivered to streams (Table 1), 

was not specifically addressed in the monitoring design for this study. For all the metrics 

developed as part of the monitoring design, existing and new roads were evaluated together and 

compared to the regional FFR targets for existing roads (Table 1). A small number of new roads 

were present within some of the sample units. The lengths of hydrologically connected road and 

estimated road sediment delivered to streams were compiled and are reported separately for the 

new roads in Section 4.4. 

Six monitoring questions were developed to provide feedback on how well improvements in 

road characteristics translate into changes in the target measures for sediment and hydrology at 

the sub-basin scale: 

• Monitoring Question 1: What is the condition of forest roads at each sample event, 

specifically those attributes management can change relative to sediment production and 

delivery? 
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• Monitoring Question 2:

o Hypothesis 2a: No reduction in road drainage connectivity to streams has 

occurred since the previous sampling event(s).

 Have road attributes that affect sediment production and delivery 

improved over time?

o Hypothesis 2b: No improvement in road attributes that affect sediment 

production and delivery has occurred since the previous sampling event(s).

• Monitoring Question 3: What is the status of road performance measures for drainage 

connectivity and sediment delivery to streams at each sample event?

• Monitoring Question 4: What is the status of road performance measures relative to their 

targets, by performance target region, at each sample event?

• Monitoring Question 5:

o Hypothesis 5a: No reduction in the road drainage connectivity performance 

measure has occurred since the previous sampling event(s).

 Have measures of road sediment performance improved over time?

o Hypothesis 5b: No reduction in the road sediment delivery performance measure 

has occurred since the previous sampling event(s).

• Monitoring Question 6:

o Hypothesis 6a: There is no direct relationship between the percentage of the road 

system that is judged to meet road standards and the reported road drainage 

connectivity performance measures.

 Will roads judged to meet FFR road standards meet the performance 

targets?

o Hypothesis 6b: There is no direct relationship between the percentage of the road 

system that is judged to meet road standards and the reported road sediment 

delivery performance measures.

In order to assess these monitoring questions and hypotheses, a series of numerical monitoring 

measures was developed that include the primary road characteristics influencing the delivery of 

sediment and water from a road system to aquatic environments (Table 2). These monitoring 

measures will be computed and compared for each sample event to determine the trend in road 

conditions through time. 
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Table 2. Monitoring Questions/Hypotheses and Measures

Monitoring Questions or 

Hypothesis Reported Monitoring Measures

Monitoring Question 1 1. Total road length draining to streams (road miles/sq mi)

2. Percent of road network draining to streams

3. Percent of road in each surface category

4. Percent of road in each traffic category

5. Percent of road in each cutslope cover category

6. Percent of drainage points by connectivity class

7. Percent of road in each road rutting category

Hypothesis 2a 1. Total road length draining to streams (road miles/sq mi)

2. Percent of road network draining to streams

Hypothesis 2b 1. Road surfacing index

2. Road traffic index

3. Cutslope cover index

4. Miles of delivering road with ruts interfering with drainage

Monitoring Question 3 1. Miles of forest road delivering to streams per miles of stream (road hydrology 

performance measure)

2. WARSEM modeled tons of road sediment delivered to streams per miles of 

stream per year (sediment performance measure)

Monitoring Question 4 1. Miles of forest road delivering to streams per miles of stream (road hydrology 

performance measure) divided by the performance target by target region

2.WARSEM modeled tons of road sediment delivered to streams per miles of 

stream per year (sediment performance measure) divided by the performance 

target by target region

Hypothesis 5a Miles of forest road delivering to streams per miles of stream (road hydrology 

performance measure)

Hypothesis 5b WARSEM modeled tons of road sediment delivered to streams per miles of 

stream per year (sediment performance measure) 

Hypothesis 6a Miles of forest road delivering to streams per miles of stream by percent of road 

length meeting FFR road standards

Hypothesis 6b WARSEM modeled tons of road sediment delivered to streams per miles of 

stream per year by the percent of road length meeting FFR road standards

(Source: Raines et al. 2005)

3 Methods

The first sample event included two phases of work. The first phase (Phase I) included 

development of a detailed field protocol and QA/QC plan, training of the inventory crew, and 

sampling 14 blocks of land in 2006. The results of the Phase I samples were used to conduct a 

statistical power analysis to estimate the total sample size required for the first sample event, 

which resulted in a decision to use a sample size of 60. The second phase of the sample event 

was conducted in 2008 and included updating the field protocol, re-training, and sampling the 

remaining 46 sample units. 

3.1 Project Coordination and Meetings

Several meetings between the contractor and CMER personnel were scheduled as part of the 

Phase I and Phase II work. Meeting minutes are included in Appendix A. 

The Phase I Start-Up Meeting was held on December 14, 2005, to review the monitoring 

objectives and methods. The Phase I Second Unit Meeting was held on March 31, 2006, with 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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the field crew to discuss any changes needed to the field protocol after sampling the first two 

sample sites. Attendance by project principal investigator Kathy Dubé at the October 24, 2006 

CMER meeting satisfied the Phase I completion meeting and is documented in the CMER 

meeting minutes. 

A kickoff meeting for Phase II was held on March 21, 2008, to review the Phase II objectives 

and methodology with UPSAG committee members. The Phase II Second Unit Meeting was 

held on May 23, 2008, following sampling of two Phase II units. The purpose of the Second 

Unit Meeting was to review data collection procedures and discuss any issues that came up with 

the survey crews. The Phase II Survey Completion Meeting was held on January 29 and 

continued on February 5, 2009 to discuss the sampling results, any issues that arose during the 

project, suggestions from the field crew for future sample events, and data analysis required to 

meet project goals. 

3.2 Field Protocol Development

A standardized field protocol manual was developed to provide consistent methods for collecting 

road condition data (Appendix D). The Field Protocol was developed based on guidelines in the 

WARSEM manual (Dubé et al. 2004) and the information required in the monitoring design 

(Raines et al. 2005). 

Several revisions to the 2006 field protocol document were made prior to the 2008 sampling 

based on suggestions by the field crews and to incorporate UPSAG requests. The following key 

changes were made and implemented during the 2008 sampling:

• Tread configuration (the percent of the road tread that drained to a particular drainage 

point being inventoried) was changed from three categories in 2006 [full (100%), half 

(50%), none (0%)] to five categories in 2008 (0%, 25%, 50%, 75%, 100%) at the 

suggestion of the field crews to better reflect conditions actually seen on the ground and 

to improve consistency between surveyors who were having a difficult time determining 

tread configuration in some cases. 

• Delivery of ditch water across long, vegetated fillslopes was clarified to help improve 

consistency. If there was less than 50 feet of vegetated fillslope between the ditch outlet 

and the stream, 100% delivery is assumed. If there is more than 50 feet of vegetated 

fillslope between the ditch outlet and the stream, the delivery flowchart is used to 

determine delivery. 

• Addition of a fifth delivery category to document road segments that closely paralleled 

streams or obvious and mapped wetlands but did not fall within another delivery 

category. This category was called “Parallel within 20 feet of a stream.” 

• Addition of a data field to document the length of road that is parallel within 20 feet of a 

stream. This includes cases where a segment may deliver directly, but the road closely 

parallels a stream and may be constructed in or occupying the floodplain. 

• Updating the flowchart that provides guidance for delivery and breaking roads into 

segments to reflect changes to delivery categories. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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The final 2008 field protocol is included on the data CD. 

3.3 Quality Assurance/Quality Control Program

A Quality Assurance Project Plan (QAPP) was developed and implemented during the initial 

2006 field season, and updated during the Phase II field season in 2008. The main elements of 

the QAPP include:

1. Standard field protocols

2. Data management procedures

3. Field crew training program

4. Quality controls during field data collection

5. Monthly field visits by management personnel

6. Duplicate crew surveys

7. Quantification of crew variability

8. Third party QA analysis

9. QA/QC reporting

Field inventory personnel were trained in the field protocol during three-day sessions prior to 

both the 2006 and 2008 field seasons; these included PowerPoint presentations and field training. 

In addition, the Principal Investigator and contractor project management personnel worked in 

the field with crew members during the course of the project to answer questions, review 

protocols, and discuss potential revisions and improvements to the protocol (“Field Assistance 

Visits”). Crew members also worked together for several days during the sampling season to 

discuss how they were making determinations in the field and improve the consistency of data 

collected (“Duplicate Crew Surveys”). 

An assessment of crew variability was conducted during both the Phase I and Phase II field 

seasons to: 1) understand where field assistance and additional training were needed to minimize 

differences between observers; and 2) help to understand, if possible, how much of the total 

variance in monitoring results may be due to observer error. Three road sections were selected 

from a West of Crest sample unit in 2006 (Phase I) and three different road sections were 

measured in an East of Crest unit in 2008 (Phase II). The test lengths were chosen to represent 

the range of road use and maintenance conditions within each sample unit. The variability tests 

were conducted after initial training and again near the end of data collection. Each of the road 

sections was evaluated by each of the crew members using standard project data collection 

instructions and techniques. 

A final version of the 2008 QAPP includes details of each of these elements and is included in 

Appendix B of this report. Appendix C is the QA/QC report for the project. 

3.4 Sample Units 

3.4.1 Sampling Frame

Sample units were selected in a stratified random manner from all forest practices rules-regulated 

(FFR) timberlands within the state. The number of units in each geographical performance 

target region was based on percent of FFR land area within each region: 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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• Coastal Spruce = 11% 

• East of Crest = 51%

• West of Crest = 38%

FFR land was estimated from the “CMERlands” GIS coverage developed by the Department of 

Natural Resources Forest Practices Division (Washington Department of Natural Resources

2005). The CMERlands coverage was developed from USGS “forested” polygon coverage 

(assessed from LandSAT imagery), Habitat Conservation Plan (HCP) areas, public land 

ownership coverages, and Native American land coverages. FFR lands were selected as those 

forestlands that were neither Federal, Tribal, nor covered by an HCP plus DNR HCP lands that 

were not within the habitat range of spotted owls or marbled murrelets and so are managed under 

normal forest practices rules (these occurred in eastern Washington). The “forested” designation 

was inclusive and often included land that was actually scrub-shrub steppe or rangeland as well 

as some agricultural land. These non-forest areas were further filtered out from individual sites 

during the site screening process. Property from small forest landowners was specifically 

included in this study. 

3.4.2 Sample Size and Unit Area

This study is designed to evaluate trend, which entails evaluating differences in results from 

sample events spaced 5 years apart. The study is designed to resample the same units in each 

sampling event and to use paired t-test analyses to assess change (Raines et al. 2005). In order to 

estimate the number of samples required to obtain good statistical power for a paired t-test, a 

measure of variability among differences (e.g., future year metric minus current year metric for 

each sample unit) would be required. Since such an estimate will not be available until multiple 

years of data are collected, the power for a simple two-sample t-test was estimated instead. 

When measurements are correlated (i.e., same sites through time), the paired t-test has higher 

power than the two-sample t-test, so the estimated sample size should be more than adequate. 

Based on variability among parameters found during earlier watershed analyses, the study plan 

originally estimated a sample size of 60 units. With 60 units at each sampling time, the power 

was greater than 80% for detecting a change of 30% in RLEN and a change of 50% in RSED 

using a two-sample t-test. Thus, with a paired t-test for a paired sample, the power is expected to 

be even greater. Data from the 14 units sampled during Phase I were analyzed to refine this 

original estimate. 

During Phase I, six-square-mile units (24 quarter sections) were used for sampling based on the 

average subbasin area in Watershed Analysis data (average area = 6.26 mi2, n=60, SD = 3.96 

mi2

; Raines et al. 2005). However, obtaining sites of this size proved to be very difficult and 

resulted in an unacceptably high site rejection rate (see next section), especially in those areas on 

the fringes of large industrial forestland blocks. Sampling such large areas was also very 

expensive due not only to the increased land area but to the fact that accessing many landowners 

and road systems greatly multiplied the sampling effort and costs. As part of an effort to reduce 

the sample unit rejection rate (by requiring fewer approved quarter sections) and to reduce costs, 

CMER analyzed the 2006 field data for the two main target metrics from the 14 Phase I sites 

using fixed area re-sampling (Figure 1). 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Rate of Change in RSED Statistical Parameters 

as a Function of Subsampling

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0 1 2 3 4 5 6

Sample Area (Sq. Miles)

Rate of Change in Mean Values ...

P-Value

Power

Rate of Change in RLEN Statistical Parameters 

as a Function of Subsampling

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0 1 2 3 4 5 6

Sample Area (Sq. Miles)

Rate of Change in Mean Values .

"P-value"

Power

Figure 1(a) and 1(b). Change in the Mean Power and P-value for (a) RSED and (b) RLEN 

as the Area of Each Sample Unit from Phase I was Increased.

Based on this analysis, CMER determined that the sample size should remain at the original 60 

but that the sample unit areas could be reduced to as little as three square miles and still provide 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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the required certainty to assess trends (Figure 1). Three square mile units would still be within 

the standard deviation of the average Watershed Analysis subbasin area used as the basis in the 

study design. Sampling four-square-mile blocks would allow for some area attrition within 

blocks (due to ownership or land use changes incompatible with the study) in future years 

without having to remove the entire block from the sample. This is a very important point given 

the current trend of land development, the desire to gain information about small forest land 

management as well as large industrial land management, and the effort required to obtain and 

permit sample units that meet the study criteria. Therefore, UPSAG recommended and CMER 

and the Forest Practices Policy Committee approved the decision to retain the original sample 

size of 60 but reduce the sample unit areas to four-square miles. The results of the CMER 

analysis suggested that reducing the sample area from six- to four-square miles would reduce 

power by less than 0.5% for RSED and 2% for RLEN (the two primary metrics being tracked) 

while reducing the costs by approximately $175,000. For the final analysis combining data from 

Phases I and II, only the first 16 selected quarter sections from the Phase I units were used (see 

following section for a description of sample unit quarter section numbering) so that all units 

analyzed had the same area. The 240 square miles sampled represents 1.7 percent of the 

estimated 9.1 million acres of Forest Practice Rule land. If 60 of the original 6 square-mile units 

were inventoried, it would have been 2.5 percent of the total land area. 

3.4.3 Site Selection

Initial unit selection followed the plan described in Raines et al. 2005 and began by randomly 

selecting section corners within the FFR land sample area. The potential sample unit consisted 

of a sixteen-square-mile block surrounding that section corner (Figure 2). Units were screened 

in the numerical order in which the corner was selected. As a unit was rejected, the next unit in 

the initial selection was evaluated until the total sample number was reached. Extra units were 

initially selected and screened to allow for further attrition as more refined site screening and 

permitting proceeded. 

Figure 2. Sample Unit/Quarter Section Selection Process (from Raines et al. 2005).
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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The intent was to sample blocks of land that contained coherent networks of roads that were 

managed as forest roads under the forest practices rules. The first step in screening units entailed 

assessing the amount of FFR land within the block. If there was less than four square miles of 

FFR land, as designated from the GIS layers, the unit was discarded without further assessment. 

If there was enough FFR land, the unit was inspected to see if the FFR areas were laid out such 

that there was a contiguous block of FFR land of suitable size, or two large contiguous blocks 

that together would make up the requisite area. The objective of assessing blocks of contiguous 

road was the key factor. For example, in a few cases the unit spanned a large river, and large 

contiguous blocks on each side could be formed and were used to make up the unit. In other 

cases, large blocks could not be formed and the unit was rejected.

After the initial screening using the CMERlands FFR GIS layer, quarter sections within units 

were evaluated using aerial photos, land parcel ownership, personal knowledge, and field 

inspection. Typically, quarter sections in the unit that could be readily identified as non-usable 

were rejected in the table for that unit. Per the study design (Raines et al. 2005, Appendix A), 

quarter sections were discarded if they contained any unacceptable non-forest use (residence, 

quarry, fire station, commercial, etc.). Roads, power lines, and railroad rights of way were 

considered acceptable non-forest uses and quarter sections containing those were retained. 

UPSAG determined that properties containing small (e.g., one-room) hunting cabins would be 

retained in the sample since such a structure’s use did not fundamentally change the use of that 

forestland, nor did it particularly indicate the intention to develop the land further. On the other 

hand, quarter sections that consisted of land parcels less than 10 acres in size were assumed to be 

under development or likely to be developed by the next sample event and were rejected. 

Agricultural, scrub-steppe range land, and large water body inclusions were assessed on a caseby-case basis. If the non-forested area made up over half of the quarter section, that quarter was 

discarded.

