Urban Stormwater Drainage Systems Research Articles

Hydrodynamic simulation of urban stormwater drain (Delhi city, India) using iRIC Model

Flooding in urban areas takes place mainly due to increased urbanization, decrease in infiltration rate and poor infrastructure for stormwater drainage network. Nays2DFlood is a recently developed solver by iRIC for the simulation of river flow regime. The number of input data requirement is few which makes this solver superior to other models but has been rarely applied to urban catchments. In this paper, a hydrodynamic model was developed to assess the model’s feasibility to simulate urban stormwater drainage system of Delhi, capital city of India for mapping inundation extents using Nays2DFlood solver. The data used in this model is a DEM (5 × 5 m resolution) and daily discharge data of the drains. The simulated drainage is analysed keeping in mind the constraints which were observed during the collection of field data; the storm-water drains are choked, the drains have improper flow gradient or damaged flow gradients. Based on the simulated results, the water depth and velocity profiles were analysed for the drain. The model identified four critical locations where the problem like zig-zag bed slope of the drain, undersized cross-section of the drain and last but not the least the backflow problem which were in close agreement with the observed field data. The flood propagation exactly predicting the inundated area. Thus, Nays2DFlood solver model can also be applied to urban catchments for identifying the flood extent.

Sustainable Design of Urban Stormwater Drainage Systems by Implementing Detention Tank and LID Measures for Flooding Risk Control and Water Quality Management

With the increasing emphasis and application of the flooding control and mitigation measures of detention tank (DT) and low impact development (LID) in urban stormwater drainage systems (USDSs), the complex drainage flow process and corresponding water quality issues have also aroused great of interests and attentions from researchers and practitioners. This paper contributes to study the urban flooding control and water quality management with the implementation of DTs and LIDs in the USDS. A many-objective optimization (MOO) based design framework and analysis method is developed for achieving four objectives of USDS design. A realistic USDS is adopted for the case study, in which the DTs and LIDs are implemented by this extended MOO-based design method to achieve the optimal result of flooding risk control and water quality improvement. The obtained results are further analyzed for the characteristics of flooding risk control and water quality component evolution in the USDS. The results and analysis demonstrate the effectiveness and applicability of the designed DTs and LIDs to mitigate the flooding risk and improve water quality in USDS.

Evaluation of evolutionary algorithms for the optimization of storm water drainage network for an urbanized area

The studies pertaining to urban storm water drainage system have picked up importance lately in light of pluvial flooding. The flooding is mostly due to urban expansion, reduction in infiltration rate and environmental change. In order to minimize flooding, hydrologists are using conceptual rainfall–runoff models as a tool for predicting surface runoff and flood forecasting. Manual calibration is often a tedious process because of the involved subjectivity, which makes the automatic approach more preferable. In this study, three evolutionary algorithms (EAs), namely SFLA, GA and PSO, were used to calibrate SWMM parameters for the two study areas of the highly urbanized catchments of Delhi, India. The work incorporates auto-tuning of a widely used SWMM, via internal coupling of SWMM with all three EAs in MATLAB environment separately. Results were tested using statistical parameters, i.e., Nash–Sutcliffe efficiency (NSE), Percent Bias (PBIAS) and root-mean-square error–observations standard deviation ratio (RSR). GA results were in good agreement with the observed data in both the study area with NSE and PBIAS values lying between 0.60 and 0.91, and 1.29 and 7.41%, respectively. Also, RSR value was near zero, indicating reasonably good model performance. Subsequently, the model reasonably predicted the flooding hotspots that should be controlled to prevent any possible inundation of the surrounding areas. SFLA results were also promising, but better than PSO. Thus, the approach has demonstrated the potential use and combination of single-objective optimization algorithms and hydrodynamic models for assessing the risk in urban storm water drainage systems, providing valuable information for decision-makers.

Assessment of different MOEAs for rehabilitation evaluation of Urban Stormwater Drainage Systems – Case study: Eastern catchment of Tehran

Design/rehabilitation of urban stormwater drainage systems has become a challenging issue due to increasing frequency and severity of floods in urbanized areas. Optimization frameworks can provide a proficient computational tool for stormwater management. In this study, using four different optimization algorithms and EPA-SWMM (Environmental Protection Agency -StormWater Management Model) software, a coupled numerical and optimization model was developed to rehabilitate the drainage system in eastern Tehran, Iran. The current drainage network suffers from a significant lack of hydraulic capacity. Thus, combinations of relief tunnels and/or storage units were evaluated and optimal rehabilitation strategies were suggested according to minimizing conflicting objective functions of costs and flooding. Results have revealed that AMALGAM (A Multi-ALgorithm, Genetically Adaptive Multi-objective) outperformed three other algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm-II), NSHS (Non-dominated Sorting Harmony Search), and NSDE (Non-dominated Sorting Differential Evolution) for the evaluation of rehabilitation of Urban Stormwater Drainage Systems (USDSs) in terms of convergence and diversity criteria.

