Wash-off Function Research Articles

Using SWMM for emergency response planning: A case study evaluating biological agent transport under various rainfall scenarios and urban surfaces

To assist in emergency preparedness for a biological agent terrorist attack or accidental pathogen release, potential contaminant levels and migration pathways of spores spread by urban stormwater were evaluated using a Storm Water Management Model (SWMM) of U.S. Coast Guard Base Elizabeth City, North Carolina. The high temporal-spatial resolution SWMM model was built using spore concentrations in stormwater runoff from asphalt, grass, and concrete collected from a point-scale field study. The subsequent modeled contamination scenarios included a notional plume release and point releases mimicking the field study under three rainfall conditions. The rainfall scenarios included a 6-hour natural rainfall event on Dec. 8, 2021 and two design storms (2-year and 100-year events). The observed spore concentrations from asphalt and concrete from the actual field experiment were applied to calibrate the washoff parameters in the SWMM model, using an exponential washoff function. The calibrated washoff coefficient (c1) and exponent (c2) were 0.01 and 1.00 for asphalt, 0.05 and 1.45 for grass, and 2.45 and 1.00 for concrete, respectively. The calibrated SWMM model simulated spore concentrations in runoff at times and magnitudes similar to the field study data. In the point release modeled scenario, the concrete surface generated 55.6% higher average spore concentrations than asphalt. Similarly, in the field experiment, a 175% (p < 0.05) higher average spore concentration in surface runoff was observed from concrete than from asphalt. This study demonstrates how SWMM may be used to evaluate spore washoff from urban surfaces under different precipitation amounts, intensities, and durations, and how visualized spatial migration pathways in stormwater runoff may be used for emergency planning and remediation.

Examination of the exponential wash-off function using experimental data

The standard exponential wash-off function has been widely adopted in urban stormwater quality models and tested in many studies of sediment wash-off experiments. There is neither sufficient information on the wash-off coefficients for other types of pollutant nor a good mathematical interpretation that accounts for the effects of surface features on wash-off processes. This study assesses the standard exponential wash-off function using experimental data on the wash-off of various types of pollutant. In-situ wash-off experiments using simulated rainfalls were conducted in typical urban areas with various landuse. Experimental data from the literature were also analysed to support the examination. Mass balance requirement was always applied as a criterion in the experimental data analysis and wash-off model examination. The experimental results indicate that wash-off processes of organic pollutants (BOD5), nitrate (NO3), total oil and grease (TOG), total petroleum hydrocarbon (TPH) and coliform stochastically comply with the standard exponential function.

Rainfall Washoff of Spores From Concrete and Asphalt Surfaces.

After a biological terrorist attack, understanding the migration of agents such as Bacillus anthracis is critical due to their deadly nature. This is important in urban settings with higher likelihood of human exposure and a large fraction of impervious materials contributing to pollutant washoff. The study goals were to understand the removal of spores from urban surfaces under different rainfall conditions, to compare washoff of two B. anthracis surrogate spores, and to compare two empirical fits for the first flush of spores from small areas. Concrete and asphalt were inoculated with either Bacillus atrophaeus or Bacillus thuringiensis kurstaki spores and exposed to simulated rainfall. The study assessed goodness-of-fit for the Storm Water Management Model (SWMM)'s exponential washoff function compared to an alternative two-stage exponential function. The highest average washoff of spores was 15% for an hour-long experiment. Spore washoff was not significantly different for the two spore types, but there were significant differences in washoff from asphalt versus concrete with more occurring from asphalt. Average kinetic energy of the storm event impacted washoff from asphalt, but not concrete. The two-stage function had a better goodness-of-fit than the SWMM exponential function. As such, emergency responders should be aware that the spread of contamination is impacted by the droplet characteristics of the storm event and the surface material type in the contaminated area; modelers should be aware that different data-fitting approaches may be more appropriate for first-flush calculations of small washoff areas than those used for continuous long-term simulation of large subcatchments.

