Preprints
https://doi.org/10.5194/gmd-2022-148
https://doi.org/10.5194/gmd-2022-148
Submitted as: development and technical paper
20 Jun 2022
Submitted as: development and technical paper | 20 Jun 2022
Status: this preprint is currently under review for the journal GMD.

Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics

Yilin Fang1, Ruby Leung1, Charlie Koven2, Gautam Bisht1, Matteo Detto3, Yanyan Cheng4, Nate McDowell1,5, Helene Muller-Landau6, S. Joseph Wright6, and Jeff Chambers2 Yilin Fang et al.
  • 1Pacific Northwest National Laboratory, Richland, WA, United States
  • 2Lawrence Berkeley National Laboratory, Berkeley, CA, United States
  • 3Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States
  • 4Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore
  • 5School of Biological Sciences, Washington State University, Pullman, WA, United States
  • 6Smithsonian Tropical Research Institute, Balboa, Panama

Abstract. Topographic heterogeneity and lateral subsurface flow at the hillslope scale of ≤ 1 km may have outsized impacts on tropical forest through their impacts on water available to plants under water stressed conditions. However, vegetation dynamics and finer‐scale hydrologic processes are not concurrently represented in Earth system models. In this study, we integrate the Energy Exascale Earth System Model (E3SM) Land Model (ELM) that includes the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES), with a three-dimensional hydrology model (ParFlow) to explicitly resolve hillslope topography and subsurface flow and perform numerical experiments to understand how hillslope scale hydrologic processes modulate vegetation along water availability gradients at Barro Colorado Island (BCI), Panama. Our simulations show that groundwater table depth (WTD) can play a large role in governing aboveground biomass (AGB) when drought-induced tree mortality is triggered by hydraulic failure. Analyzing the simulations using random forest (RF) models, we find that the domain-wide simulated AGB and WTD can be well predicted by static topographic attributes including surface elevation, slope and convexity, and adding soil moisture or ground water table depth as predictors further improves the RF models. Different model representations of mortality due to hydraulic failure can change the dominant topographic driver for the simulated AGB. Contrary to the simulations, the observed AGB in the well-drained 50-ha forest census plot within BCI cannot be well predicted by the RF models using topographic attributes and observed soil moisture as predictors, suggesting other factors such as nutrient status may have larger influence on the observed AGB. The new coupled model may be useful for understanding the diverse impact of local heterogeneity by isolating the water availability and nutrient availability from the other external and internal factors in ecosystem modeling.

Yilin Fang et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-148', Anonymous Referee #1, 04 Aug 2022
  • RC2: 'Comment on gmd-2022-148', Anonymous Referee #2, 11 Aug 2022

Yilin Fang et al.

Model code and software

A coupled model of hillslope hydrology and ecosystem dynamics, version 1.0 Yilin Fang, Ruby Leung, Charlie Koven, Gautam Bisht, Matteo Detto, Yanyan Cheng, Nate McDowell, Helene Muller-Landau, S. Joseph Wright, and Jeff Chambers https://doi.org/10.5281/zenodo.6595795

Yilin Fang et al.

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Short summary
We develop a model that integrates an Earth system model with a 3D hydrology model to explicitly resolve hillslope topography and water flow underneath the land surface to understand how local scale hydrologic processes modulate vegetation along water availability gradients. Our coupled model can be used to improve the understanding of the diverse impact of local heterogeneity and water flux on nutrient availability and plant communities.