Modeling Streamflow and Sediment Loads with a Photogrammetrically Derived UAS Digital Terrain Model: Empirical Evaluation from a Fluvial Aggregate Excavation Operation

Soil erosion monitoring is a pivotal exercise at macro through micro landscape levels, which directly informs environmental management diverse spatial and temporal scales. The of soil can be an arduous task when completed ground-based surveys there are uncertainties associated with the use large-scale medium resolution image-based digital elevation models for estimating rates. LiDAR derived have proven effective in modeling erosion, but such data proves costly to obtain, process, analyze. proliferation images other geospatial datasets generated by unmanned aerial systems (UAS) increasingly able reveal additional nuances that traditional were not obtain due former’s higher resolution. This study evaluated efficacy UAS terrain model (DTM) estimate surface flow sediment loading fluvial aggregate excavation operation Waukesha County, Wisconsin. A nested scale distributed hydrologic was constructed point cloud DTM. To evaluate effectiveness DTM, DTM used comparison consonance several statistical measures efficiency. Results demonstrate estimation across space absence LiDAR-based