A modified wash-off function for stormwater suspended solids modelling

In urban areas, the classical exponential wash-off equation for modelling of stormwater suspended solids (SS) relates the washoff of solids to the overland flow rate, assuming that runoff is proportional to rainfall. However, in catchments where infiltration occurs through the pavement surface, this assumption may not be valid. Furthermore, many researchers have concluded that the effect of rain impaction, related to rain intensity, should be considered as a separate model parameter to runoff rate. To address this problem, a semi-deterministic stormwater quality model was developed which incorporated rain intensity directly in the exponential wash-off equation. The modified function was compared to the more classical wash-off equation using a dataset of 18 storm events sampled from a separate pipe and gully system in Dublin, Ireland. The modified wash-off equation showed a consistent improvement in the fit of observed SS fluxes at the outlet of the drainage system: the Nash-Sutcliffe index of modelled performance increased from 0.39 to 0.58 on average using the modified wash-off function. The form of the modified wash-off function allows for simple integration into many stormwater quality models currently in use, without the need for any additional model parameters.

SWMM의 수질 매개변수 민감도 및 불확실성 분석

Due to the rapid industrialization and urbanization, many studies on nonpoint source load reduction by SWMM. In this study, Sensitivity and uncertainty analysis for the SWMM Water Quality parameters, Max.Buildup, Rate Constant, EMC Coefficient and Cleaning Efficient, were conducted. Exponential and EMC functions were selected in the Buildup and Washoff function, respectively. As a results of sensitivity analysis, Rate Constant has the highest sensitivity and Max.Buildup, Cleaning Efficient and EMC Coefficient in the order. Rate Constant has the highest uncertainty as well. Max.buildup uncertainty index depended on simulation time and simulation time in accordance with time of concentration was more carefully determined in urban area than in forest and agricultural area. This result will be able to take advantage of sewer design in urban area.

Predicted transport of pyrethroid insecticides from an urban landscape to surface water

The authors developed a simple screening-level model of exposure of aquatic species to pyrethroid insecticides for the lower American River watershed (California, USA). The model incorporated both empirically derived washoff functions based on existing, small-scale precipitation simulations and empirical data on pyrethroid insecticide use and watershed properties for Sacramento County, California, USA. The authors calibrated the model to in-stream monitoring data and used it to predict daily river pyrethroid concentration from 1995 through 2010. The model predicted a marked increase in pyrethroid toxic units starting in 2000, coincident with an observed watershed-wide increase in pyrethroid use. After 2000, approximately 70% of the predicted total toxic unit exposure in the watershed was associated with the pyrethroids bifenthrin and cyfluthrin. Pyrethroid applications for aboveground structural pest control on the basis of suspension concentrate categorized product formulations accounted for greater than 97% of the predicted total toxic unit exposure. Projected application of mitigation strategies, such as curtailment of structural perimeter band and barrier treatments as recently adopted by the California Department of Pesticide Regulation, reduced predicted total toxic unit exposure by 84%. The model also predicted that similar reductions in surface-water concentrations of pyrethroids could be achieved through a switch from suspension concentrate-categorized products to emulsifiable concentrate-categorized products without restrictions on current-use practice. Even with these mitigation actions, the predicted concentration of some pyrethroids would continue to exceed chronic aquatic life criteria.

Atmospheric deposition and storm induced runoff of heavy metals from different impermeable urban surfaces

Contaminants deposited on impermeable surfaces migrate to stormwater following rainfall events, but accurately quantifying their spatial and temporal yields useful for mitigation purposes is challenging. To overcome limitations in current sampling methods, a system was developed for rapid quantification of contaminant build-up and wash-off dynamics from different impervious surfaces. Thin boards constructed of concrete and two types of asphalt were deployed at different locations of a large carpark to capture spatially distributed contaminants from dry atmospheric deposition over specified periods of time. Following experimental exposure time, the boards were then placed under a rainfall simulator in the laboratory to generate contaminant runoff under controlled conditions. Single parameter effects including surface roughness and material composition, number of antecedent dry days, rain intensity, and water quality on contaminant build-up and wash-off yields could be investigated. The method was applied to quantify spatial differences in deposition rates of contaminants (TSS, zinc, copper and lead) at two locations varying in their distance to vehicle traffic. Results showed that boards exposed at an unused part of the carpark >50 m from vehicular traffic captured similar amounts of contaminants compared with boards that were exposed directly adjacent to the access route, indicating substantial atmospheric contaminant transport. Furthermore, differences in contaminant accumulation as a function of surface composition were observed. Runoff from asphalt boards yielded higher zinc loads compared with concrete surfaces, whereas runoff from concrete surfaces resulted in higher TSS concentrations attributed to its smoother surfaces. The application of this method enables relationships between individual contaminant behaviour and specific catchment characteristics to be investigated and provides a technique to derive site-specific build-up and wash-off functions required for modelling contaminant loads from impermeable surfaces.

