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GENERATING CHANNEL MORPHOLOGY DATA USING ArcGIS

Abstract

River cross sections are often extracted using field surveys at regular cross sections. This field-oriented approach allows for a tangible relationship to exist between the data and its collector but at the expense of finance, time, labor, and potentially the environment. With the advancement of geospatial tools, such data can be found online, be extracted, and even undergo analysis with contemporary Geographic Information Systems (GIS) in a completely virtual setting, transcending the need for field work in select project topics. We tested this approach with the help of ArcGIS Pro software on the Vishnu Springs headwater stream located in the Western Illinois region of the Upper Mississippi River Basin. The process first consisted of downloading a United States Geological Survey (USGS) digital elevation model (DEM) from the National Science Foundation's OpenTopography online database of our target stream. The resulting Tag Image Format file (.tif) was imported into ArcGIS Pro for geoprocessing, where the "Derive Stream As Line" tool within their Hydrology toolset generated an aligned line of the stream. The aligned streamline was then split into reaches at a uniform interval of 5 meters in the downstream direction. At the upstream end of each reach, stream cross sections were drawn perpendicular to each interval in the stream with a dedicated polyline feature layer. The "Interpolate Shape" from the 3D Analyst toolset was then utilized to produce profile graphs of each cross section, and these graphs were exported as a Joint Photographic Experts Group (.jpg) file for extraction of the channel morphology data. Using the horizontal and elevation values across each cross section, morphology data was extracted on bank full width, average bank full depth, thalweg, cross-section area, bank full width and thalweg ratio, and bank slope. Our method provided consistent cross-section data of our target stream, Vishnu Springs, with a high-spatial resolution in a more efficient process. The large amount of data that was generated in this manner is highly effective for freshwater management and research applications such as channel morphology. Therefore, our method makes an intellectual and applied contribution to fluvial geomorphology, river/freshwater science, ecological science, and other related disciplines. Future work should focus on applying this method to rivers in different eco-regions at different stream orders to promote consistent and efficient data collection and analysis.

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