A Novel SWMM Based Algorithm Application to Storm Sewer Network Design

Intensity-Duration-Frequency Curves at Ungauged Sites in a Changing Climate for Sustainable Stormwater Networks

Intensity-duration-frequency (IDF) curves representing the variation of the magnitude of extreme rainfall events with a return period and storm duration are widely used in hydrologic infrastructure design, flood risk management projects, and climate change impact studies. However, in many locations worldwide, short-duration rainfall-observing sites with long records do not exist. This paper introduces a new methodological framework for extracting IDF curves at ungauged sites transferring information from gauged ones with a relatively homogeneous extreme rainfall climate. This methodology is grounded on a simple scaling concept based on the multifractal behaviour of rainfall. A nonstationary Generalized Extreme Value (GEV) distribution fitted to annual rainfall monthly maxima at the ungauged site using a moving-time window approach is also applied to consider effects of a changing climate on IDF curve construction. An application is presented at the study site of Fourni, Crete, to derive IDF curves under changing climate conditions and present implications of the proposed methodology in the design of a sustainable stormwater network. The methodology introduced in this work results in increased rainfall extremes up to 20.5%, while the newly designed stormwater network is characterised by increased diameters of its primary conduits, compared to the ones resulting under fully stationary conditions.

Evaluation of Combined Sewer System Operation Strategies Based on Highly Resolved Online Data

Operational and structural interventions in the field of stormwater management are usually planned based on long-term simulations using rainfall-runoff models. The simulation results are often highly uncertain due to imperfections of the model structure and inevitable uncertainties of input data. The trend towards monitoring of combined sewer overflows (CSO) structures produces more and more data which can be used to replace parts of the models and reduce uncertainty. In this study we use highly resolved online flow and quality monitoring data to optimize static outflow settings of CSO tanks. In a second step, the additional benefit of real time control (RTC) strategies is assessed. In both cases the aim is the reduction of CSO emissions. The methodology is developed on a conceptual drainage system with two CSO tanks and then applied to a case study area in Southern Germany with six tanks. A measured time series of six months is sufficient for reliable optimization results in the conceptual catchment as well as in the case study area system. In the investigated system the choice of the optimization objective (minimum overflow volume or total suspended solids (TSS) load) had no significant influence on the result. The presented method is particularly suitable for areas in which reliable monitoring data are available, but hydrological parameters of the catchment areas are uncertain. One strength of the proposed approach lies in the accurate representation of the distribution of emissions between the individual CSO structures over an entire system. This way emissions can be fitted to the sensitivity of the receiving water body at the specific outlets.

Integrating Structural Resilience in the Design of Urban Drainage Networks in Flat Areas Using a Simplified Multi-Objective Optimization Framework

Structural resilience describes urban drainage systems’ (UDSs) ability to minimize the frequency and magnitude of failure due to common structural issues such as pipe clogging and cracking or pump failure. Structural resilience is often neglected in the design of UDSs. The current literature supports structural decentralization as a way to introduce structural resilience into UDSs. Although there are promising methods in the literature for generating and optimizing decentralized separate stormwater collection systems, incorporating hydraulic simulations in unsteady flow, these approaches sometimes require high computational effort, especially for flat areas. This may hamper their integration into ordinary commercially designed UDS software due to their predominantly scientific purposes. As a response, this paper introduces simplified cost and structural resilience indices that can be used as heuristic parameters for optimizing the UDS layout. These indices only use graph connectivity information, which is computationally much less expensive than hydraulic simulation. The use of simplified objective functions significantly simplifies the feasible search space and reduces blind searches by optimization. To demonstrate the application and advantages of the proposed model, a real case study in the southwest city of Ahvaz, Iran was explored. The proposed framework was proven to be promising for reducing the computational effort and for delivering realistic cost-wise and resilient UDSs.

An Efficient Framework for Multi-Objective Risk-Informed Decision Support Systems for Drainage Rehabilitation

Combining multiple modules into one framework is a key step in modelling a complex system. In this study, rather than focusing on modifying a specific model, we studied the performance of different calculation structures in a multi-objective optimization framework. The Hydraulic and Risk Combined Model (HRCM) combines hydraulic performance and pipe breaking risk in a drainage system to provide optimal rehabilitation strategies. We evaluated different framework structures for the HRCM model. The results showed that the conventional framework structure used in engineering optimization research, which includes (1) constraint functions; (2) objective functions; and (3) multi-objective optimization, is inefficient for drainage rehabilitation problem. It was shown that the conventional framework can be significantly improved in terms of calculation speed and cost-effectiveness by removing the constraint function and adding more objective functions. The results indicated that the model performance improved remarkably, while the calculation speed was not changed substantially. In addition, we found that the mixed-integer optimization can decrease the optimization performance compared to using continuous variables and adding a post-processing module at the last stage to remove the unsatisfying results. This study (i) highlights the importance of the framework structure inefficiently solving engineering problems, and (ii) provides a simplified efficient framework for engineering optimization problems.

