Selection of rainfall information as input data for the design of combined sewer overflow solutions

Jean, Marie-Ève; Duchesne, Sophie; Pelletier, Geneviève; Pleau, Martin

doi:10.1016/j.jhydrol.2018.08.064

Cited by 39 publications

(33 citation statements)

References 47 publications

(57 reference statements)

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“…For each rain event, the following independent and predictive variables were determined (Table 1): the rainfall depth (R d ), the maximum rainfall intensity at five minutes (I max ), the mean rainfall intensity (I mean ), the duration of the rainstorm event (D) and the dry weather duration before the rainfall event (D d ) [3,13,14,20,27]. The maximum intensity values (I max ) strongly depend on the time steps in which they are determined.…”

Section: Relationship Between Rain and Cso Characteristicsmentioning

confidence: 99%

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Determination of Pollution Loads in Spillways of the Combined Sewage Network of the City of Cuenca, Ecuador

Montalvo-Cedillo

Jerves-Cobo

Domínguez-Granda

2020

Water

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Combined sewer overflow (CSO) is one of the main causes of contamination in receiving bodies during the rainy period. The objective of this research was to evaluate the behavior of three combined sewage discharges into the Tomebamba River in the city of Cuenca, Ecuador. For this, the registration of 18 CSO events was carried out. The following water quality parameters were analyzed from the field survey (March 2017 to May 2018): conductivity, turbidity, BOD5, COD, fecal and total coliforms, nitrates, nitrites, ammoniacal nitrogen, dissolved orthophosphate and total phosphorus. The results show that CSOs contribute to the deterioration of the water quality of the Tomebamba River during the rainy season. The analysis of the dynamics of the pollutants determined that the maximum conductivity values occur at the beginning of the discharge, and the maximum turbidity is located near the peak discharge flow. The relationship between rain and the characteristics of the CSO was also analyzed through a canonical correlation analysis and partial least squares regression, obtaining a prediction model of pollutants based on the precipitation parameters. These results can be used for the implementation of integrated ecological models that enable a complete analysis of the city’s sanitation systems, their impact on the receiving bodies and their restoration.

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Section: Relationship Between Rain and Cso Characteristicsmentioning

confidence: 99%

“…For example, Canadian regulations require municipalities to demonstrate that new developments will not result in an increase in the frequency of CSO. For this, it is recommended to integrate land surface planning with projects to limit overall runoff [13,27].…”

Section: Introductionmentioning

confidence: 99%

Determination of Pollution Loads in Spillways of the Combined Sewage Network of the City of Cuenca, Ecuador

Montalvo-Cedillo

Jerves-Cobo

Domínguez-Granda

2020

Water

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“…They concluded that GIs alone could not entirely remove the CSO unless gray infrastructure with substantial storage was added to the system. Jean et al (2018) compared modeling and rainfall data selection methods for the estimation of the CSO volume reduction needed to achieve the CSO frequency control target and suggested continuous simulations over event‐based simulations.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Climate, Sizing, and Location Controls on Green Infrastructure Efficacy: A Timescale Framework

Hung

Harman

Hobbs

et al. 2020

Water Resources Research

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We investigate how the effectiveness of green infrastructure (GI) to mitigate the frequency and magnitude of significant discharge events and combined sewer overflows (CSOs) depend on both climate and sewershed characteristics and propose a theoretical framework for a holistic assessment of GI's efficacy. The framework is based on the comparison of three characteristic timescales that control the production of peak discharge: rainfall duration (t r ), travel time in the sewer network (t n ), and the duration of rain that would be required to fill the GI's storage (t GI ). Storm events can then be characterized by two ratios of these timescales: T n = t n /t GI and T r = t r /t GI . A third dimensionless number characterizes critical storms during which adverse events (such as CSOs) occur and allows us to identify the combinations of T n and T r for which GI may substantially mitigate those events. The results of numerical experiments with the model demonstrate that the storms for which GI can substantially reduce peak discharge and CSO volume typically occur in a narrow band of T n and T r . Within that band, the efficacy of GI may depend on the location of GI within the sewershed if network routing substantially affects the timing and magnitude of flood peaks. The proposed framework is applied to examine the efficacy of GI using historical precipitation data from two major U.S. cities: Philadelphia, PA, and Seattle, WA, and the results of this comparative analysis suggest that GI location is an important control on catchment-scale GI efficacy in Philadelphia, but less so in Seattle.Plain Language Summary Combined sewer overflows (CSO) occur when storm rainfall exceeds the capacity of the sewer system to drain it. Green infrastructure (GI) is intended to mitigate the occurrence and severity of CSOs. But how effective will it be in helping to manage CSOs? Here we present a theoretical framework to address this question, by focusing on the major physical controls on the efficacy of GI for managing CSOs, including the relative roles of climate, the size of the sewershed, and the location of the GI within it. The framework is based on three characteristic timescales: storm duration, travel time to the overflow location, and time required to fill GI storage. We use the framework to explore how GI might work differently in different places. The results show that GI is most effective under certain combinations of climate and sewershed conditions, and that the location of GI within the sewershed can be very critical. The latter effect was found to be more evident, for example, in Philadelphia, PA, than in Seattle, WA, due to differences in storm duration and intensity between these two places. In these ways, the proposed framework can support green infrastructure planning by providing insights on location-effectiveness tradeoffs.

