Skip to main content
ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Agroecosystems Management Research » Research » Publications at this Location » Publication #366089
Research Project: Agroecosystem Benefits from the Development and Application of New Management Technologies in Agricultural Watersheds

Location: Agroecosystems Management Research

Title: Automated measurement of eroding streambank volume from high-resolution aerial imagery and terrain analysis

Author
item WILLIAMS, FORREST - Iowa State University
item MOORE, PETER - Iowa State University
item ISENHART, THOMAS - Iowa State University
item Tomer, Mark

Submitted to: Geomorphology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/17/2020
Publication Date: 10/15/2020
Citation: Williams, F., Moore, P., Isenhart, T., Tomer, M. 2020. Automated measurement of eroding streambank volume from high-resolution aerial imagery and terrain analysis. Geomorphology. 367. Article e107313. https://doi.org/10.1016/j.geomorph.2020.107313.
DOI: https://doi.org/10.1016/j.geomorph.2020.107313

Interpretive Summary: Sediment is a common surface water impairment throughout the continental United States and beyond. Contributions of streambank erosion to sediment in streams and rivers are often significant, but often defy measurement. Manual analysis of aerial images and plot scale observations of streambank loss are important methods for tracking bank erosion, but are difficult to reproduce and apply to large watersheds. To estimate sediment loading across watersheds a new Aerial Imagery Migration Model (AIMM) has been devised to automate measurement of channel migration and estimate volumes of erosion and deposition related to that migration. Sediment is a common surface water impairment throughout the continental United States and beyond. Contributions of streambank erosion to sediment in streams and rivers are often significant, but often defy measurement. Manual analysis of aerial images and plot scale observations of streambank loss are important methods for tracking bank erosion, but are difficult to reproduce and apply to large watersheds. To estimate sediment loading across watersheds a new Aerial Imagery Migration Model (AIMM) has been devised to automate measurement of channel migration and estimate volumes of erosion and deposition related to that migration. The method delineates river channels from aerial photography, and compares channel locations between two time periods to map areas of erosion and deposition. Sediment volumes can then be calculated using a detailed elevation model. This model can be used to estimate volumes of sediment loss in a cost efficient way. In particular, the extent of bank erosion can now be mapped at the project-planning phase of conservation efforts could help focus bank stabilization efforts where the need is greatest. This technology will be of interest to conservation planners, watershed managers, and geologists who study stream movement.

Technical Abstract: Excessive concentrations of sediment are an important form of surface water impairment throughout the continental United States. Numerous studies have investigated the role of upland soil erosion as a Phosphorus and sediment source, but the contributions of streambank erosion are still poorly understood. River bank delineation based on visual inspection of aerial images is an important method for tracking bank erosion, but this method is not easily scaled to larger watersheds and is inherently difficult to reproduce. Additionally, remote-sensing based channel migration models often rely on satellite imagery, and are not optimized for use with high resolution aerial imagery. To estimate sediment loading on statewide scales, we have created the Aerial Imagery Migration Model (AIMM), a Python and ArcPy based automated channel migration model designed to estimate volumes of erosion and deposition related to channel migration via a three-step process. AIMM utilizes the Normalized Difference Water Index (NDWI) to derive binary representations of river channels from aerial photography, then the location of the channel is compared between two time periods to identify zones of erosion and deposition. The net volume loss related to channel migration is then calculated by using a LiDAR-derived DEM to derive estimates for the volume of erosional and depositional zones. Where public imagery is available, AIMM can be widely applied to estimate volumes of sediment loss in a time and cost efficient procedure. In particular, the use of AIMM within the project-planning phase of conservation efforts could help focus work in areas where it can have the highest impact.