A Relational Data Model for Advancing Stormwater Infrastructure Management

Abstract

To date, the knowledge benefits that can result from the growing abundance of measured stormwater data have yet to be fully realized within the industry. Obstacles due to data format and storage, retrieval, and quality control have limited the size and impact of accessing known data, resulting in data that are often siloed by project or objective, which inhibits advancements in our understanding, as well as decision making and information sharing across municipalities. Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI)’s observations data model (ODM) is a relational data model designed to organize disparate types of data; however, it does not provide avenues for the storage of stormwater monitoring–specific metadata. To facilitate stormwater infrastructure data analysis, the Villanova stormwater infrastructure data model (SIDM), constructed comparably to ODM1, was created by adding and removing tables from the ODM1 structure, along with other modifications to enable efficient data access. The novel data model presented here facilitates a comprehensive spatiotemporal analysis specific to stormwater systems to overcome traditional stormwater data siloes and harness the benefits of stormwater data through efficient avenues. The data model structure of the SIDM enables stormwater-specific data to be managed efficiently not only to provide data regarding function and performance but to advance the science around stormwater planning and management, as well as knowledge sharing across researchers, utilities, and municipalities. In this paper, we describe the logic of the design, benefits of the data model, and applications to specific green stormwater infrastructure installations. This has the potential to not only provide novel insight but open the door for applications of modeling advancement in physics-based models and beyond to artificial intelligence, data analysis, and data-informed decision making in the planning, design, operation, and maintenance of stormwater systems.