Leveraging Spatial Optimization to Inform Wastewater Infrastructure Planning

Abstract Lowndes County, Alabama, has struggled with inadequate wastewater management exacerbated by low population density, high rates of poverty, and suboptimal soil conditions prevalent throughout the Black Belt region. Steps are being taken to develop solutions, but a challenge in wastewater infrastructure planning is identifying the optimal number, location, and type of wastewater treatment systems (centralized, cluster, or onsite). Thus, the objectives of this research were to utilize a spatial optimization model, i.e., the sustainable infrastructure network planning model (SNIP), to determine the cost-optimal layout of wastewater treatment infrastructure for Lowndes County, Alabama, and assess how model results compare to existing technical assistance and proposed infrastructure improvement efforts in the town of White Hall (located in Lowndes County, AL). SNIP, created by Eggimann et al. (2015), minimizes the total wastewater system costs and requires only three input datasets: buildings, topography, and the street network. Overall, more centralized infrastructure, such as wastewater treatment plants or cluster wastewater treatment systems, is more cost optimal compared to the current heavy reliance on onsite wastewater treatment systems. Output geospatial data showing the location and capacity of wastewater treatment plants, sewer pipes, and pumps are particularly useful in communicating with stakeholders (e.g., residents, engineers, governing officials, and funders). Model outputs can guide household-level decision-making for the optimal wastewater treatment system (e.g., centralized, cluster, or onsite) not provided by current technical assistance. Ultimately, wastewater infrastructure planning requires consideration of local social, environmental, political, and economic dynamics, and this accessible tool can help communities quickly develop cost-optimal design options.