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.     

Uncertainty analysis of urban sewer system using spatial simulation of radar rainfall fields: New York City case study

The goal of this study is to investigate the uncertainty of an urban sewer system’s response under various rainfall and infrastructure scenarios by applying a recently developed nonparametric copula-based simulation approach to extreme rainfall fields. The approach allows for Monte Carlo simulation of multiple variables with differing marginal distributions and arbitrary dependence structure. The independent and identically distributed daily extreme rainfall events of the corresponding urban area, extracted from nationwide high resolution radar data stage IV, are the inputs of the spatial simulator. The simulated extreme rainfall fields were used to calculate excess runoff using the Natural Resources Conservation Service’s approach. New York City is selected as a case study and the results highlight the importance of preserving the spatial dependence of rainfall fields between the grids, even for simplified hydrologic models. This study estimates the probability of combined sewer overflows under extreme rainfall events and identifies the most effective locations in New York City to install green infrastructure for detaining excess stormwater runoff. The results of this study are beneficial for planners working on stormwater management and the approach is broadly applicable because it does not rely on extensive sewer system information.     

Estimating effective impervious area in urban watersheds using land cover,soil character and asymptotic curve number

Knowledge of the effective impervious area (EIA) or the degree to which impervious surfaces are hydraulically connected to the drainage system is useful for improving hydrological and environmental models and assessing the effectiveness of green stormwater infrastructure in urban watersheds. The goal of this research is to develop a method to estimate EIA fraction in urban watersheds using readily available data. Since EIA is dependent on rainfall–runoff response and cannot be solely determined based on the physical characteristics of a watershed, the EIA is linked with the asymptotic curve number (CN), a watershed index that represents runoff characteristics. In order for the method to be applicable to ungauged watersheds, the asymptotic CN is predicted using land cover and soil data from 35 urban catchments in Minnesota and Texas, USA. Similar data from 11 other urban catchments in Wisconsin and Texas, USA, are used to validate the results. A set of runoff depth versus EIA fraction curves is also developed to assess the impact of EIA reduction on discharge from an urban watershed in land-use planning studies.     

Storm runoff response to rainfall pattern,magnitude and urbanization in a developing urban catchment

This study explored the hydrological impacts of urbanization, rainfall pattern and magnitude in a developing catchment. The Stormwater Management Model was parameterized, calibrated and validated in three development phases, which had the same catchment area (12.3 ha) but different land use intensities. The model calibration and validation by using sub‐hourly hydro‐meteorological data demonstrated a good performance of the model in predicting stormwater runoff in the different development phases. Based on the results, a threshold between minor and major rainfall events was identified and conservatively determined to be about 17.5 mm in depth. Direct runoff for minor storm events has a linear relationship with rainfall; however, events with a rainfall depth greater than the threshold yield a rainfall–runoff regression line with a clearly steeper slope. The difference in urban runoff generation between minor and major rainfall events diminishes with the increase of imperviousness. Urbanization leads to an increase in the production of stormwater runoff, but during infrequent major storms, the runoff contribution from pervious surfaces reduces the runoff changes owing to urbanization. Rainfall pattern exerts an important effect on urban runoff, which is reflected in pervious runoff. With the same magnitude, prolonged rainfall events with unvarying low intensity yield the smallest peak flow and the smallest total runoff, yet rainfall events with high peak intensity produce the largest runoff volume. These results demonstrate the different roles of impervious and pervious surfaces in runoff generation, and how runoff responds to rainstorms in urban catchments depends on hyetograph and event magnitude. Furthermore, the study provides a scientific basis of the design guideline sustainable urban drainage systems, which are still arbitrary in many countries. Copyright © 2015 John Wiley & Sons, Ltd.     

Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis.     

