A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations

Benchmarking the quality of river discharge data and understanding its information content for hydrological analyses is an important task for hydrologic science. There is a wide variety of techniques to assess discharge uncertainty. However, few studies have developed generalized approaches to quant...

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Main Authors:	Coxon, G., Freer, J., Westerberg, I. K., Wagener, T., Woods, R., Smith, P. J.
Format:	Online
Language:	English
Published:	John Wiley and Sons Inc. 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4755227/

id	pubmed-4755227
recordtype	oai_dc
spelling	pubmed-47552272016-02-25 A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations Coxon, G. Freer, J. Westerberg, I. K. Wagener, T. Woods, R. Smith, P. J. Research Articles Benchmarking the quality of river discharge data and understanding its information content for hydrological analyses is an important task for hydrologic science. There is a wide variety of techniques to assess discharge uncertainty. However, few studies have developed generalized approaches to quantify discharge uncertainty. This study presents a generalized framework for estimating discharge uncertainty at many gauging stations with different errors in the stage‐discharge relationship. The methodology utilizes a nonparametric LOWESS regression within a novel framework that accounts for uncertainty in the stage‐discharge measurements, scatter in the stage‐discharge data and multisection rating curves. The framework was applied to 500 gauging stations in England and Wales and we evaluated the magnitude of discharge uncertainty at low, mean and high flow points on the rating curve. The framework was shown to be robust, versatile and able to capture place‐specific uncertainties for a number of different examples. Our study revealed a wide range of discharge uncertainties (10–397% discharge uncertainty interval widths), but the majority of the gauging stations (over 80%) had mean and high flow uncertainty intervals of less than 40%. We identified some regional differences in the stage‐discharge relationships, however the results show that local conditions dominated in determining the magnitude of discharge uncertainty at a gauging station. This highlights the importance of estimating discharge uncertainty for each gauging station prior to using those data in hydrological analyses. John Wiley and Sons Inc. 2015-07-19 2015-07 /pmc/articles/PMC4755227/ /pubmed/26924859 http://dx.doi.org/10.1002/2014WR016532 Text en © 2015. The Authors. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Coxon, G. Freer, J. Westerberg, I. K. Wagener, T. Woods, R. Smith, P. J.
spellingShingle	Coxon, G. Freer, J. Westerberg, I. K. Wagener, T. Woods, R. Smith, P. J. A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations
author_facet	Coxon, G. Freer, J. Westerberg, I. K. Wagener, T. Woods, R. Smith, P. J.
author_sort	Coxon, G.
title	A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations
title_short	A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations
title_full	A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations
title_fullStr	A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations
title_full_unstemmed	A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations
title_sort	novel framework for discharge uncertainty quantification applied to 500 uk gauging stations
description	Benchmarking the quality of river discharge data and understanding its information content for hydrological analyses is an important task for hydrologic science. There is a wide variety of techniques to assess discharge uncertainty. However, few studies have developed generalized approaches to quantify discharge uncertainty. This study presents a generalized framework for estimating discharge uncertainty at many gauging stations with different errors in the stage‐discharge relationship. The methodology utilizes a nonparametric LOWESS regression within a novel framework that accounts for uncertainty in the stage‐discharge measurements, scatter in the stage‐discharge data and multisection rating curves. The framework was applied to 500 gauging stations in England and Wales and we evaluated the magnitude of discharge uncertainty at low, mean and high flow points on the rating curve. The framework was shown to be robust, versatile and able to capture place‐specific uncertainties for a number of different examples. Our study revealed a wide range of discharge uncertainties (10–397% discharge uncertainty interval widths), but the majority of the gauging stations (over 80%) had mean and high flow uncertainty intervals of less than 40%. We identified some regional differences in the stage‐discharge relationships, however the results show that local conditions dominated in determining the magnitude of discharge uncertainty at a gauging station. This highlights the importance of estimating discharge uncertainty for each gauging station prior to using those data in hydrological analyses.
publisher	John Wiley and Sons Inc.
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4755227/
_version_	1613539253788082176

A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations

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