Following the initial identification and recording of ineligible quarter sections, each potential 

quarter section surrounding the central section corner was evaluated in more detail in a clockwise 

spiraling pattern out from the selected section corner (Figure 2). If the quarter section was 

eligible, it was added to the potential sample unit in order (quarter section 1, 2, 3, 4, etc. in 

Figure 2) and numbered. Weeding out the clearly ineligible quarters first simplified the detailed 

assessment by allowing working unit maps to be created in the GIS and quarters numbered. 

Using those working maps, county assessor records of land parcel boundaries and ownership 

provided further information on land use and ownership for sites and quarter sections that passed 

the photo screening. Parcel information was obtained in several ways. County assessors were 

contacted and most provided their parcel data to us in a database, and, where they had it, a GIS 

layer. When it became available, the Statewide Parcel Database (RTI 2007) was used. Internet 

searches were used to verify parcel database information and to obtain information for those 

counties that did not provide information directly. Where graphical parcel data were not 

available, property legal descriptions were used to identify properties within quarter sections. 

Since this level of data screening was very time intensive, it was left until last and only applied 

to those quarter sections that passed previous screening. Parcel data were inspected to ensure 

there were no incompatible improvements on the properties and to obtain landowner contact 

information. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Landowners were then contacted to determine if they were interested in participating in the 

monitoring project. Contact was made via letter, by telephone, and by personal contact if 

somebody whom we knew also knew the landowner. If the owner was interested in 

participating, the quarter section was retained; if any owner within a quarter denied access, that 

quarter section was dropped and the next quarter section in the sequence was used. Additional 

criteria were applied to ensure that units were reasonably blocked up and did not have short 

segments of unrelated roads distributed across them (see Raines et al. 2005, Appendix A for 

more details).

3.5 Landowner Contacts

Landowners within each sample unit were contacted to provide permission to sample the roads, 

and to acquire the following information about roads within the unit:

• Landowner category (large or small by WDNR standards)

• Road name/numbering

• Traffic levels over past 1 year - landowner either provided average number of 

loads/day or selected traffic category from those provided in the Field Protocol for 

each road within the sample unit on their ownership

• Percentage of roads within the sample unit that the landowner considered up to 

current forest practice standards (either up to standards or RMAP has been 

implemented)

• Recent road maintenance activities (within last 5 years)

• Age of roads

This information was used for statistical analysis and in the WARSEM analysis. 

3.6 Field Sampling

Roads in the selected sample units were inventoried from March – August, 2006 during Phase I 

(14 units) and from May – December, 2008 during Phase II (46 units). Field crews during both 

phases included five crew members; four of these crew members participated in both field 

seasons. One Phase I crew member was not available during Phase II and was replaced by 

another person. Details of the field sampling methods are included in the field protocol 

(Watershed Professionals Network 2006 and 2008). 

During the field inventory, all forest roads in the sample unit were either walked or driven to 

collect information on the road condition. Forest road for the purpose of this study are as defined 

by the Washington Administrative Code (WAC) Chapter 222-16-010. On that basis, the 

following were not included in the inventory:

• Foot trails

• Skid roads

• Highways/county roads

• Officially orphaned or abandoned roads [defined in WAC 222-24-053(3) and (4)]

• Vegetated roads: non-drivable vegetated roads with over 90% cover on the tread 

were inspected for at least 200 meters to ascertain there was no evidence of erosion. 

Vegetated roadways with no traffic result in little surface erosion (Swift 1984). If no 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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evidence of erosion was found, the remainder of the road was not surveyed. Nondrivable roads with less that 90% vegetative cover were inventoried. 

Roads were divided into segments by determining the hydrologic connectivity (drainage to 

streams or typed wetlands) for each portion of the road network. Delivery to streams/typed 

wetlands was classified as follows, based on studies of road sediment delivery and sediment trap 

efficiency as described in Appendices A and C of the WARSEM manual (Dubé et al. 2004), 

Ketcheson and Megahan (1996), and NCASI (2000):

0 – No delivery – the road or drainage structure outfall drains to the forest floor, with no 

evidence of sediment plumes reaching a stream or wetland

1 – Direct delivery – the road, ditch, or drainage structure outfall drains directly into a 

stream (e.g., at a stream crossing) or wetland

2 – 35% delivery – a sediment plume from the road drainage reaches a stream or wetland, 

or there is a constructed sediment trap that traps some sediment (Ketcheson and 

Megahan 1996, NCASI 2000)

3 – 10% delivery – a sediment plume from the road drainage ends between 1-20 feet from 

a stream or wetland (Ketcheson and Megahan 1996)

4 – Direct via gully – drainage from the road is delivered directly to a stream or wetland 

through a gully or landslide scar

5 – Road parallel to and within 20 feet of a water body – a road that does not fall into 

another delivery category (1-4) but parallels a stream or wetland (edge of tread is 

within 20 feet of stream/wetland/floodplain). This delivery category was added for 

Phase II field work; it was not delineated for Phase I roads. 

The road network was broken into delivering and non-delivering segments that were generally 

delineated by drainage structures (culverts, bridges, ditchouts) and grade breaks. Figure 3 shows 

an example of a road system broken into segments; delivering segments that either drain directly 

to streams (e.g., segments 1, 2, 3, 5) or are in the 35% or 10% delivery categories (e.g., segments 

4 and 6), or are closely parallel to a stream (e.g., segment 7) are numbered in the diagram. 

Figure 3. Example Road Segments

Map view (on left) and road profile (on right) show how roads were divided into 

delivering segments (numbered) and non-delivering segments (un-numbered).
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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For each delivering road segment, a GPS location was collected, and information on the 

characteristics of the road tread, cutslope, and ditch were collected and entered into the GPS 

(Table 3). A JAMAR RAC Plus I odometer was used in each vehicle to track stationing in feet 

(a string box was used for roads inventoried on foot). The location of each non-delivering 

culvert (e.g., ditch relief pipes) was also collected. No information on road characteristics was 

collected for non-delivering road segments since these segments do not contribute sediment to 

surface waters (Raines et al. 2005). 

Table 3. Data Collected on Delivering Road Segments

Attribute Possible Values How Measured or Determined

Site ID Text Input site ID number.

Segment ID Unique number; integer The GPS unit assigns this number automatically.

Road Name Text Recorded on first/last segment of road, rest blank.

Group ID Integer

Leave field blank unless this road segment drains to the same point 

as another segment; then assign both (or all) segments draining to 

the same point the same Group ID number (unique to those 

segments).

Surveyor Name Input surveyor name.

Weather

Clear

Rainy

Cloudy

Snow

Determine average conditions for day.

Reference Point ID Text Record on first/last segment of road.

Segment Start Station Number Record JAMAR reading at start of segment.

Drainage Point Station Number Record JAMAR reading at drainage point.

Segment End Station Number Record station at end of segment (JAMAR reading or string box).

Drainage Point Type

Culvert

Bridge

Ditchout

Drivable dip

Sag point

Other segment

Other/unknown

Record type of drainage structure.

Other segment – drains to other segment that delivers.

Structure Purpose

Stream crossing

Relief, no gully

Relief, gully

No structure

Stream – defined bed and banks up and

Relief – no defined bed/banks

downstream of culvert

Gully – defined bed/banks downstream but not

No structure – no structure observed

upstream of culvert

Delivery

0-none

1-direct or direct w/full trap

2-35% sediment 

3-10% sediment

4-direct via gully or 

landslide scar

5-parallel within 20 feet

Determine delivery of ditch, drainage outfall, or road segment if 

outsloped based on flowchart “Guidance for delivery and breaking 

road segments” included in the field protocol.

Stream Adjacent 

Length Length in feet Measure length of road parallel and within 20 feet of a stream/wetland.

Culvert drop >9 

inches? Y/N

Is the vertical measurement between the water flowing out of the 

culvert and the water surface of the plunge pool more than nine 

inches?

If stream is dry, measure from bottom of pipe to bottom of plunge 

pool.

Culvert downstream 

end countersunk? Y/N Is the downstream end of the culvert below the surrounding substrate?

Culvert upstream end 

countersunk? Y/N Is the upstream end of the culvert below the surrounding substrate?

Substrate extends

through culvert? Y/N Look through culvert to determine if substrate extends the entire length of culvert. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Attribute Possible Values How Measured or Determined

Average Tread Width Width in feet Measure the full width of tread surface that could be driven on at 3-

4 locations to nearest foot. Record average value (nearest foot). 

Average Ditch Width Width in feet Measure width of ditch at 3-4 locations. Record average value 

(nearest foot).

Ditch Condition

P - recently pulled or 

graded

E - scoured, eroding

A - aggrading

R - armored

S – stable

N/A

P – ditch has been recently pulled or graded

E – ditch is eroding/incising. 

A – ditch is aggrading (full)

R – ditch has been rocked/armored or is vegetated

S – ditch appears stable (not eroding currently)

Maintenance Category

1-none recent

2-grading and/or ditch 

pulling only

3-other BMPs

Visually inspect the road to determine if maintenance has been 

completed recently (within last year).

Road Slope 

<5%

5-10%

>10%

Measure and record average gradient of tread with clinometer or 

estimate within slope class: 

<5% - flat or gently sloping road 

5-10% - moderately sloped road segment

>10% - steep road

Average the gradient over entire segment. If the segment is a Vshaped stream crossing, estimate gradient on each side of crossing 

and average. 

Surfacing

A-asphalt

G-good gravel

P-pitrun or worn gravel

N-native

Determine surfacing on road tread. Use the following guidelines:

Good gravel – a good gravel surface; little dust or fines on surface

Pitrun or worn gravel – poor quality gravel surface; lots of fines or 

dust

Native – dirt surface

Rutted?

No

Yes/interfering

Yes/not interfering

Are there ruts in road (over 2” deep)? 

If so, are they interfering with tread drainage?

Grassed tread? Y/N Is grass/vegetation covering more than 50% of tread surface?

Road Configuration 

(percent of tread width 

that drains to structure)

0%

25%

50%

75%

100%

Look at configuration of road prism. Evaluate the drainage path of 

water on the tread. Record the percent of the road tread drainage 

that delivers to the drainage structure to the nearest 25%. 

Cutslope Average 

Height 

25 ft

10 ft

5 ft

2.5 ft

no cutslope

Average height of cutslope (slope length). 

Cutslope Cover 

Density 

90-100%

70-90%

50-70%

30-50%

10-30%

0-10%

N/A

Determine the average percent of the cutslope area that is covered 

with vegetation, rock, leaf litter, or other non-erodible material. 

Erosion Rating

High

Low

Default

Record rating only if obviously high (major cutslope raveling due 

to soil conditions) or low (bedrock). Otherwise record default. 

Secondary segment? Y/N Record Y if this is a secondary segment – see field protocol for 

details. 

Difficult segment? Y/N Indicates segment that is difficult or has complicated drainage.

Comments Text Note any unusual situations in the comment field. 

Photo numbers Text Enter photo number from digital camera.

Date and time yy/mm/dd hh:mm:ss Automatically recorded by GPS unit.
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3.7 Database Development

Concurrent with the development of the field protocol, an Access® database was prepared to 

store data collected during the road inventory. Data tables within the database include:

• Sample Unit Table – contains information about each sample unit.

• Landowner Table – contains contact information for each landowner.

• Road Segment Table – contains the information collected in the field, as well as 

modeled sediment delivery (from WARSEM) for each road segment that was 

determined to deliver to a stream, lake, or wetland. 

• Non-Delivering Segment Table – contains information collected in the field for nondelivering drainage structures. 

The database structure is included as an appendix to the Final Field Protocol. 

3.8 Calculation of Monitoring Measures

Data for each sample unit and road segment was compiled for computation of monitoring 

measures and graphing. The monitoring measures for each of the monitoring questions or 

hypotheses listed above in Table 3 were computed for each sample unit based on the formulas 

shown in Table 4 below. Each monitoring measure was also compiled for the three geographical 

performance target regions (East of Crest, West of Crest, Coastal/Spruce) as well as for the entire 

state-wide sample. Statistical analyses are described in more detail in Section 3.8.1. 

Table 4. Methods Used to Compute Monitoring Measures and Statistics

Monitoring Measure Computation Method

MQ1.1, H2a.1 Total road length draining 

to streams (road miles/sq mi)

a. Un-weighted delivering road length2 (mi)/Area of 

sample unit (sq mi)

b. Weighted delivering road length3 (mi)/Area of sample 

unit (sq mi)

MQ1.2 Percent of road network draining 

to streams

a. Un-weighted delivering road length2 /Total surveyed 

road length1

b. Weighted delivering road length3 /Total surveyed road 

length1

MQ1.3 Percent of road in each surface 

category

Surveyed road length in each surface category1 /Total 

surveyed road length1

MQ1.4 Percent of road in each traffic 

category

Surveyed road length in each traffic category1 /Total 

surveyed road length1

MQ1.5 Percent of road in each cutslope 

cover category

Surveyed road length in each cutslope cover category1 /

Total surveyed road length1

MQ1.6 Percent of drainage points by 

connectivity class

Number of delivery points in each connectivity category /

Total number of surveyed delivery points

MQ1.7 Percent of road in each road 

rutting category

Surveyed road length in each rutting category1 /Total 

surveyed road length1

H2b.1 Road surfacing index Road attribute index for surfacing (see B below)

H2b.2 Road traffic index Road attribute index for traffic (see B below)

H2b.3 Cutslope cover index Road attribute index for cutslope cover (see B below)

H2b.4 Miles of delivering road with ruts 

interfering with drainage

Surveyed length of roads1 with ruts that were classified as 

interfering with drainage (mi)
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Monitoring Measure Computation Method

MQ3.1 Miles of forest road delivering to 

streams per miles of stream (road 

hydrology performance measure)

a. Un-weighted delivering road length2 (mi) / Adjusted 

length of streams within sample unitC (mi)

b. Weighted delivering road length3 (mi) / Adjusted length 

of streams within sample unitC (mi)

MQ3.2 WARSEM modeled tons of road 

sediment delivered to streams per miles of 

stream per year (sediment performance 

measure)

WARSEM modeled tons of road sediment delivered to 

streams (tons/yr) / Adjusted length of streams within 

sample unitC (mi)

MQ4.1, H5a Miles of forest road 

delivering to streams per miles of stream 

(road hydrology performance measure) 

divided by the performance target by target 

region

a. Un-weighted delivering road length2 (mi) / Adjusted 

length of streams within sample unitC (mi) divided by 

upper performance target:

East of Crest = 0.12

West of Crest = 0.25

Coastal (Spruce) = 0.25

b. Weighted delivering road length3 (mi) / Adjusted length 

of streams within sample unitC (mi) divided by upper 

performance target

MQ4.2, H5b WARSEM modeled tons of 

road sediment delivered to streams per 

miles of stream per year (sediment 

performance measure) divided by the 

performance target by target region

WARSEM modeled tons of road sediment delivered to 

streams (tons/yr) / Adjusted length of streams within 

sample unitC (mi)

divided by upper performance target:

East of Crest = 3

West of Crest = 6

Coastal (Spruce) = 10

H6a Miles of forest road delivering to 

streams per miles of stream by percent of 

road length meeting performance standards

Data is displayed graphically 

H6b WARSEM modeled tons of road 

sediment delivered to streams per miles of 

stream per year by the percent of road 

length meeting performance standards

Data is displayed graphically

A. Note that there are three different ways the length of road was used in the formulas in Table 4. 

Superscripted numbers in the right column apply to the following definitions:

1. Total surveyed road length in the unit includes length of all roads surveyed (delivering and not 

delivering).

2. Total delivering road length = the total (un-weighted) length of road that was in any delivering 

class (direct, direct via gully, 35% delivery, 10% delivery). Does not include non-delivering or 

stream-parallel length. 

3. Weighted delivering road length = total delivering road length (#2 above) for each segment 

multiplied by the delivery percent (100%, 35%, 10%) multiplied by the percent of the tread width 

delivering (100%, 75%, 50%, 25%, 0%). 

B. Road Attribute Indexes for categorical values are computed using the following formula:

Totalsurveyed road length x WARSEM factor associated with least amount of erosion for that attribute

Surveyed road length in each attribute category x WARSEM factor for that attribute category

1

1

∑

C. Adjusted stream length = length of streams within each sample unit taken from WDNR GIS coverage x 

[number of road-stream crossings found in field / number of road-stream crossings in GIS]. This 

adjustment takes into consideration the fact that the GIS stream coverage may miss or have extra streams in 

many locations. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Note that the length of streams within each sample unit is included as part of the calculation of 

several of the monitoring metrics. The length of stream was based on the WDNR GIS stream 

layer, which is often not a true representation of actual streams on the ground. The road 

inventory crew checked each road/stream crossing within the sample unit to assess whether 

mapped and un-mapped streams were or were not present. The miles of streams in the GIS layer 

were then proportionally adjusted based on the actual number of stream crossings found within 

the unit versus the number of stream crossings in the GIS layer (see note C below Table 4). 