Understanding,management and modelling of urban hydrology and its consequences for receiving waters: A state of the art

Urban hydrology has evolved to improve the way urban runoff is managed for flood protection, public health and environmental protection. There have been significant recent advances in the measurement and prediction of urban rainfall, with technologies such as radar and microwave networks showing promise. The ability to predict urban hydrology has also evolved, to deliver models suited to the small temporal and spatial scales typical of urban and peri-urban applications. Urban stormwater management increasingly consider the needs of receiving environments as well as those of humans. There is a clear trend towards approaches that attempt to restore pre-development flow-regimes and water quality, with an increasing recognition that restoring a more natural water balance benefits not only the environment, but enhances the liveability of the urban landscape. Once regarded only as a nuisance, stormwater is now increasingly regarded as a resource. Despite the advances, many important challenges in urban hydrology remain. Further research into the spatio-temporal dynamics of urban rainfall is required to improve short-term rainfall prediction. The performance of stormwater technologies in restoring the water balance and in removing emerging priority pollutants remain poorly quantified. All of these challenges are overlaid by the uncertainty of climate change, which imposes a requirement to ensure that stormwater management systems are adaptable and resilient to changes. Urban hydrology will play a critical role in addressing these challenges.     

Urban hydrologic trend analysis based on rainfall and runoff data analysis and conceptual model calibration

Urban stormwater is a major cause of urban flooding and natural water pollution. It is therefore important to assess any hydrologic trends in urban catchments for stormwater management and planning. This study addresses urban hydrological trend analysis by examining trends in variables that characterize hydrological processes. The original and modified Mann‐Kendall methods are applied to trend detection in two French catchments, that is, Chassieu and La Lechere, based on approximately 1 decade of data from local monitoring programs. In both catchments, no trend is found in the major hydrological process driver (i.e., rainfall variables), whereas increasing trends are detected in runoff flow rates. As a consequence, the runoff coefficients tend to increase during the study period, probably due to growing imperviousness with the local urbanization process. In addition, conceptual urban rainfall‐runoff model parameters, which are identified via model calibration with an event based approach, are examined. Trend detection results indicate that there is no trend in the time of concentration in Chassieu, whereas a decreasing trend is present in La Lechere, which, however, needs to be validated with additional data. Sensitivity analysis indicates that the original Mann‐Kendall method is not sensitive to a few noisy values in the data series.     

Stochastic evaluation of the impact of sewer inlets’ hydraulic capacity on urban pluvial flooding

Sewer inlet structures are vital components of urban drainage systems and their operational conditions can largely affect the overall performance of the system. However, their hydraulic behaviour and the way in which it is affected by clogging is often overlooked in urban drainage models, thus leading to misrepresentation of system performance and, in particular, of flooding occurrence. In the present paper, a novel methodology is proposed to stochastically model stormwater urban drainage systems, taking the impact of sewer inlet operational conditions (e.g. clogging due to debris accumulation) on urban pluvial flooding into account. The proposed methodology comprises three main steps: (i) identification of sewer inlets most prone to clogging based upon a spatial analysis of their proximity to trees and evaluation of sewer inlet locations; (ii) Monte Carlo simulation of the capacity of inlets prone to clogging and subsequent simulation of flooding for each sewer inlet capacity scenario, and (iii) delineation of stochastic flood hazard maps. The proposed methodology was demonstrated using as case study design storms as well as two real storm events observed in the city of Coimbra (Portugal), which reportedly led to flooding in different areas of the catchment. The results show that sewer inlet capacity can indeed have a large impact on the occurrence of urban pluvial flooding and that it is essential to account for variations in sewer inlet capacity in urban drainage models. Overall, the stochastic methodology proposed in this study constitutes a useful tool for dealing with uncertainties in sewer inlet operational conditions and, as compared to more traditional deterministic approaches, it allows a more comprehensive assessment of urban pluvial flood hazard, which in turn enables better-informed flood risk assessment and management decisions.     

Evaluation of infiltration‐based stormwater management to restore hydrological processes in urban headwater streams

