In ZwillE, a reusable decision support functionality has been developed as a sub-component of a digital twin that supports the operating personnel of a drainage infrastructure company and other urban stakeholders in selecting suitable measures for dealing with extreme weather scenarios. This assistance is based on an expandable knowledge base and uses comprehensible, rule-based approaches
The comprehensible decision support component offers the municipal drainage operating staff and other municipal stakeholders involved in heavy rainfall events suggested measures for managing the current precipitation event and for proactively preparing for upcoming events. These measures include proposals for controlling the discharge in the main collectors such as changing the flow rates of the individual pumps in the inlet pumping stations or operating gate valves, but also for closing off underpasses and roads, activating warning notices or displays in areas at risk of flooding, evacuating endangered properties and securing them by means of local protective measures e.g., temporary bulkheads.
The recommendations for action regarding current or expected flooding in the urban area refer to defined locations stored with GIS coordinates. A comparison with a flood map created for the respective precipitation event can be used to automatically determine whether a threshold value of the current or expected flood height is exceeded at the respective location and, in the positive case, the associated warning level-specific measures are displayed in the control rooms as a decision-making aid for the technical operating personnel, whereby the operating personnel decide on the actual implementation of measures that lie within their respective area of responsibility. As a joint municipal task, heavy rainfall events extend beyond the remit of urban drainage. In the event of extreme heavy rainfall events, a crisis team is set up and measures are implemented in coordination between the municipal drainage department, civil engineering department, police and fire department.
