Valentin Gamerith

Applying global sensitivity analysis to the modelling of flow and water quality in sewers.

While several approaches for global sensitivity analysis (GSA) have been proposed in literature, only few applications exist in urban drainage modelling. This contribution discusses two GSA methods applied to a sewer flow and sewer water quality model: Standardised Regression Coefficients (SRCs) using Monte-Carlo simulation as well as the Morris Screening method. For selected model variables we evaluate how the sensitivities are influenced by the choice of the rainfall event. The aims are to i) compare both methods concerning the similarity of results and their applicability, ii) discuss the implications for factor fixing (identifying non-influential parameters) and factor prioritisation (identifying important parameters) and iii) rank the important parameters for the investigated model. It was shown that both methods lead to similar results for the hydraulic model. Parameter interactions and non-linearity were identified for the water quality model and the parameter ranking differs between the methods. For the investigated model the results allow a sound choice of output variables and rainfall events in view of detailed uncertainty analysis or model calibration. We advocate the simultaneous use of both methods for a first model assessment as they allow answering both factor fixing and factor prioritisation at low computational cost.

Sewer modelling based on highly distributed calibration data sets and multi-objective auto-calibration schemes

Pollutant load modelling for sewer systems is state-of-the-art, especially for the estimation of discharged pollutant loads and development of sewer management strategies. However, conventionally obtained calibration data sets are often not exhaustive and have significant drawbacks. In the Graz West catchment area (Graz, Austria), continuous high-resolution long-term online measurements for discharge and pollutant concentration have been carried out since 2002. In this paper, the application of single- and multi-objective auto-calibration schemes based on evolution strategies for a deterministic hydrological pollutant load model will be discussed. Three approaches for pollutant load modelling are examined and compared: using a constant storm weather concentration and two build-up wash-off approaches with basic respectively extended wash-off equations. It is shown that the applied auto-calibration method leads to very satisfying results for both the calibration and the validation data set, and also for the dry and the storm weather runoff. However, until now, convective storms have not been convincingly represented. The build-up wash-off approach using the basic wash-off equation shows the best correlations between measured data and simulation results. As one of the chosen objectives for the multi-objective optimisation reacted highly sensitively to measurement errors, additional improvements can be expected after refining the criteria used in this algorithm.

Single- and Multievent Optimization in Combined Sewer Flow and Water Quality Model Calibration

Over the last three decades, storm-water quality modeling has been used increasingly commonly to describe the general system behavior and assess the pollution loads transferred in and spilled out of combined sewer systems. The calibration of quality models is, in most cases, based on conventionally obtained calibration data, e.g., by automated sampling. Long-term high-resolution online measurement data are available for the Graz West catchment (Graz, Austria), allowing an assessment of the full dynamics of discharge and pollution concentrations. This paper focuses on the application and comparison of single-event and two different multievent optimization schemes for sewer-water quality model calibration. While both single- and multievent optimization lead to satisfying results for the calibration events in discharge calibration, it is shown that validation events are better reproduced by using multievent calibration. Single- and multievent autocalibration of pollution concentration is based on the best dataset obtained from the discharge calibration. As for discharge, the pollutographs are reproduced satisfactorily, and multievent calibration is more stable. In all cases, the two multievent approaches performed equally well.

Pollution load modelling in sewer systems: an approach of combining long term online sensor data with multi-objective auto-calibration schemes

Pollutant load modelling for sewer systems is state-of-the-art, especially for the estimation of discharged pollutant loads and development of sewer management strategies. However, conventionally obtained calibration data sets are often not exhaustive and have significant drawbacks. In the Graz West catchment area (Graz, Austria), continuous high-resolution long-term online measurements for discharge and pollutant concentration have been carried out since 2002.In this paper, the application of single- and multi-objective auto-calibration schemes based on evolution strategies for a deterministic hydrological pollutant load model will be discussed. Three approaches for pollutant load modelling are examined and compared: using a constant storm weather concentration and two surface accumulation-wash-off approaches with basic respectively extended wash-off equations. It is shown that the applied auto-calibration method leads to very satisfying results for both the calibration and the validation data set, and also for the dry and the storm weather runoff. Results from multi-objective calibration show better robustness in validation events than single-objective calibration. The build-up wash-off approach using the basic wash-off equation gives the best correlations between measured data and simulation results.

Implications of long-term stormwater quality modelling for design of combined sewer infrastructure

In many countries traditional simple design approaches for combined sewer overflow (CSO) structures and storage tanks are used in general practice, neglecting the significant variability observed in real systems. In this paper, two hydraulic software simulation tools and two stormwater quality model approaches are compared to assess CSO behaviour and the impact of different modelling approaches on the estimation of spilled pollutant loads in long-term simulations for an urban catchment area. A good coherence of the two runoff models is observed. The more complex stormwater quality model approach leads to significantly lower TSS interception ratios for smaller specific storage tank volumes. For both the hydraulic CSO indicators and TSS interception ratios an important annual variability is observed. Therefore, using single design value approaches or short rainfall time series in modelling can lead to significant impact on the design ratio of storage tank and CSO structures.

Online Monitoring of Combined Sewer Systems: Experiences and Application in Modeling

The full understanding of flow dynamics and pollutant concentrations in combined sewer systems is an important issue in the management and design of these syst…