Continental Scale Model-Data Iteration to Understand Hyporheic Zone Respiration Using ICON Science

In river corridors the hyporheic zone can be the dominant driver of whole channel metabolism, but it can also be a minor contributor, with literature estimates ranging from 4-96% of stream metabolism coming from the hyporheic zone. What's driving this variability is unknown and there have been no models that can explain among-stream-reach variation in the hyporheic zone contribution to stream metabolism. This significant gap in river corridor science needs to be addressed to advance our collective ability to understand and predict the future state of river corridor hydro-biogeochemical function (e.g., greenhouse gas emission rates). We have approached this challenge with a continental-scale effort aimed at producing knowledge and models that are transferable/generalizable across diverse river corridor settings. We simultaneously aim to generate science outcomes, data products, and modeling infrastructure that is mutually beneficial across a broad range of stakeholders. To do so, we are using ICON Science principles to conduct an ongoing study that is Integrated across disciplines, Coordinated via use of consistent protocols, Open throughout the research lifecycle, and Networked with multiple stakeholders to understand and respond to diverse needs. Through globally open engagement prior to initiating the study, we received feedback and modified the study design so that project outcomes would be beneficial to as many stakeholders as possible. Initial engagement was followed by crowdsourcing samples across the contiguous United States, with sampling locations guided by machine learning (ML) models. Resulting estimates of hyporheic zone respiration were used to test the ML models, update those models, and generate new ML-based guidance on where to sample next. This feedback between models and data generation is ongoing monthly, with significant changes to the spatial distribution of prioritized sampling locations. The engagement process is also approached as an iterative loop, with follow-on engagement in educational settings and direct student participation. Intentional use of ICON principles and iterative feedback between models and data is providing new opportunities for a broad range of researchers, providing unprecedented abilities to predict and understand hyporheic zone biogeochemistry, and generating FAIR products for all to benefit from.