Case Study: Moorhead Stormwater Modeling Study

Building capacity

Moorhead completed this project through a combination of in-house and hired capacity, using a $75,000 grant from the Minnesota Pollution Control Agency (MPCA) and an additional $25,000 in city funds. This money allowed the city to hire external capacity from a local engineering firm, HEI, which ran model simulations of flooding in a future climate. In-house technical capacity already existed in the form of a flood model, InfoSWMM, that was calibrated for Moorhead's geography and existing storm sewer system. The design team at HEI consisted of about five people, including modelers, GIS specialists, and designers. The city's project team included three existing staff members. 

Understanding climate risk and planning for change

The topography of Moorhead and surrounding areas is incredibly flat. This creates challenges with spring snowmelt and large rain events — floodwaters have nowhere to go. The most extreme precipitation and resulting flooding events, although impactful, are not economically feasible to address. The city therefore took a risk-based approach and focused on less extreme but higher probability events that could damage private property, public facilities, and city streets. To assess future flood risk, the design team had to make important decisions based on their own expertise: 

1. Which publicly available tool to use
2. What size storm to model
3. Which climate scenario to focus on

The team in Moorhead decided to use the Environmental Protection Agency's National Stormwater Calculator [2], a publicly available tool, because its historical simulations agreed with observations. When modeling the future, it is important to check how well model simulations reproduce reality. Most often, we validate a model – or check its accuracy – by comparing a historical simulation to observations of the same time period. If the model estimates something similar to reality, then we have more confidence in its projections. Using the Stormwater Calculator, the team determined that rain events between 2 and 4 inches produced the highest risk of damages during a projected climate change scenario. 

The Stormwater Calculator uses statistically downscaled climate projections from the 5th generation of Global Climate Models, CMIP5, to create Depth-Duration-Frequency (DDF) curves. A DDF curve shows how much rain is likely to fall in a storm that lasts for 24 hours, and how frequently a storm of that size is likely to happen — often once every 2, 10, 50, or 100 years. HEI wanted to know how a 1-in-2, 24-hour rain event (i.e., a 24-hour rain event that has a 1% chance of happening in a given year) is likely to change because of climate change. According to the Stormwater Calculator, under a very high emissions scenario, by the mid-to-late Century (2050–2070), these storms could produce 15% more rainfall than they did historically.

HEI engineers applied a 15% increase to the historical high risk rain events (2-4 inches) to model future flooding in the study area. The GIS team then overlaid those results on a map of the city to determine which locations are most at risk. The study focused on older parts of town that were constructed between 1920 and 1960 because the storm sewers in these areas were designed and constructed based on outdated criteria. They are undersized even in today's climate, and even more so considering climate change.