While this may not result in a completely accurate portrayal of stream miles, it was the most 

cost-effective method of adjusting stream miles within the scope of this project. 

The length of road delivering to steams was measured in the field and included length in each of 

the delivering categories (direct, direct via gully, 35% delivery and 10% delivery). This length 

was used for comparison with the FFR length performance measure (RLEN, Table 1 above). 

The total delivering length metric does not take into account some strategies that landowners 

may use to reduce road connectivity such as crowning or outsloping a road, installing cross 

drains (if they are still within proximity to a stream), or sediment traps. For this reason, a 

weighted road length was computed for comparison with future monitoring events. The 

weighted delivering road length was computed based on the total delivering road length, delivery 

category, and percent of tread width draining to the delivery point (Table 4). 

The multi-year, state-wide scale of the road effectiveness monitoring study precluded direct 

measurement of sediment production. For this reason, a modeling approach was chosen to 

estimate sediment production for the FFR sediment metric (MQ3.2, MQ4.2, H5b, and H6b). 

WARSEM was chosen to estimate sediment delivery for the following reasons (Raines et al. 

2005):

1. WARSEM is closely related to the Road Surface Erosion Module calculations in the 

Washington Watershed Analysis Manual (Washington Forest Practices 1997) that was 

used to develop the FFR performance targets for sediment delivery; 

2. WARSEM input variables include the important road attributes controlling road sediment 

production with categories that provide clear interpretation of improving trends;

3. Input data from WARSEM can be used in alternate models if the need arises; and

4. WARSEM is easy to use and is well suited for estimating sediment delivery for large 

datasets.

It is recognized that output from any road surface erosion model is not an accurate measure of 

sediment production or delivery at the scales of individual delivery points or individual road 

segments; however, models are useful for comparing trends in sediment production through time 

in response to changes in road conditions (Dubé et al. in press). The monitoring measures and 

statistics evaluated here include 15 different measures/indices; only two of these use WARSEMgenerated numbers. 

The Washington State Road Surface Erosion Model (WARSEM) was used to estimate the 

sediment production and delivery from each delivering road segment. The characteristic of each 

road segment (length, tread and ditch width, tread configuration, surfacing, road gradient, 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 19

cutslope height and cover, traffic use, delivery, and Township/Range/Section location) were 

entered into WARSEM. 

The erosion and delivery calculations in WARSEM are based on a set of empirical relationships 

that were developed from research on road erosion (Dubé et al. 2004). The model uses the 

following formulas to calculate road surface erosion:

Total Sediment Delivered to a Stream from each Road Segment (in tons/year) = (Tread & 

Ditch Sediment + Cutslope Sediment) x Road Age Factor 

Tread & Ditch = Geologic Erosion Factor x Tread Surfacing Factor x Traffic Factor x 

Segment Length x Road (Tread + Ditch) Width x Road Gradient Factor x Rainfall Factor 

x Delivery Factor

Cutslope = Geologic Erosion Factor x Cutslope Cover Factor x Segment Length x 

Cutslope Height x Rainfall Factor x Delivery Factor

The value for each factor in the equations is selected by WARSEM based on the road 

characteristics collected in the field and entered for each individual road segment. The delivery 

categories assigned in the field (100%, 35%, and 10%) correspond directly to WARSEM 

delivery factors. 

3.8.1 Statistical Analysis

The statistical analysis relevant to monitoring questions 1, 3, and 4, and hypothesis 6 followed 

the methods discussed in the Monitoring Design (Raines et al., 2005). The following are 

clarifications and modifications to the statistical analysis methods described in that document. 

Arithmetic means, medians, and standard deviations of the unit results are provided for each 

region. The statewide median is simply the median across all 60 units. The statewide mean and 

standard deviation are weighted means of the regional results, weighted by sample size. Some 

discussion as to the appropriateness of the arithmetic mean as an estimate of statewide metrics is 

necessary

Sample units of roughly equal land area were selected randomly in three geographic regions, 

proportional to the estimated land area subject to FFR rules. However, the sampling design 

within each region can be looked at as a cluster sample, where each unit is a cluster of roads (or 

streams, depending on the metric being estimated). Some units have many roads or streams 

while others have few roads or streams, so the clusters differ in size with regard to the amount of 

road or stream. Typically, when calculating a landscape average, larger clusters (i.e., units with 

more roads) should have greater weight than smaller clusters if one wants to infer results to 

additional stream- or road-miles. However, Washington state forestlands are tracked, assessed, 

and managed on an area-basis rather than on a road- or stream-mile basis. We need to be able to 

infer results to additional land area, not road- or stream-mile. Therefore it was decided that the 

unit-by-unit averages (i.e., not weighted by length of road or stream) were more relevant as 

management summaries of results. These averages are biased estimates of state-wide means of 

road characteristics with less precision than if samples were weighted by and inferred to road 

mile.
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For hypothesis 6, the Monitoring Design states that linear regression will be used to determine if 

there is a relationship between the percentage of the road system that is judged to meet road 

standards and two reported metrics. Because the metrics are not normally distributed or 

transformable to normal distribution, a nonparametric (Kendall’s tau; Conover 1980) 

regression/correlation test was used instead. Using the nonparametric test also loosens the 

assumption of linear regression that the x-variable is measured without error. For the 

nonparametric test, it is only necessary that the x-variable is ranked properly, which seems to be 

a reasonable assumption.

4 Results and Discussion

4.1 Crew Variability Test

The crew variability test originally had two goals: 1) to target areas for training to improve 

consistency; and 2) to provide a quantitative estimate of crew variability for delivering length 

and sediment yield. 

The test was optimized to provide feedback to and guide training for field crews for quality 

assurance purposes. The test results were very helpful to target areas for further training. From 

the results of the first test in 2006, project management personnel targeted field assistance and 

additional discussion with field crew members on assessing delivery (using the flowchart 

developed for this purpose), using a clinometer to measure road gradient, determining 

configuration (full/half/none) with care, and developing a common understanding of surfacing 

between field workers in each unit. During the 2008 season, these measurements continued to be 

stressed, along with protocols for determining delivery over fillslopes and deciding if a drainage 

swale was considered a stream or not. Road variables influencing the sediment production that 

varied most among observers included delivery, gradient, portion of tread delivering, and 

surfacing. Several of the roads in the 2008 test unit were outsloped, which means that the road 

drains over the fillslope to the stream. These types of road drainage systems are prevalent in 

Eastern Washington roads. Determination of delivery in these cases is particularly difficult, and 

was one reason for the high variability between observers during the 2008 testing. Field crew 

members who were used to surveying Westside road systems with pronounced ditch systems 

were looking at delivery from the poorly developed/short ditch systems on the Eastside (2008 

test unit) roads. Field crew members who normally surveyed Eastside road systems were 

considering delivery over the fillslopes. The post-test discussions led to a common way to look 

at outsloped Eastside road systems (delivery over fillslopes) and should have further reduced

variability for this metric after the test. In general, there is less variation in results during the 

second test each field season than in the first test, suggesting that results became more consistent 

with continued training and working together during the duplicate crew surveys (Figure 4). 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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2006 Test

0

1000

2000

3000

4000

5000

6000

Test 1 Test 2

Unweighted Length Delvering (ft) - Colored bars.

0

10

20

30

40

50

60

70

Estimated Average Annual Sediment Production (tons/yr) - 

Clear bars

Surveyor 1 2 3 4 5

2008 Test

0

500

1000

1500

2000

2500

3000

Test 1 Test 2

Unweighted Length Delvering (ft) - Colored bars.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

Estimated Average Annual Sediment Production (tons/yr) - 

Clear bars

Surveyor 1 2 3 5 6

Figure 4. Length Delivering and Sediment Production by Surveyor for 2006 and 2008 

Tests. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Because the crew variability tests were optimized for quality assurance and training purposes, the 

results are not useful for estimating measurement error for the entire project. While it is possible 

to calculate the amount of variance among surveyors based on the 2006 and 2008 test results, it 

is not appropriate to apply the results to the data collected in an entire sample unit for several 

reasons:

• The variability in delivering length and calculated total sediment production among 

observers on a single segment or section of road is quite large relative to differences among 

road segments. However, the variability among sums of road segments, which are being 

used for the larger project will be lower because they are sums (or averages), which have 

lower theoretical variance (i.e., the variance of a mean is reduced proportionally to the 

sample size). Since the crew variability study measured only a small length of road (1.4-2.4 

miles) in relation to the total road miles in a sample unit (average 23 miles/unit), it was not 

appropriate to extrapolate the results to entire units.

• Crew variability differed from the first to the second test (Figure 4) and from 2006 to 2008. 

In addition, crew members sampled different amounts of roads in different regions across the 

state. This would complicate efforts to apply appropriate variance estimates to all the sample 

units across the state and through time. 

• During subsequent sampling events, the Monitoring Design specifies that the same study 

sites will be re-sampled. Since trends between sampling events will be based upon change of 

only those variables that can be modified by management practices within each sample unit, 

there will be fewer variables with the potential for observer error. 

For the study results, these crew variability results imply that differences observed through time 

(particularly for only two time periods) could be purely due to observation error. Therefore, 

strong interpretation of data results should only be made after consistent changes through time 

(after repeated measurements) have been observed. Minimizing observer variability is important 

to this and subsequent monitoring periods. Consideration of ways to minimize variability should 

be stressed during both the planning and implementation phases of future monitoring events. 

4.2 Sample Units

This first sampling event provides information on the current (2006-2008) status of forest roads 

on lands subject to Washington Forest Practice Rule across the state. A total of 60 four-squaremile sample units were inventoried (Figure 5). The units were distributed by performance target 

geographical region based on the relative proportion of forest practice rule lands within each 

region (East of Cascade Crest = 30 sample units, Coastal/Spruce = 7 sample units, and West of 

Cascade Crest = 23 sample units). 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Figure 5. Location of Road Monitoring Sample Units.

Sample units beginning with the letter “E” are east of the Cascade crest, “W” are west of the Cascade crest, and “S” are in the Coastal Spruce zone.
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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4.2.1 Sample Unit Selection and Rejection

As described in Section 3.4.3, sample units initially selected for study were screened to ensure 

that each unit included four square miles of relatively contiguous blocks of FFR-regulated lands 

with acceptable uses, and that land owners granted access to their lands for the study. Of 164 

sample units originally selected, 37% were rejected in the initial assessment due to lack of FFR 

land, and 14% were rejected because the FFR land was not contiguous enough to create blocks 

large enough to meet study unit criteria (Table 5). Units rejected at this first stage of screening 

were not assessed in enough detail to specify particular reasons for the lack of FFR land. In later 

stages of screening, where individual quarter sections were assessed, 3% of the units were 

rejected because of too much agricultural or other non-forest area; 6% due to development at 

various levels; 3% due to landowner denial; and one unit due to inaccessibility as the result of a 

large storm in southwest Washington.

Table 5. Potential Study Unit Rejection Reasons and Rates

Reason for Rejection Number of Units

Percentage of Total 

Sites Assessed (n=164)

Not enough FFR 61 37%

Not enough contiguous FFR 23 14%

Development 10 6%

Agricultural land, non-forest 4 3%

Landowner denial 5 3%

Inaccessibility 1 1%

Total Rejected 104 63%

No sample units selected for use in the Southeastern part of the state around the Blue Mountains 

met the sample unit criteria and had enough of those landowners willing to grant access. Several 

units were initially identified in that region, but they were all rejected. Private forestland in the 

Blue Mountain area forms a narrow band between the agricultural and rangeland and the 

National Forest. Moreover, the forested areas tend to be in the valleys that weave among the 

agricultural land on plateaus and hillsides. The roads in these areas are agricultural roads and are 

not designed or maintained as forest roads under the forest practices rules and so they were not 

accepted into study units. These factors made it very difficult to compile a block of FFR land of 

the necessary size in that region. 

Roads sampled include those owned by twenty-one large landowners, thirty small landowners, 

three state agencies, and four municipalities. The sampled area is dominated by large landowner 

and State forest land properties, which constitute approximately ninety-five percent of the 

sampled area. Although property from small forest landowners was specifically included in this 

study, small forest ownerships are underrepresented (by area) in the final sample. Across the 

state it is estimated that 40 percent of FFR land is owned by small landowners (landowners 

having an average harvest of less than 2 million board feet annually; Rogers and Cooke 2009). 

However, most of the small forest landowner properties occur on the margins of developed areas

and include houses or agricultural lands that were incompatible with study site criteria. This 

intermingling with qualifying forest lands was the largest cause for rejection of individual 

quarter sections. Lack of landowner cooperation also contributed to the low acceptance rates of 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 25

quarter sections containing lands belonging to small forest landowners. CMER studies rely on 

voluntary participation by landowners. Although many small forest landowners were willing to 

cooperate, any one uncooperative landowner resulted in rejection of the entire quarter section for 

that unit. The end result is that, despite the relatively high number of participating small forest 

landowners, small forest parcels make up less than five percent of the sampled area. All large 

forest landowners and government entities approached participated in this study. 

Because small non-industrial forest ownerships (by land area) were under-represented, this study 

likely does not adequately reflect road conditions on small forest ownerships and should not be 

used to infer road conditions on those ownerships. The high rejection rate for these has 

convinced us that either a change in the sampling design or a companion study specifically 

designed to obtain access to and evaluate small forest ownerships would be required to provide 

an accurate assessment of the status of roads on those lands. 

4.2.2 Sample Unit Results

Table 6 summarizes the number of miles of road surveyed and miles of stream in each sample 

unit, the un-weighted and weighted length of road delivering to streams/wetlands, and the 

estimated sediment delivering to streams and the FFR sediment performance metrics. 

Note that one East of Crest survey units had no streams. As a result, there were no delivery 

points in this unit, and no data on road conditions were collected. This unit has 0 miles of road 

delivering and appears as a blank on the bar charts in Section 4.3.
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Table 6. Summary of Data Collected by Sample Unit

Area

Miles of 

Road 

Surveyed

Surveyed 

Road 

Density 

(mi/sq mi)

Adjusted 

Stream 

Length 

(mi)

Stream 

Density 

(mi/sq 

mi)

Unweighted 

Road 

Length 

Delivering 

(mi)

Weighted 

Road 

Length 

Delivering 

(mi)

WARSEM 

Calculated 

Delivered 

Sediment 

(tons/yr)

RLEN -

Unweighted 

Miles of 

Road 

Delivering/ 

Stream 

Length

(mi/mi)

Weighted 

Miles of 

Road 

Delivering/ 

Stream 

Length

(mi/mi)

RSED -

Sediment 

Delivered/ 

Stream 

Length 

(tons/yr/mi)

Sample units located East of Crest

27.3 7.12 5.2 1.35 1.51 0.94 1.4 0.3 0.18 0.28

25.0 6.26 4.0 1.01 0.66 0.30 0.4 0.2 0.07 0.10

26.0 6.50 5.6 1.40 0.83 0.52 0.7 0.1 0.09 0.13

24.3 6.14 8.3 2.09 5.32 3.58 13.4 0.6 0.43 1.62

20.5 5.15 3.9 0.98 1.83 1.24 2.2 0.5 0.32 0.57

18.1 4.53 7.5 1.89 1.49 0.70 6.9 0.2 0.09 0.92

29.8 7.16 3.0 0.72 1.25 0.68 1.0 0.4 0.23 0.34

13.4 3.39 4.0 1.01 0.08 0.01 0.2 0.0 0.00 0.04

14.1 3.51 0.0 0.00 0.00 0.00 0.0 0.0 0.00 0.00

5.7 1.46 7.9 2.04 0.06 0.01 0.0 0.0 0.00 0.00

13.9 3.47 1.9 0.48 0.10 0.01 0.0 0.1 0.01 0.01

22.3 5.42 8.2 2.00 2.66 1.77 1.9 0.3 0.22 0.23

2.7 0.69 7.6 1.90 0.08 0.01 0.0 0.0 0.00 0.00

26.2 6.71 17.0 4.37 2.33 1.99 10.7 0.1 0.12 0.63

17.0 4.10 7.4 1.78 0.70 0.33 0.8 0.1 0.05 0.11

19.8 4.93 14.5 3.62 4.33 3.46 14.6 0.3 0.24 1.01

20.1 5.05 3.9 0.98 1.19 0.32 3.6 0.3 0.08 0.92

22.2 5.63 8.9 2.26 0.66 0.07 0.6 0.1 0.01 0.06

4.1 1.05 10.9 2.79 0.27 0.10 0.1 0.0 0.01 0.01

10.7 2.67 23.2 5.79 1.64 1.64 3.5 0.1 0.07 0.15

25.3 6.31 4.3 1.07 1.50 0.59 1.2 0.4 0.14 0.28

16.6 4.10 5.5 1.37 0.32 0.03 0.1 0.1 0.00 0.02

21.9 5.49 8.6 2.14 1.67 1.01 4.6 0.2 0.12 0.53

10.9 2.67 13.9 3.40 0.38 0.22 0.2 0.0 0.02 0.02

31.1 7.46 13.6 3.26 1.58 1.03 7.6 0.1 0.08 0.56

17.2 4.32 9.0 2.27 1.08 0.92 1.9 0.1 0.10 0.21

15.5 3.83 5.3 1.31 0.08 0.07 0.1 0.0 0.01 0.01

20.4 5.48 5.4 1.45 0.23 0.05 0.3 0.0 0.01 0.06

20.9 5.37 9.9 2.54 0.41 0.28 0.5 0.0 0.03 0.05

14.9 3.71 6.0 1.50 0.44 0.04 0.2 0.1 0.01 0.04

Units in 

Coastal/Spruce

25.9 6.50 24.2 6.06 4.09 1.93 117.9 0.2 0.08 4.88

15.3 4.28 59.9 16.75 0.98 0.55 29.3 0.0 0.01 0.49

25.2 6.32 11.0 2.75 0.71 0.23 173.9 0.1 0.02 15.83

25.2 6.39 6.7 1.69 0.67 0.30 1.8 0.1 0.05 0.27

27.8 6.95 48.9 12.23 6.21 2.86 224.9 0.1 0.06 4.60

29.0 7.19 24.1 5.96 3.69 1.77 30.9 0.2 0.07 1.28

21.6 5.60 27.2 7.05 4.55 2.34 102.4 0.2 0.09 3.77
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Table 6. Summary of Data Collected by Sample Unit (continued)

