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Instream Geomorphic Units via GUT Analysis
Asotin Watershed, WA
AsotinWatershedMap.jpg

For the following exercise, we examine the North Fork Asotin Creek in the Asotin Watershed in Southeast Washington. The North Fork Asotin Creek is located near the center of the Asotin Watershed and is a moderately sinuous 3rd order stream. Using the GUT program (http://gut.riverscapes.xyz/) we will compare the outputs of in-channel geomorphic units for a relatively devoid reach and a relatively complex reach. 

2. North Fork Asotin F4

2.1 This reach is generally structureless. It is a straight, single channel with with large areas of featureless flat runs. 

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2.2 I am comparing year 2011 and 2015. Since the channel has little structure, it probably doesn't change much year to year so I want to give multiple years of development for the comparison.

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2.3 Similar Tier 2 units are present, such as the channel being dominated by troughs and planar features running down the center of the channel. However, the features of the 2015 survey are much more connected than lengthwise down the stream.

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Question2.3.png

2.4 This reach is dominated through time by concave and planar features. Troughs, bowl transitions and planes are common in both years.

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2.5 As with the Tier 2 units, the reach is dominated by flat Tier 3 units. A glide-run vastly outweighs any other type of in channel unit.

Question2.5.png

2.6 Yes, geomorphic units are in reasonable locations in the channel. A pool precedes the riffle and are oriented along where a thalweg might be located. Margin bars seem to be opposite pools.

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2.7 GUT seems to be doing fairly well at classifying the units. There are some areas where there are both "pools" and "pocket pools" of the same size and in similar positions along the channel, so maybe GUT is having a hard time differentiating the two. As far as the overall trends of the channel units and types of units that would be present in the channel, it seems like GUT is succeeding.

2.7A Pool

     GU Forcing: By Bar/Structure

     GU Orientation: Streamwise

     GU Position: Bank/Side of channel

     Low Flow WS Slope: Flat

     Low Flow Relative Roughness: Low

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     Bar-Forced Pool

          As determined by the GU forcing from the bar

     GUT does not classify pools into what is creating

          them, so while it did identify the pool, it did 

          not identify that it was bar-forced.

2.7B Bar

     GU Forcing: Not forced

     GU Orientation: Streamwise

     GU Position: Bank

     Low Flow WS Slope: Shallow

     Low Flow Relative Roughness: Moderate

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     Eddy Pool

          As determined by the bank-attached location

          and forced shape

     GUT just classifies this as a margin-attached bar,

          and does not go into further refinement of what

          type of margin-attached bar.

2.7B Planar

     GU Forcing: Not forced

     GU Orientation: Streamwise

     GU Position: Mid-channel

     Low Flow WS Slope: Shallow

     Low Flow Relative Roughness: Low

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     Glide

          As determined by the low relative roughness

     GUT groups glides and runs into one category,

          and with the given data this is a fair assumption.

          In order to identify it specifically as a Glide, I

          had to guess at the low relative roughness.

27Pool.PNG
27Pool.PNG
27Flat.PNG

2.8 

     A: Based on the topo lines, this is a pool. From the bar structure next to it, it is a Bar-forced pool.

 

     B: I included the smaller concavity upstream of the larger pool all as one large pool. GUT

     separated the two and called the smaller one a rapid. 

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     C: GUT classified part of what I considered a pool as a rapid. From the steep gradient, it makes

     sense why GUT classified it as a rapid, but it would make more sense to include it as part of the

     pool. 

28PoolAnnotated.jpg
28PoolGUT.PNG
Tier3Legend.PNG

3.1 This reach has much more complexity. It is more sinuous, has a much larger range of geomorphic units, and has convexities in the middle of the channel rather than limited to the sides.

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3.2 I will be comparing 2011 to 2012 for this reach. Based on the greater structural complexity, I assume there will be more changes from year to year in channel structure than in a structurally devoid channel.

