Why Model Real Time When You Can Model the Future? The Fort Wayne Experience

This manuscript summarizes the development and implementation of the forecasting tool for Fort Wayne City Utilities’ collection system model. The tool uses an embedded Python script in PCSWMM to obtain the NOAA rainfall forecast and NWS river stage forecast to simulate 48 hours into the future for operational insight. In addition to the forecasting tool, a cloud-based Azure Function was developed to run the model in the cloud and reduce wear and tear on City computers. Located at the confluence of the St. Marys, St. Joseph, and Maumee Rivers, the collection system is influenced by high river stages. The NWS river forecast is obtained by a simple web scraping technique while the NOAA forecasts are obtained using the MetPy library (Unidata, 2021). The three forecasts are then formatted to PCSWMM’s structure, automatically added to the model as rainfall, climate, and river stage time series files, with the model simulation time set to the reflect the forecast period. Figure 2 presents City Utilities’ model and the embedded script, which can be used to automatically run the model after obtaining the forecast. Similar to many combined sewer communities with a Consent Decree, City Utilities frequently simulates a typical 5-year period as part of assessing combined sewer overflow (CSO) controls. To ease the burden on City Utilities’ staff laptops, an Azure Function was developed to run the model in the Microsoft Azure cloud environment as a lower-cost alternative to a virtual machine (VM).