Risk-based modelling of surface water quality: a case study of the Charles River, Massachusetts Neil R. McIntyre a, * , Thorsten Wagener b,1 , Howard S. Wheater a,2 , Steven C. Chapra c,3 a Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK b SAHRA Hydrology and Water Resources, Harshbarger Building, University of Arizona, Tucson, AZ 85721, USA c Department of Civil and Environmental Engineering, 113 Anderson Hall, Tufts University, Medford, MA 02155, USA Received 10 July 2002; revised 28 November 2002; accepted 6 December 2002 Abstract A model of phytoplankton, dissolved oxygen and nutrients is presented and applied to the Charles River, Massachusetts within a framework of Monte Carlo simulation. The model parameters are conditioned using data from eight sampling stations along a 40 km stretch of the Charles River, during a (supposed) steady-state period in the summer of 1996, and the conditioned model is evaluated using data from later in the same year. Regional multi-objective sensitivity analysis is used to identify the parameters and pollution sources most affecting the various model outputs under the conditions observed during that summer. The effects of Monte Carlo sampling error are included in this analysis, and the observations which have least contributed to model conditioning are indicated. It is shown that the sensitivity analysis can be used to speculate about the factors responsible for undesirable levels of eutrophication, and to speculate about the risk of failure of nutrient reduction interventions at a number of strategic control sections. The analysis indicates that phosphorus stripping at the CRPCD wastewater treatment plant on the Charles River would be a high-risk intervention, especially for controlling eutrophication at the control sections further downstream. However, as the risk reflects the perceived scope for model error, it can only be recommended that more resources are invested in data collection and model evaluation. Furthermore, as the risk is based solely on water quality criteria, rather than broader environmental and economic objectives, the results need to be supported by detailed and extensive knowledge of the Charles River problem. q 2003 Elsevier Science B.V. All rights reserved. Keywords: Water quality; Risk; Monte Carlo; Sensitivity analysis; Eutrophication 1. Introduction 1.1. Motivation The reasons for and significance of uncertainty in predictions of water quality are widely recog- nised and documented elsewhere (Whitehead and Young, 1979; Hornberger and Spear, 1980; Beck, 1987; Reckhow, 1994; Reichart and Omlin, 1996; 0022-1694/03/$ - see front matter q 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0022-1694(02)00417-1 Journal of Hydrology 274 (2003) 225–247 www.elsevier.com/locate/jhydrol 1 Tel.: þ1-5206268799; fax: þ 1-5206211422. 2 Tel.: þ44-2075946019; fax: þ 44-2078239401. 3 Tel.: þ1-6176273654; fax: þ 1-6176273994. * Corresponding author. Tel.: þ 44-2075946019; fax: þ 44- 2078239401. E-mail addresses: n.mcintyre@ic.ac.uk (N.R. McIntyre), thorsten@sahra.arizona.edu (T. Wagener), h.wheater@ic.ac.uk (H.S. Wheater), schapr01@tufts.edu (S.C. Chapra).