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

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Damian Sharp
5 years ago
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1 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. 1

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3 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. 3

4 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 4

5 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? 5

6 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 6

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8 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 8

9 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 9

10 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. 10

11 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. 11

12 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 12

13 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 13

14 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) 14

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16 The sediment generated on road segments is routed to drain points shown as brown circles 16

17 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 17

18 2.1 thousand tons of road sediment delivered per year in SF Payette 18

19 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. 19

20 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. 20

21 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 21

22 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 22

23 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. 23

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.

24 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 24

25 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 25

26 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 26

27 Variation in production between HUCS due to road density 27

28 Delivery based on land types No relationship i.e. landtypes are a poor predictor in this environment 28

29 GRAIP predicts 5 times more delivery. More variation between models at watershed scale due to generalized delivery estimates in BOISED 29

30 There is not similarity in the SDRs and they vary widely between basins 30

31 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. 31

32 If the goal is monitoring watershed condition or prioritization of projects, it is important to know the road hydrology 32

33 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. 33

34 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

35 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. 35

36 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. 36

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$We can screen by total sediment delivery of each type of road drainage structure or the fractional delivery.$

38 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. 38

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

39 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 39

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Hungry Creek Watershed Road Maintenance and Stony Quarry Development

Notice of Proposed Action Opportunity to Provide Scoping Comments Hungry Creek Watershed Road Maintenance and Stony Quarry Development Mt. Hough Ranger District Plumas National Forest Plumas County, California