Traitement et analyse de séries chronologiques continues de ...

Treatment and analysis of continuous turbidities series for the test of urban
stormwater quality models
Abstract
Few storm water quality models are currently used for operational purposes. Nevertheless,
more and more urban water managers are tackling this issue. This work, carried out in
partnership with the INSA Lyon and the engineering consulting company SAFEGE, is such an
example of this interest.
Current research works focus on parsimonious modelling approaches that match the amount
of data available for calibration. Two types of reality representation are proposed: global
approaches at the catchment scale or models with a simplified representation of sewer
processes. Moreover uncertainties analysis now appears as an integrated step and a powerful
tool in models testing. Bayesian approach allows such type of analysis that improves our
knowledge on models structure.
In parallel, development of in sewer continuous measurements based on spectrometry and
turbidimetry techniques, provides large data base of continuous total suspended solids (TSS)
and chemical oxygen demand (COD) concentrations. Much information on pollutant fluxes
dynamics at short time steps can be provided.
To our knowledge, this research work is one of the first studies in urban hydrology based on
a large turbidity database. Two sites are implemented next to Lyon, France: Chassieu (separated
sewer) and Ecully (combined sewer), with measurements over the period 2004-2008. The first
two objectives of this work were validation and analysis of the existing database. The third
objective was to test multi-regression and Accumulation-Erosion-Transfer modelling
approaches, with this new database. Semi-automatic treatment and data analysis tools have been
used for this purpose. In the meantime, a deep bibliographic work on uncertainties analysis
methods and models test has been carried out.
263 and 239 stormwater events were selected for the modelling work, namely for Chassieu
and Ecully. Data analysis provided insights for making assumptions on the pollutant fluxes
generation and proposing adapted models. Test of multi-regression approach confirmed
conclusions of previous research works: it is necessary to build local approaches based on
detailed data analysis.
Models that were obtained for event mean concentrations poorly reproduced observed data.
For event mass, data variability could be reproduced in trend. However point values can not be
reproduced satisfyingly. Formal Bayesian approach was used for testing a simple global
Accumulation-Erosion-Transfer model for Chassieu. First results evidenced the difficulties of
the model to reproduce the dynamics variability. This may be due to the simple structure.
However these first tests have demonstrated the efficiency of the Bayesian analysis procedure.
In particular, the application of the learning principle showed that model structure can be
significantly and efficiently improved.
Key words: Bayesian analysis, COD, data treatment, modelling, urban stormwater loads,
TSS, turbidity