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The GRAIP model is a product of work we have been doing on roads for a number

of years in Oregon and Idaho. We have had help with the GIS tools from Dave and

Ajay at Utah State. The Boise NF contributed to this effort by collecting the dataset

for SFP. The EPA supported the data collection in SF Payette.

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Roads have a variety of impacts both acute and chronic on the land including

sediment production and delivery, mass wasting, stream crossing failure, habitat

fragmentation and cumulative effects.

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With 383,000 miles of roads on FS there are many decisions to be made.

Closing and decomissioning, Maintenance Upgrade

Repair and Urgency and Priority Where and when to spend limited resources

How do we make decisions – what is the information needed to make good

decisions

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Information Needed to make informed decisions about where to focus efforts

Whether assesing watershed condition, Cumulative Effects, Treatment/BMP

effectiveness

---How do we get that information?

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The GRAIP package includes the entire process from data collection to analysis and

mapping

2 person crew

Sub-meter GPS unit

Vehicle

Laptop and software

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A road inventory is conducted using GPS to locate drain points and road segments

A data dictionary queries the crew on road attributes and

drain point conditions

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This image outline the hydrology of the road as it interacts with the channel network

Each road segment has two potential flow paths, and drain numbers

Each drain point such as this culvert, has a drain number that is used to route water

and sediment from the road to the drain

We use two person crew, one to drive and one to run up and down the slope

collecting data. The progress of the inventory varies from 2-5 miles per day

depending on the drivability and condition of the road and the hydrologic connection

with the stream. Recent large watershed efforts using trained crews to collect data

on all sorts of open and closed roads have averaged 2.5 miles per day. The cost for

this type of study has averaged about $200/road mile. With most of the cost being

salary, travel and vehicle expenses.

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We have applied GRAIP widely across the Northwest. Since 2008 we have been

using the tool tomonitore a large number of road treatment projects (46) throughout

Regions 1, 4, 5, and 6.

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GRAIP begins with a preprocessing tool that checks the data for errors and

populates a database.

Once the data are imported to GIS GRAIP works as a set of drop downs in Arc Map.

First sediment production is calculated

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Sediment production is calculated using a base rate modified by a series of local

factors from the inventory

Zena Creek data from Megahan was used for a base rate for this work

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The following examples were taken from a survey of the SF Payette in Idaho, NE of

Boise. 450 miles of road were inventoried. MG=tons

This figure shows areas of high sed production(=road surface erosion)

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The sediment generated on road segments is routed to drain points shown as

brown circles

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The delivery is recorded at each drain point in the field.

Contributing sediment is routed downslope and accumulated in the receiving

channel segment shown in color

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2.1 thousand tons of road sediment delivered per year in SF Payette

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This map illustrates areas of high local sediment delivery to channels and should

highlight areas of impact.

Undisturbed basins in this area transport 10 tons/km2/year over several years as

measured by Megahan in the South Fork of the Salmon River.

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Drain point condition is evaluated to asses function and maintenance needs. Of the

7165 drain points asses in the SF Payette 13% needed help and 2% needed

replacement.

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The next module is mass wasting and associated analyses

SI is the stability index of Pack and Tarbotton, similar to SHALSTAB based on

infinite slope model

ESI is the erosion stability index

Stream crossing failure index

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First the hillslope SI is calculated without roads to show if roads were build on

places that would fail

Then the contributing area of the roads is added at the drain point to calculate the

additional risk

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The ESI predicts the risk of gullying below a drain point.

Plot of all the drain points in a subbasin in green. The red points have gullies. The

ESI lines were picked to divide the drain points into quarters. Points with an ESI >8

have a 25% probability of having a gully.

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These maps show 3 levels of road detail

Danny Lee observed the relationship between road density and aquatic habitat

degradation on a broad scale in the Columbia River Basin.

Many of our existing tools – E.G. R1/R4 or ECA/ERA, SEDMODL models rely on

line coverages – where are roads and how many, requiring assumptions about

delivery.

Substantial recent science says that how roads affect the environment depends

largely on where they discharge water and sediment at drain points

Until now, no tools took advantage of such data if they were available, GRAIP is

design to do that

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Other available tools such as BOISED, R1R4 and SedModL use existing road data

only, must make assumptions about sediment delivery.

Methods such as Roads Analysis assuming relationships between road location and

impacts require local validation.

GRAIP gives a snapshot of the current condition of the roads, shows where the

problems actually are, allows for prioritizatopn based on various risk factors,

monitoring over time

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BOISED is a tool commonly used in the Rocky Mtn region. Sediment production is

from base rates, slope classes, geologic types and delivery based on land types

BOISED predicts 48% of GRAIP production due primarily to slope class based

calculations

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Variation in production between HUCS due to road density

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Delivery based on land types No relationship i.e. landtypes are a poor predictor in

this environment

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GRAIP predicts 5 times more delivery. More variation between models at

watershed scale due to generalized delivery estimates in BOISED

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There is not similarity in the SDRs and they vary widely between basins

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Another common method of estimating road impacts is using density as a proxy for

road impacts. There is a great deal of scatter in the road density to sediment

delivery relationship that can be explained by finer scale inspection.

BOISED, SedModL, road density may get the trend right because more road miles,

stream crossings etc will yield more sediment but until you know something about

the connectivity and the length and slope of flow paths on roads it is hard to get the

delivery right.

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If the goal is monitoring watershed condition or prioritization of projects, it is

important to know the road hydrology

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How did the existing metrics work to predict gullies? Distance from stream did not

predict effectively as there is not a good relationship with distance.

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If contributing area were the main driver for gullies, low slope position would contain

the most gullies. Slope position discriminated better than distance from channel,

although gullies were not common in the lower slope position as was noted in

Bisson 1999

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Each slope bin contains approximately equal numbers of drain points. Local slope

has the expected relationship with gullies at the low and high end, but does not

discriminate well in the 15-55% range where we need to differentiate most. This

suggests that it is important to know how much water is contributing to these points

in addition to slope.

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ESI is the tool we have selected to asses risk of gullying. ESIt provides a

reasonable threshold value at which gullying becomes a high risk.

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GRAIP is a useful for assessing BMP effectiveness. We can screen by total

sediment delivery of each type of road drainage structure or the fractional delivery.

In this case BBDs were the superior drain type with only 2% delivering sediment to

the channel.

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The hydrologic impacts of roads are varied and diverse and analyzing them can be

challenging without the proper tools

Knowing where the water is moving on the road and assessing the delivery allow for

better predictions of road impacts.

The data collection can take time at 2-5 miles per day, but it is warranted in many

areas where good delivery estimates are required and where high value aquatic

resources and endangered species are at risk.

GRAIP provides fine sediment production and delivery predictions,

Mass wasting risk analysis

Surface erosion risk analysis

Habitat fragmentation maps

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