EGU23-10820
https://doi.org/10.5194/egusphere-egu23-10820
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Using Boa for Multi-Objective Optimization of the hydrodynamic canopy transpiration model FETCH3.14

Madeline Scyphers1, Justine Missik1, Gil Bohrer1, Joel Paulson2, Yair Mau3, Marcela Silva4, Ashley Matheny5, and Ana Maria Restrepo Acevedo5
Madeline Scyphers et al.
  • 1Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, OH, USA
  • 2Department of Chemical and Biomolecular Engineering, The Ohio State University, OH, USA
  • 3Institute of Environmental Sciences, The Hebrew University of Jerusalem, Rehovot, Israel
  • 4Department of Civil Engineering, Monash University, Clayton, VIC, Australia
  • 5Department of Geological Sciences, Jackson School of Geosciences, University of Texas at Austin, TX, USA
Species-specific hydraulic traits play a critical role in determining the response of ecosystem carbon and water fluxes to water stress. Improving the representation of plant hydraulic behavior in vegetation and land-surface models is critical for improving our predictions of the impacts of water stress on ecosystem carbon and surface fluxes given that biodiverse representation of forest canopies remain challenging for land-surface models. Here, we use FETCH3.14, a multispecies, canopy-level, hydrodynamic transpiration model which builds upon the previous versions of the Finite-difference Ecosystem-scale Tree Crown Hydrodynamics model (FETCH). FETCH3.14 is parameterized by our newly developed package, Bayesian Optimization for Anything (BOA), which facilitates and eases hyperparameter optimization using multi-scale and multi-variate observations.

BOA incorporates multiple sources of data easily, reduces optimization setup time, and eases advanced use cases such as High-Performance Computing (HPC) parallelization and optimization restarting. BOA facilitates multi-source data assimilation for FETCH3.14 from a disparate range of sources including ET observations, soil and stem water potential observations, and carbon flux observations to provide insights about species-specific hydraulic traits. We use flux data from representative model trees that get scaled to the plot level based on the composition of species and structure of the canopy in the plot, which allows parameterization using tree level observations (sap flux, stem water storage) and plot level observations (eddy covariance evapotranspiration). We use BOA to set up a multi-objective optimization inverse problem with little overhead or extra boilerplate code. This approach allows us to utilize multi-scale observations to resolve information about species-specific hydraulic parameters, including parameters that are difficult or impossible to measure in the field.

How to cite: Scyphers, M., Missik, J., Bohrer, G., Paulson, J., Mau, Y., Silva, M., Matheny, A., and Restrepo Acevedo, A. M.: Using Boa for Multi-Objective Optimization of the hydrodynamic canopy transpiration model FETCH3.14, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10820, https://doi.org/10.5194/egusphere-egu23-10820, 2023.