From GIS to VA: : A Method to Support Infrastructure Planning

The planning of water and wastewater (VA) infrastructure is increasingly challenged by climate change, urbanization, and a shortage of qualified personnel. As urban areas grow, infrastructure systems must expand and become more efficient to meet increasing demands. Despite the growing need for streamlined and inclusive planning processes, Geographic Information System (GIS) based workflows are not commonly used in VA planning at WSP. A literature study was conducted to examine current approaches and to identify key challenges in integrating GIS into VA planning. This included a review of two VA planning projects conducted at WSP, that helped highlight relevant methods, data sources, and workflow limitations. Building on these insights, this thesis investigates how GIS, automation, and diverse data sources can be integrated to support decision-making in VA planning. The goal is to enhance collaboration between VA and GIS specialists by identifying relevant datasets and applying a semi-automated, GIS-based method to the planning process. The proposed method uses existing ArcGIS tools in ArcGIS ModelBuilder to create a semi-automated workflow that supports the early stages of water and wastewater pipeline planning. By combining preconfigured geoprocessing models with sorted datasets from previous projects, the method demonstrates how GIS can be used to support VA planners in prioritizing and visualizing pipeline-related data. Applying this methodology resulted in a summary table with key VA planning challenges such as existing infrastructure, pipeline networks, geotechnical and hydrological conditions, topography, environmental and legal constraints and economic factors. It also generated three GIS layers: one visualizing hard stops (areas where construction is not feasible), one showing soft stops (areas where construction is possible but constrained), and a third presenting the results from the multi-criteria decision analysis (MCDA). The MCDA layer evaluates areas based on weighted positive and negative parameters. These include factors such as proximity to roads (positive) and shallow soil depth (negative), with suitability visualized as a color gradient on the GIS layer. The study followed an explorative and iterative approach allowing the GIS-based method to be continuously refined through testing and adjustments. While the planner’s personal judgment and experience influenced dataset selection and parameter weighting, the workflow proved valuable for standardizing early-stage VA-planning which currently is a manual and subjective process. A comparison of the route alternatives in this thesis with the original route from previous project showed that one of the MCDA-derived paths closely aligned. With further development such as integrating Least Cost Path (LCP) analysis, a GIS layer for pressurized pipes and consideration for flood risks the GIS method could result in even more accurate and optimized routing outcomes.