A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Exploring near-optimal locations for bioretention systems in catchment scale using many-objective evolutionary optimization
Low impact developments (LIDs) are control measures to restore the hydrologic regime and enhance stormwater quality. Due to LID’s expensive capital and maintenance cost, the placement of LID controls in a watershed is an important planning task and still an open question in the specialized literature. This study proposes a simulation-optimization approach to place bioretention systems within a watershed to optimize their effectiveness. The Stormwater Management Model (SWMM) and the Non-dominated Sorting Genetic Algorithm III (NSGAIII) were coupled to identify the near-optimal locations of bioretentions for near-optimal quality and quantity controls, considering runoff volume, peak flow, total suspended solids, total nitrogen, and cost. Trade-offs were identified between cost versus other objective functions. The results suggest no specific spatial preference in placement of bioretentions under different rainfall regimes in watershed scale. However, in subcatchment scale, the near-optimal placement under single storm events is either maximum or none, while distributed under continuous simulation.
Exploring near-optimal locations for bioretention systems in catchment scale using many-objective evolutionary optimization
Low impact developments (LIDs) are control measures to restore the hydrologic regime and enhance stormwater quality. Due to LID’s expensive capital and maintenance cost, the placement of LID controls in a watershed is an important planning task and still an open question in the specialized literature. This study proposes a simulation-optimization approach to place bioretention systems within a watershed to optimize their effectiveness. The Stormwater Management Model (SWMM) and the Non-dominated Sorting Genetic Algorithm III (NSGAIII) were coupled to identify the near-optimal locations of bioretentions for near-optimal quality and quantity controls, considering runoff volume, peak flow, total suspended solids, total nitrogen, and cost. Trade-offs were identified between cost versus other objective functions. The results suggest no specific spatial preference in placement of bioretentions under different rainfall regimes in watershed scale. However, in subcatchment scale, the near-optimal placement under single storm events is either maximum or none, while distributed under continuous simulation.
Exploring near-optimal locations for bioretention systems in catchment scale using many-objective evolutionary optimization
Shahrokh Hamedani, Abtin (author) / Do Lago, Cesar (author) / Giacomoni, Marcio H. (author)
Urban Water Journal ; 20 ; 813-830
2023-08-09
18 pages
Article (Journal)
Electronic Resource
Unknown
Exploring Uncertainty in Uncalibrated Bioretention Models
| Springer Verlag | 2018
Modelling Bioretention Systems
| Springer Verlag | 2018
| Wiley | 2022