# Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation
## 3 Methodology
### Sensitivity Analysis
#### 3.3.2 Sensitivity Analysis on Biome-BGC Model  
Based on the EFAST (SimLab 2.2), 5000 pseudo values were generated for each parameter according to the probability distribution function (PDF). We used the contributions of the 25 crucial ecophysiological parameters to the five-year average GPP to measure the sensitivity of the model to parameters.  
The uncertainty information of the 25 crucial parameters for broadleaf Korean pine, characterized by PDF, is listed in Table 1. Defining the PDF for each crucial parameter was the first step for EFAST, and the variability of the parameters was mainly obtained from [PERSON] et al. [10].  
\begin{table}
\begin{tabular}{c c c c} \hline
**Parameter** & **Description** & **Unit** & **Distribution \({}^{a}\)** \\ \hline FRC:LC & New fine C: new leaf C & kgC (kgC)\({}^{-1}\) & U(0.53, 6.5) \\ SC:LC & New stem C: new leaf C & kgC (kgC)\({}^{-1}\) & U(0.62, 4.9) \\ LWC:TWC & New live wood C: new total wood C & kgC (kgC)\({}^{-1}\) & U(0.028, 0.189) \\ CRC:SC & New root C: new stem C & kgC (kgC)\({}^{-1}\) & U(0.12, 0.7) \\ CGP & Current growth proportion & Prop. & U(0.25, 0.75) \\ C:N\({}_{\mathrm{leaf}}\) & C:N of leaves & kgC (kgN)\({}^{-1}\) & N(34.5, 5.4) \\ C:N\({}_{\mathrm{lit}}\) & C:N of leaf litter & kgC (kgN)\({}^{-1}\) & N(55, 16) \\ C:N\({}_{\mathrm{fr}}\) & C:N of fine root & kgC (kgN)\({}^{-1}\) & N(48, 15) \\ C:N\({}_{\mathrm{dw}}\) & C:N of dead wood & kgC (kgN)\({}^{-1}\) & U(300, 800) \\ L\({}_{\mathrm{ced}}\) & Leaf litter cellulose proportion & \% & N(0.2, 0.01) \\ Li\({}_{\mathrm{ig}}\) & Leaf litter lignin proportion & \% & N(0.18, 0.0008) \\ FR\({}_{\mathrm{col}}\) & Fine root cellulose proportion & \% & U(0.2, 0.6) \\ FR\({}_{\mathrm{ig}}\) & Fine root lignin proportion & \% & U(0.1, 0.5) \\ DW\({}_{\mathrm{ig}}\) & Dead wood lignin proportion & \% & N(0.23, 0.0049) \\ W\({}_{\mathrm{txt}}\) & Canopy water interception coefficient & LAI\({}^{-1}\)day\({}^{-1}\) & N(0.045, 0.012) \\ K & Canopy light extinction coefficient & Unites & N(0.4, 0.007) \\ LALII\({}_{\mathrm{1 DPP}}\) & All-sided to projected leaf area ratio & LAI LAI\({}^{-1}\) & U(2.3, 3.14) \\ SLA & Canopy average specific leaf area & m\({}^{2}\) (kgC)\({}^{-1}\) & N(25, 10) \\ FLNR & Fraction of leaf N in Rubisco & Unites & U(0.01, 1) \\ G\({}_{\mathrm{max}}\) & Maximum stomatal conductance & ms\({}^{-1}\) & N(0.005, 0.0007) \\ G\({}_{\mathrm{bl}}\) & Boundary layer conductance & ms\({}^{-1}\) & N(0.03, 0.12) \\ LWP\({}_{\mathrm{i}}\) & Leaf water potential: start of conductance reduction & Mpa & U(\(-1.11\), \(-0.21\)) \\ LWP\({}_{\mathrm{f}}\) & Leaf water potential: complete conductance reduction & Mpa & U(\(-5,-1\)) \\ VPD\({}_{\mathrm{i}}\) & Vapor pressure deficit: start of conductance reduction & Pa & U(5000, 1000) \\ VPD\({}_{\mathrm{f}}\) & Vapor pressure deficit: complete conductance reduction & Pa & U(2000, 6000) \\ \hline \end{tabular} \({}^{a}\) U(min, max): uniform distribution, N (mean, standard deviation): normal distribution.  
\end{table}
Table 1: Distribution of Biome-BGC crucial ecophysiological parameters [10].