Disciplines

Fresh Water Studies | Geographic Information Sciences | Geomorphology | Spatial Science

Abstract (300 words maximum)

River cross-sections are often extracted using field surveys at measured intervals. This field-oriented approach allows for a tangible relationship 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, extracted, and even analyzed with contemporary Geographic Information Systems (GIS) in a completely virtual setting, transcending the need for fieldwork 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) of the stream from the National Science Foundation's OpenTopography online database. The resulting file 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. From the upstream direction, 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 to Microsoft Excel for analysis. 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 generated in this manner is highly effective for freshwater management and research applications such as channel morphology.

Academic department under which the project should be listed

RCHSS - Geography & Anthropology

Primary Investigator (PI) Name

Dr. Ranbir Kang

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Generating Channel Morphology Data Through ArcGIS Pro

River cross-sections are often extracted using field surveys at measured intervals. This field-oriented approach allows for a tangible relationship 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, extracted, and even analyzed with contemporary Geographic Information Systems (GIS) in a completely virtual setting, transcending the need for fieldwork 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) of the stream from the National Science Foundation's OpenTopography online database. The resulting file 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. From the upstream direction, 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 to Microsoft Excel for analysis. 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 generated in this manner is highly effective for freshwater management and research applications such as channel morphology.