Transcending the Uniqueness of Place in the Age of Big Data

The 2019 conference will serve as a venue for field scientists and modelers to develop a comprehensive vision of the future of catchment science.

Catchment science uses intensive observation to understand how physical, chemical and biological processes interact to shape the landscape-scale functioning of ecosystems. It has frequently redefined paradigms of process understanding in hydrology, biogeochemistry, and ecology. However, transferring process knowledge to other sites and scaling knowledge to river basins has proven challenging. Advances in computing power have enabled the construction of integrated models at high spatial resolution and continental scale not only on grids but also on river reaches and their associated catchments. Is a reach-based landscape discretization more amenable to hypothesis testing than a gridded one because it captures physically meaningful landscape units? The ubiquitous predictions made by such models may provide a new approach to transcending the uniqueness of place.

This conference will explore how field-based process understanding is integrated into high-resolution, spatially extensive models. The predictions of such models essentially represent a conjecture of how hypothesized catchment processes are integrated at river basin to continental scales. The conference will also explore how these processes change in a non-stationary environment. High-resolution land-surface data (e.g. DEMs, land cover, stream networks) coupled with high-performance computing have enabled initial development of such models which tend to focus on physical processes, but challenges remain to develop comparable data sets for the subsurface (e.g. mineralogy, hydraulic properties), and how to best capture the state of the art in our understanding of hydrology, biology, ecology and geochemistry.

Conference sessions will consider the interplay between hypotheses, field observations, and models: How have "big data" techniques, such as data mining and pattern identification, impacted catchment science? Have high frequency sensor data provided new insights into hydrologic and biogeochemical processes?