Dynamically Linked Stormwater and Traffic Models
- Publication Type:
- Conference Proceeding
- Citation:
- Hydrology and Water Resources Symposium, HWRS 2022, 2022, pp. 743-749
- Issue Date:
- 2022-01-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| informit.915935300109994.pdf | Published version | 2.92 MB |
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Within urban environments, stormwater drainage systems and transport networks are two areas where modelling is a common approach to generation of data relevant to their management. There is a long history in the usage of both stormwater and transport models. However, a common theme of this history is the operation of stormwater and transport models independently with the generated data from one being unrelated to data generated by the other. In other words, the time-dependent hydrologic failure of a stormwater system is not incorporated into the constraints experienced by a transport network. At the same time, the direct intangible transport costs associated with the hydrologic failure of a stormwater system are not included in the estimates of the average annual damages. When the real world is considered, however, there are linkages between the transport network and the stormwater drainage system with the conditions in one influencing the other. To mitigate the disconnect, a project aimed at linking stormwater and transport models has commenced at UTS. Using the Alexandria Canal catchment as a case study, a stormwater model based on SWMM is being developed for the prediction of the time and magnitude of hydrologic failures of the stormwater system. An agent-based transport model (ABM), with agents representing both vehicles and pedestrians, is being developed to predict delay times induced by ponding of stormwater runoff. Presented herein will be a discussion of current development. This development has focussed on the dynamic linkage of SWMM with the ABM-based transport model for individual events; in other words, the instantaneous flows predicted by SWMM are part of the data used by the agents in deciding upon their actions and hence their movements. Also shown will be some preliminary results.
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