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Discharge and nutrient uncertainty: implications for nutrient flux estimation in small streams

Discharge and nutrient uncertainty: implications for nutrient flux estimation in small streams
Discharge and nutrient uncertainty: implications for nutrient flux estimation in small streams
The measurement of discharge is fundamental in nutrient load estimation. Because of our ability to monitor discharge routinely, it is generally assumed that the associated uncertainty is low. This paper challenges this preconception, arguing that discharge uncertainty should be explicitly taken into account to produce robust statistical analyses. In many studies, paired discharge and chemical datasets are used to calculate ‘true’ loads and used as the benchmark to compare with other load estimates.

This paper uses two years of high frequency (daily and sub-hourly) discharge and nutrient concentration data (nitrate-N and total phosphorus (TP)) collected at four field sites as part of the Hampshire Avon Demonstration Test Catchment (DTC) programme. A framework for estimating observational nutrient load uncertainty was used which combined a flexible non-parametric approach to characterising discharge uncertainty, with error modelling that allowed the incorporation of errors which were heteroscedastic and temporally correlated.

The results showed that the stage–discharge relationships were non-stationary, and observational uncertainties from ±2 to 25% were recorded when the velocity–area method was used. The variability in nutrient load estimates ranged from 1.1 to 9.9% for nitrate-N and from 3.3 to 10% for TP when daily laboratory data were used, rising to a maximum of 9% for nitrate-N and 83% for TP when the sensor data were used. However, the sensor data provided a better representation of the ‘true’ load as storm events are better represented temporally, posing the question: is it more beneficial to have high frequency, lower precision data or lower frequency but higher precision data streams to estimate nutrient flux responses in headwater catchments?
1099-1085
135-152
Lloyd, C. E. M.
55b165eb-f156-42b4-9ef5-b84881a640ed
Freer, J. E.
338b5dd6-83a7-43a3-901d-d8ed2b00233b
Johnes, P. J.
dd7c0c67-9deb-45bd-80e9-2362f5fb2294
Coxon, G.
9fa1fd97-47cc-4949-b66e-2757184c3194
Collins, A. L.
0ab4072f-a112-48e5-9625-1d229aa63660
Lloyd, C. E. M.
55b165eb-f156-42b4-9ef5-b84881a640ed
Freer, J. E.
338b5dd6-83a7-43a3-901d-d8ed2b00233b
Johnes, P. J.
dd7c0c67-9deb-45bd-80e9-2362f5fb2294
Coxon, G.
9fa1fd97-47cc-4949-b66e-2757184c3194
Collins, A. L.
0ab4072f-a112-48e5-9625-1d229aa63660

Lloyd, C. E. M., Freer, J. E., Johnes, P. J., Coxon, G. and Collins, A. L. (2015) Discharge and nutrient uncertainty: implications for nutrient flux estimation in small streams. Hydrological Processes, 30 (1), 135-152. (doi:10.1002/hyp.10574).

Record type: Article

Abstract

The measurement of discharge is fundamental in nutrient load estimation. Because of our ability to monitor discharge routinely, it is generally assumed that the associated uncertainty is low. This paper challenges this preconception, arguing that discharge uncertainty should be explicitly taken into account to produce robust statistical analyses. In many studies, paired discharge and chemical datasets are used to calculate ‘true’ loads and used as the benchmark to compare with other load estimates.

This paper uses two years of high frequency (daily and sub-hourly) discharge and nutrient concentration data (nitrate-N and total phosphorus (TP)) collected at four field sites as part of the Hampshire Avon Demonstration Test Catchment (DTC) programme. A framework for estimating observational nutrient load uncertainty was used which combined a flexible non-parametric approach to characterising discharge uncertainty, with error modelling that allowed the incorporation of errors which were heteroscedastic and temporally correlated.

The results showed that the stage–discharge relationships were non-stationary, and observational uncertainties from ±2 to 25% were recorded when the velocity–area method was used. The variability in nutrient load estimates ranged from 1.1 to 9.9% for nitrate-N and from 3.3 to 10% for TP when daily laboratory data were used, rising to a maximum of 9% for nitrate-N and 83% for TP when the sensor data were used. However, the sensor data provided a better representation of the ‘true’ load as storm events are better represented temporally, posing the question: is it more beneficial to have high frequency, lower precision data or lower frequency but higher precision data streams to estimate nutrient flux responses in headwater catchments?

Full text not available from this repository.

More information

Published date: 29 July 2015
Organisations: Geography & Environment

Identifiers

Local EPrints ID: 389591
URI: https://eprints.soton.ac.uk/id/eprint/389591
ISSN: 1099-1085
PURE UUID: 169ba371-5815-4579-ab73-30b686f50cba

Catalogue record

Date deposited: 09 Mar 2016 12:57
Last modified: 15 Jul 2019 20:42

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