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Ghassan Chebbo - One of the best experts on this subject based on the ideXlab platform.

  • Stochastic evaluation of annual micropollutant loads and their uncertainties in separate Storm Sewers
    Environmental Science and Pollution Research, 2017
    Co-Authors: Ali Hannouche, Regis Moilleron, Ghassan Chebbo, Claude Joannis, Johnny Gasperi, Marie-christine Gromaire, Sylvie Barraud, Véronique Ruban
    Abstract:

    This article describes a stochastic method to calculate the annual pollutant loads and its application over several years at the outlet of three catchments drained by separate Storm Sewers. A stochastic methodology using Monte Carlo simulations is proposed for assessing annual pollutant load, as well as the associated uncertainties, from a few event sampling campaigns and/or continuous turbidity measurements (representative of the total suspended solids concentration (TSS)). Indeed, in the latter case, the proposed method takes into account the correlation between pollutants and TSS. The developed method was applied to data acquired within the French research project BINOGEV^ (innovations for a sustainable management of urban water) at the outlet of three urban catchments drained by separate Storm Sewers. Ten or so event sampling campaigns for a large range of pollutants (46 pollutants and 2 conventional water quality parameters: TSS and total organic carbon (TOC)) are combined with hundreds of rainfall events for which, at least one among three continuously monitored parameters (rainfall intensity, flow rate, and turbidity) is available. Results obtained for the three catchments show that the annual pollutant loads can be estimated with uncertainties ranging from 10 to 60%, and the added value of turbidity monitoring for lowering the uncertainty is demonstrated. A low inter-annual and inter-site variability of pollutant loads, for many of studied pollutants, is observed with respect to the estimated uncertainties, and can be explained mainly by annual precipitation.

  • priority pollutants in urban Stormwater part 1 case of separate Storm Sewers
    Water Research, 2012
    Co-Authors: S Zgheib, Regis Moilleron, Ghassan Chebbo
    Abstract:

    Organic and mineral pollutants have become part of today's urban environment. During a rain event, Stormwater quality as well as the corresponding contaminant loads is affected by both atmospheric deposition and the various types of impervious surfaces (roads, rooftops, parking lots etc.) on which runoff occurs. This study provides results on Stormwater pollution in Paris and its suburbs from three separate Storm Sewers (n=20 samples). These results show that the Stormwater had been contaminated by 55 chemical substances out of the 88 investigated. A particular attention was given to Stormwater particle contamination. Concentrations are provided for: metals, PAHs, PCBs, organotins, alkylphenols, phthalates, pesticides, and VOCs. Our findings are among the first available in the literature since the relevant analyses were all conducted on both the particulate (P) and dissolved (D) phases. For most substances, particles from the three Storm Sewers were more heavily contaminated than dredged sediments and settleable particles from the Seine River. As a consequence of this finding, the release of untreated Stormwater discharges may impact the receiving waters and contribute to sediment contamination.

  • towards the determination of an optimal scale for Stormwater quality management micropollutants in a small residential catchment
    Water Research, 2012
    Co-Authors: Adele Bressy, Ghassan Chebbo, Marie-christine Gromaire, Catherine Lorgeoux, Mohamed Saad, Florent Leroy
    Abstract:

    Stormwater and atmospheric deposits were collected on a small residential urban catchment (0.8 ha) near Paris in order to determine the levels of certain micropollutants (using a preliminary scan of 69 contaminants, followed by a more detailed quantification of PAHs, PCBs, alkylphenols and metals). Atmospheric inputs accounted for only 10%-38% of the Stormwater contamination (except for PCBs), thus indicating substantial release within the catchment. On this small upstream catchment however, Stormwater contamination is significantly lower than that observed downstream in Storm Sewers on larger adjacent urban catchments with similar land uses. These results likely stem from cross-contamination activity during transfers inside the sewer system and underscore the advantages of runoff management strategies at the source for controlling Stormwater pollutant loads. Moreover, it has been shown that both contamination levels and contaminant speciation evolve with the scale of the catchment, in correlation with a large fraction of dissolved contaminants in upstream runoff, which differs from what has been traditionally assumed for Stormwater. Consequently, the choice of treatment device/protocol must be adapted to the management scale as well as to the targeted type of contaminant.

Tsangjung Chang - One of the best experts on this subject based on the ideXlab platform.