Urban nonpoint source pollution buildup and washoff models for simulating storm runoff quality in the Los Angeles County

Many urban nonpoint source pollution models utilize pollutant buildup and washoff functions to simulate storm runoff quality of urban catchments. In this paper, two urban pollutant washoff load models are derived using pollutant buildup and washoff functions. The first model assumes that there is no residual pollutant after a storm event while the second one assumes that there is always residual pollutant after each storm event. The developed models are calibrated and verified with observed data from an urban catchment in the Los Angeles County. The application results show that the developed model with consideration of residual pollutant is more capable of simulating nonpoint source pollution from urban storm runoff than that without consideration of residual pollutant. For the study area, residual pollutant should be considered in pollutant buildup and washoff functions for simulating urban nonpoint source pollution when the total runoff volume is less than 30 mm.

Estimation of storm runoff loads based on rainfall-related variables and power law models – Case study in Alexandra

This paper compares the use of simple regression equations of three commonly used pollutant build-up and wash-off functions, namely linear, power and exponential functions, to estimate event pollutant loads. The comparative study indicated that, event loads are better estimated as power functions of storm-related independent variables. On the notion that rainfall data are more readily available, easy and less expensive to collect than runoff data, the calibrated model was verified using rainfall volume as independent variable. The verified model was then used to develop load-duration-intensity curves to serve as predictive tools. Planners and engineers can use these predictive tools to obtain an approximate estimate of event pollutant loads in storm runoff from Alexandra (and also other townships with similar physical, land-use, climatic and hydraulic characteristics and water quality issues) for the purpose of managing or improving drainage conditions in the township.

An investigation of wash-off controlling parameters at urban and commercial monitoring sites

The relationship between the parameters of the wash-off function and the controlling hydrologic variables are investigated in this paper, assuming that the pollutant generation process basically depends on the watershed rainfall-runoff response characteristics. Data collected during an intense monitoring program carried out by the Department of Environmental Engineering of the University of Genova (Italy) within a residential area, an auto dismantler facility, a tourism terminal and a urban waste truck depot are used to this aim. The observed runoff events are classified into different TSS mass delivery processes and the occurrence of the first flush phenomenon is also investigated. The correlation between the mathematical parameters describing the exponential process and the hydrological parameters of the corresponding rainfall-runoff event is analysed: runoff parameters and in particular the maximum flow discharge over the time of concentration of the drainage network are proposed as the controlling factor for the total mass of pollutant that is made available for wash-off during each runoff event.

Hydrologic influence on stormwater pollution at two urban monitoring sites

The pollutant transport process operated by stormwater runoff on urban paved surfaces and the relationship between the parameters of the wash-off function and the controlling hydrologic variables are investigated in the present work. Data collected during two monitoring campaigns carried out at the plot scale within a residential area and an auto dismantler site are used to this aim. The observed runoff events are classified into different mass delivery processes and the occurrence of the first flush phenomenon is also investigated. The maximum flow discharge obtained as the average value over the time of concentration of the drainage network is proposed as the controlling factor for the total mass of pollutant that is made available for wash-off during each runoff event.

Analytical Urban Storm Water Quality Models Based on Pollutant Buildup and Washoff Processes

This paper presents methodology and major procedures for the development of analytical urban storm water quality models following derived probability distribution theory, which involves conceptualization of the three major components, i.e., the rainfall–runoff transformation, pollutant buildup, and washoff processes. In this study, two different types of the rainfall–runoff transformations are employed in an attempt to improve model performance by considering spatial variations of parameters associated with runoff generation mechanisms. By integrating different types of the rainfall–runoff transformations and pollutant buildup function with washoff function, two different types of pollutant washoff load models are formulated. Thereby, the probability distributions of the rainfall characteristics are mathematically transformed to create system storm water quality control measures, such as the average pollutant event mean concentration and long-term pollutant loads to receiving waters. These storm water qua...