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3.3 The layout of this reach changes much more than the previous structureless reach, despite less time between the compared years. General trends are convexities along the edges and concavities near the center/where the thalweg would be.

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Question3.3.png

3.4 No Tier 2 form is dominant in this reach, and the reach remains complex through time.

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3.5 As with the Tier 2 units, there is a larger variety of Tier 3 units present in each year. Between years there are mid channel bars and margin attached bars in the same general location, but their exact extents change. The lowest point in the reach also gets much more complex in 2012.

Question3.5.png

3.6 Yes, geomorphic units are in reasonable locations in the channel. Bars seem to occur on inside bends and pools opposite of the bars. Units are elongate in the direction of the thalweg/flow.

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3.7 GUT seems to be doing fairly well at classifying the units. There are occasional units that do not make sense, such as mid-channel bars being present on the sides of the channel, or small pockets of rapids where it is unlikely rapids would develop. But the general distribution of bars and pools seems to be logical.

3.7A Pool

     GU Forcing: Channel Bend/Bar

     GU Orientation: Streamwise

     GU Position: Mid/Side

     Low Flow WS Slope: Low

     Low Flow Relative Roughness: Low

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     Bar-Forced Pool

          As determined by the GU forcing from the bar

     GUT does not classify pools into what is creating

          them, so while it did identify the pool, it did 

          not identify that it was bar-forced.

3.7B Bar

     GU Forcing: By planform

     GU Orientation: Streamwise

     GU Position: Bank-attached

     Low Flow WS Slope: Moderate

     Low Flow Relative Roughness: Moderate

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     Point Bar

          As determined by the Planform GU forcing

     GUT only goes down to classifying the bars as

          margin-attached, so while it is correct, refining

          further to Point bar has to be manually done.

37Pool.PNG
37Bar.PNG

3.7B Plane

     GU Forcing: By flow width

     GU Orientation: Streamwise

     GU Position: Channel spanning

     Low Flow WS Slope: Shallow/Moderate

     Low Flow Relative Roughness: Moderate

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     Run or Rapid

          As determined by the GU position and slope

     Here, without being able to refine the WS Slope

          and Roughness in person, GUT does as good

          of a job of classifying as I can do

37Flat.PNG

3.8 

     A: Based on the topo lines, there is either a chute cutoff or an eddy bar.

 

     B: The area I included for the bar being cut off by the chute cutoff is much bigger than what GUT

     classified it as.

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     C: As with the previous examples, my classifications have more modifying terms attached to

     them. GUT fills in a lot of space with glide-run or riffle classifications rather than pinpointing

     where the chute cutoff occurs or the riffle crest occurs.

38unitsAnnotated.jpg
38unitsGUT.PNG
Tier3Legend.PNG

4.1 GUT places much of the channel into the trough/bowl/concave category at the Tier 2 scale. While this is technically accurate, I might classify some of these areas as planar from a field study. The general shape of a channel is a trough, so I would be more lenient on the cutoff between a planar feature and a convex feature. GUT seems to do fairly well delineating the convex features.

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4.2 It seems that GUT groups a lot of mid channel features into the Glide-Run category. GUT also does not account for channel constrictions or channel widening, a common attribute we would use in the field. Since GUT is based on the topography/channel bed surface, it does not consider water surface slope or roughness in its classification. Overall, it seems that GUT is and effective way to get an approximate layout of the whole reach, but if it is necessary to pinpoint individual features, a field study is still necessary.

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4.3 Some Tier 4 attributes could be assigned. An estimate of the Tier 4 vegetation could be made from landcover data, but attributes such as grain size would have to be identified in field. The vegetation classification would likely have a large amount of error depending on the landcover raster resolution.

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4.4 Desktop mapping through topography is efficient and accurate enough for wider scope studies. When comparing reaches such as what we were doing in this exercise, the units area plenty refined to draw conclusions about the health of each reach. However, if you were doing a study to determine which bars need to be excavated, etc. you would want to do a field visit and manually refine the GUT boundaries further. 

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