Synthetic Pollutograph by Prediction Indices: An Evaluation in Several Urban Sub-Catchments

Abstract

A generalized methodology applicable to any urban sub-catchment to calculate the pollution curve due to combined sewer overflows would help to implement integrated management policies to reduce urban impacts on the environment. An existing methodology to predict the pollutographs associated to rainfall events is tested in five different sub-catchments with very different pluviometry. Ninety-three rainfall events have been considered by measuring the in-sewer turbidity along the runoff episodes. Such data is then evaluated to obtain two prediction indices: the time to peak of pollutograph ITPP, and the maximum turbidity concentration ICMAX. These indices may be used with linear regressions to calculate the characteristics of pollutographs, such as the time to the peak, TPP, the maximum concentration of turbidity, CMAXtb, and the time to descent, TDP. These parameters allow to estimate the pollutographs of a sub-catchment. The comparison between pollutographs measured in the Ensanche sub-catchment and those calculated with the methodology shows a good agreement in terms of the root mean square deviation between samples and estimated values with the model proposed. Hence, the methodology could be a key way to find synthetic pollutographs for any sub-catchment.

Fine Sediment Modeling During Storm-Based Events in the River Bandon, Ireland

“…Er (%) all storm events VanSickle and Beschta [2] modified 9.0% Garcia et al [3,4] Figure 12 presents the cumulative event suspended sediment, ESS, in tons for the period of study for all 27 storm events. It may be concluded that, in general, all the models proposed at the annual scale are able to reproduce the measured values of SSC for the storm events.…”

“…The final two variables, DWP and PEEV, were not previously included in the proposed models and constitute a novelty when applying these models. Van Sickle and Bechsta [2] Garcia et al [3,4] Shear stress based model The importance of the present work is based on the recognition that, to model the suspended sediment concentration during different storm events, the following has to be taken into account: the quantity of fine sediments existing in the bed at the initiation of the storm event and how consolidated these sediments are. This is done through the following measurable variables: the existing fine sediment volume stored in the bed, S(t−1); the period between storm events, DWP; and the volume eroded during the previous event, PEEV.…”

“…Compliance with the European Union Water Framework Directive, the Freshwater Fish Directive, and the Habitats Directive requires the monitoring and modeling of fine sediment behavior and concentrations in riverine systems. Modeling provides an understanding of the dynamics of suspended sediment flux and allows the study of impacts of fine sediments on, for example, riverine fish populations [1][2][3][4][5][6]. Different types of model are commonly used to quantify the suspended sediment concentration, SSC, in gravel-bed rivers.…”

“…Vansickle and Beschta [2] proposed an empirically-based model for storm events that takes into account sediments stored in the bed and also allows calculation of the SSC in the streamflow during storm events. Other models are statistically-based [3,4] and were originally proposed to predict the pollutograph, i.e., the concentration of a substance transported in a sewer like-flow during storm events. a sewer like-flow during storm events.…”

“…One is the empirically-based model of Vansickle and Beschta [2], modified due to the introduction of a variable parameter to take into account the variation of the bed storage and its consolidation. The others are the statistically-based model of Garcia et al [3,4] and a shear stress-based model. The total accumulated value of suspended sediments mobilized at each storm event is compared with measured values.…”