Urbanization threatens headwater stream ecosystems globally. Watershed restoration practices, such as infiltration‐based stormwater management, are implemented to mitigate the detrimental effects of urbanization on aquatic ecosystems. However, their effectiveness for restoring hydrologic processes and watershed storage remains poorly understood. Our study used a comparative hydrology approach to quantify the effects of urban watershed restoration on watershed hydrologic function in headwater streams within the Coastal Plain of Maryland, USA. We selected 11 headwater streams that spanned an urbanization–restoration gradient (4 forested, 4 urban‐degraded, and 3 urban‐degraded) to evaluate changes in watershed hydrologic function from both urbanization and watershed restoration. Discrete discharge and continuous, high‐frequency rainfall‐stage monitoring were conducted in each watershed. These datasets were used to develop 6 hydrologic metrics describing changes in watershed storage, flowpath connectivity, or the resultant stream flow regime. The hydrological effects of urbanization were clearly observed in all metrics, but only 1 of the 3 restored watersheds exhibited partially restored hydrologic function. At this site, a larger minimum runoff threshold was observed relative to the urban‐degraded watersheds, suggesting enhanced infiltration of stormwater runoff within the restoration structure. However, baseflow in the stream draining this watershed remained low compared to the forested reference streams, suggesting that enhanced infiltration of stormwater runoff did not recharge subsurface storage zones contributing to stream baseflow. The highly variable responses among the 3 restored watersheds were likely due to the spatial heterogeneity of urban development, including the level of impervious cover and extent of the storm sewer network. This study yielded important knowledge on how restoration strategies, such as infiltration‐based stormwater management, modulated—or failed to modulate—hydrological processes affected by urbanization, which will help improve the design of future urban watershed management strategies. More broadly, we highlighted a multimetric approach that can be used to monitor the restoration of headwater stream ecosystems in disturbed landscapes.     

Use of RORB and SWMM models to an urban catchment in Singapore

The Runoff Routing Model (RORB) and the Storm Water Management Model (SWMM) are evaluated for the purpose of stormwater drainage design and management in an urban catachment in Singapore although the full capability of the SWMM model has not been utilized. Data preparation for testing the models are highlighted and sample runs are carried out for an actual storm event. Limitations and constraints of the parameter estimation are discussed. Comparison of the runoff results are made between RORB and SWMM models. Both the models can be incorporated without much difficulty to simulate urban drainage system in Singapore.     

Antecedent soil moisture conditions of different soil types in South‐western Ontario,Canada

Soil moisture conditions prior to input design storms need to be known in the planning and design of urban stormwater control facilities using the design storm approach. Limited information is available on these soil moisture conditions which are commonly referred to as the antecedent soil moisture conditions. In this study, a deterministic continuous simulation model was used to simulate antecedent soil moisture conditions under south‐western Ontario, Canada, climate conditions. A wide range of different soil types were investigated and various statistical analyses on the simulated antecedent soil moisture results were performed. Frequency analyses illustrated typical distributions of antecedent soil moisture conditions and the influence of finer and coarser textured soil particles. Empirical equations were developed for the estimation of average antecedent soil moisture conditions based on commonly known soil characteristics. Satisfactory performance of the empirical equations was demonstrated by comparing between field average antecedent soil moisture data and empirically estimated average antecedent soil moisture values. These equations are therefore recommended for use in urban stormwater studies incorporating the design storm approach. Copyright © 2010 John Wiley & Sons, Ltd.     

A statistically based runoff‐yield model coupling infiltration excess and saturation excess mechanisms

A statistically based runoff‐yield model is proposed in this paper. The model considers spatial heterogeneities of rainfall, soil infiltration capacity and soil water storage capacity that are main factors controlling runoff‐yield process. It assumes that the spatial variation of rainfall intensity at each time step can be characterized by a probability density function, which is estimated by matching the hyetograph through goodness‐of‐fit measure, whereas the spatial heterogeneities of soil infiltration capacity and soil water storage capacity are described by parabola‐type functions. Surface runoff is calculated according to infiltration excess mechanism; the statistical distribution of surface runoff rate can be deduced with the joint distribution of rainfall intensity and soil infiltration rate, thus obtaining a quasi‐analytical solution for surface runoff. Based on saturation excess mechanism, the groundwater flow (flows below the ground are collectively referred to as groundwater flow) is calculated by infiltration and the probability distribution of soil water storage capacity. Consequently, the total runoff is composed of infiltration excess and saturation excess runoff components. As an example, this model is applied to flood event simulation in Dongwan catchment, a semi‐humid region and a tributary of Yellow River in China. It indicates that the proposed runoff‐yield model could achieve acceptable accuracy. Copyright © 2011 John Wiley & Sons, Ltd.     

A note on estimating urban roof runoff with a forest evaporation model

A model developed for estimating the evaporation of rainfall intercepted by forest canopies is applied to estimate measurements of the average runoff from the roofs of six houses made in a previous study of hydrological processes in an urban environment. The model is applied using values of the mean rates of wet canopy evaporation and rainfall derived previously for forests and an estimate of the roof storage capacity derived from the data collected in the previous study. Although the model prediction is sensitive to the value of storage capacity, close correlation between the modelled and measured runoff indicates that the model captures the essential processes. It is concluded that the process of evaporation from an urban roof is sufficiently similar to that from a forest canopy for forest evaporation models to be used to give a useful estimate of urban roof runoff. Copyright © 2007 John Wiley & Sons, Ltd.     

