Catchment-wide validated assessment of combined sewer overflows (CSOs) in a mediterranean coastal area and possible disinfection methods to mitigate microbial contamination

Crocetti, Paolo; Eusebi, Anna Laura; Bruni, Cecilia; Marinelli, Enrico; Darvini, Giovanna; Carini, Claudio Bernardo; Bollettini, Cristiana; Recanati, Virginia; Akyol, Çağrı; Fatone, Francesco

doi:10.1016/j.envres.2020.110367

Cited by 14 publications

(10 citation statements)

References 38 publications

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“…Climate change and progressive urbanization result in an increase in the volume of stormwater outflow from catchments, which leads to flooding and deterioration of water quality in receivers (Crocetti et al, 2020;Fletcher et al, 2013). To reduce the incidence of these phenomena, runoff model generation is needed.…”

Section: Introductionmentioning

confidence: 99%

“…This can be achieved using hydrodynamic models based on physical equations representing stormwater outflows. One of the common tools is the SWMM (Storm Water Management Model) program (Buahin and Horsburgh, 2015;Crocetti et al, 2020;Gironás et al, 2010). SWMM allows for simulation of sewage quantity (Guan et al, 2015), quality (Dotto et al, 2012), including objects located in sewer networks (separation and combined sewer networks.…”

Section: Introductionmentioning

confidence: 99%

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Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments

Fatone

Szeląg

Kiczko

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. Knowledge of the variability of the hydrograph of outflow from urban catchments is highly important for measurements and evaluation of the operation of sewer networks. Currently, hydrodynamic models are most frequently used for hydrograph modeling. Since a large number of their parameters have to be identified, there may be problems at the calibration stage. Hence, sensitivity analysis is used to limit the number of parameters. However, the current sensitivity analytical methods ignore the effect of the temporal distribution and intensity of precipitation in a rainfall event on the catchment outflow hydrograph. This article presents a methodology of constructing a simulator of catchment outflow hydrograph parameters (volume and maximum flow). For this purpose, uncertainty analytical results obtained with the use of the GLUE (generalized likelihood uncertainty estimation) method were used. A novel analysis of the sensitivity of the hydrodynamic catchment models was also developed, which can be used in the analysis of the operation of stormwater networks and underground infrastructure facilities. Using the logistic regression method, an innovative sensitivity coefficient was proposed to study the impact of the variability of the parameters of the hydrodynamic model depending on the distribution of rainfall, the origin of rainfall (on the Chomicz scale), and the uncertainty of the estimated simulator coefficients on the parameters of the outflow hydrograph. The developed model enables the analysis of the impact of the identified SWMM (Storm Water Management Model) parameters on the runoff hydrograph, taking into account local rainfall conditions, which have not been analyzed thus far. Compared with the currently developed methods, the analyses included the impact of the uncertainty of the identified coefficients in the logistic regression model on the results of the sensitivity coefficient calculation. This aspect has not been taken into account in the sensitivity analytical methods thus far, although this approach evaluates the reliability of the simulation results. The results indicated a considerable influence of rainfall distribution and intensity on the sensitivity factors. The greater the intensity and rainfall were, the lower the impact of the identified hydrodynamic model parameters on the hydrograph parameters. Additionally, the calculations confirmed the significant impact of the uncertainty of the estimated coefficient in the simulator on the sensitivity coefficients. In the context of the sensitivity analysis, the obtained results have a significant effect on the interpretation of the relationships obtained. The approach presented in this study can be widely applied at the model calibration stage and for appropriate selection of hydrographs for identification and validation of model parameters. The results of the calculations obtained in this study indicate the suitability of including the origin of rainfall in the sensitivity analysis and calibration of hydrodynamic models, which results from the different sensitivities of models for normal, heavy, and torrential rain types. In this context, it is necessary to first divide the rainfall data by origin, for which analyses will be performed, including sensitivity analysis and calibration. Considering the obtained results of the calculations, at the stage of identifying the parameters of hydrodynamic models and their validation, precipitation conditions should be included because, for the precipitation caused by heavy rainfall, the values of the sensitivity coefficients were much lower than for torrential ones. Taking into account the values of the sensitivity coefficients obtained, the calibration of the models should not only cover episodes with high rainfall intensity, since this may lead to calculation errors at the stage of applying the model in practice (assessment of the stormwater system operating conditions, design of reservoirs and flow control devices, green infrastructure, etc.).

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments

Fatone

Szeląg

Kiczko

et al. 2021

Hydrol. Earth Syst. Sci.

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“…SWMM is frequently applied in CSO modeling and control studies (Barone et al, 2019; Crocetti et al, 2021; García et al, 2017; Jean et al, 2018; Liao et al, 2015). In Liao et al (2015), CSO control scenarios has been designed by using SWMM (Liao et al, 2015).…”

Section: Mechanistic Modelingmentioning

confidence: 99%

“…Runoff simulation is important for CSO management (Field & Cibik, 1980), flood management (Ouyang et al, 2012;Rabori & Ghazavi, 2018), impact of climate change on urban drainage systems (Kovacs & Clement, 2009), sponge city (Jia et al, 2018) and sponge airport (J. applications, and low-impact development (LID) applications (Chui et al, 2016). SWMM is frequently applied in CSO modeling and control studies (Barone et al, 2019;Crocetti et al, 2021;García et al, 2017;Jean et al, 2018;Liao et al, 2015). In Liao et al (2015), CSO control scenarios has been designed by using SWMM (Liao et al, 2015).…”

Section: Storm Water Management Modelmentioning

confidence: 99%

Smart management of combined sewer overflows: From an ancient technology to artificial intelligence

et al. 2023

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Sewer systems are an essential part of sanitation infrastructure for protecting human and ecosystem health. Initially, they were used to solely convey stormwater, but over time municipal sewage was discharged to these conduits and transformed them into combined sewer systems (CSS). Due to climate change and rapid urbanization, these systems are no longer sufficient and overflow in wet weather conditions. Mechanistic and data-driven models have been frequently used in research on combined sewer overflow (CSO) management integrating low-impact development and gray-green infrastructures.Recent advances in measurement, communication, and computation technologies have simplified data collection methods. As a result, technologies such as artificial intelligence (AI), geographic information system, and remote sensing can be integrated into CSO and stormwater management as a part of the smart city and digital twin concepts to build climate-resilient infrastructures and services. Therefore, smart management of CSS is now both technically and economically feasible to tackle the challenges ahead. This review article explores CSO characteristics and associated impact on receiving waterbodies, evaluates suitable models for CSO management, and presents studies including above-mentioned technologies in the context of smart CSO and stormwater management. Although integration of all these technologies has a big potential, further research is required to achieve AI-controlled CSS for robust and agile CSO mitigation.

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“…However, the distribution of discharged volumes is often uneven, with a small number of the CSO structures responsible for the greatest fraction of the discharged volume. 7,8…”

Section: Introductionmentioning

confidence: 99%

A stochastic approach for assessing the chronic environmental risk generated by wet-weather events from integrated urban wastewater systems

Ianes,

Cantoni,

Remigi

et al. 2023

Environ. Sci.: Water Res. Technol.

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Catchment-wide validated assessment of combined sewer overflows (CSOs) in a mediterranean coastal area and possible disinfection methods to mitigate microbial contamination

Cited by 14 publications

References 38 publications

Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments

Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments

Smart management of combined sewer overflows: From an ancient technology to artificial intelligence

A stochastic approach for assessing the chronic environmental risk generated by wet-weather events from integrated urban wastewater systems

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