Abstract

This case study describes an economically feasible approach to generate synthetic rating curves that enhance utility of stage-only river gauges. The study is based on a network of 250 bridge-mounted river-stage sensors (BMRSS) that the Iowa Flood Center has deployed in Iowa. The authors investigated using the step-backwater model with the Hydrologic Engineer Center’s River Analysis System (HEC-RAS) to develop a stage-discharge relationship. The authors installed BMRSS at eight sites collocated with USGS gauging stations with well-established stage-discharge ratings to serve as reference. They also surveyed the channel cross sections in the upstream and downstream vicinity of the sensor locations. To account for uncertainty of channel roughness and free surface slope, they ran the model using a Monte Carlo simulation. The resulting rating curve realizations were compared with the USGS reference. The study reports the distribution of relative errors in the synthetic curve estimates, conditioned on the value of discharge. The results show average discharge errors of less than 5% for flows within the main channel banks and less than 3% in the floodplain. The average stage error is 0.43 m (range of 0.2–0.9 m). The authors also explored the error induced by using airborne light detection and ranging (LiDAR)-based topographic surveys for the cross-sectional geometry. They assessed the model-based methodology at an additional 19 locations where USGS maintains rating curves and concluded that the results were inferior compared with those obtained using conventional geodetic surveys. The study provides a basis for expanded monitoring of streams and rivers with stage-only sensors.

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Data Availability Statement

Some or all data, models, and code generated or used during the study are available from the corresponding author upon request.

Acknowledgments

The authors would like to acknowledge the invaluable assistance of partners including the Iowa Silver Jackets program, the US Army Corp of Engineers (USACE), the National Weather Service (NWS), the Iowa Department of Natural Resources (IDNR), and the US Geological Survey (USGS), especially Jon Nania, who helped improve this paper.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 26Issue 1January 2021

History

Received: Dec 27, 2019
Accepted: Aug 4, 2020
Published online: Oct 31, 2020
Published in print: Jan 1, 2021
Discussion open until: Mar 31, 2021

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Research Scientist, Iowa Institute for Hydraulic Research—Hydroscience and Engineering, Univ. of Iowa, 100 C. Maxwell Stanley Hydraulics Lab, Iowa City, IA 52242 (corresponding author). ORCID: https://orcid.org/0000-0001-9517-4895. Email: [email protected]
Marcela Rojas
Engineer, Iowa Institute for Hydraulic Research—Hydroscience and Engineering, Univ. of Iowa, Iowa City, IA 52242.
Marian Muste
Research Engineer, Iowa Institute for Hydraulic Research—Hydroscience and Engineering, Univ. of Iowa, Iowa City, IA 52242.
Witold F. Krajewski
Professor, Iowa Institute for Hydraulic Research—Hydroscience and Engineering, Univ. of Iowa, Iowa City, IA 52242.
Gabriel Perez
Research Assistant, Iowa Institute for Hydraulic Research—Hydroscience and Engineering, Univ. of Iowa, Iowa City, IA 52242.
Shirley Johnson
Hydrologist, US Army Corps of Engineers, 1500 Rock Island Dr., Rock Island, IL 61201.
Hydrologist, US Army Corps of Engineers, 1500 Rock Island Dr., Rock Island, IL 61201. ORCID: https://orcid.org/0000-0001-7069-3963
Toby Hunemuller
Chief Hydrology Section, US Army Corps of Engineers, 1500 Rock Island Dr., Rock Island, IL 61201.
Bill Cappuccio
Flood Plain Management Engineer, Iowa Dept. of Natural Resources, 502 E. 9th St., Des Moines, IA 50319.
Senior Service Hydrologist, National Weather Service, 9607 NW Beaver Dr., Johnston, IA 50131. ORCID: https://orcid.org/0000-0001-8094-739X

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