AI-based design of urban stormwater detention facilities accounting for carryover storage
Journal
Journal of Hydrology
Journal Volume
575
Pages
1111-1122
Date Issued
2019
Author(s)
Abstract
Rapid urbanization in metropolitan areas easily triggers flashy floods. Urban drainage systems conveying stormwater out of cities are key infrastructure elements for flood mitigation. This study develops an intelligent urban flood drainage system accounting for carryover storage through optimizing the multi-objective operation rules of pumping stations for effectual flood management in Taipei City. The Yu-Cheng pumping station constitutes the study case, and a large number of datasets collected from 17 typhoon/storm events are adopted for model construction and validation. Three objective functions are designed to minimize: (1) the sum of water level fluctuations in the flood storage pond (FSP); (2) the sum of peak FSP water levels; and (3) the mean absolute difference of pump switches between two consecutive times along operation sequence. The non-dominated sorting genetic algorithm II (NSGA-II) is applied to searching the Pareto-optimal solutions that optimize the trade-off between the objectives. We next formulate the optimal operation rules through a two-tier sorting process based on a compromised Pareto-optimal solution. The comparison of the simulated results obtained from both the optimal operation rules and current operation rules indicate that the optimal operation rules outperform current operation rules for all three objectives, with improvement rates reaching 43% (OBJ1), 3% (OBJ2) and 71% (OBJ3), respectively. We demonstrate that the derived intelligent urban flood drainage system can serve as reliable and efficient operational strategies for urban flood management and flood risk mitigation. © 2019 Elsevier B.V.
Subjects
Flood risk mitigation; Multi-objective optimization; Non-dominated sorting genetic algorithm-II (NSGA-II); Pump operation rules; Real-time urban flood control
Other Subjects
Drainage; Economic and social effects; Flood control; Genetic algorithms; Large dataset; Multiobjective optimization; Optimal systems; Pareto principle; Pumping plants; Pumps; Storms; Water distribution systems; Water levels; Flood risks; Mean absolute differences; Non dominated sorting genetic algorithm ii (NSGA II); Operational strategies; Pareto optimal solutions; Pump operation; Urban flood control; Water-level fluctuation; Floods; drainage network; flood control; flooding; genetic algorithm; multiobjective programming; operations technology; optimization; pump; real time; risk assessment; runoff; water storage; Taipei; Taiwan; Citrus maxima
Type
journal article