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

Urban stormwater quality: A review of methods for continuous field monitoring

Urban stormwater is contaminated by a wide range of substances whose concentrations vary greatly between locations, as well as between and during rain events. This literature review evaluates advantages and limitations of current methods for using continuous water quality monitoring for stormwater characterization and control. High-temporal-resolution measurements have been used to improve the understanding of stormwater quality dynamics and pollutant pathways, facilitate the performance evaluation of stormwater control measures and improve operation of the urban drainage system with real-time control. However, most sensors used to study stormwater were developed for either centralized water treatment or natural water contexts and adaptation is necessary. At present, the primary application of interest in stormwater - characterization of pollutant concentrations - can only be achieved through the use of indirect measurements with site-specific relationships of pollutants to basic physical-chemical parameters. In addition, various problems arise in the field context, associated with intermittent or variable flow rates, the accumulation of debris and sediment, adverse conditions for electrical equipment and human factors. Obtaining reliable continuous stormwater quality data requires the adoption of best practices, including the calibration and regular maintenance of sensors, verification of data and accounting for the considerable uncertainties in data; however, the literature review showed that improvement is needed among the scientific community in implementing and documenting these practices.

Distribution-Based Calibration of a Stormwater Quality Model

Stormwater quality models are usually calibrated using observed pollutographs. As current models still rely on simplified model concepts for pollutant accumulation and wash-off, calibration results for continuous pollutant concentrations are highly uncertain. In this paper, we introduce an innovative calibration approach based on total suspended solids (TSS) event load distribution. The approach is applied on stormwater quality models for a flat roof and a parking lot for which reliable distributions are available. Exponential functions are employed for both TSS buildup and wash-off. Model parameters are calibrated by means of an evolutionary algorithm to minimize the distance between a parameterized lognormal distribution function and the cumulated distribution of simulated TSS event loads. Since TSS event load characteristics are probabilistically considered, the approach especially respects the stochasticity of TSS buildup and wash-off and, therefore, improves conventional stormwater quality calibration concepts. The results show that both experimental models were calibrated with high goodness-of-fit (Kolmogorov–Smirnov test statistic: 0.05). However, it is shown that events with high TSS event loads (>0.8 percentile) are generally underestimated. While this leads to a relative deviation of −28% of total TSS loads for the parking lot, the error is compensated for the flat roof (+5%). Calibrated model parameters generally tend to generate wash-off proportional to runoff, which is indicated by mass-volume curves. The approach itself is, in general, applicable and creates a new opportunity to calibrate stormwater quality models especially when calibration data is limited.

Field validation of a new low-cost method for determining occurrence and duration of combined sewer overflows

Combined sewer overflow (CSO) events produced in combined sewer systems (CSS) during wet weather conditions are a threat for the receiving water bodies. The large number of CSO structures normally present in a CSS makes that the monitoring of the complete CSO network in a simultaneous way would drastically increase the investment costs. In this paper, a new methodology is presented aiming to characterize the occurrence and duration of CSO events by means of low-cost temperature sensors. Hence, a large number of CSO structures can be simultaneously monitored and the system can be characterized as a whole. The method assumes temperature differences between the overflowing mix of wastewater and stormwater and the sewer gas phase, so the temperature shift produced during a rainfall episode is related to a CSO event occurrence. The method has been tested and validated in La Garriga CSS (Spain) where the temperature at 13 CSO weirs was monitored for a period of 1 year (57 rainfall episodes). For the whole set of CSO events, occurrence and duration were successfully determined in 80% of cases. Advantages, limitations and potential applications of the method are discussed at the end of the paper.