Pin-pointing groundwater infiltration into urban sewers using chemical tracer in conjunction with physically based optimization model

Groundwater infiltration into sanitary sewers increases hydraulic loadings of sewage collection systems and threatens wastewater treatment efficiency. However, cost-effective approach to quantify this important process still needs to be improved in order to better manage this common issue. This paper presents a method for determining the origin and amount of groundwater entering the urban sewer system. On a catchment scale, by measuring and tracking a chemical tracer (i.e., artificial sweetener acesulfame) in the urban sewers, the magnitude of daily groundwater flows in each sub-catchment could be quantified based on a Monte Carlo chemical mass balance approach. For the study site, 7.9% of the sewer length contributed 58% of the total groundwater infiltration. In the identified high-risk sub-catchment, groundwater sources and their spatial-temporal flows could be further pinpointed and elucidated by physically based numerical self-optimization model using microbial genetic algorithm method, which was verified by on-site sewer flow measurements, as well as time-series tracer concentration patterns at the terminal outlet. It was found that the diurnal variations of groundwater seepage into sewer network was linked to the in-pipe water level associated with sewage pumps operation mode, demonstrating the importance of in-pipe water level regulation in controlling groundwater infiltration. Compared with traditional visual inspection or direct flow measurement methods, the proposed approach exhibits distinct advantages in determining groundwater sources and flows in large sewer systems.

Assessing Redundancy in Stormwater Structures Under Hydraulic Design

As environmental change is happening at an unprecedented pace, a reliable and proper urban drainage design is required to alleviate the negative effects of unexpected extreme rainfall events occurring due to the natural and anthropogenic variations such as climate change and urbanization. Since structure/configuration of a stormwater network plays an imperative role in the design and hydraulic behavior of the system, the goal of this paper is to elaborate upon the significance of possessing redundancy (e.g., alternative flow paths as in loops) under simultaneous hydraulic design in stormwater pipe networks. In this work, an innovative approach based on complex network properties is introduced to systematically and successively reduce the number of loops and, therefore, the level of redundancy, from a given grid-like (street) network. A methodology based on hydrodynamic modelling is utilized to find the optimal design costs for all created structures while satisfying a number of hydraulic design constraints. As a general implication, when structures are subject to extreme precipitation events, the overall capability of looped configurations for discharging runoff more efficiently is higher compared to more branched ones. The reason is due to prevailing (additional) storage volume in the system and existing more alternative water flow paths in looped structures, as opposed to the branched ones in which only unique pathways for discharging peak runoff exist. However, the question arises where to best introduce extra paths in the network? By systematically addressing this question with complex network analysis, the influence of downstream loops was identified to be more significant than that of upstream loops. Findings, additionally, indicated that possessing loop and introducing extra capacity without determining appropriate additional pipes positions in the system (flow direction) can even exacerbate the efficiency of water discharge. Considering a reasonable and cost-effective budget, it would, therefore, be worthwhile to install loop-tree-integrated stormwater collection systems with additional pipes at specific locations, especially downstream, to boost the hydraulic reliability and minimize the damage imposed by the surface flooding upon the metropolitan area.

Impact of Self-Cleansing Criteria Choice on the Optimal Design of Sewer Networks in South America

This paper aims to analyze different sediment self-cleansing criteria and to find out what the corresponding implications are on the optimal design of sewer systems. A methodology based on enumeration is used to find the sewer network design that minimizes the costs of construction while fulfilling a number of design criteria including self-cleansing constraints. Three stormwater and wastewater sewer networks are used for the analyses. The results indicate that in cases where the terrain slopes and design flow rates are higher, the self-cleansing restrictions are irrelevant to the optimal design. However, when the terrain slopes and the design flow rates are lower, these restrictions affect the final design. Using the results obtained, a graph is constructed showing the limit at which self-cleansing restrictions become a constraining parameter in optimal design for sewer networks. It is expected that this graph will be useful for the design of future sewer networks in low-income areas, where the design of traditional, gravity-based sewer systems is essential.