The Impact of Policies for Surface Water Protection During Wet Weather - Prototype of an Agent-Based Model to Assess Non-Technical Challenges to Monitoring CSOs
Creators: name: Derwort, Samuel
Publisher: name: Zenodo
Year: 2021
Subjects: agent-based modeling
combined sewer overflow
urban drainage
theory of planned behavior
opinion dynamics
sensor adoption

description: During wet weather, combined sewer overflow (CSO) tanks discharge wastewater into the environment to reduce the load on the wastewater treatment plant. In Switzerland, it is currently unknown how much exactly these discharges contribute to the pollution of receiving waters. This gap of knowledge could be overcome through the installation of cost-effective sensor technology in the CSO tanks and the regular evaluation of the monitoring data. The majority of Swiss wastewater associations do not evaluate the monitoring data more than once a year or aggregate it to a lower temporal resolution, which diminishes the data's potential performance-based compliance assessment and better planning of future infrastructure. This lack of evidence stands in stark contrast to the high requirements towards data management and large financial investments in wastewater treatment plants (WWTP). As practical technological solutions for sensor and data transfer technologies exist, as well as role-model utilities, which use the data effectively, the deficits are most probably political and organizational. However, it is unclear which policies can be recommended to overcome these obstacles. With a focus on the behavior and interactions of stakeholders of Swiss urban drainage management, this master thesis aims at evaluating policies to improve sensor adoption in CSO tanks. A prototype of an agent-based model (ABM) is developed based on theoretical concepts from psychology and social simulation, as well as context knowledge, e.g. for the choice of the stakeholders. To assess the potential for an empirically grounded ABM, data sets of different categories are combined and integrated into the prototype. During the process of data collection, a novel data set from Chestonag was obtained. To include urban drainage management practice, a quality check is performed via a rule-book-like list of assumptions and interviews with domain experts from cantonal authorities. For demonstration purposes, three different scenarios are developed evaluating the impact of the following policies: i) the planning instrument GEP ('Generelle Entwässerungsplanung'), ii) a regulation requiring the installation of sensors in CSO tanks, and iii) better monitoring technology. These are supplemented by four numerical experiments to assess the behavior and uncertainties of the model. In addition, a sensitivity analysis is performed using a simple screening method. Results from the scenarios for policy evaluation suggest that policy ii) is most effective. The model predicts that most agents adopt sensors shortly after the start of the simulation period in 2017, with a decreasing adoption rate after several years. However, as the ABM is a prototype, absolute results are not reliable, and also relative results have to be carefully examined. Interestingly, the sensitivity analysis reveals that the initial parameters of the agents have a high impact on the model output. The limited availability of empirical data, e.g. historical data of sensor adoption, to initialize the agent parameters leads to great uncertainties. Therefore, model parameters were adjusted ad hoc and an empirical validation is not possible. However, experts at least partly agreed to the assumptions that were taken regarding Swiss urban drainage management. In conclusion, an ABM developed for the analysis of policies cannot be expected to have predictive power, unless suitable data sets are available, which is a common challenge to ABMs. In fact, particular data sets simply might not be obtainable, such as historical data of sensor adoption. Nevertheless, the approach of ABM can be useful for system understanding. Taking a multidisciplinary approach of ABM has contributed a new understanding of the deficits regarding sensor adoption and opened up new paths for research. Further work should concentrate on data collection, the refinement of the agent behavior model using the Theory of Planned Behavior and the opinion dynamics model using survey data that is currently collected in the scope of the POLAAR project.
description: Included: Master Thesis Report, Developed Python Code, Code Documentation, POLAAR Project funded by Bundesamt für Umwelt, BAFU