Hydrodynamic simulation of urban stormwater drain (Delhi city, India) using iRIC Model

Flooding in urban areas takes place mainly due to increased urbanization, decrease in infiltration rate and poor infrastructure for stormwater drainage network. Nays2DFlood is a recently developed solver by iRIC for the simulation of river flow regime. The number of input data requirement is few which makes this solver superior to other models but has been rarely applied to urban catchments. In this paper, a hydrodynamic model was developed to assess the model’s feasibility to simulate urban stormwater drainage system of Delhi, capital city of India for mapping inundation extents using Nays2DFlood solver. The data used in this model is a DEM (5 × 5 m resolution) and daily discharge data of the drains. The simulated drainage is analysed keeping in mind the constraints which were observed during the collection of field data; the storm-water drains are choked, the drains have improper flow gradient or damaged flow gradients. Based on the simulated results, the water depth and velocity profiles were analysed for the drain. The model identified four critical locations where the problem like zig-zag bed slope of the drain, undersized cross-section of the drain and last but not the least the backflow problem which were in close agreement with the observed field data. The flood propagation exactly predicting the inundated area. Thus, Nays2DFlood solver model can also be applied to urban catchments for identifying the flood extent.

Development of a stochastic framework to design/rehabilitate urban stormwater drainage systems based on a resilient approach

Urban floods may cause a wide range of undesirable consequences in populated areas when drainage networks do not have enough capacity or encounter unexpected loads such as blockage. Although both external loads (like heavy rainfalls) and internal factors such as structural failure/blockage of different parts of networks play an important role on urban inundation, most of the implemented design approaches only consider effects of external loads on Urban Stormwater Drainage Systems (USDSs). In this study, a new resilient and stochastic approach is developed by connecting a multi objective optimization algorithm to a numerical solver/meta-model within a Copula-based Monte-Carlo framework in order to design/rehabilitate of USDSs considering the related probabilities of external and internal unexpected conditions of loading. Results indicate the importance of considering the resilience in the rehabilitation of Tehran Stormwater Drainage System (TSDS), Tehran, Iran. Optimal strategies including a set of bypass lines, relief tunnels, and storage units, exhibited satisfactory performance in terms of enhancing the network resiliency.

3D Numerical Modeling of Geyser Formation by Release of Entrapped Air from Horizontal Pipe into Vertical Shaft

AbstractGeysers are explosive eruptions of air-water mixture from manholes in drainage systems. When the design capacity of urban storm water drainage systems is exceeded during extreme rainfall, r...

Optimization of storage tank locations in an urban stormwater drainage system using a two-stage approach

Storage is important for flood mitigation and non-point source pollution control. However, to seek a cost-effective design scheme for storage tanks is very complex. This paper presents a two-stage optimization framework to find an optimal scheme for storage tanks using storm water management model (SWMM). The objectives are to minimize flooding, total suspended solids (TSS) load and storage cost. The framework includes two modules: (i) the analytical module, which evaluates and ranks the flooding nodes with the analytic hierarchy process (AHP) using two indicators (flood depth and flood duration), and then obtains the preliminary scheme by calculating two efficiency indicators (flood reduction efficiency and TSS reduction efficiency); (ii) the iteration module, which obtains an optimal scheme using a generalized pattern search (GPS) method based on the preliminary scheme generated by the analytical module. The proposed approach was applied to a catchment in CZ city, China, to test its capability in choosing design alternatives. Different rainfall scenarios are considered to test its robustness. The results demonstrate that the optimal framework is feasible, and the optimization is fast based on the preliminary scheme. The optimized scheme is better than the preliminary scheme for reducing runoff and pollutant loads under a given storage cost. The multi-objective optimization framework presented in this paper may be useful in finding the best scheme of storage tanks or low impact development (LID) controls.

The influence of particle size on the first flush strength of urban stormwater runoff.

