The application of high temporal resolution data in river catchment modelling and management strategies

Crockford, L. and O'Riordain, S. and Taylor, D. and Melland, A. R. and Shortle, G. and Jordan, P. (2017) The application of high temporal resolution data in river catchment modelling and management strategies. Environmental Monitoring and Assessment, 189 (9). ISSN 0167-6369


Modelling changes in river water quality, and by extension developing river management strategies, has historically been reliant on empirical data collected at relatively low temporal resolutions. With access to data collected at higher temporal resolutions, this study investigated how these new dataset types could be employed to assess the precision and accuracy of two phosphorus (P) load apportionment models (LAMs) developed on lower resolution empirical data. Predictions were made of point and diffuse sources of P across ten different sampling scenarios. Sampling resolution ranged from hourly to monthly through the use of 2000 newly created datasets from high frequency P and discharge data collected from a eutrophic river draining a 9.48 km2 catchment. Outputs from the two LAMs were found to differ significantly in the P load apportionment (51.4% versus 4.6% from point sources) with reducing precision and increasing bias as sampling frequency decreased. Residual analysis identified a large deviation from observed data at high flows. This deviation affected the apportionment of P from diffuse sources in particular. The study demonstrated the potential problems in developing empirical models such as LAMs based on temporally relatively poorly-resolved data (the level of resolution that is available for the majority of catchments). When these models are applied ad hoc and outside an expert modelling framework using extant datasets of lower resolution, interpretations of their outputs could potentially reduce the effectiveness of management decisions aimed at improving water quality.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version, in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Institute for Agriculture and the Environment
Date Deposited: 28 Feb 2018 00:47
Last Modified: 28 Feb 2018 05:38
Uncontrolled Keywords: agriculture, modelling, phosphorus, water quality, pollution, high frequency data
Fields of Research : 05 Environmental Sciences > 0502 Environmental Science and Management > 050206 Environmental Monitoring
Socio-Economic Objective: D Environment > 96 Environment > 9611 Physical and Chemical Conditions of Water > 961103 Physical and Chemical Conditions of Water in Fresh, Ground and Surface Water Environments (excl. Urban and Industrial Use)
Identification Number or DOI: 10.1007/s10661-017-6174-1

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