One of the emerging issues in utility management and capital financing is how to address the impact of affordable housing on a wastewater system. Utilities often receive pressure to waive or reduce development impact fees for what is seen as more desirable or diverse and potentially more equitable housing supply. This is counterbalanced by the challenge that if those developments do not pay for the cost of their impact to the system, another segment of the customer base will. This leaves the utility stuck between two valid policy goals and leaving both groups unhappy with any changes made.
To create a path forward, Clackamas Water Environment Services (WES) explored a more nuanced effort to measure the impact of housing size as a proxy for water consumption on the wastewater system. As a regional wastewater system crossing multiple water providers, WES does not assign equivalent dwelling units (EDUs) based on direct water consumption data, but used the traditional “a house is a house” model with a 20% discount for multi-family dwellings. WES pulled winter water consumption data from several underlying water providers, then cross-indexed with census data and home size information to create a model of flow contributions to the system.
WES found a statistically significant difference in wastewater discharges that correlated to the size of the dwelling, with small 800 square foot dwellings at one end and 3000 square foot dwellings at the other. After slicing the data several different ways, WES established key deviations from the baseline consumption of a 2000 square foot home. These deviations supported the creation of a 5-tiered EDU assignment (and therefore development impact fee assignment) for new development that reduced the cost of affordable housing, and increased the cost of large homes.
This nuanced distinction created a path forward to enabling lower affordable housing fees while having a strong, evidence-based approach that there was no subsidy being given by another customer segment. WES proposes to share how the analysis was done, how to draw conclusions from the data, and how to implement a tiered development impact fee structure.