Urban Runoff Model Research Articles

Modeling the Effect of Summertime Heating on Urban Runoff Temperature1

Abstract: The summertime heating of runoff in urban areas is recognized as a common and consistent urban climatological phenomenon. In this study, a simple thermal urban runoff model (TURM) is presented for the net energy flux at the impervious surfaces of urban areas to account for the heat transferred to runoff. The first step in developing TURM consists of calculating the various factors that control how urban impervious areas absorb heat and transfer it to moving water on the surface. The runoff temperature is determined based on the interactions of the physical characteristics of the impervious areas, the weather, and the heat transfer between the moving film of runoff and the impervious surface common in urban areas. Key surface and weather factors that affect runoff temperature predictions are type of impervious surface, air temperature, humidity, solar radiation before and during rain, rainfall intensity, and rainfall temperature. Runoff from pervious areas is considered separately and estimated using the Green‐Ampt Mein‐Larson rainfall excess method. Pervious runoff temperature is estimated as the rainfall temperature. Field measurements indicate that wet bulb temperature can be used as a surrogate for rainfall temperature and that runoff temperatures from sod average just 2°C higher than rainfall temperatures. Differences between measured and predicted impervious runoff temperature average approximately 2°C, indicating that TURM is a useful tool for determining runoff temperatures for typical urban areas.

Compaction’s Impacts on Urban Storm-Water Infiltration

Soil infiltration is a critical component of most urban runoff models. However, it has been well documented that, during urbanization, soils are greatly modified, especially in relation to soil density. Increased soil compaction results in soils that do not behave in a manner predicted by traditional infiltration models. Laboratory and field tests were conducted to investigate detailed infiltration behavior of disturbed urban soils for a variety of soil textures and levels of compaction. The results from traditional permeability tests on several soil groups showed that, as expected, the degree of compaction greatly affected the steady-state infiltration rate. The field tests highlighted the importance of compaction on the infiltration rate of sandy soils, with minimal effect seen from antecedent moisture conditions. For the clayey soils, however, both the compaction level and antecedent moisture conditions were important in determining the steady-state infiltration rate.

Establishing Stage‐Discharge Relationships in Multiple‐Channelled, Ephemeral Rivers: a Case Study of the Diamantina River, Australia

AbstractThe method for deriving a stage‐discharge relationship has a significant impact on the shape of the river's rating curve. We compare rating curves for a single gauging station on a mutiple‐channelled river in Australia compiled using three different methods – the Urban Runoff and Basin Systems (URBS) rainfall‐runoff model, an empirically‐based velocity‐area method, and the predictive Hydrologic Engineering Centre‐River Analysis System (HEC‐RAS) computer model. The rainfall‐runoff model was found to predict lower discharges for stage heights over 3.5 m than both the empirically‐based velocity‐area method and the HEC‐RAS model. The empirically‐based velocity‐area model predicts similar discharges to the rainfall‐runoff model for stage heights less than 3 m but much higher discharges for larger flood events. The HEC‐RAS model predicts higher discharges than both other rating curves at all stage heights probably due to under‐estimation of the impact of surface roughness on flow velocity. The three models are discussed with particular reference to their use on multiple‐channelled rivers.

격자기반의 도시유역 지표면 유출모형의 개발 및 적용

A grid-based urban surface runoff model for simulating the temporal variation and spatial distribution of overland flow in a drainage area was developed. The process of routing of overland flow is modeled by the nonlinear storage equation which is composed of the continuity equation and the Manning`s equation. For model operation, the drainage area is divided into grid areas, and spatially distributed topographical and hydrological information for model inputs is provided. Then overland flow is routed for each of the discretized cells of the area. In order to test the applicability of this model, temporal variations and spatial distributions of flow depth and overland flow was simulated in a fictitious and a real urbanized Kunja drainage area. Results indicate that the model can simulate reasonably well the urban runoff hydrograph.

From single-objective to multiple-objective multiple-rainfall events automatic calibration of urban storm water runoff models using genetic algorithms

The calibration of storm water runoff models is a complex task. Early attempts focused on the choice of a performance criterion function that could capture all the facets of the problem into a single-objective framework. Subsequently, the awareness that a good calibration must necessarily take into account conflicting objectives led to the adoption of more sophisticated multi-objective approaches. Only recently, the focus has shifted towards effective ways of exploiting the mounting information provided by the availability of many sets of concurrent rainfall and flow measurements. This paper revisits through a case study the transition just elucidated: the calibration of a SWMM model applied to a catchment in Singapore is tackled through a single-objective, a multi-objective and a multi-objective multiple-event (MOME) paradigm respectively. A new approach to support the latter is presented herein. It consists in formulating the problem of model calibration as a multi-objective problem with m x r objective functions, where m and r are the number of performance criteria and rainfall events respectively, that must be optimized simultaneously. Results suggest that the new MOME framework performs significantly better than the others tested on the case study presented.