Area

Miles of 

Road 

Surveyed

Surveyed 

Road 

Density 

(mi/sq 

mi)

Adjusted 

Stream 

Length 

(mi)

Stream 

Density 

(mi/sq 

mi)

Unweighted 

Road 

Length 

Delivering 

(mi)

Weighted 

Road 

Length 

Deliverin

g (mi)

WARSE

M 

Calculate

d 

Delivered 

Sediment 

(tons/yr)

Unweighted 

Length of 

Road 

Delivering/

Stream 

Length 

(mi/mi)

Weighted 

Length of 

Road 

Deliverin

g/ Stream 

Length 

(mi/mi)

Sediment 

Delivered/ 

Stream 

Length 

(tons/yr/ mi)

Sample units located West of Crest

28.8 7.27 17.4 4.41 7.08 4.42 217.3 0.4 0.25 12.45

29.9 7.63 26.8 6.85 4.78 2.36 407.6 0.2 0.09 15.19

26.4 6.56 13.0 3.23 4.89 2.79 60.6 0.4 0.21 4.65

33.0 7.63 15.5 3.60 7.35 3.76 137.0 0.5 0.24 8.82

29.2 7.35 21.1 5.31 7.93 2.05 30.2 0.4 0.10 1.43

22.9 5.83 22.7 5.78 3.13 1.20 26.1 0.1 0.05 1.15

17.1 4.33 23.5 5.94 3.35 1.12 73.9 0.1 0.05 3.15

27.7 6.95 4.6 1.16 1.72 0.60 7.6 0.4 0.13 1.66

27.2 6.74 14.5 3.58 6.64 2.91 93.5 0.5 0.20 6.47

14.6 3.79 15.8 4.11 1.86 1.00 9.7 0.1 0.06 0.62

26.4 6.79 13.7 3.53 0.73 0.22 7.5 0.1 0.02 0.55

26.0 6.51 18.7 4.69 5.96 2.02 47.6 0.3 0.11 2.54

22.7 5.71 4.6 1.17 0.49 0.17 0.4 0.1 0.04 0.09

25.4 6.41 22.6 5.71 3.25 0.93 24.3 0.1 0.04 1.07

8.9 2.44 59.2 16.22 4.37 2.35 205.6 0.1 0.04 3.48

20.6 5.64 14.3 3.91 5.69 2.35 163.7 0.4 0.16 11.47

24.2 6.26 4.3 1.12 0.63 0.24 1.5 0.1 0.05 0.35

24.7 6.31 19.2 4.90 4.74 2.07 266.0 0.2 0.11 13.88

23.4 5.86 10.0 2.51 1.75 0.90 28.5 0.2 0.09 2.85

24.8 6.09 23.9 5.86 3.21 0.79 39.9 0.1 0.03 1.67

21.3 5.32 11.1 2.78 4.42 2.04 13.5 0.4 0.18 1.22

25.4 6.43 32.6 8.25 0.49 0.26 7.6 0.0 0.01 0.23

24.3 6.16 24.5 6.20 6.53 3.61 68.9 0.3 0.15 2.82

Road density (miles of road/square mile of area), is commonly cited as a metric for the impacts 

of roads on streams. Although data from sample units suggest a generally positive correlation 

between road density and the length of road hydrologically connected to streams (Figure 6), and

the predicted sediment input to streams (Figure 7), there is not always a direct correlation due to 

other contributing factors. The location of the road network in relation to the stream network, as 

well as road condition and traffic levels are important factors for determining the relative effect 

of roads on streams, aquatic habitat, and water quality. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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0

1

2

3

4

5

6

7

8

9

0 2 4 6 8 10

Road Density (miles/sq mi)

Un-weighted Road Length Delivering (mi)

Figure 6. Un-weighted Road Length Delivering in Sample Unit vs. Road Density. 

Includes all sample units across state

0

50

100

150

200

250

300

350

400

450

0 2 4 6 8 10

Road Density (miles/sq mi)

Sediment Delivery (tons/yr)

Figure 7. Estimated Sediment Delivered to Streams in Sample Unit vs. Road Density. 

Includes all sample units across state

The total length of road delivering to streams was measured in the field and included both direct 

and indirect (35%, 10%) delivery categories, and so includes road segments where some of the 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 29

strategies land managers use to reduce the amount of road runoff and sediment draining to 

streams – such as crowning or outsloping a road, installing a sediment trap, or installing a crossdrain culvert with partial delivery – have been applied. In order to understand the magnitude of 

the difference such measures may make, a weighted delivering length was also calculated that 

takes into consideration delivery percentage and percent of road tread delivering to each drainage 

point. Figure 8 shows the comparison of un-weighted (total delivering length) and weighted 

road length. Across the state, the weighted road length delivering was an average of 45% of the 

un-weighted road length delivering. 

0

1

2

3

4

5

0 2 4 6 8

Un-weighted Road Length Delivering (mi)

Weighted Road Length Delivering (mi).

1:1 line

Figure 8. Un-weighted vs. Weighted Road Length Delivering for the Sample Units. Includes all sample units across state

Road managers are also interested in which parts of their road system are delivering the most 

sediment. Figure 9 shows the length of road in four sediment yield categories (average annual 

delivered sediment in tons/yr at a drainage point) in each of the sample units. The majority of 

the road system in the units had either no sediment delivery, or less than one ton/yr of delivery to 

streams. A small portion of road drainage points in some of the Coast and West of Crest units 

had over 3 tons/yr of sediment delivery. Targeting segments with higher sediment yields for 

road maintenance and improvements may be a cost-effective method to reduce total delivery of 

road surface erosion to streams. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

Sample Unit

Length (ft) in Sediment Yield Category

>3 tons

1-3 tons

0-1 tons

0 tons

Drainage 

Point 

Sediment 

Yield 

Category 

(tons/yr)

East of Crest West of Crest Coastal/ 

Spruce

Figure 9. Length of Road by Sediment Yield Category in Each Sample Unit Showing 

Overall Variability Among Sites. 

4.3 Monitoring Questions and Measures

Six monitoring questions/hypotheses, each with one or more metrics, were developed in the 

study plan to determine the status of forest road characteristics that relate to water and sediment 

delivery to streams. The mean median, and standard deviation of the monitoring measures listed 

in Table 2 (above) were computed for each geographic target region as well as state-wide

(Table 7). The following sections describe the results for each of the monitoring 

questions/hypotheses. 
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Table 7. Mean, Median and Standard Deviation of Monitoring Measures by Region and State. 

Monitoring Question or Hypothesis

East of Crest n=30 Coast/Spruce n=7 West of Crest n=23 Statewide n=60

Mean Median

Stand. 

Dev. Mean Median

Stand. 

Dev. Mean Median

Stand. 

Dev. Mean Median

Stand. 

Dev.

MQ1, H2a

1a. Total un-weighted road length delivering

per unit area (road miles/sq mi) 0.29 0.19 0.31 0.76 0.91 0.55 1.00 1.11 0.59 0.62 0.40 0.47

1b. Total weighted road length delivering per 

unit area (road miles/sq mi) 0.18 0.08 0.24 0.36 0.44 0.26 0.44 0.51 0.30 0.30 0.23 0.27

2a. Percent of road network delivering (unweighted length/length inventoried) 6% 4% 6% 12% 13% 8% 17% 19% 11% 11% 7% 8%

2b. Percent of road network draining to 

streams (weighted length/length inventoried) 4% 2% 5% 6% 6% 4% 8% 7% 6% 5% 4% 5%

3. Percent of road in 

each surface category 

(based on total length 

delivering)

Asphalt 0% 0% 2% 0% 0% 0% 0% 0% 0% 0% 0% 2%

Good gravel 8% 0% 22% 23% 20% 13% 15% 15% 13% 12% 2% 18%

Pitrun/worn gravel 14% 8% 18% 67% 73% 16% 77% 77% 20% 44% 48% 19%

Native 74% 89% 32% 10% 9% 10% 8% 3% 14% 42% 25% 24%

4. Percent of road in 

each traffic category 

(based on total length 

delivering)

Very heavy 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

Heavy 0% 0% 0% 9% 0% 22% 0% 0% 0% 1% 0% 8%

Mod Heavy 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

Moderate 0% 0% 1% 7% 0% 12% 7% 0% 14% 4% 0% 10%

Light 8% 0% 21% 3% 0% 4% 8% 0% 12% 7% 0% 17%

Occasional 84% 100% 32% 81% 84% 22% 85% 92% 18% 84% 100% 26%

None 5% 0% 20% 0% 0% 0% 0% 0% 0% 2% 0% 14%

5. Percent of road in 

each cutslope cover 

category (based on total 

length delivering)

90-100 % 41% 36% 34% 45% 53% 15% 61% 65% 20% 49% 56% 27%

70-89 % 16% 15% 15% 23% 21% 8% 14% 11% 11% 16% 15% 13%

50-69 % 12% 5% 16% 11% 8% 9% 7% 4% 8% 10% 5% 13%

30-49 % 4% 0% 9% 4% 4% 4% 3% 1% 6% 4% 0% 8%

10-29 % 3% 0% 8% 2% 0% 4% 1% 0% 1% 2% 0% 6%

0-9 % 0% 0% 1% 2% 0% 4% 0% 0% 0% 0% 0% 1%

N/A 20% 16% 18% 13% 13% 14% 14% 13% 12% 17% 13% 15%

6. Percent of drainage 

points by connectivity 

class

Direct 47% 49% 34% 55% 52% 13% 58% 57% 19% 52% 53% 27%

Direct via gully 4% 0% 6% 8% 9% 5% 9% 9% 8% 6% 3% 7%

35% Delivery 10% 9% 10% 24% 23% 9% 22% 20% 17% 16% 14% 13%

10% Delivery 34% 19% 35% 13% 14% 7% 10% 8% 8% 23% 12% 25%

Stream Parallel 2% 0% 5% 0% 0% 1% 2% 0% 4% 2% 0% 5%

7. Percent of road in 

each road rutting 

category (based on total 

length delivering)

Not Rutted 92% 100% 20% 88% 98% 22% 98% 100% 4% 94% 100% 16%

Rutted -

Interfering 4% 0% 6% 8% 0% 16% 1% 0% 2% 3% 0% 7%

Rutted - Not 

Interfering 2% 0% 5% 4% 0% 6% 1% 0% 2% 1% 0% 4%
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Monitoring Question or Hypothesis

East of Crest n=30 Coast/Spruce n=7 West of Crest n=23 Statewide n=60

Mean Median

Stand. 

Dev. Mean Median

Stand. 

Dev. Mean Median

Stand. 

Dev. Mean Median

Stand. 

Dev.

,MQ3, H5a H5b

1a. Un-weighted miles of forest road 

delivering per miles of stream (road 

hydrology performance measure) 

0.16 0.11 0.16 0.11 0.13 0.06 0.24 0.18 0.14 0.19 0.14 0.14

1b. Weighted miles of forest road 

delivering per miles of stream (road 

hydrology performance measure)

0.09 0.07 0.11 0.05 0.06 0.03 0.11 0.09 0.07 0.09 0.07 0.09

2. WARSEM modeled tons of road 

sediment delivered per miles of stream per 

year (sediment performance measure) 

0.30 0.12 0.39 4.44 3.77 5.38 4.25 2.54 4.73 2.30 0.56 3.47

MQ4

1a. Un-weighted miles of forest road 

delivering per miles of stream (road 

hydrology performance measure) divided 

by the performance target by target region 

1.33 0.88 1.34 0.46 0.51 0.23 0.96 0.71 0.57 1.09 0.67 1.01

1b. Weighted miles of forest road 

delivering per miles of stream (road 

hydrology performance measure) divided 

by the performance target by target region

0.76 0.60 0.89 0.21 0.23 0.12 0.42 0.36 0.30 0.56 0.35 0.65

2. WARSEM modeled tons of road 

sediment delivered per miles of stream per 

year (sediment performance measure)

divided by the performance target by target 

region 

0.10 0.04 0.13 0.44 0.38 0.54 0.71 0.42 0.79 0.37 0.15 0.53
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 33

4.3.1 Monitoring Question 1

What is the condition of forest roads at each sample event, specifically those attributes 

management can change relative to sediment production and delivery? 

MQ 1.1 and H2a1 Total road length draining to streams per unit area (road miles/sq mi)

The total length of road draining to streams per unit area sampled provides a measure of the 

length of road that is hydrologically connected to streams in each sample unit (Figure 10). 

Across the state, half of the sample units had less than 0.4 miles/sq mi of delivering road. Units 

in the West of Crest and Coast/Spruce geographic zones had more weighted road length 

delivering than those in the East of Crest zone, as would be expected given the overall lower 

stream densities in the East of Crest sample units. 

East of Crest

0

5

10

15

20

25

0-0.4 0.4-0.8 0.8-1.2 1.2-1.6 1.6-2

Delivering Length/Unit Area (miles/sq mi)

Number of Sample Units in Region

Coast/Spruce

0

5

10

15

20

25

0-0.4 0.4-0.8 0.8-1.2 1.2-1.6 1.6-2

Delivering Length/Unit Area (miles/sq mi)

Number of Sample Units in Region

 Figure 10. MQ1.1 Total Road Length Delivering to Streams per Unit Area. 

MQ 1.2 and H2a2 Percent of road network draining to streams

The percentage of the road network draining to streams was calculated using the un-weighted 

length of road delivering. Across the state, more than half of the sample units had less than 10

West of Crest

0

5

10

15

20

25

0-0.4 0.4-0.8 0.8-1.2 1.2-1.6 1.6-2

Delivering Length/Unit Area (miles/sq mi)

Number of Sample Units in Region

State-wide (Percent)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

0-0.4 0.4-0.8 0.8-1.2 1.2-1.6 1.6-2

Delivering Length/Unit Area (miles/sq mi)

Percent of Sample Units across 

State
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 34

percent of the road network delivering (Figure 11). As with MQ1.1 (length of road delivering), 

units East of the Cascade Crest had the lowest percent of the road network delivering to streams 

and units in the West of Crest region had the highest percent of the road network delivering. 

State-wide, an average of 11 percent of the surveyed road length delivered to streams, either 

directly, via a gully, or partially through an indirect sediment plume pathway across the forest 

floor. The percent of connected road network can vary greatly among watersheds based on 

values reported in other studies, although it should be noted that the survey methods and 

definitions of road connectivity between different studies make direct comparison of results 

complex. Martin (2009) reports an average of 12 percent of the surveyed road length on private 

timberlands was hydrologically connected in a landowner-conducted survey of 1,047 miles of 

road throughout Washington. Watershed Analyses conducted in the 1990’s on timberlands 

owned by Boise Cascade ranged from 3 to 57 percent connectivity, with watersheds in drier, 

inland areas of Washington, Oregon, and Idaho having 3 to 17 percent connectivity and 

watersheds in wetter areas (e.g., Coast Range of Oregon) having 45 to 57 percent connectivity

(Domoni Glass, personal communication). A survey of roads in the Sierra Nevada Mountains of 

California by Coe (2006) found 25 percent connectivity, and a survey in the Oregon Cascades by 

Wemple et al. (1996) reports 57 percent connectivity (although 24 percent of this was connected 

via gully without confirmation that the gully reached a stream). 