  • a novel approach to model dynamic flow interactions between Storm sewer system and overland surface for different land covers in urban areas
    Journal of Hydrology, 2015
    Co-Authors: Tsangjung Chang, Chiaho Wang, Albert S Chen
    Abstract:

    In this study, we developed a novel approach to simulate dynamic flow interactions between Storm Sewers and overland surface for different land covers in urban areas. The proposed approach couples the one-dimensional (1D) sewer flow model (SFM) and the two-dimensional (2D) overland flow model (OFM) with different techniques depending on the land cover type of the study areas. For roads, pavements, plazas, and so forth where rainfall becomes surface runoff before entering the sewer system, the rainfall–runoff process is simulated directly in the 2D OFM, and the runoff is drained to the sewer network via inlets, which is regarded as the input to 1D SFM. For green areas on which rainfall falls into the permeable ground surface and the generated direct runoff traverses terrain, the deduction rate is applied to the rainfall for reflecting the soil infiltration in the 2D OFM. For flat building roofs with drainage facilities allowing rainfall to drain directly from the roof to sewer networks, the rainfall–runoff process is simulated using the hydrological module in the 1D SFM where no rainfall is applied to these areas in the 2D OFM. The 1D SFM is used for hydraulic simulations in the sewer network. Where the flow in the drainage network exceeds its capacity, a surcharge occurs and water may spill onto the ground surface if the pressure head in a manhole exceeds the ground elevation. The overflow discharge from the sewer system is calculated by the 1D SFM and considered a point source in the 2D OFM. The overland flow will return into the sewer network when it reaches an inlet that connects to an un-surcharged manhole. In this case, the inlet is considered as a point sink in the 2D OFM and an inflow to a manhole in the 1D SFM. The proposed approach was compared to other five urban flood modelling techniques with four rainfall events that had previously recorded inundation areas. The merits and drawbacks of each modelling technique were compared and discussed. Based on the simulated results, the proposed approach was found to simulate floodings closer to the survey records than other approaches because the physical rainfall–runoff phenomena in urban environment were better reflected.

  • inundation simulation for urban drainage basin with Storm sewer system
    Journal of Hydrology, 2000
    Co-Authors: Shiuanhung Chen, Tsangjung Chang
    Abstract:

    An urban inundation model, combining a Storm sewer model SWMM, two-dimensional (2D) diffusive overland-flow model and operations of pumping stations, has been developed to simulate inundation in urban areas caused by the surcharge of Storm Sewers and outlet pumping stations. The movement of water in the studied urban watershed is characterized by two components, namely, the Storm sewer flow component and the surcharge-induced inundation component. SWMM is employed to solve the Storm sewer flow component and to provide the surcharged flow hydrographs for surface runoff exceeding the capacity of the Storm Sewers. The 2D diffusive overland-flow model considering the non-inertia equation with Alternative Direction Explicit numerical scheme is then used to calculate the detailed inundation zones and depths due to the surcharged water on overland surface. Drainage by pumping stations at outlets of the Storm sewer system has also been taken into consideration. The parameters of the model are calibrated and verified for discrete Storms. The combined model is suitable for analysis of inundation on urban areas due to overflow of Storm Sewers and flooding caused by failure of pumping stations. Simulated results can be applied to establish flood-mitigation measures.

Regis Moilleron - One of the best experts on this subject based on the ideXlab platform.

  • Stochastic evaluation of annual micropollutant loads and their uncertainties in separate Storm Sewers
    Environmental Science and Pollution Research, 2017
    Co-Authors: Ali Hannouche, Regis Moilleron, Ghassan Chebbo, Claude Joannis, Johnny Gasperi, Marie-christine Gromaire, Sylvie Barraud, Véronique Ruban
    Abstract:

    This article describes a stochastic method to calculate the annual pollutant loads and its application over several years at the outlet of three catchments drained by separate Storm Sewers. A stochastic methodology using Monte Carlo simulations is proposed for assessing annual pollutant load, as well as the associated uncertainties, from a few event sampling campaigns and/or continuous turbidity measurements (representative of the total suspended solids concentration (TSS)). Indeed, in the latter case, the proposed method takes into account the correlation between pollutants and TSS. The developed method was applied to data acquired within the French research project BINOGEV^ (innovations for a sustainable management of urban water) at the outlet of three urban catchments drained by separate Storm Sewers. Ten or so event sampling campaigns for a large range of pollutants (46 pollutants and 2 conventional water quality parameters: TSS and total organic carbon (TOC)) are combined with hundreds of rainfall events for which, at least one among three continuously monitored parameters (rainfall intensity, flow rate, and turbidity) is available. Results obtained for the three catchments show that the annual pollutant loads can be estimated with uncertainties ranging from 10 to 60%, and the added value of turbidity monitoring for lowering the uncertainty is demonstrated. A low inter-annual and inter-site variability of pollutant loads, for many of studied pollutants, is observed with respect to the estimated uncertainties, and can be explained mainly by annual precipitation.

