Geospatial and Field-Based Methods for Predicting and Quantifying Stream Bank Erosion
Layla El-Khoury
MS Student
Biological & Agricultural Engineering Dept.
NC State University
Raleigh, North Carolina
Authors: Barbara Doll, NC State University, Jack Kurki-Fox, NC State University, Melanie Carter, Virginia Tech
Streambank erosion can be the most significant source of in-stream sediment loads [a] contributing between 17 to 92% of the total load [b]. The threatened Eastern Hellbender is one example of an aquatic species whose habitats are diminished by incised and eroded streams [c]. Restoring streams in addition to implementing conservation practices in the Ridge and Valley and Blue Ridge physiographic regions where the Eastern Hellbender lives, will revitalize their population. The Natural Resources Conservation Service Working Lands for Wildlife and Environmental Quality Incentives Program (EQIP) seeks to direct restoration efforts to streams with the greatest potential for reduction of downstream sediment loads in this region. Similarly, many cities and counties want to allocate water and 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 requires 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. Further, better-predicting erosion rates and identifying and verifying tools for quantifying streambank erosion volumes are needed. This study includes an evaluation and comparison of both desktop and field-based procedures for predicting, measuring, and quantifying erosion rates including US Geological Survey (USGS)’s recently developed ‘positive openness’ raster dataset [d], the Bank Assessment for Non-point Source Consequences of Sediment (BANCS) model, time-series analysis of aerial imagery, repeated physical measures of stream geometry, and comparison of LiDAR (Light Detection and Ranging) surveys [b].
This presentation will cover preliminary results of the Ridge and Valley and Blue Ridge Virginia and Mine Creek Positive Openness studies including validation of BANCs streambank erosion predictions using traditional cross-section monitoring and time series analysis of streambank movement using aerial photos, and use of the USGS positive openness raster dataset for predicting areas of streambank erosion. Potential improvements to overcome the limitations of BEHI will be discussed in relation to creating predictions of erosion rates.
Sources:
[a] Stott, T. 1997. A comparison of stream bank erosion processes on forested and moorland streams in the Balquhidder Catchments, central Scotland. Earth Surface Processes and Landforms 22(4): 383-399.
[b] Purvis, R. A. and G. A. Fox. 2016. Streambank sediment loading rates at the watershed scale and the benefit of riparian protection. Earth Surface Processes and Landforms 41(10): 1327-1336.
[c] Virginia DWR. 2020. Eastern Hellbender. Available at: https://dwr.virginia.gov/wildlife/information/eastern-hellbender/.
[d] Rowley, T.H., Hopkins, K.G., and Terziotti, S., 2018, Geomorphological Features of North Carolina: U.S. Geological Survey data release, https://doi.org/10.5066/P9PRAVAQ.
About Layla El-Khoury
Coming Soon