This research team will build a database of the locations of onsite wastewater treatment systems in Alabama and Mississippi’s five coastal counties. One prominent type of onsite wastewater treatment systems is a septic system. In areas lacking septic system location data, the group will generate a model that will predict septic system density in coastal locations where density is unknown. They will also develop and test the accuracy of a pollution potential model that will predict areas of high septic system failure risk based on environmental, climatic and septic system criteria (for example, slope of terrain, precipitation amounts, storm surge and age of systems). The team will test the model using targeted water quality sampling strategies and lab analysis. The creation of this model will provide a critical first step in understanding where the environment and surrounding communities might be at risk of contaminant exposure from septic systems now and into the future. The project results will provide a mechanism to identify communities that face social and or economic burdens that make them more vulnerable to septic system pollution outcomes. The researchers will work closely with an advisory committee made up of local government, extension and research entities to ensure project relevance for local stakeholders.
Abstract
Onsite wastewater treatment systems (OWTS) are a prevalent and affordable means of wastewater treatment in the United States, especially in rural communities. In fact, it is estimated that over 40% of residents in Mississippi (MS) and Alabama (AL) rely on OWTS to treat their wastewater with some of the highest reliance among coastal areas. Although many OWTSs can go decades without any issues, some scholars estimate the OWTS failure rate to be upwards of 40%. Recent research also suggests that the contribution of OWTS as a non-point source of water contamination is greater than once expected and should be explicitly considered in local watershed management plans. However, due to a lack of oversight and regulation (and the fact that OWTS are located underground), OWTS locations are often unknown or undocumented which makes quantifying their potential contribution to watershed pollution exceedingly difficult. Additionally, there are sectors of the population that simply cannot afford to install or maintain the infrastructure required to treat wastewater, and as a result inequities in contaminant exposure linked to OWTS failure may disproportionately affect vulnerable populations. In this work we propose to develop cutting-edge modeling and ground-truthing approaches for understanding the complex human-environmental relationship between OWTSs, human practices, and coastal habitats and ecosystems. This project will build the first comprehensive database of OWTS locations in coastal areas of MS and AL to build a spatially explicit pollution potential model associated with OWTS failure across coastal MS and AL.
We will work with local agencies responsible for OWTSs management in MS and AL and Extension partners to explore four interrelated objectives associated with this project: 1) construct a spatially explicit OWTS database with human and environmental variables that will enable modeling and validation; 2) create an OWTS pollution potential model to pinpoint areas where surface water and humans may be at heightened risk of contamination from OWTS failure as a function of climate hazard exposure (flooding and storm surge), existing social vulnerability status, environmental and structural characteristics, and prevalence of OWTS; 3) validate the model created in Objective 2 through an in-situ sampling strategy covering both high and low risk locations across several watersheds in MS and AL; 4) synthesize and share results with a broad audience through our Advisory Committee made up of representatives from local government agencies and Extension programs in MS and AL.
The results of this work will contribute to MASGC goals 3, 4, 7 and 8, and can be used to inform our understanding of how non-point source pollution from OWTS affects coastal surface water resources. Additionally, we will highlight areas where risk of contamination caused by climate hazards is greatest and provide a mechanism to identify communities that face social and or economic burdens that make them more vulnerable to the outcomes of OWTS pollution. We will work directly with county Extension offices to develop targeted outreach and informational material, water resource managers for implementing watershed management plans, and local stakeholders to build awareness around OWTS risk.
Objectives
The overall goal of this research is to work with local agencies responsible for OWTSs management in MS and AL via our Advisory Committee to deepen our understanding of the spatial distribution and community reliance on OWTS, and to assess the environmental risks associated with their failure to better equip communities for future environmental and health burdens on coastal communities. There are four interrelated objectives associated with this goal.
- Database Creation
- Pollution Potential & Vulnerability Modeling
- Model Validation & Refinement
- Disseminate Results & Data
Methodology
Objective 1 - Database Creation
Task 1.1: Create OWTS Inventory; collaborate with members of our Advisory Committee to facilitate networking and data sharing to obtain OWTS location data for five counties in MS (Jackson, Harrison, Hancock) and AL (Mobile, Baldwin) to build a spatially-explicit database of OWTS locations.
Task 1.2: Develop Human-Environmental Database; create inventory of existing datasets from federal agencies for both the human and environmental components of this study.
Task 1.3: Estimate OWTS Density; use information collected on known OWTS locations across MS and AL to develop a predictive model based on environmental and infrastructural covariates that we will use to estimate OWTS density at unknown coastal locations.
Objective 2 - Pollution Potential & Vulnerability Modeling
Task 2.1: Develop and Validate Pollution Potential Model; construct an OWTS pollution potential model for coastal counties in MS and AL. GIS-based model uses Multi-Criteria Decision Analysis with environmental, human and OWTS input layers to predict areas of high OWTS failure risk.
Task 2.2: Assess Community Vulnerability Profile; evaluate the relationship between socio-economic and demographic characteristics of coastal communities in MS and AL to determine the level of social vulnerability and assess how it relates to estimated OWTS pollution potential.
Objective 3 - Model Validation & Refinement
Task 3.1: Reactive and conservative tracers for OWTS effluent will be measured in streambed groundwater and used to ground-truth the pollution potential model. We will collect ~200 samples throughout 8-10 watersheds in MS and AL.
Objective 4 - Disseminate Results & Data
Task 4.1: collaborate with our Advisory Committee (see list of project partners), that work directly in and with members of coastal MS and AL communities to share results. Data visualization and sharing tools will be developed as open access portals to share results with stakeholders through co-production of knowledge with the Advisory Committee.
Rationale
OWTSs are a prevalent and affordable means of wastewater treatment in the United States, especially in rural communities. In fact, it is estimated that over 40% of residents in Mississippi and Alabama rely on OWTS to treat their wastewater; some of the highest reliance on OWTS in the country. Due to a lack of oversight and regulation (and the fact that OWTS are located underground), OWTS locations are often unknown or undocumented in some areas of the country due to data digitization and accessibility issues. However, recent research findings from the PIs on this proposal suggest that the contribution of OWTS as a non-point source of water contamination is greater than once expected and should be considered in local watershed management plans, thus OWTS location data are critical. Additionally, there are sectors of the population that simply cannot afford to install or maintain the infrastructure required to treat wastewater and therefore, inequities exist which exacerbate the contamination risk to vulnerable populations. With the existing limitations of OWTS data and relatively high reliance on OWTS among coastal communities, the true extent of risk from OWTS failure to vulnerable coastal communities in MS and AL is currently unknown. Thus, in this work we propose to develop cutting-edge modeling and ground-truthing approaches for understanding the complex human-environmental relationship between OWTSs, human practices, and coastal habitats and ecosystems. Thus, this proposal is critical and innovative as it will build the first comprehensive database of OWTS locations in coastal areas of MS and AL to model and validate the risks associated with OWTS failure to both the environment and human health in coastal MS and AL, a region already vulnerable to climate hazards.