Crowdsourcing Hydrologic Data

Numerical modeling in water resources is frequently constrained by a "data-poor" reality, particularly within small headwater streams or urban areas where traditional monitoring costs are prohibitive. This presentation examines the utility of crowdsourcing and citizen science—leveraging platforms like CrowdHydrology—to acquire high-resolution hydrologic data through ubiquitous mobile technologies. While these methods significantly extend the spatial and temporal reach of data collection and foster public scientific literacy, they introduce complexities regarding data uncertainty, volunteer recruitment bias, and participant ethics. Consequently, this talk evaluates examples and tools researchers can use to integrate citizen-provided observations into robust hydrologic projects and models, ensuring that non-traditional data streams maintain scientific integrity.

Dr. Chris Lowry is a faculty member in the Department of Earth Sciences at the University at Buffalo. His research focuses on groundwater-dependent ecosystems and water security. Most of this work is within the first 10 meters of the earth’s surface and uses a combination of field methods and numerical models. His field sites range from pristine settings in high-elevation meadows to rain gardens in urban environments. He is particularly excited about improving numerical models using novel approaches to collecting hydrologic data, including new field methods, geophysics, and citizen science.