The presence of a first flush (FF) of suspended solids (SS) in stormwater runoff has important implications for the design of treatment facilities, as does the particle size of solids. Whilst numerous studies have examined the FF behaviour of SS, few have disaggregated FF trends by particle size. In this study, the FF behaviour of SS was investigated in five size ranges, sampled from an urban stormwater drainage system located in Dublin, Ireland. A weak FF was exhibited in the gross fraction of SS, with just two events from 14 transporting more than 50% of the SS mass in the first 25% of runoff, implying that treatment structures should be capable of removing SS throughout the storm event. In the majority of rain events, the FF strength increased with decreasing particle size, probably related to the lower intensities required to dislodge solids at the onset of rainfall. Although FF strength was correlated with rain event characteristics, prediction intervals were too broad to confirm FF presence based on rainfall data alone. Therefore, the design of smaller treatment volumes based on an assumption of FF must be justified by local monitoring data.

Development and Calibration of a Dual Drainage Model for the Cooksville Creek Watershed, Canada

Under storm conditions urban stormwater drainage systems may undergo various flow regimes including backwater, surcharging, reverse flow and surface ponding. E…

Multi-Objective Optimal Design of Detention Tanks in the Urban Stormwater Drainage System: LID Implementation and Analysis

Under the influences of climate change and rapid urbanization, extreme rainfall events become more and more intensive and the urban flooding issues have been frequently faced in many cities in the world. Previous practical and scientific experiences have demonstrated that appropriate utilization of detention facilities and low impact development (LID) devices for urban region design could be important and effective ways to the flooding control and drainage service management of an urban stormwater drainage system (USDS). This paper investigates the optimal design and application of detention tank network and LID devices for achieving these multiple objectives in the USDS. The framework and method of LID-based multi-objective optimal design of detention tanks in USDS is first developed in this study, and a practical case in SA city of China is then taken for the application. The results of this study confirm the feasibility and validity of the proposed methodological framework for the LID-based multi-objective optimal design of detention tanks in the USDS. Specifically, both total investment costs and flooding risk have been greatly reduced by the optimal implementation of the detention tank and LID measures. Meanwhile, the results indicate that the LID devices may have global effect to the flooding control and the detention tanks can be locally efficient to reduce the flooding risk. Finally, the findings of this study are discussed in the paper for their practical implications to the practical design and management of USDS.

Optimal location and sizing of storage units in a drainage system

Adapting urban stormwater drainage systems is essential to handling increased urbanization and climate change. Within an urban area, storage units are an efficient solution to reduce peak runoff, but their implementation involves complex decisions. This paper presents a novel optimization model for defining, in existing sewer drainage systems, the number of storage units, their location, size and the orifice dimensions. The orifice is used to reduce storage unit outflow regulating downstream flows. These components allow an integrated flow control and flooding reduction throughout the network. The desired solution should offer the lowest cost and try to avoid any major flooding impact. The model includes hydraulic, flood and capacity constraints and it is solved through a simulated annealing algorithm that calls upon a dynamic rainfall-runoff simulator for complete evaluation of each solution. The performance of the optimization model is assessed through a case study inspired by a real urban sewer network.

Spatial fuzzy clustering approach to characterize flood risk in urban storm water drainage systems

Increasing environmental stress of drainage systems leads to frequent occurrence of urban flooding, which generates significant adverse economic, social, and environmental impacts. In this study, spatial fuzzy clustering approach (SFCA) is developed to estimate possible flood risks in storm water drainage systems and address complexity and uncertainties of flood risk assessment. The proposed approach is capable of gaining insights into system behavior by exploring spatial patterns of flood risk. The corresponding algorithm is utilized to divide a drainage system into various clusters to reflect flood risk levels along the network space. Application to a sample drainage system demonstrates that it provides an appropriate technique to determine spatial distribution of flood risks. Results reveal that areas with high, moderate, and low risk identified by SFCA correspond to a certain degree of environmental stress. The findings of this study can serve as a preliminary basis to guide managers in their evaluation of flood risks in various drainage management scenarios.

