Event-based design tool for construction site erosion and sediment controls

Trenouth, William R.; Gharabaghi, Bahram

doi:10.1016/j.jhydrol.2015.06.054

Cited by 11 publications

(5 citation statements)

References 12 publications

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“…Meteorological as well as traffic study data were collated for these events as input data used to train predictive neural networks models for the estimation of the key parameters needed to define the statistical distribution of seasonal event mean TSS and heavy metals concentrations, as well as the mean annual unit area loads of several commonly reported heavy metal species. Accurate predictive tools are needed to estimate the lifetime loading of heavy metals so that appropriately selected and sized treatment media can be implemented for the protection of environmentally sensitive areas (Schmueli, 2010;McIntyre et al, 2015;Trenouth and Gharabaghi, 2015a) (see Fig. 5).…”

Section: Resultsmentioning

confidence: 99%

“…(8) (Sattar and Gharabaghi, 2015). Dh and DE are the calculated change int eh objective function and resultant change in parameter, respectively (Atieh et al, 2015b;Trenouth and Gharabaghi, 2015a).…”

Section: Uncertainty Analysismentioning

confidence: 99%

“…Our work attempts to do so through assembly of a large dataset comprised of 940 highway runoff events, which report a total of eight separate physicochemical parameters (TSS, Cu, Zn, Pb, Cr, TN, TKN and TP), as well as five of the parameters widely understood to govern the pollutant concentrations in runoff (rainfall depth [RD], rainfall intensity [RFI], average annual daily traffic [AADT], antecedent dry period [ADP] and seasonality [season]). Acknowledging these uncertainties, the predictive utility trained ANNs applied in the context of complex, nonlinear systems cannot be understated, and this makes their use worth investigating (Kisi et al, 2013;Trenouth and Gharabaghi, 2015a).…”

Section: Introductionmentioning

confidence: 99%

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Highway runoff quality models for the protection of environmentally sensitive areas

Trenouth

Gharabaghi

2016

Journal of Hydrology

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Section: Resultsmentioning

confidence: 99%

Section: Uncertainty Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Highway runoff quality models for the protection of environmentally sensitive areas

Trenouth

Gharabaghi

2016

Journal of Hydrology

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“…ANNs loosely resemble the pattern-recognition framework of the human brain and are an alternative prediction technique to traditional statistically-based models such as multiple regression (ASCE Task Committee, 2000). ANNs are able to extract complex, non-linear relationships and have demonstrated strong performance in their application to environmental phenomenon (Atieh, Mehltretter, Gharabaghi, & Rudra, 2015;Trenouth & Gharabaghi, 2015a). The model developed by used a global data set consisting of more than 900 discrete storm events to predict the mean daily unit area load (µg/m 2 * d) of pollutants on a road surface, and is based on the following input parameters: For all inputs, the log-transformed mean and standard deviation was used, giving a total of eight input variables.…”

Section: Re (Removal Efficiency)mentioning

confidence: 99%

Compost Biofilters for Protection of Environmentally Sensitive Areas Receiving Roadway Runoff

McTaggart¹,

Trenouth²,

Stajowski³

et al. 2018

ESR

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Runoff from roads is well recognized as containing a host of heavy metals that may degrade water quality. This awareness has driven a focus towards management strategies intended to attenuate the transport of heavy metals to nearby water bodies. Composted biomass has been shown to have the ability to retain common roadway runoff pollutants, leading to interest in its use as a filter material for the protection of environmentally sensitive areas. Compost biofilters can be constructed in a tubular geometry to intercept surface flow and can be amended with polymers for the targeted removal of specific pollutants. Addressing the need for validation of this concept under field conditions, commercially available tubular biofilters with three different polymeric amendments were studied to assess their efficiency in removing heavy metals and total suspended solids. The filters each contained a mixture of municipal compost and were installed in series as a treatment train adjacent to a busy section of highway 401 in southern Ontario, Canada. Untreated inflow concentrations of chromium, cadmium, copper and lead exceeded Ontario Provincial Water Quality Objectives (PWQO). The biofilter treatment train reduced chromium to below its PWQO, while copper remained above. Results demonstrate removal efficiencies for the treatment train ranging from 15.5% (nickel) to 93.6% (chromium). The low removal efficiency of nickel is attributed in part to its low inflow concentration. Each consecutive filter also reduced TSS concentrations, with an event mean removal efficiency of 50% for the treatment train as a whole.

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“…In urban environment the resulting erosion causes the soiling and damage of buildings, soiling of roads with subsequent secondary dust generation and, last but not least, the clogging of sewers in which the eroded soil with remainders of concrete mix often cause the failure of sewerage and drainage systems [7], [8]. At the same time it increases the mechanical load and, due to the concentration of chemical agents in the soil, also the chemical load of the waste water treatment plants.…”

Section: Design Construction and Safety Of Underground Structuresmentioning

confidence: 99%

Environment Effects - Dust Pollution and Soil Protection

Svoboda

Kurth

2016

AMM

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Human activities have a considerable effect upon the development of all components of the natural environment. The activity of construction represents a considerable influence upon the environment, with its significance growing with the rate of urbanisation. The high concentration of people in cities and towns has resulted in this urban environment representing the living community for over 50 percent of the population. Construction based activities not only provide material conditions for an urban population, but also influence its social behaviour. As such, no civil engineering designs are able to ignore the influences or impacts which structures may have on the environment especially dust pollution and erosion of soil that is one of the principal resources of the biosphere. As a limited and irreplaceable natural resource it becomes the limiting factor of the development of society in case of its destruction or degradation. By being the living space of most plants it enables energy transformation in the framework of the ecosystem by way of the autothropic stratum represented by the green vegetation. Organic matter produced on the soil serves in numerous ways, whether directly or indirectly, the needs of man. Also the subsoil water runoff depends on soil properties. The loss of soil transforms the subsoil water runoff into surface water runoff with all negative consequences of such transformation.

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Event-based design tool for construction site erosion and sediment controls

Cited by 11 publications

References 12 publications

Highway runoff quality models for the protection of environmentally sensitive areas

Highway runoff quality models for the protection of environmentally sensitive areas

Compost Biofilters for Protection of Environmentally Sensitive Areas Receiving Roadway Runoff

Environment Effects - Dust Pollution and Soil Protection

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