Integrated hydro-bacterial modelling for predicting bathing water quality

Guoxian Huang,Roger A Falconer,Binliang Lin

doi:10.1016/j.ecss.2017.01.018

Guoxian Huang, Roger A Falconer + Show 1 more

Open Access

https://doi.org/10.1016/j.ecss.2017.01.018

Copy DOI

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%.

Highlights

Bathing water quality is of increasing international concern, and public awareness of the impacts of poor bathing water quality on health risk has increased in recent years
The main differences between the sediment-E.coli interaction model and the clear water model are: (i) the decay rate in clear water is greater than that for water with sediments in suspension; (ii) the E.coli concentration reduction rate due to the net E.coli loss within the water column is an order of magnitude smaller than the reduction caused by dilution due to advection and diffusion (Pramod et al, 2010); and (iii) the time dependent transport and ConcentraƟon resuspension of sediment particles, which are associated with E.coli adsorption and desorption to the sediments, may further change the movement of E.coli
The integrated model includes the river network (RNM1D) model and the open source 2D/3D Environmental Fluid Dynamics Code (EFDC) model, in which the upper boundaries are specified from the results for two catchment models for rural regions and the Inforworks model for urban regions

Summary

Introduction

Bathing water quality is of increasing international concern, and public awareness of the impacts of poor bathing water quality on health risk has increased in recent years. Beach closures frequently occur due to the non-compliance of water quality to the required standards. In order to comply with the standards required by regulatory authorities world-wide, many bathing water quality improvement measures have been drawn up and many projects have been carried out worldwide to study noncompliance. Bathing water non-compliance is a complex problem, since it involves many aspects and processes (Huang et al, 2015b) including: catchment management (Byappanahalli et al, 2015), arrangements relating to the siting of sewage pipe networks and outfalls (Fan et al, 2015; Obiri-Danso and Jones, 1999), waste water treatment methods, weather conditions (Ackerman and Weisberg, 2003; Kashefipour et al, 2002), sediment suspension and transport (Gao et al, 2013), currents, waves, and sea birds and pets (Converse et al, 2012; Wither et al, 2005; Wright et al, 2009) etc. It is still unfeasible to track the sources of Faecal Indicator Organisms (FIOs) and predict the fate and transport of FIO processes (Boehm et al, 2002), based only on case-specific measured data with a low spatio-temporal resolution (de Brauwere et al, 2014b)

Methods

Results

Conclusion