A derived probability distribution approach to stormwater quality modeling

The closed-form analytical stormwater quality models are developed for simulating urban catchment pollutant buildup and washoff processes. By integrating the rainfall–runoff transformation with pollutant buildup and washoff functions, stormwater quality measures, such as the cumulative distribution functions (CDFs) of pollutant loads, the expected value of pollutant event mean concentrations (EMCs) and the average annual pollutant load can be derived. This paper presents methodologies and major procedures for the development of urban stormwater quality models based on derived probability distribution theory. In order to investigate the spatial variation in model parameters and its impact on stormwater pollutant buildup and washoff processes as well as pollutant loads to receiving waters, an extended form of the original rainfall–runoff transformation which is based on lumped runoff coefficient approach is proposed to differentiate runoff generation mechanisms between the impervious and pervious areas of the catchment. In addition, as a contrast to the aggregated pollutant buildup models formulated with a single lumped buildup parameter, the disaggregated form of the pollutant buildup model is proposed by introducing a number of physically-based parameters associated with pollutant buildup and washoff processes into the pollutant load models. The results from the case study indicate that analytical urban stormwater management model are capable of providing results in good agreement with the field measurements, and can be employed as alternatives to continuous simulation models in the evaluation of long-term stormwater quality measures.

Runoff Quality Analysis of Urban Catchments with Analytical Probabilistic Models

The assessment of stormwater runoff pollution from urban catchments is addressed within a probabilistic framework. The methodology utilizes probability density functions of rainfall event characteristics, a runoff coefficient based rainfall-runoff transformation, and commonly used pollutant buildup and washoff processes representations. Employing derived probability distribution theory, analytical probabilistic runoff quality models are derived using exponential buildup and washoff functions. The derived analytical models yield expressions for expected event pollutant washoff load, annual average washoff load, the probability distribution of event washoff load, and the long-term average pollutant event mean concentration (EMC). These derived models are verified with available field data from an urban catchment located in the Greater Toronto Area. The verification results suggest that these analytical probabilistic models can be used for the assessment of runoff pollutant loads from urban catchments during planning-level analyses. These are computationally efficient closed-form mathematical expressions that can be easily incorporated into the spreadsheets and are thus a useful tool as an alternative or complement to more resource-intensive simulation models.

Quality of roof runoff for groundwater infiltration

The assumption that roof runoff can be considered as non-polluted stormwater that can be discharged directly into natural water bodies without impairing their quality and use was examined in a field study. Concentrations of major ions; total C, N, and P; heavy metals (Cu, Zn, Pb, Cd, Cr, Mn, Fe) and pesticides (triazines, acetamides, phenoxy acids) were measured in runoff from an inclined tile roof, an inclined polyester roof and a flat gravel roof. Runoff from the first two roofs showed initially very high concentrations declining rapidly to lower constant levels. This first-flush effect was modelled using a first-order rate law (wash-off function). For most constituents, concentrations were in the range of the wet deposition after the first few mm runoff depth and total loads in the runoff corresponded approximately to the total (dry and wet) atmospheric deposition load. The flat gravel roof depicted a different behaviour. Rainwater was first retained before it overflowed. Consequently gravel will be weathered and most pollutants were partially retained in the gravel layer. However, corrosion of Cu in drains (rate about 5 g m −2 y −1) produced such high Cu concentrations that direct disposal of runoff is questionable.

Transport of polycyclic aromatic hydrocarbons through a partly urbanized river basin

The PAH-pollutant loads resulting from storm runoff to a receiving stream are associated with high concentrations of suspended sediments. This is explained by the sorption coefficients and isotherms on street dust, suspended solids, bedload and other sorbents. Pollutographs for a stream with storm runoff mainly from storm water overflows from a combined sewered medium sized town show strong ‘first-flush’ phenomena. Rainfall and bedload contribute only to a lesser extent to the overall transport which stems from street dust washoff. High correlation between total PAH load and maximum flow, but no relation between total PAH load and the number of days since the previous storm, indicates a ‘low washoff case’ under ‘transport limited’ conditions. 3.4-Benzopyrene load was modeled by a pollutant washoff function analoguous to that of the EPA storm water model.

Development of Improved Stormwater Quality Models

It is not possible to derive general pollutant washoff functions, for either storm event total loadings or instantaneous fluxes, that contain a given set of independent variables and give reasonable results for most areas, even with calibration. Therefore, a methodology is outlined that facilitates the development of models that can be used with increased confidence to predict urban stormwater pollutant washoff. The methodology consists of testing several linear and linear transform multiple regression models for estimating pollutant washoff loadings as a function of storm and basin characteristics, using measured data. The best model can be chosen for each pollutant using the coefficient of determination (R²) and other criteria. This methodology eliminates the need to estimate both pollutant buildup and washoff.