A Hypothesis-Driven ModEx Approach for Mechanistic Understanding of Hyporheic Zone Biogeochemistry

Authors

Jianqiu Zheng* ([email protected]), Vanessa Garayburu-Caruso, Amy Goldman, James Stegen, Tim Scheibe

Institutions

Pacific Northwest National Laboratory, Richland, WA

URLs

• https://www.pnnl.gov/projects/river-corridor

Abstract

The hyporheic zone plays a dominant role in channel metabolism and biogeochemistry for river corridor systems. Hyporheic sediment respiration often exhibits high spatial variability within and across river basins, imposing a substantial challenge for building transferable process representations in predictive models of river corridor biogeochemical functions. This study used a hypothesis-driven approach that integrates theoretical knowledge generation, model development, and numerical experimentation to address this challenge. This approach allowed the research team to incorporate process information from new data and physical consistency with previously developed theories for more accurate and scalable biogeochemical predictions.

Building upon the team’s previous hypotheses regarding thermodynamic controls, returns on investment, and bioavailability that provide partial explanations for observed patterns in sediment respiration across continental scale, researchers further hypothesized that the biological and physical properties of hyporheic zone sediments modulate variations of sediment respiration rates. A numerical experiment showed low substrate accessibility significantly reduces the probability for a microbe to be surrounded by substrate, and thus decreases the effective organic matter concentration, leading to lower predictions of respiration rates. Similarly, increasing variations in microbial biomass among sites disproportionately generated wider distributions of predicted rates. Both numerical observations provided additional explanatory power for empirical distributions of rate measurements.

In addition, the modeling experiments provided new model-generated hypotheses that require specific data types to evaluate, such as microbial biomass and sediment grain size distribution that are readily available from the WHONDRS (Worldwide Hydro-biogeochemistry Observation Network for Dynamic River Systems) research consortium, thus furthering the hypotheses-driven ModEx cycle. This study illustrates the concept and application of hypothesis-driven ModEx in which each model-data hand off is based on and guided by specific hypotheses. This is distinct from traditional ModEx approaches that emphasize data assimilation.