The dilemma of spatial representation for urban hydrology semi-distributed modelling: Trade-offs among complexity, calibration and geographical data

- GIS data are progressively included in a semi-distributed urban runoff model.
- Increasing spatial distribution of build-up/wash-off is tested for SS simulations.
- High-frequency time series are used for calibration and validation.
- Land-use data prove the most useful for water quantity modelling.
- A compromise solution for spatial distribution of water quality parameters is found.

SummarySemi-distributed models are widely used in urban hydrology, supported by the abundance and detail of geographical data. The inclusion of these data into hydrological models requires however an increasing complexity of the model structure with spatially distributed parameters, potentially driving to over-parameterisation issues. In this paper, different configurations and model structures, including an increasing quantity of geographical information, are tested for both water quantity and water quality on the widely used SWMM5 model for a 2.3 km2 catchment. The Nash criterion is used to calibrate the model and compare alternative configurations. Results for water quantity modelling show that the inclusion of some basic geographical information, particularly on land uses, clearly improves performances, but further refinements are less effective. Uncalibrated models with sufficient land use information reach performances comparable with those of calibrated models. For water quality modelling (suspended solids concentration), the best modelling performance is obtained by a compromise solution with moderate spatial distribution of parameters: no spatial distribution drives to limited performances, while an excessive one to severe over-parameterisation. A comparison to suspended solids measurements realized on a single road of the catchment shows that parameters providing good performances at the catchment scale are a realistic, although non optimal, representation of local scale processes.