Integrated river and Coastal flow, sediment and Escherichia coli modelling for bathing water quality

Huang, Guoxian, Falconer, Roger Alexander ORCID: https://orcid.org/0000-0001-5960-2864 and Lin, Binliang ORCID: https://orcid.org/0000-0001-8622-5822 2015. Integrated river and Coastal flow, sediment and Escherichia coli modelling for bathing water quality. Water 7 (9) , pp. 4752-4777. 10.3390/w7094752

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Abstract

Due to the increasing economic and cultural value of bathing waters and the shellfish industry in the UK and worldwide, water quality in estuarine and coastal waters has attracted considerable public attention in recent years. To obtain accurate predictions of the concentration distributions of faecal indicator organisms (FIOs) in coastal waters for better management of bathing water compliance, it is necessary to build an integrated modelling system to predict the complete diffuse and point source inputs from river and catchment basins. In the present paper, details are given of the development of such an integrated modelling system for simulating the transport and decay processes of FIOs, from catchment areas upstream from the coastal region, in which a distributed catchment module, a 1D river network module and a 2D estuarine and coastal module are linked dynamically by boundary inputs and outputs. Extensive measured data from the catchments, river networks and estuaries have been collated to determine the model parameters. Verification results of the distribution of water levels, flows and velocities, and suspended sediment and Escherichia coli concentrations, at controlled monitoring sites are presented, which show that the integrated model predictions generally agree well with the measurements, although locally appreciable errors can occur. The model results also highlight the importance of including the flux of FIOs via sediments being an important factor in terms of assessing the quality of bathing waters. The main factors influencing the relatively high concentration values in the bathing region are analysed, based on the model predictions and measured data, with four categories of FIO concentration levels being reviewed.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Publisher:	MDPI
ISSN:	2073-4441
Funders:	NERC
Date of First Compliant Deposit:	30 March 2016
Date of Acceptance:	25 August 2015
Last Modified:	07 May 2023 10:44
URI:	https://orca.cardiff.ac.uk/id/eprint/76256

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