Multi-objective Optimal Design of Detention Tanks in the Urban Stormwater Drainage System: Uncertainty and Sensitivity Analysis

Design of detention tanks becomes important to the flooding control and drainage service management of an urban stormwater drainage system (USDS). While the hydrological and hydraulic models and methods have been widely developed in the literature for the optimal design and management of USDS, there is not yet a general methodological framework that is applicable for all practical systems. This is mainly because of various complexities in practical USDS, such as different design objectives (i.e., multi-objective design) and local design criteria and policies, as well as variety of inevitable uncertainties in the system. Previous work by the authors has focused on the first two aspects, in which a viable design framework has been developed and applied for multi-objective optimal design of detention tanks in the USDS under conditions of different local design criteria; and this paper deals with the third factor, aiming to explore and extend further the optimal design methodological framework to USDS with uncertainties. A real-life USDS in China is applied for this investigation. Uncertainty analysis is firstly conducted to characterize the importance of different uncertainty factors considered in the studied system. The uncertainty analysis result is thereafter incorporated into the previously developed multi-objective optimal design framework, in which the Monte-Carlo simulation method is adopted for the stochastic process investigation. The case application and analysis indicate different influences of uncertainty factors in the system to the multi-objective design results of detention tanks (total cost and flooding risk) in the studied USDS. The results and findings of this study are also discussed in the paper for their practical implications to the design and management of USDS.

Multi-Objective Optimal Design of Detention Tanks in the Urban Stormwater Drainage System: Framework Development and Case Study

Detention tank plays an important role in the flooding control in the downstream areas of the urban stormwater drainage system (USDS) during the wet weather seasons. For complex watersheds with specific local flooding control policies, the conventional optimization and design methods are found to be not sufficient for effectively and optimally locating and sizing appropriate detention tanks any more. This paper investigates the optimal design of detention tanks under the constraints of local flooding control criteria, with the aim to develop an efficient and robust method and framework for the design of detention tank network. Coupled with the SWMM-based hydraulic simulation, a modified particle swarm optimizer is adopted to find out non-dominated solutions to minimize both the engineering cost and flooding risks by taking the local design criteria into consideration for the more realistic local engineering application. To validate the proposed method, a real-life case in SA city in China is taken for example to obtain optimal layout and sizes of the detention tank network under different construction factors and design conditions. Different rainfall return periods are also tested to guarantee the robustness of the optimal solutions. The results of this study confirm the feasibility and validity of the proposed methodological framework for multi-objective optimal design of detention tanks in the USDS.

AVALIAÇÃO DA FRAGILIDADE NO SISTEMA DE DRENAGEM PLUVIAL URBANA: O CASO DA BACIA HIDROGRÁFICA DO CÓRREGO DAS MELANCIAS EM MONTES CLAROS – MG

The fragility of a system based on different principles, can be used as policy in public policies aimed at planning, management and decision making. In this sense, the present study aims to evaluate the weakness in the watershed of the stream of Melancias by applying the Fragility Index System - IFS under the system of urban stormwater drainage of the basin, paying attention to: i) identify the elements and possible failures of micro and macro drainage through photographic record and ii) adapt, implement and evaluate IFS to obtain the degree of fragility of urban storm drainage in the watershed of the stream of Melancias. This study relied on the Fragility Index System - FIS in identifying factors that influence the urban stormwater drainage system. This study were taken 3 Points Study - on-site visit by PEs within their watershed, and to identify the elements faults micro and macro drainage and adapt and apply IFS to obtain the degree of fragility in the stream of Melancias basin. Were identified and the elements of micro and macro drainage with their flaws and found the degree of fragility Very Strong. We conclude that with this efficient methodology, it is possible to identify gaps in urban stormwater drainage systems in the basin; and this requires greater attention in the correction and prevention of waterlogging and flooding.

APLICAÇÃO DE INDICADORES DE FRAGILIDADE DO SISTEMA DE NATUREZA AMBIENTAL NA BACIA HIDROGRÁFICA DO RIO CINTRA-MG

The problems arising from unplanned urbanization are due to the lack of urban development policies, such as master plans (RIBEIRO e ROOKE, 2010). The use of indicators constitutes an instrument of great importance for proper management of public affairs. For this, the three areas (PEs) were selected in the basin, quote: east, middle course and mouth of the river, for the application of indicators of environmental fragility of nature system. The basin was identified erosion, negative interactions of drainage systems with domestic wastewater, solid waste, among others. The General Indices Fragility (IGFs) were found 57, 49 and 72 respectively to the east, middle course and river estuary, featuring high grade fragility under the environmental aspect, ranging from strong to very strong. We conclude that the use of indicators of fragility is extremely importance to public administration, particularly as a tool for identifying intervening factors and fragility of urban stormwater drainage systems.

