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Sensitivity analysis of the maximum entropy production method to model evaporation in boreal and temperate forests

Citation

Maheu, Audrey et al. (2021), Sensitivity analysis of the maximum entropy production method to model evaporation in boreal and temperate forests, Dryad, Dataset, https://doi.org/10.5061/dryad.cjsxksn4v

Abstract

The maximum entropy production (MEP) approach has been little used to simulate evaporation in forests and its sensitivity to input variables has yet to be systematically evaluated. This study addresses these shortcomings. First, we show that the MEP model performed well in simulating evaporation during the snow-free period at six sites in temperate and boreal forests (0.68 ≤ NSE ≤ 0.82). Second, we computed a sensitivity coefficient S  representing the proportion of change in the input variable transferred to the latent heat flux (λE). Net radiation (Rn) was the most influential variable (S » 1) at all sites, indicating that an increase in Rn translates into an equivalent increase in λE. The MEP model avoided the issue of oversensitivity to air temperature (S < 0.5 at peak evaporation) and captured limitations to transpiration associated with the atmospheric evaporative demand. Overall, the MEP model offers a promising tool for climate change studies.

Methods

We selected six sites hosting eddy-covariance flux towers from the AmeriFlux and Fluxnet networks. At each site, we modeled evaporation using the maximum entropy production method (Wang and Bras, 2011) for the snow-free period. We performed a sensitivity analysis using the method of Beven (1979) to assess the sensitivity of the MEP model to variations to input variables.

Usage Notes

FOLDER ORGANIZATION

|- Figure 1 --> ETpred
| |- Data
| |- Code
| |- Results
| |- Plot

|- Figure 2 --> Sensitivity analysis
| |- Data
| |- Code
| |- Results
| |- Plot

|- Figure 3 --> VPD vs ET/Rn
| |- Code
| |- Plot

|- Table 2 --> performance ETpred
| |- Code
| |- Results

|- Table S2 --> impact of fixing ns=1
| |- Code
| |- Data
| |- Results

|- Table S3 --> impact of energy budget closure correction
| |- Code
| |- Data
| |- Results

Funding

Natural Sciences and Engineering Research Council of Canada, Award: RGPIN-04199

National Science Foundation, Award: EAR‐1331846

National Aeronautics and Space Administration, Award: NNX15AT41G