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Fundamental Hydraulics of Cross Sections in Natural Rivers: Preliminary Analysis of a Large Data Set of Acoustic Doppler Flow Measurements
Author(s) -
Bjerklie David M.,
Fulton John W.,
Dingman S. Lawrence,
Canova Michael G.,
Minear Justin T.,
Moramarco Tommaso
Publication year - 2020
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2019wr025986
Subject(s) - hydraulics , streamflow , acoustic doppler current profiler , data set , range (aeronautics) , hydrology (agriculture) , geological survey , scale (ratio) , set (abstract data type) , stage (stratigraphy) , flow (mathematics) , geology , environmental science , doppler effect , natural (archaeology) , current (fluid) , drainage basin , computer science , geotechnical engineering , geography , engineering , cartography , geophysics , paleontology , oceanography , physics , geometry , mathematics , astronomy , aerospace engineering , artificial intelligence , programming language
We have assembled a comprehensive and publicly accessible U.S. Geological Survey (USGS) streamflow measurement data set, called HYDRoSWOT, from a USGS National Water Information System archive of acoustic Doppler current profiler river discharge measurements collected from a wide range of rivers throughout the United States. The data set provides a wealth of information on the range of hydraulic characteristics of river cross sections in the United States. Preliminary exploration of the data set, filtered for quality control, indicates that rivers tend toward consistent and predictable forms as discharge increases. The ratio of maximum‐to‐mean depth is highly predictable and is remarkably consistent across all river sizes and discharges. Distributions of hydraulic characteristics provide a large‐scale perspective on the general hydraulic characteristics of rivers. The data set affords the opportunity to analyze hydraulic relations for individual rivers as a function of stage, geomorphic setting, and energy environments and, combined with additional information contained in this data set, might yield predictive relations that could help constrain and parameterize river hydraulic models.