Peterborough used to rely on estimates of where impervious and pervious surfaces were located; with Ecopia they can not only know for sure where these vastly different areas are, but also further segment impervious surfaces to enhance their models with more detail. The team now classifies impervious surfaces as either directly or indirectly connected to the city’s sewer systems in order to develop more accurate runoff coefficients. With this segmentation, directly connected impervious surfaces like roads, driveways, and parking lots have a higher coefficient than indirectly connected impervious surfaces such as roofs and sidewalks. This separation better simulates runoff response and improves the accuracy of the IFM in stormwater management and planning, a huge improvement from previous methods.
“With the IFM, we have a far greater understanding of flood risks in our community. Our flood reduction capital program uses this intelligence to identify future projects, test a range of scenarios, and prioritize work, all with the goal of achieving the highest level of flood reduction with limited capital funding. Land-use planning is also better informed with the IFM, resulting in future development that is protected from flood risk and limits or eliminates exacerbating flood risks for other areas of the City.” - Ian Boland, Senior Watershed Project Manager for the City of Peterborough
Accurately modeling the complexity of land cover in urban areas like downtown Peterborough was top of mind for city hydrologists as they implemented Ecopia’s data. Much of the damage during 2004’s flood, as well as subsequent stormwater events, was concentrated in urban areas with varying types of impervious surfaces. To plan for future stormwater events and develop a higher resiliency for the community, Peterborough leverages Ecopia’s building footprint dataset in their 2D mesh representation of the city. The digital terrain model of cells containing buildings is artificially raised to signify how water will move around those structures in a flood event and into other cells.
The team then uses a kinematic wave method to calculate rainfall runoff catchment based on the previously discussed different segments of impervious surfaces (directly and indirectly connected). In Peterborough’s more rural areas with less impervious surfaces, a Soil Conservation Service (SCS) Curve Number (CN) is used to determine flood risk and stormwater resiliency. The CN indicates the runoff and infiltration potential of soil derived from Ecopia’s land cover data, allowing hydrologists to more specifically model the effects of stormwater events on pervious surfaces.
As the Peterborough team evaluated different sources of data for their flood modeling and stormwater management efforts, they sought a dataset that was detailed, consistent, and fresh enough to develop climate resilience strategies with. Because of the guaranteed >95% precision of features and the frequency of updates, Ecopia stood out from the beginning as a source of truth Peterborough could rely on to accurately improve and scale their planning.
“Ecopia’s ability to efficiently extract all land cover features, whether manmade or natural, enables us to develop flood models that represent reality. The planimetric level detail map was critical for our stormwater engineering consultants, Jacobs, to help support the development of our IFM.” - Ian Boland, Senior Watershed Project Manager for the City of Peterborough
Ricardo Santaella of Jacobs added:
“The outputs from Ecopia will be very helpful in the future as it can be used to track for development and land cover changes. These modifications can then be used to update the model and evaluate the implications in terms of flood risk exposure at a local or global level. One of the main benefits from the Ecopia product is that manual delineation of polygons is not required, thus saving a significant amount to update a previous dataset.”
The AI and ML used by Ecopia to extract land cover features from imagery means that data for Peterborough is updated on a more frequent cadence than before, and delivered in a consistent format that simplifies the flood modeling process. With Ecopia data, the team no longer needs to spend time combining data of varying quality from disparate sources, and can instead devote their energy to further enhancing their stormwater management plans. The detailed classification of land cover provided by Ecopia, as well as the human-like precision in which each feature is digitized, gives Peterborough the flexibility and confidence needed to build the most advanced flood models and better plan for future stormwater events.
With Ecopia’s data, the City of Peterborough has a comprehensive view of how water features relate to both pervious and impervious surfaces. Explore a sample of data from Peterborough below: