Leveraging High-Resolution LiDAR and Stream Geomorphic Assessment Datasets to Expand Regional Hydraulic Geometry Curves for Vermont
-
2021-09-30
-
Details
-
Creators:
-
Corporate Creators:
-
Corporate Contributors:
-
Subject/TRT Terms:
-
Resource Type:
-
Geographical Coverage:
-
Edition:Final Report
-
Corporate Publisher:
-
Abstract:In the two decades since Regional Hydraulic Geometry Curves (RHGCs) were first developed for Vermont streams, new remote-sensing data have been generated including digital elevation models derived from Light Detection and Ranging (lidar) data, and stream geomorphic assessments have been completed for more than 2,300 miles of river. Availability of these new data sets represented a cost-effective opportunity to revisit the analysis to update RHGCs for Vermont rivers without the need to engage in resource-intensive field work. We sought to improve upon the RHGCs, by (1) expanding the number of observations, and (2) reducing the variability in the relationships between drainage area and each of the response variables, bankfull width, mean depth, and cross-sectional area. To do so, we leveraged stream geomorphic data collected from 2005 through present; as well as high-resolution lidar data for estimation of basin characteristics. With the addition of 10 new sites, RHGCs have been expanded to cover drainage areas up to 396 (from 194) square miles. Additionally, stratification of the curves by channel slope at a threshold of 0.1% has improved prediction of bankfull width as a function of drainage area. Use of updated curves to design more geomorphically-compatible bridges and culverts will lead to greater resilience and durability of these transportation structures during extreme flood events. Greater longevity of structures translates to improved benefit-cost ratios when the full life cycle of these structures is analyzed and compared to that of undersized structures. Geomorphically-compatible structures also have co-benefits of supporting aquatic and terrestrial organism passage objectives.
-
Format:
-
Funding:
-
Collection(s):
-
Main Document Checksum:urn:sha-512:9d3813a505872bbc5a366133e4181741590bdbf41d0fab9053709bc50b73bbbf9593f163d851547fb9cce6c11b64f157cc73f10c883f639e23d2fefbdde0b1f3
-
Download URL:
-
File Type: