Matt Magruder Colloquia

Environmental Research Manager, MMSD

The Milwaukee Metropolitan Sewerage District (MMSD) manages a service area of 423 square miles. Green stormwater infrastructure (GSI) is an important component of MMSD’s wet-weather management, helping reduce peak inflows that contribute to combined sewer overflow (CSO), separate sewer overflow (SSO), and flooding.  MMSD, seeking to optimize GSI investments, had numerous questions about GSI effectiveness, including quantifying the effect of existing GSI, identifying where additional GSI deployment would make the greatest impact, quantifying performance impacts of additional GSI development, and exploring how climate change may impact system performance and the effectiveness of GSI.  As part of MMSD and Marquette University’s collaborative WaterCare research program, MMSD, Marquette, and Confluency teamed together to investigate these questions. A multi-pronged approach was defined to investigate the feasibility, impact, and resilience of climate infrastructure. These distinct but related analytical approaches are:

• Multi-Factor Geospatial GSI Prioritization
• Hydraulic Analysis of GSI Alternatives
• Climate Resilience Analysis

Multi-Factor Geospatial GSI Prioritization: Over 40 data layers were analyzed to score benefits within five categories: Hydraulic, Geographic, Feasibility, Socioeconomic, and Biodiversity.  A python-based geoprocessing tool was developed to automate the intersection and summary of data layers at the subcatchment scale. A benefit weighting approach was used to create several distinct prioritization scenarios, and an ArcGIS Online dashboard was developed to visualize GSI prioritization under different scenarios (Figure 1). Key aspects of the GIS prioritization tool include:

• Ability of MMSD staff to re-run independently
• Inclusion of hydraulic impacts from thousands of hydraulic simulations
• Inclusion of climate change resilience metrics
• Use of agile methods to iterate rapidly and affordably towards MMSD objectives.

Hydraulic Analysis: The impacts of GSI differ based on system type, and hydraulic capacity of the sewer system. MMSD’s system already manages over 98% of wet-weather runoff.  A composite wet-weather benefit metric was developed that weights benefits based on reduced CSO, SSO, tunnel inflow, and flow to the treatment plant. GSI planning areas were grouped into 53 distinct groups across the service area. Impervious area was reduced by 20% and 40% within the GSI planning area to simulate the impact of inflow reduction in a type-agnostic manner. 12 individual storms were evaluated using event-based simulation, and the full 2014 rainfall was evaluated to understand continuous impacts. Aggregate GI scenarios were then defined to evaluate the impact of grouped high-performing areas in aggregate.

Climate Resilience: Statistically downscaled climate data was obtained from the Wisconsin Initiative on Climate Change Impacts (WICCI) – these datasets included spatially varying rainfall across the service area across a roughly 12 year period. Temperature and precipitation for the 12 historical events were updated based on conditions in 28 distinct general circulation models (GCMs), 3 shared socioeconomic pathways (SSPs), for mid-century and end-of century. GCMs were screened based on equilibrium sensitivity to define a reduced set of 10 GCMs. Each event was simulated under each climate scenario for 9 distinct GSI prioritization scenarios.  Figure 2 shows the change in CSO versus precipitation across the suite of climate scenarios evaluated. Figure 3 shows the variability in climate change impacts on rainfall, CSO, and SSO, across SSP conditions. A climate change robustness metric was developed to quantify a GSI scenario’s ability to offset adverse hydraulic impacts from future climate scenarios, and incorporated as a layer in the multi-factor GSI prioritization tool.  Inclusion of a climate resilience metric is a way of including robustness to potential adverse impacts from climate change as one consideration, among many, for identifying GSI implementation areas that provide the most benefit across a range of uncertain climate futures.

Outcome: The multi-pronged GSI planning process, including the utility facing prioritization dashboard, has provided an improved ability for MMSD to discuss GSI investment needs, identify high-impact locations where GSI would provide greatest benefit, and balance longer-range considerations such as the potential to buffer adverse impacts of climate change. Integration of large-scale automated simulation approaches, together with downscaled climate data, provided novel datasets for a more comprehensive quantification of hydraulic impact and climate resilience. The agile delivery approach of the planning tool helped MMSD input and feedback be incorporated into the utility dashboard, and enable self-service updates and re-runs as additional and/or newer datasets become available or scoring priorities evolve.