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“…Полную картину изменения расходов сточных вод в течение года невозможно получить без изучения влияния поступления сточных вод в периоды выпадения дождевых осадков и снеготаяния, а также без определения коэффициентов неравномерности в периоды поступления смеси хозяйственно-бытовых сточных вод и поверхностных стоков [13][14][15].…”

Section: Introductionunclassified

Research of sewage intake of small settlements during the period of rain and snowmelt

Ivanenko

Senicheva

2019

Vestnik MGSU

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Изучение режима поступления городских сточных вод малых населенных пунктов в период выпадения дождей и снеготаяния С. [603][604][605][606][607][608][609] Изучение режима поступления городских сточных вод малых населенных пунктов в период выпадения дождей и снеготаяния И.И. Иваненко, К.С. Сеничева Санкт-Петербургский государственный архитектурно-строительный университет (СПбГАСУ), 190005, г. Санкт-Петербург, ул. 2-я Красноармейская, д. 4 А ННОТА Ц И Я Введение. Используемые в практике проектирования коэффициенты неравномерности поступления стоков для населенных пунктов с численностью жителей 1000 человек, как было определено в процессе анализа литературных данных, весьма разнятся по значениям, что может привести к существенным ошибкам в расчетах при проектировании головных очистных сооружений. На трех объектах, расположенных в Ленинградской области, проведены замеры расходов сточных вод. Ранее были определены коэффициенты неравномерности поступления сточных вод в сухой период года и предложена математическая зависимость для описания колебаний суточного коэффициента неравномерности стоков в течение года. Авторы продолжили работу в направлении определения коэффициентов неравномерности для населенных пунктов с численностью жителей 1000 человек. Дана информация по коэффициентам неравномерности в период выпадения дождей и снеготаяния для двух объектов. Материалы и методы. Для измерения суточных расходов городских сточных вод в деревне Большой Двор и поселке Цвылево Ленинградской области использованы расходомеры Взлет ЭР ЛайтМ ЭРСВ-540Ф-В. С помощью доступного архива погоды составлена выборка значений, соответствующих выпадению дождя и снеготаянию в период с 15.12.2016 по 14.12.2017 гг., определены соответствующие коэффициенты суточной неравномерности расходов стоков. Проведено сравнение данных различных объектов. Результаты. Предложена зависимость суточного коэффициента неравномерности периода таяния снега от средней температуры воздуха. Приведены результаты по влиянию количества осадков и продолжительности предшествующего периода засухи на суточный коэффициент неравномерности во время выпадения дождя. Выводы. Дополнена ранее разработанная методика определения расчетных расходов сточных вод для малых объектов с числом жителей 1000 человек. К ЛЮЧЕВЫЕ СЛОВА: водоотведение, малые населенные пункты, суточный коэффициент неравномерности, выпадение дождя, снеготаяние, определение расчетных расходов, коэффициенты неравномерности Д Л Я Ц ИТИРОВА НИ Я: Иваненко И.И., Сеничева К.С. Изучение режима поступления городских сточных вод малых населенных пунктов в период выпадения дождей и снеготаяния // Вестник МГСУ.

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Selection of rainfall information as input data for the design of combined sewer overflow solutions

Cited by 39 publications

References 47 publications

Determination of Pollution Loads in Spillways of the Combined Sewage Network of the City of Cuenca, Ecuador

Determination of Pollution Loads in Spillways of the Combined Sewage Network of the City of Cuenca, Ecuador

Assessment of Climate, Sizing, and Location Controls on Green Infrastructure Efficacy: A Timescale Framework

Research of sewage intake of small settlements during the period of rain and snowmelt

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