East of Crest

0

2

4

6

8

10

12

14

16

18

0-5 5-10 10-15 15-20 20-25 25-30

Percent of Road Network Draining to Streams

Number of Sample Units in Region

 

Coast/Spruce

0

2

4

6

8

10

12

14

16

18

0-5 5-10 10-15 15-20 20-25 25-30

Percent of Road Network Draining to Streams

Number of Sample Units in Region

Figure 11. MQ1.2 Percent of Road Network Draining to Streams. 

West of Crest

0

2

4

6

8

10

12

14

16

18

0-5 5-10 10-15 15-20 20-25 25-30

Percent of Road Network Draining to Streams

Number of Sample Units in Region

State-wide (Percent)

0%

5%

10%

15%

20%

25%

30%

35%

40%

0-5 5-10 10-15 15-20 20-25 25-30

Percent of Road Network Draining to Streams

Percent of Sample Units across 

State
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 35

MQ 1.3 Percent of road in each surface category 

The type and quality of road surfacing has an effect on how well the road holds up to traffic use 

and the amount of sediment produced from the road surface. Good quality, durable gravel 

surfacing holds up better and produces less sediment than native-surfaced roads. Poor quality or 

pitrun gravel produces an intermediate amount of sediment. 

Surfacing on inventoried roads was classified into one of four categories: Asphalt, good gravel, 

pitrun/worn gravel, and native (unsurfaced). Since gravel surfacing breaks down with traffic use, 

there is a continuum from good gravel to worn gravel. This phenomenon is particularly evident 

on heavily traveled mainline gravel roads. Good gravel was differentiated from pitrun by 

visually determining if the gravel particles were clearly visible or if the gravel particles were

embedded in fines. For consistency, at the start of each sample unit field crews assessed the 

condition of surfacing on the roads and agreed upon the surface type. 

Surfacing in the East of Crest units was primarily native; pitrun/worn gravel dominated 

Coast/Spruce and West of Crest roads (Figure 12). 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 36

East of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Asphalt Good gravel Pitrun/ worn gravel Native no streams in sample unit

Coastal/Spruce

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Asphalt Good gravel Pitrun/ worn gravel Native

West of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Asphalt Good gravel Pitrun/ worn gravel Native

Figure 12. MQ1.3 Percent of Delivering Road Network by Surfacing. 

This information is also included in numerical format in Table 7. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 37

MQ 1.4 Percent of road in each traffic category 

Traffic on unpaved roads has been shown to increase sediment production as the road surface is 

broken down into fine-grained particles that can be eroded by surface runoff, and passage by 

truck tires produces a pumping action that brings fines to the surface. 

Landowners reported the daily average traffic use over the past year on their roads within each 

sample unit. Traffic levels were grouped into categories based on WARSEM traffic categories 

(none, occasional, light, moderate, moderately heavy, heavy, and very heavy). Traffic use on 

most of the road network sampled across the state was occasional, with a daily average of less 

than 1 log truck/day (Figure 13). Several of the units in each of the geographic areas had some 

roads with light use (1-2 log trucks/day) or moderate use (3-4 log trucks/day). Two of the units 

in the Coast/Spruce zone had roads with heavy traffic (4-5 log trucks/day); these units included 

mainline roads in areas of recent active hauling. Traffic use in each sample unit is open to 

change between sample periods as traffic patterns shift to accommodate haul from different 

harvest units through time.
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 38

East of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Very heavy Heavy Mod Heavy Moderate Light Occasional None no streams in sample unit

Coastal/Spruce

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Very heavy Heavy Mod Heavy Moderate Light Occasional None

West of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Very heavy Heavy Mod Heavy Moderate Light Occasional None

Figure 13. MQ1.4 Percent of Road Network by Traffic Level. 

This information is also included in numerical format in Table 7. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 39

MQ 1.5 Percent of road in each cutslope cover category 

The percent of rock or vegetative cover on cutslopes influences the erosion rates on the cutslope. 

Cutslope cover data was collected in 10% cover increments on all delivering road segments. 

Higher cover categories would be expected to have less erosion from the cutslope. Some road 

segments had no cutslope; a cover rating of ‘n/a’ was used for these segments. 

Cutslope cover varied widely, but in general there was more cover on West of Crest and 

Coast/Spruce road segments than on East of Crest segments (Figure 14). This is expected due to 

denser vegetation coverage from higher precipitation rates on the West side of the state. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 40

East of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 90-100% 70-89% 50-69% 30-49% 10-29% 0-9% N/A no streams in sample unit

Coastal/Spruce

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 90-100% 70-89% 50-69% 30-49% 10-29% 0-9% N/A

West of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 90-100% 70-89% 50-69% 30-49% 10-29% 0-9% N/A

Figure 14. MQ1.5 Percent of Road Network by Cutslope Cover Category. 

This information is also included in numerical format in Table 7. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 41

MQ 1.6 Percent of drainage points by connectivity category 

Forest roads can alter surface runoff patterns in a watershed by intercepting groundwater via the 

cutslope or collecting runoff on the relatively impermeable tread. If the drainage from the road 

prism enters a stream or wetland, it can route water and sediment to the stream at a different rate 

than without the road in place. 

Road drainage connectivity was assessed by assigning each road segment into one of six delivery 

categories:

• No delivery (no data was collected on these segments)

• Drains directly into stream channel/typed wetland

• Drains directly into stream channel/typed wetland via a gully

• 35% delivery to a stream/typed wetland

• 10% delivery to a stream/typed wetland

• No evidence of delivery, but road parallels within 20 feet of a stream/wetland

The percent of delivering points in each delivery category varied widely between sample units

(Figure 15). The location of roads in relationship to streams in each sample unit played a large 

role in delivery, as did grading and placement of cross-drain culverts and drainage dips near 

streams. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 42

East of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Points

 Direct Direct via gully 35% Delivery 10% Delivery Stream Parallel no streams in sample unit

Coastal/Spruce

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Points

 Direct Direct via gully 35% Delivery 10% Delivery Stream Parallel

West of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Points

 Direct Direct via gully 35% Delivery 10% Delivery Stream Parallel

Figure 15. MQ1.6 Percent of Drainage Points by Connectivity Class. 

This information is also included in numerical format in Table 7. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 43

MQ 1.7 Percent of road in each road rutting category 

Ruts in the road surface can result in increased erosion by channeling drainage into a 

concentrated flow path. In addition, ruts can change the intended drainage pathway on the road 

surface by capturing water on an outsloped or crowned road and directing it down the road tread 

to a stream instead of allowing it to disperse across the fillslope. Ruts can be formed by traffic 

on soft road surfaces, such as saturated native surfaced roads, or by concentrated water running 

down long, steep (over 10%) sections of road. For the present study, ruts were defined as wheel 

indentations over two inches deep and classified into three categories: no ruts, ruts not 

interfering with tread drainage, and ruts interfering with drainage. 

Over half of the sample units had no ruts on delivering road segments, and most of the units had 

no ruts on over 90% of the delivering road length (Figure 16). A few units in the East of Crest 

and one in the Coast/Spruce regions had ruts on up to 40% of the delivering road length. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 44

East of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Not Rutted Rutted - Not Interfering Rutted - Interfering no streams in sample unit

Coastal/Spruce

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Not Rutted Rutted - Not Interfering Rutted - Interfering

West of Crest

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sample Unit

Percent of Delivering Road Length

 Not Rutted Rutted - Not Interfering Rutted - Interfering

Figure 16. MQ1.7 Percent of Delivering Road Length by Rutting Category. 

This information is also included in numerical format in Table 7. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 45

4.3.2 Monitoring Question 2

Have road attributes that affect sediment production and delivery improved over time?

Note that this question will be answered through comparison with future sample event results; 

data for the first sample event are presented here. 

H2b1 Road surfacing index 

The road surfacing index is a combined/weighted metric that is computed by multiplying the 

length of road in each road surfacing class by the WARSEM numerical factor for that class and 

dividing the sum of all classes by the total length x lowest numerical WARSEM factor for road 

surfacing. A lower road surfacing index indicates that relatively less erosion would come from 

roads in that unit based on the distribution of surfacing in the unit. 

Units in the East of Crest region had higher surfacing indices than units in the Coast/Spruce or 

West of Crest regions. This distribution reflects the higher percentage of roads with native 

surfaces in East side units (Figure 17). 

East of Crest

0

5

10

15

20

25

30

0-5 5-10 10-15 15-20 20-25 25-30 30-35

Road Surfacing Index

Number of Sample Units in Region

Coastal/Spruce

0

5

10

15

20

25

30

0-5 5-10 10-15 15-20 20-25 25-30 30-35

Road Surfacing Index

Number of Sample Units in Region

Figure 17. H2b1 Road Surfacing Index. 

West of Crest

0

5

10

15

20

25

30

0-5 5-10 10-15 15-20 20-25 25-30 30-35

Road Surfacing Index 

Number of Sample Units in Region

State-wide (Percent)

0

5

10

15

20

25

30

35

0-5 5-10 10-15 15-20 20-25 25-30 30-35

Road Surfacing Index 

Percent of Sample Units across 

State
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 46

H2b2 Road traffic index 

The road traffic index is a combined/weighted metric that is computed by multiplying the length 

of road in each road traffic class by the WARSEM numerical factor for that class and dividing 

the sum of all classes by the total length x lowest numerical WARSEM factor for traffic. A 

lower road traffic index indicates that relatively less erosion would come from roads in that unit 

based on the distribution of traffic use in the unit. 

Units in the East of Crest region had lower traffic indices than units in the Coast/Spruce or West 

of Crest regions (Figure 18). One unit in the Coast/Spruce zone had very heavy traffic on a 

mainline with many delivery points. 

East of Crest

0

5

10

15

20

25

30

0-25

25-5050-75

75-100

100-125125-150150-175175-200200-225225-250250-275275-300300-325

Road Traffic Index

Number of Sample Units in Region

Coastal/Spruce

0

5

10

15

20

25

30

0-25

25-5050-75

75-100

100-125125-150150-175175-200200-225225-250250-275275-300

300-325

Road Traffic Index

Number of Sample Units in Region

Figure 18. H2b2 Road Traffic Index. 

H2b3 Cutslope cover index 

The cutslope cover index is a combined/weighted metric that is computed by multiplying the 

length of road in each cutslope cover class by the WARSEM numerical factor for that class and 

dividing the sum of all classes by the total length x lowest numerical WARSEM factor for 

West of Crest

0

5

10

15

20

25

30

0-25

25-5050-75

75-100

100-125125-150150-175175-200200-225225-250250-275275-300300-325

Road Traffic Index 

Number of Sample Units in Region

State-wide (Percent)

0

10

20

30

40

50

60

70

80

90

0-25

25-5050-75

75-100

100-125125-150150-175175-200200-225225-250250-275275-300300-325

Road Traffic Index 

Percent of Sample Units across 

State
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 47

cutslope cover. A lower cutslope cover index indicates that relatively less erosion would come 

from roads in that unit based on the distribution of cutslope cover in the unit. 

Cutslope cover indices are relatively evenly distributed between 0.5-3 in East of Crest units, with 

a slight skew toward lower indices in Coast/Spruce and West of Crest units (Figure 19). 

East of Crest

0

5

10

15

20

25

30

0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3

Cutslope Cover Index

Number of Sample Units in Region

Coastal/Spruce

0

5

10

15

20

25

30

0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3

Cutslope Cover Index

Number of Sample Units in Region

Figure 19. H2b3 Cutslope Cover Index. 

H2b4 Miles of delivering road with ruts interfering with drainage

The distribution of units by miles of delivering road with ruts that were determined to interfere 

with drainage is shown in Figure 20. Less than 0.2 miles of roads with interfering ruts were 

found in the majority of units, although a few units had a relatively large number of rutted roads. 

State-wide (Percent)

0

5

10

15

20

25

30

35

0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3

Cutslope Cover Index 

Percent of Sample Units across 

State

West of Crest

0

5

10

15

20

25

30

0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3

Cutslope Cover Index 

Number of Sample Units in Region
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 48

East of Crest

0

5

10

15

20

25

30

0 0.01-

0.2

0.2-0.4 0.4-0.6 0.6-0.8 0.8-1 1-1.2

Miles Of Delivering Road With Ruts Interfering With 

Drainage

Number of Sample Units in Region

West of Crest

0

5

10

15

20

25

30

0 0.01-

0.2

0.2-0.4 0.4-0.6 0.6-0.8 0.8-1 1-1.2

Miles Of Delivering Road With Ruts Interfering With 

Drainage 

Number of Sample Units in Region

Coastal/Spruce

0

5

10

15

20

25

30

0 0.01-

0.2

0.2-0.4 0.4-0.6 0.6-0.8 0.8-1 1-1.2

Miles Of Delivering Road With Ruts Interfering With 

Drainage

Number of Sample Units in Region

Figure 20. H2b4 Miles of Delivering Road with Ruts Interfering with Drainage. 

4.3.3 Monitoring Question 3

What is the status of road performance measures for drainage connectivity and sediment 

delivery to streams at each sample event?

MQ 3.1 and H5a Miles of forest road delivering to streams per miles of stream (road hydrology 

performance measure)

Schedule L-1 of the Forests & Fish Report provides two performance measures with targets for 

existing roads. The first is a measure of the hydrologic connectivity of the road system in 

relation to the stream density in a sample unit (RLEN), and was calculated as the miles of road 

delivering to streams per miles of stream in each sample unit. The higher this number is, the 

more road network drains to streams in the unit. Sample units in the East of Crest region had 

less road delivering/miles of stream than units in the Coast/Spruce or West of Crest regions. 

State-wide (Percent)

0

10

20

30

40

50

60

70

0 0.01-

0.2

0.2-0.4 0.4-0.6 0.6-0.8 0.8-1 1-1.2

Miles Of Delivering Road With Ruts Interfering With 

Drainage 

Percent of Sample Units across 

State
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 49

East of Crest

0

2

4

6

8

10

12

14

16

0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.8

Miles of Road Delivering/Mile of Stream

Number of Sample Units in Region

Coastal/Spruce

0

2

4

6

8

10

12

14

16

0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.8

Miles of Road Delivering/Mile of Stream

Number of Sample Units in Region

Figure 21. MQ3.1 Miles of Delivering Road per Mile of Stream (FFR Hydrology 

Performance Measure).

Figure 22 shows the cumulative percentages of sample units as a function of miles of road

connected to the stream network per mile of stream (RLEN) for each region and statewide. 

These graphs can be thought of as counting the number of units (or percentage of study units) 

that have RLEN values less than or equal to the value on the x-axis. For instance, it can be seen 

in Figure 22 that 68 percent of the sample units had RLEN values of less than 0.2 mile of 

delivering road per stream mile. The range of each regional target (upper and lower target) is 

also shown on the graph so that the percentage of sample units meeting either the upper or lower 

end of the target range can be determined for each region. 

West of Crest

0

2

4

6

8

10

12

14

16

0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.8

Miles of Road Delivering/Mile of Stream

Number of Sample Units in Region

State-wide (Percent)

0%

5%

10%

15%

20%

25%

30%

35%

40%

0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.8

Miles of Road Delivering/Mile of Stream

Percent of Sample Units across 

State
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 50

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

RLEN - Unweighted Miles of Delivering Road/Miles of Stream

Cumulative Percent

Entire State

East of Crest

Coast/Spruce

West of Crest

East of Crest Target (0.08-0.12)

Coast and West of Crest Target (0.15-0.25)

Figure 22. MQ3.1 Cumulative Percent of Sample Units, Miles of Delivering Road per Mile 

of Stream (RLEN).

MQ 3.2 and H5b WARSEM modeled tons of road sediment delivered to streams per mile of 

stream (road sediment performance measure)

The other FFR performance measure is tons of road sediment delivered to streams per mile of 

stream. This metric focuses on the relative amount of sediment delivered to streams in the 

sample unit. All sample units in the East of Crest region had less than 2 tons of sediment/mile of 

stream (Figure 23). Most units in the Coast/Spruce zone had less than 6 tons/mile, and units in 

the West of Crest region varied the most, with up to 16 tons/mile 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 51

East of Crest

0

5

10

15

20

25

30

35

0-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16

Tons of Delivered Sediment/Year/Mile of Stream

Number of Sample Units in Region

Coastal/Spruce

0

5

10

15

20

25

30

35

0-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16

Tons of Delivered Sediment/Year/Mile of Stream

Number of Sample Units in Region

Figure 23. MQ3.1 Sediment Delivered/Year per Mile of Stream (FFR Sediment 

Performance Measure).

