Performance and uncertainties of TSS stormwater sampling strategies from online time series.

The event mean concentrations (EMCs) that would have been obtained by four different stormwater sampling strategies are simulated by using total suspended solids (TSS) and flowrate time series (about one minute time-step and one year of data). These EMCs are compared to the reference EMCs calculated by considering the complete time series. The sampling strategies are assessed with datasets from four catchments: (i) Berlin, Germany, combined sewer overflow (CSO); (ii) Graz, Austria, CSO; (iii) Chassieu, France, separate sewer system; and (iv) Ecully, France, CSO. A sampling strategy in which samples are collected at constant time intervals over the rainfall event and sampling volumes are pre-set as proportional to the runoff volume discharged between two consecutive sample leads to the most representative results. Recommended sampling time intervals are of 5 min for Berlin and Chassieu (resp. 100 and 185 ha area) and 10 min for Graz and Ecully (resp. 335 and 245 ha area), with relative sampling errors between 7% and 20% and uncertainties in sampling errors of about 5%. Uncertainties related to sampling volumes, TSS laboratory analyses and beginning/ending of rainstorm events are reported as the most influent sources in the uncertainties of sampling errors and EMCs.

On the implementation of reliable early warning systems at European bathing waters using multivariate Bayesian regression modelling.

For ensuring microbial safety, the current European bathing water directive (BWD) (76/160/EEC 2006) demands the implementation of reliable early warning systems for bathing waters, which are known to be subject to short-term pollution. However, the BWD does not provide clearly defined threshold levels above which an early warning system should start warning or informing the population. Statistical regression modelling is a commonly used method for predicting concentrations of fecal indicator bacteria. The present study proposes a methodology for implementing early warning systems based on multivariate regression modelling, which takes into account the probabilistic character of European bathing water legislation for both alert levels and model validation criteria. Our study derives the methodology, demonstrates its implementation based on information and data collected at a river bathing site in Berlin, Germany, and evaluates health impacts as well as methodological aspects in comparison to the current way of long-term classification as outlined in the BWD.

Impacts of combined sewer overflows on a large urban river - Understanding the effect of different management strategies.

To support decision makers in planning effective combined sewer overflow (CSO) management strategies an integrated modelling and impact assessment approach has been developed and applied for a large urban area in Berlin, Germany. It consists of an urban drainage model, a river water quality model and a tool for the quantification of adverse dissolved oxygen (DO) conditions in the river, one of the main stressors for urban lowland rivers. The coupled model was calibrated successfully with average Nash-Sutcliffe-efficiencies for DO in the river of 0.61 and 0.70 for two validation years. Moreover, the whole range of observed DO concentrations after CSO down to 0 mg L-1 is simulated by the model. A local sensitivity analysis revealed that in the absence of CSO dissolved oxygen principally depends on phytoplankton dynamics. Regarding CSO impacts, it was shown that 97% of the observed DO deficit can be explained by the three processes (i) mixing of river water with CSO spill water poor in DO, (ii) reduced phytoplankton activity due to CSO-induced turbidity and (iii) degradation of organic matter by heterotrophic bacteria. As expected, process (iii) turned out to be the most important one. However depending on the time lag after CSO the other processes can become dominant. Given the different involved processes, we found that different mitigation schemes tested in a scenario analysis can reduce the occurrence of critical DO deficits in the river by 30-70%. Overall, the study demonstrates that integrated sewer-river-models can be set up to represent CSO impacts under complex urban conditions. However, a significant effort in monitoring and modelling is a requisite for achieving reliable results.

Calibration of UV/Vis spectrophotometers: A review and comparison of different methods to estimate TSS and total and dissolved COD concentrations in sewers, WWTPs and rivers.

UV/Vis spectrophotometers have been used for one decade to monitor water quality in various locations: sewers, rivers, wastewater treatment plants (WWTPs), tap water networks, etc. Resulting equivalent concentrations of interest can be estimated by three ways: i) by manufacturer global calibration; ii) by local calibration based on the provided global calibration and grab sampling; iii) by advanced calibration looking for relations between UV/Vis spectra and corresponding concentrations from grab sampling. However, no study has compared the applied methods so far. This collaborative work presents a comparison between five different methods. A Linear Regression (LR), Support Vector Machine (SVM), EVOlutionary algorithm method (EVO) and Partial Least Squares (PLS) have been applied on various data sets (sewers, rivers, WWTPs under dry, wet and all weather conditions) and for three water quality parameters: TSS, COD total and dissolved. Two criteria (r(2) and Root Mean Square Error RMSE) have been calculated - on calibration and verification data subsets - to evaluate accuracy and robustness of the applied methods. Values of criteria have then been statistically analysed for all and separated data sets. Non-consistent outcomes come through this study. According to the Kruskal-Wallis test and RMSEs, PLS and SVM seem to be the best methods. According to uncertainties in laboratory analysis and ranking of methods, LR and EVO appear more robust and sustainable for concentration estimations. Conclusions are mostly independent of water matrices, weather conditions or concentrations investigated.

Influence of local calibration on the quality of online wet weather discharge monitoring: feedback from five international case studies.

This paper reports about experiences gathered from five online monitoring campaigns in the sewer systems of Berlin (Germany), Graz (Austria), Lyon (France) and Bogota (Colombia) using ultraviolet-visible (UV-VIS) spectrometers and turbidimeters. Online probes are useful for the measurement of highly dynamic processes, e.g. combined sewer overflows (CSO), storm events, and river impacts. The influence of local calibration on the quality of online chemical oxygen demand (COD) measurements of wet weather discharges has been assessed. Results underline the need to establish local calibration functions for both UV-VIS spectrometers and turbidimeters. It is suggested that practitioners calibrate locally their probes using at least 15-20 samples. However, these samples should be collected over several events and cover most of the natural variability of the measured concentration. For this reason, the use of automatic peristaltic samplers in parallel to online monitoring is recommended with short representative sampling campaigns during wet weather discharges. Using reliable calibration functions, COD loads of CSO and storm events can be estimated with a relative uncertainty of approximately 20%. If no local calibration is established, concentrations and loads are estimated with a high error rate, questioning the reliability and meaning of the online measurement. Similar results have been obtained for total suspended solids measurements.

Urban flood risk assessment using sewer flooding databases.

Sustainable water management is a global challenge for the 21st century. One key aspect remains protection against urban flooding. The main objective is to ensure or maintain an adequate level of service for all inhabitants. However, level of service is still difficult to assess and the high-risk locations difficult to identify. In this article, we propose a methodology, which (i) allows water managers to measure the service provided by the urban drainage system with regard to protection against urban flooding; and (ii) helps stakeholders to determine effective strategies for improving the service provided. One key aspect of this work is to use a database of sewer flood event records to assess flood risk. Our methodology helps urban water managers to assess the risk of sewer flooding; this approach does not seek to predict flooding but rather to inform decision makers on the current level of risk and on actions which need to be taken to reduce the risk. This work is based on a comprehensive definition of risk, including territorial vulnerability and perceptions of urban water stakeholders. This paper presents the results and the methodological contributions from implementing the methodology on two case studies: the cities of Lyon and Mulhouse.