Storm Sewer Network Optimization for Urban Flood Mitigation by Coupling Multi-objective Evolutionary Algorithms (MOEAs) and PCSWMM
Creators: Chen, Dexin
Publisher: name: University of Alberta Library
Year: 2023

<p>Flooding is one of the most frequently met disasters in urban areas in the context of climate change and more intensive anthropogenic activities. Urban drainage system (UDS), defined as surface runoff and sewage collection and transport system, is an essential part of urbanization. The capacity of UDS can substantially influence the flooding levels of urban catchments. However, there are always bottle necks in the complex sewer network that substantially affect the capacity of UDS and thus worsen urban flooding. <br>
To improve the performance of UDS, multi-objective evolutionary algorithms (MOEAs) have been applied to optimize UDS, as they can explore trade-offs between conflicting objectives. However, most previous studies only conducted pipe size optimization in a small-scale area (with less than 100 sewers) without considering pipe slope and engineering criteria. This thesis focuses on urban stormwater drainage system and aims to develop and evaluate a method for simultaneously optimizing sewer size and slope in a large-scale area (with 2930 sewers). The goal is to minimize the sewer rehabilitation/upgrade costs and flood volume in the complex in real-life storm sewer network. <br>
To realize the goal, a new storm sewer network optimization system was proposed that integrated a storm water management model (PCSWMM) with one of MOEAs Preference-inspired coevolutionary algorithm (PICEA-g) using a programming language (MATLAB) as the platform. Specific improvements were made to the PICEA-g algorithm to better tackle the problem, which include new methodologies for initializing candidate solutions, the use of divide and conquer technique, enhanced goal vector boundaries and fitness calculation, and enhanced genetic operators (crossover and mutation). <br>
The new optimization system was tested in a small sample area (16.68 ha and 78 conduits) and applied to the entire study area (777.6 ha and 2930 conduits) based on both 1D and 2D hydraulic modeling of the UDS. Sewer pipe size and slope were used as decision variables, and then the number of flooded nodes (manholes) and cost were taken as objective functions. The results of the storm sewer network before and after the optimization were compared and discussed, indicating a significant improvement by using the optimization system. For the test area, the flooded nodes reduced from 15 to 0 after optimization. For the study area, the flooded manholes decreased from 284 to 115 in the 1D model; when using the 2D model, the flooded nodes dropped from 73 to 30 and 44 in two different modeling scenarios. This comparison indicated that the new optimization system worked effectively using both 1D and 2D modeling. The optimization system can be used as a tool to assist drainage network engineers in developing sewer network optimization strategies and prioritizing detailed rehabilitation/upgrade projects at different scales (single or multiple neighborhood scale, city-wide and regional scale).<br>
Finally, limitations of the optimization system such as practicability, variation range and software were discussed. And future research directions were suggested at the end of the thesis.</p>