  • priority pollutants in urban Stormwater part 1 case of separate Storm Sewers
    Water Research, 2012
    Co-Authors: S Zgheib, Regis Moilleron, Ghassan Chebbo
    Abstract:

    Organic and mineral pollutants have become part of today's urban environment. During a rain event, Stormwater quality as well as the corresponding contaminant loads is affected by both atmospheric deposition and the various types of impervious surfaces (roads, rooftops, parking lots etc.) on which runoff occurs. This study provides results on Stormwater pollution in Paris and its suburbs from three separate Storm Sewers (n=20 samples). These results show that the Stormwater had been contaminated by 55 chemical substances out of the 88 investigated. A particular attention was given to Stormwater particle contamination. Concentrations are provided for: metals, PAHs, PCBs, organotins, alkylphenols, phthalates, pesticides, and VOCs. Our findings are among the first available in the literature since the relevant analyses were all conducted on both the particulate (P) and dissolved (D) phases. For most substances, particles from the three Storm Sewers were more heavily contaminated than dredged sediments and settleable particles from the Seine River. As a consequence of this finding, the release of untreated Stormwater discharges may impact the receiving waters and contribute to sediment contamination.

Véronique Ruban - One of the best experts on this subject based on the ideXlab platform.

  • Stochastic evaluation of annual micropollutant loads and their uncertainties in separate Storm Sewers
    Environmental Science and Pollution Research, 2017
    Co-Authors: Ali Hannouche, Regis Moilleron, Ghassan Chebbo, Claude Joannis, Johnny Gasperi, Marie-christine Gromaire, Sylvie Barraud, Véronique Ruban
    Abstract:

    This article describes a stochastic method to calculate the annual pollutant loads and its application over several years at the outlet of three catchments drained by separate Storm Sewers. A stochastic methodology using Monte Carlo simulations is proposed for assessing annual pollutant load, as well as the associated uncertainties, from a few event sampling campaigns and/or continuous turbidity measurements (representative of the total suspended solids concentration (TSS)). Indeed, in the latter case, the proposed method takes into account the correlation between pollutants and TSS. The developed method was applied to data acquired within the French research project BINOGEV^ (innovations for a sustainable management of urban water) at the outlet of three urban catchments drained by separate Storm Sewers. Ten or so event sampling campaigns for a large range of pollutants (46 pollutants and 2 conventional water quality parameters: TSS and total organic carbon (TOC)) are combined with hundreds of rainfall events for which, at least one among three continuously monitored parameters (rainfall intensity, flow rate, and turbidity) is available. Results obtained for the three catchments show that the annual pollutant loads can be estimated with uncertainties ranging from 10 to 60%, and the added value of turbidity monitoring for lowering the uncertainty is demonstrated. A low inter-annual and inter-site variability of pollutant loads, for many of studied pollutants, is observed with respect to the estimated uncertainties, and can be explained mainly by annual precipitation.

T.j Chang - One of the best experts on this subject based on the ideXlab platform.

  • Inundation simulation for urban drainage basin with Storm sewer system
    Journal of Hydrology, 2000
    Co-Authors: M.h Hsu, S.h Chen, T.j Chang
    Abstract:

    Copyright © 2000 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Hydrology . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Hydrology Vol. 234 (2000), DOI: 10.1016/S0022-1694(00)00237-7An urban inundation model, combining a Storm sewer model SWMM, two-dimensional (2D) diffusive overland-flow model and operations of pumping stations, has been developed to simulate inundation in urban areas caused by the surcharge of Storm Sewers and outlet pumping stations. The movement of water in the studied urban watershed is characterized by two components, namely, the Storm sewer flow component and the surcharge-induced inundation component. SWMM is employed to solve the Storm sewer flow component and to provide the surcharged flow hydrographs for surface runoff exceeding the capacity of the Storm Sewers. The 2D diffusive overland-flow model considering the non-inertia equation with Alternative Direction Explicit numerical scheme is then used to calculate the detailed inundation zones and depths due to the surcharged water on overland surface. Drainage by pumping stations at outlets of the Storm sewer system has also been taken into consideration. The parameters of the model are calibrated and verified for discrete Storms. The combined model is suitable for analysis of inundation on urban areas due to overflow of Storm Sewers and flooding caused by failure of pumping stations. Simulated results can be applied to establish flood-mitigation measures