Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Determining Feature Based Hydraulic Geometry and Rating Curves using a Physically Based, Computationally Efficient Framework

Version 1 : Received: 21 December 2022 / Approved: 21 December 2022 / Online: 21 December 2022 (06:59:11 CET)

How to cite: Johnson, J.M.; Coll, J.; Clarke, K.C.; Afshari, S.; Saksena, S.; Yeghiazarian, L. Determining Feature Based Hydraulic Geometry and Rating Curves using a Physically Based, Computationally Efficient Framework. Preprints 2022, 2022120390. https://doi.org/10.20944/preprints202212.0390.v1 Johnson, J.M.; Coll, J.; Clarke, K.C.; Afshari, S.; Saksena, S.; Yeghiazarian, L. Determining Feature Based Hydraulic Geometry and Rating Curves using a Physically Based, Computationally Efficient Framework. Preprints 2022, 2022120390. https://doi.org/10.20944/preprints202212.0390.v1

Abstract

Hydraulic relationships are important for water resource management, hazard prediction, and modelling. Since Leopold first identified power law expressions that could relate streamflow to top-width, depth, and velocity, hydrologists have been estimating ‘At-a-station Hydraulic Geometries’ (AHG) to describe average flow hydraulics. As the amount of data, data sources, and application needs increase, the ability to apply, integrate and compare disparate and often noisy data is critical for applications ranging from reach to continental scales. However, even with quality data, the standard practice of solving each AHG relationship independently can lead to solutions that fail to conserve mass. The challenge addressed here is how to extend the physical properties of the AHG relations, while improving the way they are hydrologically addressed and fit. We present a framework for minimizing error while ensuring mass conservation at reach - or hydrologic Feature - scale geometries’(FHG) that complies with current state-of-the-practice conceptual and logical models. Through this framework, FHG relations are fit for the United States Geological Survey’s (USGS) Rating Curve database, the USGS HYDRoacoustic dataset in support of the Surface Water Oceanographic Topography satellite mission (HYDRoSWOT), and the hydraulic property tables produced as part of the NOAA/Oakridge Continental Flood Inundation Mapping framework. The paper describes and demonstrates the accuracy, interoperability, and application of these relationships to flood modelling and presents this framework in an R package.

Keywords

hydraulic geometry; rating curves; flood mapping; accuracy; data acquisition; data needs

Subject

Environmental and Earth Sciences, Environmental Science

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