A distributed monthly hydrological model for integrating spatial variations of basin topography and rainfall

Hydrological models at a monthly time‐scale are important tools for hydrological analysis, such as in impact assessment of climate change and regional water resources planning. Traditionally, monthly models adopt a conceptual, lumped‐parameter approach and cannot account for spatial variations of basin characteristics and climatic inputs. A large requirement for data often severely limits the utility of physically based, distributed‐parameter models. Based on the variable‐source‐area concept, we considered basin topography and rainfall to be two major factors whose spatial variations play a dominant role in runoff generation and developed a monthly model that is able to account for their influences in the spatial and temporal dynamics of water balance. As a hybrid of the Xinanjiang model and TOPMODEL, the new model is constructed by innovatively making use of the highly acclaimed simulation techniques in the two existing models. A major contribution of this model development study is to adopt the technique of implicit representation of soil moisture characteristics in the Xinanjiang model and use the TOPMODEL concept to integrate terrain variations into runoff simulation. Specifically, the TOPMODEL topographic index ln(a/tanβ) is converted into an index of relative difficulty in runoff generation (IRDG) and then the cumulative frequency distribution of IRDG is used to substitute the parabolic curve, which represents the spatial variation of soil storage capacity in the Xinanjiang model. Digital elevation model data play a key role in the modelling procedures on a geographical information system platform, including basin segmentation, estimation of rainfall for each sub‐basin and computation of terrain characteristics. Other monthly data for model calibration and validation are rainfall, pan evaporation and runoff. The new model has only three parameters to be estimated, i.e. watershed‐average field capacity WM, pan coefficient η and runoff generation coefficient α. Sensitivity analysis demonstrates that runoff is least sensitive to WM and, therefore, it can be determined by a prior estimation based on the climate and soil properties of the study basin. The other two parameters can be determined using optimization methods. Model testing was carried out in a number of nested sub‐basins of two watersheds (Yuanjiang River and Dongjiang River) in the humid region in central and southern China. Simulation results show that the model is capable of describing spatial and temporal variations of water balance components, including soil moisture content, evapotranspiration and runoff, over the watershed. With a minimal requirement for input data and parameterization, this terrain‐based distributed model is a valuable contribution to the ever‐advancing technology of hydrological modelling. Copyright © 2006 John Wiley & Sons, Ltd.     

Modelling of stormwater biofilters under random hydrologic variability: a case study of a car park at Monash University,Victoria (Australia)

Biofiltration systems represent an effective technology for the management of urban stormwater runoff volumes and quality. The performance of these systems, although largely dependent on their physical characteristics, is also strongly affected by the natural variability of runoff occurrence and volumes. This article presents a model that describes the statistical behaviour of the main variables involved in the water balance of a biofiltration system, given its main physical properties (filter media and vegetation types) and accounting for the natural inflow variability in terms of occurrence and water volumes. The model permits the analytical derivation of the long‐term (e.g. annual) probability density function of the soil water content in the filter media and the estimation of the main statistics of water fluxes, that is, outflow, evapotranspiration and overflow. By relating the soil water content in the filter media before inflow events to the outflow total nitrogen concentrations, the model also gives estimates of the statistics of nitrogen removal performance as a function of inflow variability. The model was tested against field data collected at a stormwater biofiltration system in Melbourne, Australia. The model could be used to rapidly assess the hydrologic and nitrogen treatment performance of alternative applications of biofiltration for stormwater management across a range of climates. Copyright © 2011 John Wiley & Sons, Ltd.     

Simulation of green roof test bed runoff

Low Impact Development (LID) aims to mitigate the hydrological impacts of urbanization by replication of processes in natural catchments. Green roofs covered with vegetation and pervious substrate are one alternative among a wide range of LID tools. Water retention of green roofs depends on many factors (e.g. local climate), and measurements remain crucial in evaluating their performance. The simulation of green roof retention by a hydrological model is one option to evaluate their potential benefits before implementation. In this paper, we evaluated the ability of the recently introduced LID green roof module of the stormwater management model to replicate runoff from monitored green roof test beds under Nordic climate conditions. A parameter sensitivity analysis was conducted to identify calibration parameters. The model showed an overall acceptable performance, and the results indicated the importance of accurately estimating potential evapotranspiration rates for inter‐event periods, which is essential in representing the retention capacity regeneration. Copyright © 2015 John Wiley & Sons, Ltd.     