Figure 24 shows the cumulative percentages of sample units as a function of sediment delivered 

per mile of stream (RSED). The range of each regional target (upper and lower target) is also 

shown on the graph so the percent of sample units meeting either the upper or lower end of the 

target range can be determined for each region. 

West of Crest

0

5

10

15

20

25

30

35

0-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16

Tons of Delivered Sediment/Year/Mile of Stream

Number of Sample Units in Region

State-wide (Percent)

0%

10%

20%

30%

40%

50%

60%

70%

80%

0-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16

 Tons of Delivered Sediment/Year/Mile of Stream

Percent of Sample Units across 

State
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20

RSED - Tons of Sediment Delivered/Miles of Stream

Cumulative Percent

Entire State

East of Crest

Coast/Spruce

West of Crest

East of Crest Target (1-3)

West of Crest Target (2-6)

Coast Target (6-10)

Figure 24. MQ3.1 Cumulative Percent of Sample Units, Tons of Delivered Sediment per 

Mile of Stream (RSED).

4.3.4 Monitoring Question 4

What is the status of road performance measures relative to their targets, by performance 

target region, at each sample event?

MQ 4.1 Miles of forest road delivering to streams per miles of stream (road hydrology 

performance measure) divided by the performance target by target region

Monitoring Question 4.1 looks at the road hydrology performance measure in each unit in 

relationship to the upper limit of the performance target for that region. If the ratio of the 

measure/target is one or less, the unit meets the target. If the ratio is greater than one, the unit 

exceeds the target. 

Across the state, 62 percent of the sample units meet the sample hydrology target (Figure 25). 

The sample unit that far exceeded the standard (East of Crest Unit, 5-6 bin) had a large number 

of mid-slope roads resulting in numerous stream crossings despite the moderate overall stream 

density. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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East of Crest

0

2

4

6

8

10

12

14

16

18

0-1 1-2 2-3 3-4 4-5 5-6

Miles of Road Delivering/Miles of Stream/Performance 

Target 

Number of Sample Units in Region

Above Target

Below 

Target

Coastal/Spruce

0

2

4

6

8

10

12

14

16

0-1 1-2 2-3 3-4 4-5 5-6

Miles of Road Delivering/Miles of Stream/Performance 

Target 

Number of Sample Units in Region

Above Target

Below 

Target

Figure 25. MQ4.1 Miles of Delivering Road per Mile of Stream Divided by Regional 

Performance Target. 

MQ 4.2 WARSEM modeled tons of road sediment delivered to streams per miles of stream (road 

sediment performance measure) divided by the performance target by target region

Monitoring Question 4.2 looks at the road sediment performance measure in each unit in 

relationship to the upper limit of the performance target for that region. If the ratio of the 

measure/target is one or less, the unit meets the target. If the ratio is greater than one, the unit 

exceeds the target. 

Across the state, 88 percent of the sample units meet the sediment target (Figure 26). All sample 

units in the East of Crest region meet the target. One unit in the Coast/Spruce region and several 

in the West of Crest region do not meet the target. 

West of Crest

0

2

4

6

8

10

12

14

16

0-1 1-2 2-3 3-4 4-5 5-6

Miles of Road Delivering/Miles of Stream/Performance 

Target 

Number of Sample Units in Region

Above Target

Below 

Target

State-wide (Percent)

0%

10%

20%

30%

40%

50%

60%

70%

0-1 1-2 2-3 3-4 4-5 5-6

 Miles of Road Delivering/Miles of Stream/Performance 

Target 

Percent of Sample Units across 

State

Above Target

Below 

Target
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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East of Crest

0

5

10

15

20

25

30

0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3

Tons of Delivered Sediment/Year/Mile of 

Stream/Performance Target 

Number of Sample Units in Region

Below Target Above Target

Coastal/Spruce

0

5

10

15

20

25

30

0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3

Tons of Delivered Sediment/Year/Mile of 

Stream/Performance Target 

Number of Sample Units in Region

Below Target Above Target

Figure 26. MQ4.2 Sediment Delivered/Year per Mile of Stream Divided by Regional 

Performance Target.

4.3.5 Monitoring Question 5

Have measures of road sediment performance improved over time?

This monitoring question will be assessed through comparison of the initial and subsequent 

sampling events. 

4.3.6 Monitoring Question 6

Will roads judged to meet FFR road standards meet the performance targets?

In order to assess how much of the road system in each sample unit either had RMAP work 

completed or was up to current road standards, each landowner was asked the percentage of 

roads on their lands in the unit that they consider to be up to standards. This measure was 

compiled for each sample unit by combining the percent of roads reported to meet standards 

from each landowner by the percent of the road system on their land in each sample unit. As this 

metric was based on landowner judgment and was not verified by field crews, it should be 

regarded as an estimate rather than a precise measurement. Figure 27 shows the percent of 

West of Crest

0

5

10

15

20

25

30

0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3

Tons of Delivered Sediment/Year/Mile of 

Stream/Performance Target 

Number of Sample Units in Region

Below Target Above Target

State-wide (Percent)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3

 Tons of Delivered Sediment/Year/Mile of 

Stream/Performance Target 

Percent of Sample Units across 

State

Below Target Above Target
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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sample units by the percent of roads reported to be up to current road standards for each region 

and across the entire state. Overall, a high percentage of roads were reported to be up to 

standards, with over half of the units reporting that at least 85 percent of the roads meet 

standards. Percent of roads meeting standards was highest in the East of Crest region, and lowest 

in the West of Crest region. 

0%

10%

20%

30%

40%

50%

60%

70%

0 10 20 30 40 50 60 70 80 90 100

Percent of Roads in Sample Unit Reported Up to FFR Road Standards

Percent of Sample Units

East of Crest Coastal/Spruce West of Crest State

Figure 27. Percent of Sample Units with Percent of Roads Reported to be up to FFR Road 

Standard

H6a Miles of forest road delivering to streams per miles of stream (road hydrology performance 

measure) vs. percent of road length in each unit meeting FFR road standards

H6b WARSEM modeled tons of road sediment delivered to streams per miles of stream (road 

sediment performance measure vs. percent of road length in each unit meeting FFR road 

standards

The FFR performance metrics for road length delivering (MQ3.1) and sediment delivery

(MQ3.2) were calculated for each sample unit, divided by the FFR performance target for that 

metric (shown in Table 1) and plotted by the percent of roads within the sample unit that were 

reported by landowners to meet current road rule standards. This relationship between percent 

roads meeting performance standards and the ratio of each sample unit performance measure to 

the regional target are displayed in Figures 28 and 29. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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0%

100%

200%

300%

400%

500%

600%

0 10 20 30 40 50 60 70 80 90 100

Percent of Roads in Sample Unit Up to Standards

Un-weighted Miles of Road Delivering/Miles of 

Stream Expressed as Percent of Regional Target

East of Crest Coast (Spruce) West of Crest

Above Target

Below Target

Figure 28. Miles of Delivering Road/Miles of Stream (MQ3.1) Expressed as Percent of 

Regional Target vs. Percent of Road Miles in Sample Unit Reported to be up to Standards.

0%

50%

100%

150%

200%

250%

300%

0 10 20 30 40 50 60 70 80 90 100

Percent of Roads in Sample Unit Up to Standards

Tons of Sediment/Year/Miles of Stream 

Expressed as Percent of Regional Target

East of Crest Coast (Spruce) West of Crest

Above Target

Below Target

Figure 29. Tons of Delivered Sediment/Miles of Stream (MQ3.2) Expressed as Percent of 

Regional Target vs. Percent of Road Miles in Sample Unit Reported to be up to Standards.
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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For MQ3.1, length of road delivering, there is no evidence of a relationship with the reported 

percent of roads up to standards (one-tailed Kendall’s trend test p = 0.327). This may reflect a 

general RMAP objective of prioritizing road maintenance on road sections with the highest need

for maintenance/repairs. 

All of the Coast/Spruce zone units met the road mile delivering target, but in the East of Crest 

and West of Crest zones only 57 percent of the units met the road mile delivering target. This 

was true even though 93 percent of the units reported more than 80 percent of their roads were 

up to standards. The reported percentage of roads up to standards varied widely for the Coastal 

and West units. The sample unit that far exceeded the standard (East of Crest Unit, 535 percent

of standard) had a large number of mid-slope roads resulting in numerous stream crossings 

despite the moderate overall stream density. 

For MQ3.2, sediment delivered, there is a significant monotonic decrease in sediment delivered 

with increase in percent of roads meeting performance standards within the sampling unit (p = 

0.0028). The regional results for sediment delivery are quite different than the road length 

delivering results, with all of the East of Crest units meeting the sediment performance target, 

and 74 percent of the West of Crest units and 86 percent of the Coastal/Spruce units meeting the 

target.

The reasons for the differences in meeting delivering length and sediment targets between the 

different geographic regions are likely due to a combination of factors, including a much lower 

stream density on East of Crest units (metrics are divided by miles of stream in each unit), and 

much lower precipitation on the Eastside resulting in lower calculated sediment production in 

those units. It is also possible that landowners prioritized roads for RMAP work and upgrades to 

first work on those areas with roads that they judged to need the most improvements. 

It should also be noted that in some of the selected sample unit areas it will be much more 

difficult to meet the target values as beacause of the location of the existing roads in relation to 

the stream network. For example, areas with a ridgetop road system (Figure 30 left side) have a 

much lower density of road/stream crossings (blue squares) and therefore a much lower chance 

for long lengths of delivering roads than a unit with primarily midslope and valley bottom roads 

(right side of Figure 30). Moreover, some geologic materials and soils are more erodible than 

others and/or more prone to gullying. 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Figure 30. Sample Unit Maps Showing Difference in Delivery Between Units with Ridgetop Roads (left) and Midslope/Valley 

Bottom Roads (right)

Example 

Units

Legend
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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4.4 New Roads Evaluation

While the majority of this study evaluates road effects collectively at the sub-basin scale, the data 

set also allows site-scale evaluation of new roads. A total of 11.8 miles of new roads, defined as 

being constructed within two years of the field sampling, were present within 11 of the sample 

units; these units were distributed among all three rule regions. The FFR performance target for 

sediment delivered to streams from new roads is “virtually none” (see Table 1 in Section 2 

above), which does not lend itself to objective determination of success or failure. Despite the 

subjective target and small sample size, this evaluation provides an initial assessment of new

roads built under post-2000 Forest Practices Rules.

Table 8 summarizes the miles of new road length and estimated sediment delivery from new 

roads in each of the 11 sample units. Delivery from the new roads varied greatly – five of the 

units with new roads had no delivery from the new road segments, while between 1 and 79 

percent of the new road length in the remaining six units delivered to streams. The specific 

location of the new roads determined whether or not the road segments were hydrologically 

connected to streams. In several units, the new roads were a number of short spurs off existing 

roads and did not cross streams. However, in four of the units the new roads were midslope 

roads constructed in locations without previous road systems; these crossed many small 

drainages and did drain to streams. In the two units with the highest percentage of new 

delivering (72 and 79 percent), it did not appear that measures were taken to minimize the length 

of new road connected. The average length of road connected at drainage structures in these two 

units was 838 and 942 feet respectively. It did appear that an effort was made to minimize 

connectivity in the other units, with the average length of connected road at each crossing less 

than 250 feet in all but one of the remaining units. Across all the sample units, 17 percent of the 

new roads were hydrologically connected compared to 11 percent of all roads sampled across the 

state. 

Sediment delivery from the new road segments was relatively minimal in eight of the 11 units 

(Table 8). Sediment delivery ranged from 0 to 136.5 tons/year. Note that the WARSEM 

computation of sediment delivery for new roads includes a factor for road age, with 10 times 

more sediment produced from a road constructed within the past year as an old road (see 

WARSEM technical documentation, Dubé et al. 2004). Therefore, the average of 18 

tons/mile/year of sediment computed from new roads cannot be directly compared with the 

average of 2.1 tons/mile/year of sediment produced from existing roads across the state. 

Measurements of sediment produced from newly constructed roads shows erosion rates decline 

quickly and reach rates similar to older roads within 2-3 years (Ketchenson et al. 1999, Luce and 

Black, 1999, Grace 1999, Swift 1984, Dryness 1975, Megahan 1974, Megahan and Kidd 1972). 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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Table 8. Summary of New Roads by Sample Unit

Region

Miles of New 

Road in Unit

Un-weighted 

New Road 

Length 

Delivering (mi)

Percent of New 

Road Length 

Delivering

WARSEM 

Calculated 

Delivered 

Sediment

(tons/yr)

Delivered 

Sediment per 

mile of new 

road 

(tons/mile/yr)

East of Crest 0.86 0 0% 0 0

1.54 0.02 1% 0.04 0.03

Coastal Spruce 1.59 0.17 11% 17.3 10.9

0.40 0 0% 0 0

2.79 0 0% 0 0

0.23 0.18 79% 4.9 21.5

1.04 0.37 35% 51.2 49.4

West of Crest 0.44 0.32 72% 1.8 4.1

0.43 0 0% 0 0

2.29 1.00 44% 136.5 59.7

0.19 0 0% 0 0

Total for New 

Roads 11.8 2.1 17% 211.8 18.0

Total for All 

Roads 

Evaluated 

Across State 

(new and old)

1283 147 11% 2,699 2.1

5 Summary and Recommendations for Future Sample Events

New Forest Practice Rules for forest roads under WDNR jurisdiction were adopted in 

Washington State in 2001. Implementation of the road rules for existing roads is planned over a 

15-year time horizon through the completion of Road Maintenance and Abandonment Plans. 

The objectives of the Road Sub-Basin Scale Effectiveness Monitoring Program are:

• to determine if the road characteristics that affect runoff and sediment delivery to streams 

are improving through time as RMAP are implemented between 2001 and 2016; and

• to determine the extent to which roads on lands subject to WDNR forest practice rules

meet the FFR performance targets (Table 1). 

Characteristics of forest roads in a total of 60 four-square-mile stratified random sample units 

across the state were inventoried between 2006 and 2008, five to seven years after the forest 

practice rules were adopted. This is the first sample event planned for the Road Sub-Basin Scale 

Effectiveness Monitoring Program, and provides the first look at the current status of forest 

roads. 

A high percentage of roads in the sample units across the state were reported to either have 

RMAP work complete, or already be up to current road rule standards, with over half of the 

sample units reported to have at least 85 percent of road length meeting standards. An average 

of 11 percent of the road network delivered to streams or wetlands. Across the state, 62 percent 
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

Page 61

of the sample units met the Forests & Fish Report (FFR) hydrology performance target (miles of 

delivering road/miles of stream) and 88 percent of the units met the FFR sediment performance 

target (tons of delivered sediment/year/miles of stream). These results include new and existing 

roads combined. 

Statewide, no relationship was found between length of road delivering and percent of unit 

reported to be up to standards; however, a statistically significant decreasing relationship was 

found between sediment delivery and percent of roads up to standards. These findings suggest 

that, while there may be locations where there is higher hydrologic connectivity or sediment 

input from roads, overall across the state there is a trend of decreasing sediment input as roads 

are brought up to modern standards. 

Based on the findings of this first sample period, the following recommendations are made for 

future monitoring events:

• Continue with the next planned monitoring period (planned interval of 5 years) to 

confirm the findings that, in general, roads conditions improve and they meet the 

performance metrics as they are brought up to FFR standards. 

• Continue to stress measures to minimize observer variability. To help reduce observer 

variance, minimize the number of field crew members to the extent practical. Five crew 

members were used during this first sample event. Training, duplicate crew surveys, and 

continued training through the field season are important to help minimize variance due 

to observer error.

• Re-evaluate the most effective method to conduct observer variability testing prior to the 

next sampling period. One addition to the existing methods that may prove helpful is to 

have the project leader survey the test road segments to use as a benchmark for observer 

variability. This could point out which attributes are most prone to variability, indicating

that more training or guidance is needed. 

• As specified in the Study Design, the same study units are planned to be re-sampled 

during subsequent sample events. Prior to the next sampling period, methods for resampling units (Field Protocol, Section 4.11) should be thoroughly discussed to specify 

how field crews will determine if each road attribute has changed (or not) between 

sampling events. 

• Prior to the next planned sample event, methods for sampling should be discussed with a 

statistician regarding variables that will be or will not be re-sampled for each unit. Also, 

the method for analyzing changes should be carefully considered prior to sampling. 

• Consider developing a companion study specifically designed to obtain access to and 

evaluate road conditions on small forest ownerships.
CMER 08-801 Road Sub-Basin Scale Effectiveness Monitoring Report

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6 References

Bilby, R.E., K. Sullivan and S.H. Duncan, 1989. The Generation and Fate of Road-surface 

Sediment in Forested Watersheds in Southwestern Washington. Forest Science Vol. 35, 

No. 2, pp. 453-468.

