Impact of rainfall temporal resolution on urban water quality modelling performance and uncertainties.

A key control on the response of an urban drainage model is how well the observed rainfall records represent the real rainfall variability. Particularly in urban catchments with fast response flow regimes, the selection of temporal resolution in rainfall data collection is critical. Furthermore, the impact of the rainfall variability on the model response is amplified for water quality estimates, as uncertainty in rainfall intensity affects both the rainfall-runoff and pollutant wash-off sub-models, thus compounding uncertainties. A modelling study was designed to investigate the impact of altering rainfall temporal resolution on the magnitude and behaviour of uncertainties associated with the hydrological modelling compared with water quality modelling. The case study was an 85-ha combined sewer sub-catchment in Bogotá (Colombia). Water quality estimates showed greater sensitivity to the inter-event variability in rainfall hyetograph characteristics than to changes in the rainfall input temporal resolution. Overall, uncertainties from the water quality model were two- to five-fold those of the hydrological model. However, owing to the intrinsic scarcity of observations in urban water quality modelling, total model output uncertainties, especially from the water quality model, were too large to make recommendations for particular model structures or parameter values with respect to rainfall temporal resolution.

[1]  Gabriele Freni,et al.  Urban runoff modelling uncertainty: Comparison among Bayesian and pseudo-Bayesian methods , 2009, Environ. Model. Softw..

[2]  G Chebbo,et al.  A benchmark methodology for managing uncertainties in urban runoff quality models. , 2005, Water science and technology : a journal of the International Association on Water Pollution Research.

[3]  Luca Vezzaro,et al.  Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling. , 2012, Water research.

[4]  G. Freni,et al.  Uncertainty in urban stormwater quality modelling: the effect of acceptability threshold in the GLUE methodology. , 2008, Water research.

[5]  J. Vaze,et al.  Experimental study of pollutant accumulation on an urban road surface , 2002 .

[6]  Sandro Artina,et al.  Simulation of a storm sewer network in industrial area: Comparison between models calibrated through experimental data , 2007, Environ. Model. Softw..

[7]  W. Hunt,et al.  Intra-event variability of Escherichia coli and total suspended solids in urban stormwater runoff. , 2012, Water research.

[8]  P. Willems Quantification and relative comparison of different types of uncertainties in sewer water quality modeling. , 2008, Water research.

[9]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[10]  G. Freni,et al.  Uncertainty assessment of an integrated urban drainage model , 2009 .

[11]  Gabriele Freni,et al.  Uncertainty in urban stormwater quality modelling: the influence of likelihood measure formulation in the GLUE methodology. , 2009, The Science of the total environment.

[12]  Wolfgang Schilling,et al.  Rainfall data for urban hydrology: what do we need? , 1991 .

[13]  G. Freni,et al.  Uncertainty analysis of the influence of rainfall time resolution in the modelling of urban drainage systems , 2005 .

[14]  Wolfgang Rauch,et al.  Required accuracy of rainfall data for integrated urban drainage modeling , 1998 .