Establishing rainfall depth–duration–frequency relationships at daily raingauge stations in Hong Kong

Summary Rainfall intensity (depth)–duration–frequency (IDF/DDF) relationships provide information essential for urban stormwater drainage system design and other hydrosystem infrastructures. For catchments where drainage areas are small, rainfall DDF relationships with short duration can be established based on rainfall records from automatic raingauges. Due to the progression of technology development, wide spread installation of automatic raingauges does not happen until 2–3 decades ago. Therefore, record lengths at majority of automatic raingauges are relatively short and the derived rainfall DDF relationships on the basis of at-site frequency analysis are potentially subject to significant sampling error. On the other hand, many conventional raingauges exist long before automatic raingauges were deployed. However, daily rainfall data with long records at conventional raingauges are of limited use to establish rainfall DDF relationships in areas with small catchment size like Hong Kong where design storm duration significantly shorter than 24-h are needed. This study presents a practical methodological framework to derive rainfall DDF relationships with short duration at conventional raingauge locations. The core components of the framework include the scaling model of rainfalls of different durations, the establishment of relationship between annual maximum daily rainfall and rolling-time 1440 min rainfall, the quantification of statistical features of estimated annual maximum 1440 min rainfalls, and the assessment of uncertainty of derived rainfall DDF relationships at conventional raingauges.

Ecologically relevant geomorphic attributes of streams are impaired by even low levels of watershed effective imperviousness

Urbanization almost inevitably results in changes to stream morphology. Understanding the mechanisms for such impacts is a prerequisite to minimizing stream degradation and achieving restoration goals. However, investigations of urban-induced changes to stream morphology typically use indicators of watershed urbanization that may not adequately represent degrading mechanisms and commonly focus on geomorphic attributes such as channel dimensions that may be of little significance to the ecological goals for restoration. We address these shortcomings by testing if a measure characterizing urban stormwater drainage system connections to streams (effective imperviousness, EI) is a better predictor of change to ecologically relevant geomorphic attributes than a more general measure of urban density (total imperviousness, TI). We test this for 17 sites in independent watersheds across a gradient of urbanization. We found that EI was a better predictor of all geomorphic variables tested than was TI. Bank instability was positively correlated with EI, while width/depth (a measure of channel incision), bedload sediment depth, and frequency of bars, benches, and large wood were negatively correlated. Large changes in all geomorphic variables were detected at very low levels of EI (<2–3%). Excess urban stormwater runoff, as represented by EI, drives geomorphic change in urban streams, highlighting the dominant role of the stormwater drainage system in efficiently transferring stormwater runoff from impervious surfaces to the stream, as found for ecological indicators. It is likely that geomorphic condition of streams in urbanizing watersheds, particularly those attributes of ecological relevance, can only be maintained if excess urban stormwater flows are kept out of streams through retention and harvesting. The extent to which EI can be reduced within urban and urbanizing watersheds, through techniques such as distributed stormwater harvesting and infiltration, and the components of the hydrologic regime to be addressed, requires further investigation.

Multiplicative cascade models for fine spatial downscaling of rainfall: parameterization with rain gauge data

Abstract. Capturing the spatial distribution of high-intensity rainfall over short-time intervals is critical for accurately assessing the efficacy of urban stormwater drainage systems. In a stochastic simulation framework, one method of generating realistic rainfall fields is by multiplicative random cascade (MRC) models. Estimation of MRC model parameters has typically relied on radar imagery or, less frequently, rainfall fields interpolated from dense rain gauge networks. However, such data are not always available. Furthermore, the literature is lacking estimation procedures for spatially incomplete datasets. Therefore, we proposed a simple method of calibrating an MRC model when only data from a moderately dense network of rain gauges is available, rather than from the full rainfall field. The number of gauges needs only be sufficient to adequately estimate the variance in the ratio of the rain rate at the rain gauges to the areal average rain rate across the entire spatial domain. In our example for Warsaw, Poland, we used 25 gauges over an area of approximately 1600 km2. MRC models calibrated using the proposed method were used to downscale 15-min rainfall rates from a 20 by 20 km area to the scale of the rain gauge capture area. Frequency distributions of observed and simulated 15-min rainfall at the gauge scale were very similar. Moreover, the spatial covariance structure of rainfall rates, as characterized by the semivariogram, was reproduced after allowing the probability density function of the random cascade generator to vary with spatial scale.