Bohle, Todd, 2010, personal communication via e-mail. 

Brake, D., M. Molnau, and J.G. King, 1997. Sediment Transport Distances and Culvert 

Spacings on Logging Roads within the Oregon Coast Mountain Range. Presented at the 

1997 Annual International ASAE Meeting Minneapolis, MN. Paper No. IM-975018. 

Burroughs, E.R. Jr., and J.G. King, 1989. Reduction of Soil Erosion on Forest Roads. General 

Technical Report INT-264. USDA Forest Service, Intermountain Research Station, 

Ogden, Utah. 

Coe, D., 2006. Sediment Production and Delivery from Forest Roads in the Sierra Nevada, 

California. Master of Science Thesis, Colorado State University, Spring 2006.

Conover, W.J., 1980. Practical Nonparametric Statistics. Second Edition. John Wiley and Sons, 

Inc., New York, New York.

Dubé, K., C. Luce, T. Black, and M. Riedel, in preparation. Comparison of Road Surface 

Erosion Models with Measured Road Surface Erosion Rates. Paper prepared for the 

National Council for Air and Stream Improvements, December 11, 2008. 

Dubé, K., W. Megahan, and M. McCalmon, 2004. Washington Road Surface Erosion Model. 

Prepared for the Washington Department of Natural Resources. February 20, 2004. 

available online at 

http://www.dnr.wa.gov/BusinessPermits/Topics/ForestPracticesApplications/Pages/fp_w

arsem.aspx

Dryness, C.T., 1975. Grass-legume Mixtures for Erosion Control along Forest Roads in Western 

Oregon. Journal of Soil and Water Conservation, July-Aug. 1975, pp. 169-173.

Foltz, R.B., 1996. Traffic and No-Traffic on an Aggregate Surfaced Road: Sediment Production 

Differences. Paper presented at Food and Agriculture Organization Seminar on 

Environmentally Sound Forest Road and Wood Transport, Sinaia, Romania, June 17-22, 

1996.

Foltz, R. B., and E.R. Burroughs. Jr., 1990. Sediment Production from Forest Roads with Wheel 

Ruts. In: Watershed Planning and Analysis; Proceedings of a Symposium, July 9-11 

1989, Durango CO. ASCE, pp. 266-275.

Glass, Domoni, 2001, personal communication. File transmitted by diskette. 

Grace, J.M., III. 1999. Erosion Control Techniques on Forest Road Cutslopes and Fillslopes in 

North Alabama. In: Seventh International Conference on Low Volume Roads. Volume 

2; Transportation Research Record 1652; pp. 227-234.
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Haupt, H.F., and W.J. Kidd, Jr., 1965. Good Logging Practices Reduce Sedimentation in Central 

Idaho. Journal of Forestry, Vol. 63, pp. 664-670

Haupt, H.F., 1959. Road and Slope Characteristics Affecting Sediment Movement from 

Logging Roads. Journal of Forestry, Vol. 57, pp. 329-332.

Ketcheson, G.L. and W.F Megahan, 1996. Sediment Production and Downslope Sediment 

Transport from Forest Roads in Granitic Watersheds. USDA Forest Service, 

Intermountain Research Station. Research Paper INT-RP-486. 

Ketcheson, G.L., W.F. Megahan, and J.G. King, 1999. “R1-R4” and “BOISED” Sediment 

Prediction Model Tests using Forest Roads in Granitics. Journal of the American Water 

Resources Association Vol. 35, No. 1, pp. 83-98. 

Kochenderfer, J.N., and J.D. Helvey, 1987. Using Gravel to Reduce Soil Losses from Minimum 

Standard Forest Roads. Journal of Soil and Water Conservation, Vol. 42 pp. 46-50. 

Luce, C.H., and T.A. Black, 1999. Spatial and Temporal Patterns in Erosion from Forest Roads. 

In: M.S. Wigmosta and S.J. Burges, eds. The Influence of Land Use on the HydrologicGeomorphic Responses of Watersheds. AGU Monographs.

MacDonald, L., and D. Coe, 2008. Road Sediment Production and Delivery: Processes and 

Management. In Proceedings of the First World Landslide Forum. International 

Programme on Landslides and International Strategy for Disaster Reduction. United 

Nations University, Tokyo, Japan, pp 381-384.

Martin, D., 2009. Forest Road Runoff Disconnection Survey of Private Timberlands in 

Washington. Washington Forest Protection Association, Olympia WA. January 30, 

2009. 

Megahan, W.F., 1974, Erosion over time on severely disturbed granitic soils: a model: USDA 

Forest Service Intermountain Research Station General Technical Report INT-156, 

Boise, ID.

Megahan, W.F., and G.L. Ketcheson, 1996. Predicting Downslope Travel of Granitic Sediments 

from Forest Roads in Idaho. Water Resources Bulletin, Vol. 32, No. 2, pp. 371-382. 

Megahan, W.F., and W.J. Kidd, 1972. Effect of Logging Roads on Sediment Production Rates 

in the Idaho Batholith. USDA Forest Service, Research Paper INT-123, 14p. 

Intermountain Forest and Range Experiment Station, Ogden, Utah.

Meyers, E., 2007. Reducing Sediment Production from Forest Roads during Wet-Weather Use. 

PhD. Dissertation, Oregon State University, August 3, 2007. 

Mills, K, L., Dent, and J. Robben, 2003. Wet Season Road Use Monitoring Project. Oregon 

Department of Forestry, Forest Practices Monitoring Program, Technical Report #17. 

June 2003. 
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NCASI, 2000. Handbook of Control and Mitigation Measures for Silvicultural Operations. 

Unpublished Draft Technical Bulletin. Research Triangle Park, NC:National Council for 

Air and Stream Improvements, Inc. 

Raines, M., R. Conrad, J. Clark, D. Coe, R. Palmquist, C. Veldhuisen, 2005. Road Sub-Basin 

Scale Effectiveness Monitoring Design. Prepared for the Washington Department of 

Natural Resources. May 9, 2005. 

Reid, L.M,, 1981. Sediment Production from Gravel-surfaced Forest Roads, Clearwater Basin, 

Washington. M.S. Thesis, University of Washington. 

Reid, L.M., and T. Dunne, 1984. Sediment Production from Forest Road Surfaces. Water 

Resources Research Vol. 20, No. 11, pp. 1753-1761.

Rogers, L. W. and A. G. Cooke, 2009. The 2007 Washington State Forestland Database, Final 

Report. Rural Technology Initiative, University of Washington. March 24, 2009. pp. 47

and appendices.

Rural Technology Institute, 2007. Washington Statewide Parcel Database, 2007 9.2 version 1. 

Restricted Distribution GIS (ArcGIS 9.2) dataset compiled by the University of 

Washington Rural Technology Initiative for the Washington State Parcels Working 

Group. Seattle, WA.

Sugden, B.D., and S.W. Woods, 2007. Sediment Production from Forest Roads in Western 

Montana. Journal of the American Water Resources Association. Volume 43, No. 1, pp. 

193-206.

Sullivan, K.O., and S.H. Duncan, 1981. Sediment Yield from Road Surfaces in Response to 

Truck Traffic and Rainfall. Weyerhaeuser Technical Report 042-4402.80. 

Weyerhaeuser Company, Technical Center, Tacoma, WA 98477.

Swift, L.W. Jr., 1984. Gravel and Grass Surfacing Reduces Soil Loss from Mountain Roads. 

Forestry Science, Vol. 30, pp. 657-670. 

Swift, L.W. Jr., 1985. Soil Losses from Roadbeds and Cut and Fill Slopes in the Southern 

Appalachian Mountains. Southern Journal of Applied Forestry, Vol. 8 No. 4, pp. 209-

213.

Trimble, G.R., and R.S. Sartz, 1957. How far from a Stream Should a Logging Road be 

Located? Journal of Forestry, Vol. 55, pp. 339-341.

Washington Department of Natural Resources, 2005. "CMERlands" Available GIS Data. August 

2005. http://www.dnr.wa.gov/AboutDNR/BoardsCouncils/CMER/Pages/Home.aspx. 

Washington Forest Practices, 1997. Standard Methodology for Conducting Watershed Analysis, 

Version 4.0. Washington State Department of Natural Resources, Forest Practices 

Division. November 1997.
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Watershed Professionals Network, 2006. Washington Road Sub-Basin Scale Effectiveness

Monitoring Field Protocol. Prepared for the Washington Department of Natural 

Resources. Version dated February 28, 2006 (used for 2006 field work). 

Watershed Professionals Network, 2008. Washington Road Sub-Basin Scale Effectiveness 

Monitoring Field Protocol. Prepared for the Washington Department of Natural 

Resources. Version dated April 17, 2008 (also updated at end of 2008 field season –

version dated March 31, 2009). 

Wemple, B., J. Jones, and G. Grant, 1996. Channel Network Extension by Logging Roads in 

Two Basins, Western Cascades, Oregon. American Water Resources Association, Water 

Resources Bulletin. Vol. 32 No. 6, pp. 1995-1207.

Appendix A. Meeting Minutes 

A-1

WDNR Road Sub-Basin Scale Effectiveness Monitoring

Phase I Kickoff Meeting Minutes

Wednesday, December 14 1 PM

Attendees: Kathy Dubé, Mary Raines, Curt Veldhuisen, Jenelle Black

By conference call: Karen Kuzis, Julie Dieu, Dawn Hitchens, Nancy Sturhan

1. Introduction and Meeting Purpose (Jenelle Black)

Purpose of meeting was to review the objectives and proposed methodology for the road subbasin scale effectiveness monitoring project so contractor (WPN) and UPSAG committee 

members have shared vision of how project will proceed. 

2. Goals and Objectives of Monitoring Project (Jenelle Black)

Jenelle reviewed goals in RFQQ:

• Provide a way to measure if the FFR road rules are having a positive effect on the 

condition of roads on forested lands in Washington.

• This assessment will establish baseline condition – assessment will be repeated at 5 year 

increments (separate project)

• Current project will develop methods and protocols for assessment methodology (spelled 

out in the monitoring design), develop crew training materials, train crew, and survey the 

first group of road sites (anticipated to be 17 – 20 sites)

• QA/QC procedures are quite involved and are also part of this project – objective is to 

provide statistically valid sample and be able to judge amount of error associated with 

field measurements

• Survey protocol will also include fish passage questions from ISAG. For reporting 

purposes, these can be included in a separate table in the database, linked to information 

collected on that drainage structure. 

The group discussed the responsibilities of team members:

• On the DNR/CMER side, Jenelle Black is project manager. UPSAG team members will 

be available to review documents and guide process, as requested by the DNR/CMER 

project manager. Dawn Hitchens will handle contract/billing questions. Nancy Sturhan 

will be available to answer any policy questions.

• The WPN team will divide work among Kathy Dubé (technical issues, protocol, 

training), Karen Kuzis (contract/billing and logistics), and Mary Raines (QA/QC lead).

3. Field Protocol and Training (Kathy Dubé)

Kathy said that most of the data collection methods are clear, but she had a few questions on 

ways to deal with segments that are unusual, particularly as far as delivery and road drainage 

configuration. After some discussion, the group decided Kathy is going to list the 

questions/special situations and provide a suggested approach to addressing the situations. 
A-2

UPSAG will review these and come to agreement about how they will be handled. Question also 

came up as to how the FFR metric of miles of road/miles of stream will deal with partial delivery 

segments. This is really a policy issue. WPN will provide suggestions and UPSAG again will 

make final determination. 

Marking segments in field – Kathy has a list of several methods for monumenting the starting 

points of road segments that could be used depending on landowners and logistics: GPS, 

odometers, paper base maps with notes, and photos. Julie Dieu said that after experimenting 

with several different methods, they have found that putting metal tags on the base of 

trees/stumps near the top of the cutslope is a good way to deal with this. Use aluminum nails. 

Scratch info into tag, or use plastic tags and write on both sides (UV rays fade writing). The 

group decided that several methods should be available and planned for, depending on the site 

and any landowner constraints. As long as the method used for each monument is welldocumented, the use of multiple methods is not expected to be a problem.

Nancy Sturhan asked who will make changes to the WARSEM code. Marc McCalmon has been 

designated as the person to do this. He worked on the original WARSEM code and currently 

works for WDFW. There were some concerns about whether or not he would have time to do 

this or if we needed an alternate person available. Nancy/Jenelle will work on scheduling this 

with Tim Quinn (Marc’s boss). We anticipate 1 week of Marc’s time, in January or February. 

Training Location - Several sites were discussed. Jenelle said it would be nice if we could use 

one of the actual monitoring sites – maybe Skagit or Grays Harbor area – for training. Kathy 

also mentioned a DNR-owned property near Seattle that was used for the WARSEM project that 

might be available. We discussed that it might be hard to find an Eastside site that was snowfree at time of training – may need to hit that site later in Spring, as the crews start to work on 

that side. 

Training Date – targeting February

How many DNR/UPSAG members and who can or do want to attend the training? Jenelle was 

going to do some inquiry about who (from where) may want to attend. Curt said he may attend 

one day. Kathy said up to 12 people in the field portion of the training is OK – as many as want 

can attend the first day (classroom). 

Julie Dieu mentioned that in her experience, having crew members train the next generation of 

field crew was the most effective method (job shadow for a week or so – worked well). 

4. QA/QC Program (Mary Raines)

Mary asked if the training materials and field protocols part of the QA/QC document or if they 

are separate documents that reference the other? The group said either way would work as long 

as they are integrated. Kathy and Mary are going to coordinate development, probably separate 

documents which will tier off of each other. In response to a question by Mary, the QAPP 

should include the methods and statistical tests for evaluating operator variability. 
A-3

Jenelle expressed an expectation that the QA process will include methods for identifying and 

correcting problems and errors at all levels in data collection and processing, and that tracking 

operator variability throughout the process rather than just at the beginning and end of data 

collection would be one way to do this. This suggestion will be taken into consideration during 

the QAPP development if practical, but it is not specified in the contract. 

5. Field Surveys (Kathy Dubé)

Site selection status – Sites have been identified but status is unclear. Jenelle is working on this. 

UPSAG members may be able to help? Jenelle is going to follow-up and determine what needs 

to happen to let WPN know which sites to sample. 

Protocol needs to include how to determine what’s a road vs. a cat road. On Westside, rocked 

vs. native can be helpful. Also, gradient over 18%. 

6. Reporting 

Kathy will have Specific Questions on Field Approach by Jan 3rd – maybe a Draft Field Protocol. 

Mary will have outline of QAPP by Jan 3rd. UPSAG Meeting is Jan 10th

Jenelle will provide a list of UPSAG meeting dates so we can plan monthly report submissions 

(normally meetings are first Tuesday of each month; will let us know if different). We will plan 

to send in monthly reports on last Tuesday of month.
A-4

WDNR Road Sub-Basin Scale Effectiveness Monitoring

Phase I Second Unit Meeting Notes

Date: March 31, 2006

Time: 8 AM

Purpose: Discuss any changes to field protocol necessary based on first two field sites 

(S001, S002)

Personnel: Dan Thomas, Jesse Saunders, Matt Rourke, Brett Winterowd, Pete Malinak, 

Karen Kuzis, Jenelle Black, Mary Raines, Kathy Dubé

Discussion Topics:

1. Any comments on delivery flowchart (attached file)? No – looks good, is working. 

2. Changes to either the GPS data dictionaries or the paper data forms made during first 

week (see Road Form short.xls):

• New form (Road log) for keeping track of mileage on each road segment 

completed. 

• Added Begin Reference Point ID on Reference Point form (GPS and paper)

• Changed Road Name to text on Williamson’s data dictionary

• Minor tweaks such as adding S002

• Begin RP is set to “1” as a default – it can be easy to forget to input this number. 

Dan will look into flagging this in a manner so it can’t be missed as easily. 

3. GPS road line feature does not need to be run if there is a good road layer in GIS. Only 

run a road line if it’s a new road (not on map) or the road layer looks obviously wrong 

based on the orthophotos.

4. One item that is hard to rate in the field is road maintenance category. It’s hard 

sometimes to determine what is “recent” in the field – within the last year? Last 5 years? 

Discussed that recent maintenance is within last five years, and the objective is to break 

out RMAP activities from normal maintenance. Normal maintenance includes surfacing, 

grading, and ditch cleaning. Other BMPs includes anything else such as new culverts, 

sediment traps, etc. that are intended to bring roads up to current/RMAP standards. 