Application of MCMC–GSA model calibration method to urban runoff quality modeling

In stormwater quality modeling, estimating the confidence level in conceptual model parameters is necessary but difficult. The applicability and the effectiveness of a method for model calibration and model uncertainty analysis in the case of a four parameters lumped urban runoff quality model are illustrated in this paper. This method consists of a combination of the Metropolis algorithm for parameters’ uncertainties and correlation assessment and a variance-based method for global sensitivity analysis. The use of the Metropolis algorithm to estimate the posterior distribution of parameters through a likelihood measure allows the replicated Latin hypercube sampling method to compute the parameters’ importance measures. Calibration results illustrate the usefulness of the Metropolis algorithm in the assessment of parameters’ uncertainties and their interaction structure. The sensitivity analysis demonstrates the insignificance of some parameters in terms of driving the model to have a good conformity with the data. This method provides a realistic evaluation of the conceptual description of the processes used in models and a progress in our capability to assess parameters’ uncertainties.

A benchmark methodology for managing uncertainties in urban runoff quality models

In this paper we present a benchmarking methodology, which aims at comparing urban runoff quality models, based on the Bayesian theory. After choosing the different configurations of models to be tested, this methodology uses the Metropolis algorithm, a general MCMC sampling method, to estimate the posterior distributions of the models' parameters. The analysis of these posterior distributions allows a quantitative assessment of the parameters' uncertainties and their interaction structure, and provides information about the sensitivity of the probability distribution of the model output to parameters. The effectiveness and efficiency of this methodology are illustrated in the context of 4 configurations of pollutants' accumulation/erosion models, tested on 4 street subcatchments. Calibration results demonstrate that the Metropolis algorithm produces reliable inferences of parameters thus, helping on the improvement of the mathematical concept of model equations.

Curve Numbers in Stormwater Runoff Simulation

Urban runoff models require the determination of excess rainfall for pervious areas in catchments. This is generally achieved by means of infiltration equatio…

Modeling the Effects of Air Quality Policy Changes on Water Quality in Urban Areas

This paper describes the development and application of an integrated modeling framework composed of an urban air chemistry model, an urban runoff model, and a water-quality model. The models were linked to simulate the fate and transport of air emissions of nitrogen compounds in the air, urban watershed, surface water runoff, and in a coastal receiving-water body. The model linkage is demonstrated by evaluating the potential water quality implications of reducing NOx emissions by 32%, volatile organic compound emissions by 51%, and ammonia emissions by 30%, representing changes from 1987 levels to proposed 2000 target levels in Los Angeles, California, USA. Simulations of the Los Angeles dry season during the summer of 1987 (June 1 to August 31) indicated that by reducing emissions from 1987 to proposed year 2000 levels, the dry deposition nitrogen loads to Santa Monica Bay and the Ballona Creek watershed were reduced 21.4% and 15.0%, respectively. Water quality modeling results indicated that dry season atmospheric load reductions to the Ballona Creek Estuary did not reduce chlorophyll-a levels or significantly raise nighttime dissolved oxygen levels because the magnitude of the reductions was negligible compared to non-atmospheric inputs of nitrogen compounds. Simulations of the time period from November 18, 1987 to December 4, 1987 during the Los Angeles wet season indicated that air emissions reductions produced an 18.6% reduction in the dry deposition nitrogen load to Santa Monica Bay, a 15.5% reduction in the dry deposition nitrogen load to the Ballona Creek watershed, a 16.8% reduction in the wet deposition nitrogen load to the Ballona Creek watershed, and a 16.1% reduction in the stormwater discharge load from the Ballona Creek watershed. Although the wet season load reductions are significant, modeling results of the ultimate effect on the Ballona Creek Estuary water quality were inconclusive.

