Watershed Dynamics and Evolution Science Focus Area Modeling Crosscut: Model-Data Integration Strategies for Stream Metabolism Studies
Authors
Saubhagya Rathore*, Phong Le, Scott L. Painter (paintersl@ornl.gov), Eric M. Pierce
Institutions
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN
URLs
Abstract
Conservative and reactive tracer tests, laboratory experiments, and continuous stream chemistry measurements are among the techniques available to characterize stream hydro-biogeochemical function. The Watershed Dynamics and Evolution SFA is developing and testing approaches and software to aid in the interpretation of those measurements, with a focus on stream metabolism. In particular, a novel multiscale model (Painter 2018) for transport in stream corridors is being combined with uncertainty-aware estimation of model parameters through Bayesian inference and the Markov chain Monte Carlo algorithm. Previous research showed that jointly interpreting tracer data from multiple observation points or different biogeochemical experiments increases the reliability of parameter estimates (Rathore et al. 2021; Rathore et al. 2022; Le et al. in review). Models can also be essential in evaluating experimental designs and assessing potential for system mischaracterization, as demonstrated by Rathore et al. (in review), for photosensitive tracers as a strategy to separate hyporheic and surface storage zone effects. This research extends those parameter identifiability studies to include stream metabolism models. A stream metabolism model was implemented into the PFLOTRAN software and combined with the project’s multiscale stream corridor model in the Advanced Terrestrial Simulator to construct a reach- to watershed-scale reactive transport model for dissolved oxygen dynamics. Using the Modeling Crosscut team’s reactive transport model, scientists performed numerical experiments to interpret synthetic dissolved oxygen time series through Bayesian inverse modeling under different relative contributions of gross primary productivity, ecosystem respiration, reaeration, and groundwater exchange to study parameter uncertainty and identifiability. These insights are helpful for designing data collection campaigns aiming to characterize stream metabolic function. Furthermore, the workflow tools developed will be used to analyze new measurements as they become available.
References
Le, V. P., et al. “A Multiscale Model for Solute Transport in Stream Corridors with the Unsteady Flow.” In review.
Painter, S. L. 2018. “Multiscale Framework for Modeling Multicomponent Reactive Transport in Stream Corridors,” Water Resources Research 54(10), 7216–7230. DOI:10.1029/2018WR022831.
Rathore, S. S., et al. 2021. “On the Reliability of Parameter Inferences in a Multiscale Model for Transport in Stream Corridors,” Water Resources Research 57(5), e2020WR028908. DOI:10.1029/2020WR028908.
Rathore, S. S., et al. 2022. “Joint Estimation of Biogeochemical Model Parameters from Multiple Experiments: A Bayesian Approach Applied to Mercury Methylation,” Environmental Modelling & Software 155, 105453. DOI:10.1016/j.envsoft.2022.105453.
Rathore, S. S., et al. “Numerical Evaluation of Photosensitive Tracers as a Strategy for Separating Surface and Subsurface Transient Storage in Streams.” In review.