5. Vegetated ditchlines tended to trap quite a bit of sediment, but “vegetated” is not called 

out as a separate ditch condition. (Kathy noted we don’t have much research data on this, 

but it’s obvious if there is future research, this could change. Vegetated ditches do not 

transport sediment in the same way as “stable” ditchlines. We group these conditions 

under “stable” in the database.) Keep as “stable” for now. 

6. At road intersections, note road junction road name in comments field on Reference Point 

form. 
A-5

7. At stream crossings with no culvert apparent (e.g. Humboldt, or a ford) we will put in a 

new field called “Other/unknown” in the Drainage Structure Type field. 

8. Brett asked about surfacing in the situation where there was a lot of leaf litter/organic 

matter over what used to be gravel. He recorded it at pitrun. We all agreed. 

9. QA/QC going OK; checking records at end of day, and correcting items after conversion 

to a shape file. 

10. Deliverables for each unit includes (2 hard copies of each plus an electronic file where 

applicable): 

• Copy of field maps (marked with your name - small maps as well as large map)

• Copy of any data sheets (we used a few where the GPS wasn't recording satellites)

• Report of road miles surveyed (road log - field form) so we know how many miles we 

get paid for

• Photos (hard copies and electronic)

• Final Maps (Ted produces these - marked with intersection/culvert/drainage points, 

streams, roads, project boundary - electronic file as well as hard copies)

• Copy of GPS data files (convert to shape files and give to Ted - and Kathy will load 

the road segment data into the road database to run WARSEM - only need electronic 

copy of these)

11. It is most helpful to have completed the landowner interview BEFORE

• Keys, 

the field crews 

are on the ground to get:

• Directions to field unit, 

• ROAD NAMES and GIS layers 

• Any access issues (or areas to be careful of)

• Road maintenance levels
A-6

WDNR Road Sub-Basin Scale Effectiveness Monitoring Phase II

Kickoff Meeting Minutes

Friday March 21, 2008 9 AM

Attendees (conference call): Jenelle Black, Julie Dieu, Kathy Dubé, Dawn Hitchens, Karen 

Kuzis, Laura Vaugeois, Curt Veldhuisen

7. Introduction and Meeting Purpose 

Purpose of meeting was to review the objectives and proposed methodology for Phase II of the 

road sub-basin scale effectiveness monitoring project so contractor (WPN) and UPSAG 

committee members have shared vision of how project will proceed. 

8. Updates to Methods

a. Wetlands

Current protocol includes delivery to Type A and B wetlands. Jenelle mentioned that 

there is a new wetland layer on the DNR website (date 12/2007) that Ted should use for 

making field maps. She also mentioned that we should continue to note delivery to any 

un-mapped but obvious typed wetlands that are apparent from the orthophoto coverage. 

and make notes in the comment field during the inventory if there are wetlands we see on 

the ground and we cannot easily determine if they are Typed wetlands or not. We will 

discuss wetlands during training. There is interest from other CMER groups on the data 

we are collecting pertaining to wetlands.

b. Roads next to streams

There was discussion of how to handle roads that run alongside streams and wetlands 

(and through wetlands). Currently the protocol looks at delivery from drainage structures 

(constructed or not) and includes some amount of delivery if a sediment plume ends 

within 20 feet of a stream. Jenelle was concerned that we are not capturing any 

information on roads that have dispersed runoff and may deliver some sediment. 

Existing research and observations suggest that dispersed runoff may only transport 

sediment 10-15 feet from road. Concern was also expressed that we remain consistent 

with methodology from first set of sample units (Phase I). Consensus: An additional 

delivery category will be added – category 5 – for road segments that would have been 

classified no delivery (category 0) but that are along or through a stream or wetland and 

the edge of the road tread is within 20 feet of a stream/floodplain or typed wetland. The 

begin/end station and all other road attributes will be collected for these segments. 

9. Site Selection/Landowner Contacts

a. Blue Mountains

Jenelle said that sites in the Blue Mountains area are tricky because there are cultivated 

ag lands on the hilltops and some inter-fingering forest lands in valleys/north slopes. 

Farm roads are commonly used for hauling, and are not being maintained as forest roads. 

UPSAG decided not to include the forest roads in the monitoring; consequently many of 

the potential units in this are have dropped out. 
A-7

b. Description of site selection process for report

Jenelle will write a description of the site selection process that will be included either 

within the text or within an appendix of the final report. 

c. Procedure for sites in “December 2007 storm” area

We discussed the procedure to use for units within the area hit hard by the December 

2007 storm (SW Washington). There is concern that there may be enough damage that 

access either to the unit or on roads within the unit would be extremely difficult and 

beyond what any of us had budgeted for (both slides and blowdown). The pros and cons 

of sampling sooner (capture storm damage – but is it representative?) vs. later (storm 

damaged roads may be freshly fixed, but more likely to be able to access roads) were 

discussed. Consensus: Check with landowners of these sites soon to determine extent of 

problem (possibly also look on the air photos UPSAG will be obtaining for the mass 

wasting study?). Then check back with UPSAG to determine how to proceed. 

d. Landowner letter

Jenelle has updated the landowner letter and will send it out Monday to landowners in 

units we anticipate to be sampling soon – rest of landowners as they are identified. 

10. Field Training/Testing Methods and Plan

a. Training currently scheduled for April 14-15 in units near Ellensburg

b. Then crews will complete 1-2 units in Ellensburg area (April 16-17...) with 

Kathy/Jenelle/Karen available for ride-alongs. 

c. Second Unit meeting after they complete these units and are still in area

d. First Variability Test at end of week (April 18). Kathy will run through roads selected 

for testing to make sure any ambiguous items (such as weird road junctions) are cleared 

up before test and will flag start/stop locations. 

e. Training will include PowerPoint presentation and then field training (first with paper, 

then GPS/Jamars). Will include last year’s training plus discussion of wetlands, roads 

next to streams, any other revisions. OK to discuss differences between observers we 

found from last year’s variability testing. 

11. QA/QC Methods and Plan

a. Field Assistance Program (ride-alongs). Kathy/Jenelle/Karen – will ride along first week 

of field sampling, also available second week as needed if questions (Jenelle gone April 

21-22). Then ride along one day/sampling month with each crew member for duration. 

b. Replicate surveys. Try to schedule several during first 2 weeks of inventory, plus others 

throughout sampling season. Williamson crew found it helpful to do a quick check at the 

beginning of each unit to confirm surfacing calls, any other issues they saw with unit. 

c. Third Party QA/QC. Karen will do this. Objective is to make sure crew members are 

following field methods and QA/QC protocols. 

d. Data Cross-check. Each member checks data at end of day (issue with INFO not having 

enough time last year – going too fast – will discuss with them). Also check at end of 
A-8

each unit; Kathy performs final QA/QC to ensure all data fields filled in, all photos, 

maps, etc. are in file. Will use unit check off list as we did last time. 

e. Will provide general feedback to crew members on areas of concern following first 

variability test (no site specific information that could bias test at end of project). 

f. Will make sure notes from each replicate survey and field assistance program visit are 

distributed to all crew members so they can see what items were discussed. 

12. Field Crews

Have 5 field crews from Phase I plus one new field crew member (Amanda Ogden) to help 

Williamson crews. 

13. Sampling Plan

Sampling will start in units near Ellensburg in conjunction with training/testing. Many west side 

units should be clear of snow and ready to go – we’ll be checking on access as noted in 3.c. 

above. Williamson would like to go on Eastside units – will be checking snow/mud conditions. 
A-9

WDNR Road Sub-Basin Scale Effectiveness Monitoring Phase II

Second Unit Meeting Minutes

Friday May 23, 2008

Attendees Kathy Dubé, Scott Hotchkiss, Pete Malinak, Jesse Saunders, Dan Thomas, Brett 

Winterowd, (via conference call) Jenelle Black, Karen Kuzis

14. Introduction and Meeting Purpose 

Purpose of meeting was to review the data collection procedures from the training, first, and 

second sample unit, and discuss any issues that came up in field assistance visits or replicate 

crew surveys to date. 

15. Discussion

a. When is a skid trail vs. a road?

Contract says inventory roads, not skid trails (roads = driven on by logging trucks). 

Sometimes the distinction is not obvious, particularly if skid trails are constructed/graded. 

Came across examples in E008 - unit was harvested in last 5 years – making skid trails more 

obvious. The skid trail in question was graded and looked like a road for part of its length, 

but like a skid trail for last half of length and has not received maintenance. The manual 

says the roads only count if constructed to be driven on by trucks. Brent noted a reliable 

factor for identifying roads vs. skid trails are the location of landings and slash piles. If there 

is no landing at the end it probably wasn’t used as a road. Crews will have to use some 

judgment in gray areas. The situation is most likely to arise in areas that have been 

harvested more recently.

b. Spring and seeps were observed in numerous cut slopes – when is it a stream? 

Some are obvious seeps starting in a cut slope and forming a channel downstream (often in 

road ditch) which is then defined as gully. If there is an obvious upslope channel then it is a 

stream.

The definition was more difficult where water was coming out a bit above the cut slope. 

Kathy and the crews decided if the water and channel looks like it start is within 10-20 ft of 

cut slope and is associated with the ground disturbance at the cut slope, it should be 

classified as a seep. If the channel is further up the hill and cut into native material call it a 

stream.

c. When should you note sediment delivery that is not necessarily related to the roads being 

surveyed?

Jenelle observed a landing constructed on a spring complex that delivered and mitigation 

measures weren’t working. She also noted skid trails constructed and filled in type 5 

channels diverting water down skid trail to the stream. She had made notes of these 

situations on the map. After consideration she thought we might not want to attribute nonroad related problems to specific landowners in notes or on the maps. Better approach 

would be to keep a list of observed sediment delivery sources not necessarily related to 

roads in a separate notebook and pass the information onto Kathy and Jenelle. If needed this 

can be communicated to landowners informally by Jenelle and if similar conditions are 
A-10

observed in more than one location may be noted in the report as item for future 

consideration. If we find sediment sources not related to roads keep notes on separate paper 

don’t make specific notes on field forms and maps. 

d. Surfacing

Remember to agree on surfacing at beginning of the unit.

e. Monuments

Put monument tags at the base of the trees – do not make them too obvious as targets.

f. Recording Non-Delivering Stream Adjacent Roads

Dan at INFO is concerned this was not included in the original Scope of Work and will 

likely take more time especially in units with a high density of streams and wetlands. May 

need a change on work order.

Kathy noted the 1st unit had two additional segments non delivering segments they had to 

stop at 3 other segments measuring the distance. The 2nd unit 2 segments which were 

delivering and would be recorded anyway. 

Jenelle noted if crews are driving along a road adjacent to stream they should be getting out 

and looking at the stream/road adjacent to the stream to assess delivery anyway. Dan noted 

if the segment is not delivering you don’t need to make a segment. 

Dan also noted on the Westside wetlands dam water and there are lots of wetlands adjacent 

to roads where they will need to add segments. Kathy noted the difference is adding 

segments even if no delivery. Dan will evaluate how long it takes to add the new segments 

to address Jenelle’s concern that they would have been stopping and looking at these areas 

anyway.

Kathy noted a quick review showed 2,000 to 4,000 feet stream adjacent road in each unit. 

The team will have a call with Dan after they complete the Hancock Unit (W043) next week 

to discuss how much work this actually added.

g. Consistency Issue - Delivery

Kathy told the crews they need to get in the habitat of following the delivery flow chart to 

stay consistent.

16. Other items discussed after meeting – field crews please note

a. Powerline roads

Issue came up in E037 regarding powerline roads. Roads used just for powerline access are 

not subject to DNR regulations. Roads used for both powerline and timber haul are. Jenelle 

suggested checking with landowners in these units to determine which roads to survey/not 

survey. 

b. GPS point at end of road

Dan said he normally takes a GPS point at the end of the road to mark the end point of 

survey for Ted. 
A-11

c. Blocked roads

Jenelle said field crews should remember protocol on blocked roads. Walk road out with 

string box for 200 meters. If 90% veg cover on road, can stop. If less than 90% veg cover, 

keep walking to end (or point where 90% cover for 200 meters). Note blockage, how far 

you went/if vegetated on map. 

17. Next Steps

Today the crews are heading to complete variability testing in Unit E083.

Next week (5/27 to 30) Info will sample W043 (Hancock) and the following week (6/2 to 6/6) 

they will be in Forks for Units S007 and S005. 

Williamson starting June 2nd at a unit to be determined. Possibly E069? depending on 

permissions.
A-12

WDNR Road Sub-Basin Scale Effectiveness Monitoring Phase II

Phase II Survey Completion Meeting Minutes

Thursday January 29, 2009

8 AM via conference call

Attendees Kathy Dubé, Jesse Saunders, Dan Thomas, Brett Winterowd, Jenelle Black, 

Karen Kuzis, Ted Hitzroth

Meeting Purpose 

Purpose of meeting was to discuss sampling results, any issues that arose during the project and 

the analysis of sample data required to meet project goals. 

Items Discussed

1. Phase II Field Sampling

a. Any issues or suggestions for next time? Any specific things noted in field that 

should be considered for analysis of particular units (i.e., most roads were vegetated 

so we didn’t survey very far; lots of pulled culverts)

• Add a new field in the non-delivering point file for presence of BMPs (some nondelivering culverts didn’t deliver because landowners had done a great job with 

BMPs – should be noted)

• Add a method to show if a road is not surveyed, and why. Note these roads on 

field map, and why not surveyed (e.g., vegetated, blocked, not found on ground). 

Add this information into GIS road layer (line feature attributes) and map. One 

reason this is important is because number of stream crossings in GIS vs. found in 

field is used to adjust miles of stream in unit (FFR metric)

• Logistics:

o Fro efficiency, define unit, contact landowners as far in advance as 

possible. 

o Good for field crews to know contacts, who has keys. Can be an issue 

on Eastside where some landowners don’t know which locks are on 

which gates. 

• Training/documentation ideas:

o Describe Eastern/Western WA road differences and how to classify 

them (ditches, etc.)

o Definition of a stream, disconnected stream. 

2. Post-Sampling Processing

a. Any issues or suggestions for next time?

• Add Point ID for non-delivering culverts

• Add lat/longitude into Access database for each point so that other users can 

download into hand-held GPS units

3. QA/QC Protocols (training, management visits, replicate surveys/ride-alongs, crew 

variability assessment)

a. Any issues or suggestions for next time?
A-13

• Make sure that field crews review data at end of day to help catch incorrect 

entries (particularly stationing that’s way off)

• Training:

o Stress how to define a stream in the field, and include training on 

methods for disconnected streams. 

o Include differences between Eastern and Western WA road 

construction techniques and how to code (for example, 

presence/absence of ditches, outsloped roads). 

o Start field training with easier sites, then move onto more complex 

sites

o Maybe base training in Cle Elum area and include one field day on E 

WA roads, one field day on W WA roads. 

• Crew variability – might get better measure of variability if easier road segments 

were used instead of confusing ones. 

4. Data Analysis

a. Database Entry 

• How to deal with new fields – stream adjacent – with 2006 data? Add new 

field into Access database, populate with -8888 for 2006 data to indicate that 

no data was collected in 2006

b. Selection of 4 square mile area for 2006 data units

• Jenelle will send a clipped coverage to Ted, Ted will send Kathy a file listing 

points that are in/out of 4 square mile area. 

At this point the call was ended and Kathy, Jenelle, and Karen discussed the following items on 

Thursday February 5.

c. Database update: 

• add fields for latitude/longitude for each point

• pull Qsecs 17-24 from 2006 data into separate data tables within database. 

d. Statistical analysis (operator variability, Monitoring Design Table 10 Questions –

MQ1, MQ3, MQ4) – Alice is unpacking in her new location; she said that she can 

do analysis at end of February. 

5. Report Outline, Schedule

a. Proposed outline, work products

• Audience: assume there will be readers who do not know about CMER, 

monitoring program. 

• Intro – can get text from study design, RFP

• Map – just put dot for each unit to show general area

• Do not report results by unit in report (unit by unit summary in Access 

database)

• Summarize results by region, large vs. small landowners

• Summary – list monitoring questions and summary answers

• Recommendations for future sampling events, scientific study. No policy 

recommendations. 
A-14

b. Schedule – draft report end of February

6. CMER Presentation

a. Abstract due 2/18

b. Draft PowerPoint to Jenelle by 2/27 (review 3/2 in Olympia)

c. Final PowerPoint to Jenelle by 3/16

d. CMER Science Conference 3/18 – Kathy presents in Olympia

e. CMER meeting presentation April 28?
Appendix B. Quality Assurance Project Plan (QAPP)

The Quality Assurance Project Plan is available electronically on the data CD. 

Appendix C. QA/QC Report

The QA/QC Report is available electronically on the data CD. 

Appendix D. Field Protocol

The 2008 field protocol is available electronically on the data CD.