Improvements in Urban Sub-Catchment Runoff Modeling

This chapter describes the development of an improved sub-catchment runoff modeling technique for urban catchments to help overcome parameter scaling and probl…

On Automatic Calibration of the SWMM Model

Conceptual urban runoff (CUR) models, such as the U.S. Environmental Protection Agency Storm Water Management Model (Huber and Dickinson, 1988), or SWMM, are c…

POLYNOMIAL‐BASED DISAGGREGATION OF HOURLY RAINFALL FOR CONTINUOUS HYDROLOGIC SIMULATION1

ABSTRACTHydrologic modeling of urban watersheds for designs and analyses of stormwater conveyance facilities can be performed in either an event‐based or continuous fashion. Continuou simulation requires, among other things, the use of a time series of rainfall amounts. However, for urban drainage basins, which are typically small, the temporal resolution of the rainfall time series must be quite fine, and often on the order of 5 to 15 minutes. This poses a significant challenge because rainfall‐gauging records are usually kept only for hourly or longer time steps. The time step sizes in stochastic rainfall generators are usually also too large for application to urban runoff modeling situations. Thus, there is a need for methods by which hourly rainfall amounts can be disaggregated to shorter time intervals. This paper presents and compares a number of approaches to this problem, which are based on the use of polynomial approximating functions. Results of these evaluations indicate that a desegregation method presented by Ormsbee (1989) is a relatively good performer when storm durations are short (2 hours), and that a quadratic spline‐based approach is a good choice for longer‐duration storms. Based on these results, the Ormsbee technique is recommended because it provides good performance, and can be applied easily to long time series of precipitation records. The quadratic spline‐based approach is recommended as a close second choice because it performed the best most consistently, but remains more difficult to apply than the Ormsbee technique. Results of this study also indicate that, on average, all of the disaggregation methods evaluated introduce a severe negative bias into maximum rainfall intensities. This is cause for some well‐justified concern, as the characteristics of runoff hydrographs are quite sensitive to maximum storm intensities. Thus, there is a need to continue the search for simple yet effective hourly rainfall disaggregation methods.

Incorporating concepts from physical theory into stochastic modelling of urban runoff pollution

On evaluating the present or future state of integrated urban water systems, sewer drainage models, with rainfall as primary input, are often used to calculate the expected return periods of given detrimental acute pollution events and the uncertainty thereof. The model studied in the present paper incorporates notions of physical theory in a stochastic model of water level and particulate chemical oxygen demand (COD) at the overflow point of a Dutch combined sewer system. A stochastic model based on physical mechanisms has been formulated in continuous time. The extended Kalman filter has been used in conjunction with a maximum likelihood criteria and a non-linear state space formulation to decompose the error term into system noise terms and measurement errors. The bias generally obtained in deterministic modelling, by invariably and often inappropriately assuming all error to result from measurement inaccuracies, is thus avoided. Continuous time stochastic modelling incorporating physical, chemical and biological theory presents a possible modelling alternative. These preliminary results suggest that further work is needed in order to fully appreciate the method's potential and limitations in the field of urban runoff pollution modelling.

Incorporating concepts from physical theory into stochastic modelling of urban runoff pollution

On evaluating the present or future state of integrated urban water systems, sewer drainage models, with rainfall as primary input, are often used to calculate the expected return periods of given detrimental acute pollution events and the uncertainty thereof. The model studied in the present paper incorporates notions of physical theory in a stochastic model of water level and particulate chemical oxygen demand (COD) at the overflow point of a Dutch combined sewer system. A stochastic model based on physical mechanisms has been formulated in continuous time. The extended Kaiman filter has been used in conjunction with a maximum likelihood criteria and a non-linear state space formulation to decompose the error term into system noise terms and measurement errors. The bias generally obtained in deterministic modelling, by invariably and often inappropriately assuming all error to result from measurement inaccuracies, is thus avoided. Continuous time stochastic modelling incorporating physical, chemical and biological theory presents a possible modelling alternative. These preliminary results suggest that further work is needed in order to fully appreciate the method's potential and limitations in the field of urban runoff pollution modelling.

