Geospatial and field-based methods for predicting and quantifying stream bank erosion

Poster 174 – Click on poster below to view presentation from author.

Click on poster to view presentation from author.

Layla El-Khoury

North Carolina State University

Co-Authors: Barbara Doll, Jack Kurki-Fox, Melanie Carter

Streambank erosion can be the most significant source of in-stream sediment loads contributing between 17 to 92% of the total load. Often restoration groups seek to direct restoration efforts to streams with the greatest potential for reduction of downstream sediment loads. Similarly, many cities want to allocate stormwater fees towards stream restoration efforts intended to reduce the impacts of erosion to downstream reservoirs, public utilities and private property. Prioritizing streams for restoration often require survey and assessment of hundreds of miles of streams to identify the best suited locations for restoration. Developing a systematic, efficient approach that maximizes desk-top geospatial tools for identifying problem areas that can reduce effort and maximize their limited resources is essential. A potential desktop geospatial procedure for identifying eroding streambanks is the USGS’s recently developed ‘positive openness’ raster dataset for North Carolina which identifies the locations of concave surfaces using high-resolution topographic data to calculate relief angles. Validation of the tool’s ability to identify eroding and unstable streams in urban/suburban watersheds is needed as tree cover and structures may affect surface angle measurements. Erosion rates and volumes can be quantified by time-series analysis of aerial imagery, repeated physical measures of stream geometry, and comparison of LiDAR surveys. These tools for predicting and measuring erosion have not been tested or compared to see if they yield similar results. While the BEHI method is widely applied, validation by comparing the predictions to measured erosion rates has been limited. Preliminary study results will be presented examining if BEHI and NBS predict future erosion rates or capture past events, if positive openness can accurately identify eroding streams and comparing methods to quantify erosion rates.

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All posts are publicly visible after review by site administrator. Students’ responses to posted questions is factored into scoring for the poster competition. Finalists announced May 25 and awards presented May 26, 2021.

2 thoughts on “Geospatial and field-based methods for predicting and quantifying stream bank erosion

  1. Hi Layla, this is very important work. I wonder if you could comment on the relationship between this research and stream restoration. Are you planning to evaluate the effect of restoration on erosion? If so, what would you expect to see?

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  2. Hi Mauricio,
    Thank you for sharing your interest in this work! Right now with the scope of my project and thesis I am not planning to evaluate the effect of restoration on erosion though I do think that would be a really interesting extension to this work that would be worth evaluating. For the sites in Virginia, the goal is to use the predicted and measured erosion rates to provide an estimate for the sediment load at each site and also an associated nutrient load since we also took soil samples at the cross sections. NRCS and Virginia Tech Conservation Management Institute will use sediment loads to help select which sites would benefit the most from restoration (which sites would hopefully have the largest reduction of instream sediment loads if they were restored) and inform restoration designs. The Bank Erosion Hazard Index (BEHI) is meant to show erosion potential so if it were applied to a restored stream, ideally all of the BEHI scores would be in the low or very low range. It is harder to apply BEHI on stable stream sections than on eroding ones especially with the root density percentage. It would be interesting to see if BEHI could be used as a reliable measure to evaluate the effect of restoration on erosion.
    As for the Mine Creek watershed study, the goal is to use the positive openness tool prior to restoration. It would be fascinating for a longer term study to be done with the positive openness layer to see if changes were seen in the layer at sites that were restored compared to those that were not. Currently I am not sure if the layer would be able to accurately reflect changes where there was restoration. A few of the sites we had randomly selected had been repaired/restored but still showed a signal on the map indicating there were incised/eroding. That is in part to the layer’s resolution which is 3 m (though USGS is working on refining it to a 1 m resolution). With a smaller resolution, the layer is less likely to pick up on previously incised channels that have been restored.

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