Abstract
The scope of literature related to septic system maintenance from an educational and behavioral perspective, rather than a quantitative water quality approach, is limited. The water resources management community needs improved insight into the human factors related to septic system maintenance decisions and identification of effective intervention strategies. Using a modified Theory of Planned Behavior (TPB; Ajzen 1991) framework, the purpose of this study was to identify factors that predict homeowners’ intention to have their systems inspected and pumped within the next three years. As part of a small-scale educational program, a survey was sent to 1,374 homeowners with septic systems in Jackson and Matagorda counties, Texas. A Boruta feature-selection algorithm was applied under the structure of random forests classification to four models with the following variable domains: 1) demographic variables only, 2) septic system variables only, 3) past behavior variables only, and 4) perceptions of septic system maintenance (TPB) variables only. A fifth comprehensive model with all variables was also tested to compare the influence of all variables in a saturated model. Application of the machine-learning algorithm revealed that the most important factors predicting positive intentions of septic system maintenance were length of time since last inspection, inspection frequency, service contract enrollment, cost of annual maintenance, and the TPB attitude statement “I think maintaining my septic system is helpful for the environment.” Though less influential, septic system age and type were also reliable predictors of intentions to participate in septic system maintenance. This study provides new information for educational initiatives addressing the human dimensions of septic system management and could be a stepping-stone for future research to expand this approach to broader, generalizable studies and other water resource topics.
