Integrated hydro-bacterial modelling for predicting bathing water quality

Huang, Guoxian, Falconer, Roger A. ORCID: https://orcid.org/0000-0001-5960-2864 and Lin, Binliang ORCID: https://orcid.org/0000-0001-8622-5822 2017. Integrated hydro-bacterial modelling for predicting bathing water quality. Estuarine, Coastal and Shelf Science 188 , pp. 145-155. 10.1016/j.ecss.2017.01.018

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (3MB) | Preview

Abstract

In recent years health risks associated with the non-compliance of bathing water quality have received increasing worldwide attention. However, it is particularly challenging to establish the source of any non-compliance, due to the complex nature of the source of faecal indicator organisms, and the fate and delivery processes and scarcity of field measured data in many catchments and estuaries. In the current study an integrated hydro-bacterial model, linking a catchment, 1-D model and 2-D model were integrated to simulate the adsorption-desorption processes of faecal bacteria to and from sediment particles in river, estuarine and coastal waters, respectively. The model was then validated using hydrodynamic, sediment and faecal bacteria concentration data, measured in 2012, in the Ribble river and estuary, and along the Fylde coast, UK. Particular emphasis has been placed on the mechanism of faecal bacteria transport and decay through the deposition and resuspension of suspended sediments. The results showed that by coupling the E.coli concentration with the sediment transport processes, the accuracy of the predicted E.coli levels was improved. A series of scenario runs were then carried out to investigate the impacts of different management scenarios on the E.coli concentration levels in the coastal bathing water sites around Liverpool Bay, UK. The model results show that the level of compliance with the new EU bathing water standards can be improved significantly by extending outfalls and/or reducing urban sources by typically 50%.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords:	Cloud to coast (C2C); Computational hydraulics; Faecal indicator organisms; Health impact assessment; Sediment transport; Water quality
Additional Information:	This is an open access article under the terms of the CC-BY Attribution 4.0 International license.
Publisher:	Elsevier
ISSN:	0272-7714
Funders:	Natural Environment Research Council
Date of First Compliant Deposit:	18 February 2017
Date of Acceptance:	13 January 2017
Last Modified:	19 Nov 2023 15:56
URI:	https://orca.cardiff.ac.uk/id/eprint/98380

Citation Data

Cited 22 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item