Water balance prediction in stormwater infiltration basins using 2-D modeling: An application to evaluate the clogging process

Sustainable urban drainage systems are built along roads and in urban areas to collect urban runoff and avoid flooding, and to filter water pollutants. Sediment collected by runoff is deposited in the stormwater basin and progressively reduces water infiltration efficiency, leading to the clogging of the basin. To help stormwater basin managers and stakeholders better understand and predict clogging rates in order to elaborate maintenance plans and schedules, water transport prediction models are necessary. However,because of the heterogeneous sediment hydrodynamic properties inside the stormwater basin, a twodimensional(2-D) water flow model is required to predict water levels and possible overflow as accurately as possible. Saturated hydraulic conductivity(Ks) and sediment water retention curves were measured in the overall sediment layer of the stormwater basin, in addition to sediment layer thickness and organic matter content(11 sampling points). Sediment depth was used to predict organic matter(OM) content, and the OM was used to predict Ks. Water height in the basin was modeled with the HYDRUS-2 D model by taking into account the sediment hydrodynamic properties distribution. The HYDRUS-2 D model gave a satisfactory representation of the measured data. Scenarios of the hydraulic properties of stormwater basin sediment were tested over time, and hydraulic resistance, R, was calculated to assess the stormwater basin performance. Presently, after 20 years of functioning, the stormwater basin still ensures efficient water infiltration, but the first outflow(Hydraulic resistance,R 24 h)) is expected to appear in the next 5 years, and clogging(R 47 h) in the next 13 years. This 2-D water balance model makes it possible to integrate the hydrodynamic heterogeneity of a stormwater basin. It gives interesting perspectives to better predict 2-D/3-D contaminant transport.     

Improving sustainability of urban drainage systems for climate change adaptation using best management practices: a case study of Tehran,Iran

Although the effectiveness of best management practices (BMPs) in reducing urban flooding is widely recognized, the improved sustainability achieved by implementing BMPs in upstream suburban areas, reducing downstream urban floods, is still debated. This study introduces a new definition of urban drainage system (UDS) sustainability, focusing on BMP usage to enhance system performance after adaptation to climate change. Three types of hydraulic reliability index (HRI) plus robustness and improvability indices were used to quantify the potential enhanced sustainability of the system in a changing climate, together with a climate change adaptability index (CCAI). The sustainability of UDS for the safe conveyance of storm-water runoff was investigated under different land-use scenarios: No BMP, BMP in urban areas, and BMP inside and upstream of urban areas, considering climate change impacts. Rainfall–runoff simulation alongside drainage network modelling was conducted using a storm-water management model (US EPA SWMM) to determine the inundation areas for both base-line and future climatic conditions. A new method for disaggregating daily rainfall to hourly, proposed to provide a finer resolution of input rainfall to SWMM, was applied to a semi-urbanized catchment whose upstream runoff from mountainous areas may contribute to the storm-water runoff in downstream urban parts. Our findings confirm an increase in the number of inundation points and reduction in sustainability indices of UDS due to climate change. The results present an increase in UDS reliability from 4% to 16% and improvements in other sustainability indicators using BMPs in upstream suburban areas compared to implementing them in urban areas.     

Long‐term runoff forecasting by combining hydrological models and meteorological records

Reservoir operation is generally based on the inflows of the upstream catchment of the reservoir. If the arriving inflows can be forecasted, that can benefit reservoir operation and management. This study attempts to construct a long‐term inflow‐forecasting model by combining a continuous rainfall–runoff model with the long‐term weather outlook from the Central Weather Bureau of Taiwan. The analytical results demonstrate that the continuous rainfall–runoff model has good inflow simulation performance by using 10‐day meteorological and inflow records over a 33‐year period for model calibration and verification. The long‐term inflow forecasting during the dry season was further conducted by combining the continuous rainfall–runoff model and the long‐term weather outlook, which was found to have good performance. Copyright © 2005 John Wiley & Sons, Ltd.