A Bayesian approach to model the trends and variability in urban stormwater quality associated with catchment and hydrologic parameters

• Bayesian hierarchical model for runoff pollutograph is proposed The combines catchment and event specific characteristics Rain intensity, duration, antecedent dry period can explain pollutant variability Effective impervious area of the create high in pollutographs Stormwater pollution has become a key environmental issue urban areas. Reliable estimation stormwater discharge important implementing robust water quality management strategies. Even though significant attempts have been undertaken to develop models, deterministic approaches proven inappropriate as they do not address quality. Due random nature rainfall differences characteristics, it difficult generate desired level certainty. modelling an effective tool developing complex models with large number sources variability. A does look single value parameters, but rather determines distribution parameters from which all inference drawn. This study introduces linear regression describe incorporating associated uncertainties parameters. incorporates including area, time concentration, rain average intensity contributors effects.