Bedrock river width is an essential geometric parameter relevant to understanding flood hazards and gauging station rating curves, and is critical to stream power incision models and many other landscape evolution models. Obtaining bedrock river width measurements, however, typically requires extensive field campaigns that take place in rugged and steep topography where river access is often physically challenging. Although prior work has turned to measuring channel width from satellite imagery, these data present a snapshot in time, are typically limited to rivers ≥ 10–30 m wide due to the image resolution, and are physically restricted to areas devoid of vegetation. For these reasons, we are generally data limited, and the factors impacting bedrock channel width remain poorly understood. Due to these limitations, researchers often turn to assumptions of width‐scaling relationships with drainage area or discharge to estimate bedrock channel width. Here we present a new method of obtaining bedrock channel width at a desired river discharge through the incorporation of a high‐resolution bare‐earth digital elevation model (DEM) using MATLAB Topotoolbox and the HEC‐RAS river analysis system. We validate this method by comparing modeled results to US Geological Survey (USGS) field measurements at existing gauging stations, as well as field channel measurements. We show that this method can capture general characteristics of discharge rating curves and predict field‐measured channel widths within uncertainty. As high‐resolution DEMs become more available across the United States through the USGS three‐dimensional elevation program (3DEP), the future utility of this method is notable. Through developing and validating a streamlined, open‐source, and freely available workflow of channel width extraction, we hope this method can be applied to future research to improve the quantity of channel width measurements and improve our understanding of bedrock channels.
High‐resolution digital elevation models (DEMs) have revolutionized research in geomorphology by allowing for detailed quantitative analysis of Earth's surface. Satellite stereo images offer the promise of expanding the availability of high‐resolution DEMs over broad areas, but rigorous evaluation of the scientific application of these datasets remains limited. In this study, we consider DEMs built using stereo pairs of high‐resolution (0.5 m) satellite imagery and the open‐source DEM extraction algorithm, Surface Extraction from TIN Space‐search Minimization (SETSM). We selected locations across a range of landscapes to evaluate the application of these DEMs to geomorphic problems, with particular attention to hillslope analyses where high spatial resolution has been shown to be important for revealing topographic signatures of tectonic and environmental processes. We compared the quality of SETSM 2 m DEMs to LiDAR‐derived DEMs and the widely available SRTM‐30 m and ALOS‐30 m DEMs by comparing the elevation data and derivative products (e.g., slope, aspect, and curvature). We found that SETSM DEMs performed noticeably better than SRTM and ALOS DEMs, but with systematic biases relative to LiDAR DEMs in regions with vegetation. Moreover, noise in the initial SETSM elevation data is amplified with every subsequent derivative, significantly decreasing quality. Finally, we evaluated the potential use of SETSM products for change detection. Applying DEM differencing to a major landslide, we found volume and sediment thickness from SETSM DEMs were similar to volumes and thicknesses from other studies. This example illustrates the capabilities of SETSM and other satellite‐based stereo‐photogrammetry for contributing to rapid response after natural disasters. Overall, we conclude that DEMs derived from satellite image stereo‐photogrammetry can markedly improve on lower resolution global elevation data for terrain analysis and can open possibilities for change detection, but that care needs to be taken in their application especially in regions with significant vegetation.
more » « less- NSF-PAR ID:
- 10363955
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Earth Surface Processes and Landforms
- Volume:
- 47
- Issue:
- 3
- ISSN:
- 0197-9337
- Page Range / eLocation ID:
- p. 706-722
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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