Towards a Shallow Groundwater Routine for Modeling Infiltration BMPs in Urban Stormwater Models

Groundwater flow is an important component of the hydrologic cycle in urban areas. However, few urban runoff models realistically simulate shallow groundwater …

A statistical approach to urban runoff pollution modelling

In evaluating the present or future state of integrated urban water systems, sewer drainage models are often used in calculating the expected return periods of given detrimental acute pollution events and the uncertainty thereof. In the present study an urban runoff pollution model is developed for a Dutch combined sewer catchment. The water quantity model consists, in its final shape, of a combination of linear reservoirs in series and some physical characteristics of the sewer system. Attached to the water quantity model, a model was developed to simulate the suspended chemical oxygen demand (COD) concentration at the point of combined sewer overflow (CSO). The model structure has been developed on the basis of a rainfall input series and a water level and a suspended COD concentration output series. Physically interpretable parameters have been included where this could be statistically justified by the available observation. Model development has been based on an approximate likelihood ratio test, tests for parameter significance, parameter correlation and information criteria. It has been possible to formulate a model to describe the rainfall-runoff process at the Loenen catchment with a coefficient of determination (R2) of 0.83 for the water level at the overflow weir. The best model contained eight estimated parameters of which six were directly interpretable in traditional urban drainage terms. A three parameter suspended COD concentration model was developed with an R2 of 0.44. Though considerably less successful than the water quantity modelling, the results are interesting when viewed in relation to the small number of model parameters. Furthermore the model structure can be linked to existing resuspension theory involving a critical shear stress.

A statistical approach to urban runoff pollution modelling

In evaluating the present or future state of integrated urban water systems, sewer drainage models are often used in calculating the expected return periods of given detrimental acute pollution events and the uncertainty thereof. In the present study an urban runoff pollution model is developed for a Dutch combined sewer catchment. The water quantity model consists, in its final shape, of a combination of linear reservoirs in series and some physical characteristics of the sewer system. Attached to the water quantity model, a model was developed to simulate the suspended chemical oxygen demand (COD) concentration at the point of combined sewer overflow (CSO). The model structure has been developed on the basis of a rainfall input series and a water level and a suspended COD concentration output series. Physically interpretable parameters have been included where this could be statistically justified by the available observation. Model development has been based on an approximate likelihood ratio test, tests for parameter significance, parameter correlation and information criteria.It has been possible to formulate a model to describe the rainfall-runoff process at the Loenen catchment with a coefficient of determination (R2) of 0.83 for the water level at the overflow weir. The best model contained eight estimated parameters of which six were directly interpretable in traditional urban drainage terms. A three parameter suspended COD concentration model was developed with an R2 of 0.44. Though considerably less successful than the water quantity modelling, the results are interesting when viewed in relation to the small number of model parameters. Furthermore the model structure can be linked to existing resuspension theory involving a critical shear stress.

On storm movement and its applications

Rainfall-runoff models applicable for design and analysis of sewage systems in urban areas are further developed in order to represent better different physical processes going on on an urban catchment. However, one important part of the modelling procedure, the generation of the rainfall input is still a weak point. The main problem is lack of adequate rainfall data which represent temporal and spatial variations of the natural rainfall process. Storm movement is a natural phenomenon which influences urban runoff. However, the rainfall movement and its influence on runoff generation process is not represented in presently available urban runoff simulation models. Physical description of the rainfall movement and its parameters is given based on detailed measurements performed on twelve gauges in Lund, Sweden. The paper discusses the significance of the rainfall movement on the runoff generation process and gives suggestions how the rainfall movement parameters may be used in runoff modelling.

Practical simulation of sediment transport in urban runoff

A model for simulating sediment transport in urban areas has been developed based on the concept of "equivalent solids reservoirs." The processes of erosion, deposition, and routing have been represented by simple algorithms, which are applied to typical urban drainage elements (surfaces, gutters, pipes, and detention ponds). Input requirements are limited and include two sediment characteristics (particle size and relative density), scour and deposition parameters, and initial sediment loadings. Hydraulic properties of the drainage elements and the inflow hydrograph to each element are also required. This sediment transport submodel is an integral part of Q'URM, the Queen's University Urban Runoff Model. It has been developed and calibrated on the basis of data from a stormwater quality sampling program on the Calvin Park basin in Kingston, Ontario, and verified on the basis of data from an independent study of runoff quality in the Malvern basin in Burlington, Ontario. Key words: urban hydrology, sediment transport, simulation, measurement.

Spatial and temporal variability of dry dustfall and associated trace elements: Hamilton, Canada

Abstract Atmospheric total solids (TS) and elemental dry deposition rates were examined at four sites in Hamilton, Canada. TS and elemental loadings typically decreased in magnitude according to landuse: industrial > Central Business District > suburban > rural. Variability in elemental concentration enrichment vas related to landuse, and for Cu, variability was also related to changes in the dominant wind direction between sample periods. Information on dry dustfall is important for various types of research, including urban runoff and air quality modelling, ecosystem nutrient cycling and epidemiological studies.