Chin J Plant Ecol ›› 2018, Vol. 42 ›› Issue (12): 1131-1144.

• Research Articles •

### Testing parameter sensitivities and uncertainty analysis of Biome-BGC model in simulating carbon and water fluxes in broadleaved-Korean pine forests

LI Xu-Hua,SUN Osbert Jianxin()

1. College of Forestry, Beijing Forestry University, Beijing 100083, China
• Received:2018-09-18 Revised:2018-12-06 Online:2019-04-04 Published:2018-12-20
• Contact: Osbert Jianxin SUN E-mail:jshe@pku.edu.cn
• Supported by:
Supported by the Forestry Research for the Public Benefits of Ministry of Finance of China(201404201)

Abstract:

Aims The emergence and application of ecosystem process models have provided useful tools for studying carbon and water balances of terrestrial ecosystems at large spatiotemporal scales, but the accuracy of model simulations is affected by the parameterization of key variables among many factors. Sensitivity analysis is commonly used to screen the critical parameters that have predominant influences on model simulations. The objective of this study was to identify the critical ecophysiological parameters in Biome-BGC model in simulating annual net primary productivity (NPP) and evapotranspiration (ET) of broadleaved-Korean pine forests in Northeast China.

Methods We simulated carbon and water fluxes of broadleaved-Korean pine forests with the Biome-BGC (version 4.2) at a daily time step based on site- and species-specific parameters. Daily meteorological data for the period 1958-2015 was obtained from the China Meteorological Administration. Initialization parameters such as geographical position, soil depth, and soil texture of the site were obtained from field measurements. Among the 43 ecophysiological parameters represented in the model, 30 were derived either from field measurements or from published data for the study sites in literature, and the default values were used for 13 of the parameters. The modeled forest NPP was compared with the tree-ring width index to test the model’s ability to simulate the inter-annual variations in forest productivity. The modeled NPP and ET were also compared with existing remote sensing products for the period 2000-2014 for validation purpose. Sensitivity analysis was conducted using a variance-based sensitivity analysis method—Extended Fourier Amplitude Sensitivity Test (EFAST) to acquire the first order and total order sensitivity index of the parameters.

Important findings Our locally parameterized Biome-BGC model well simulated the carbon and water fluxes of the broadleaved-Korean pine forests. The uncertainty of simulated NPP is higher for Korean pine trees than for broad-leaved trees, while that of ET was small for both tree types. Both NPP and ET of broad-leaved trees were generally less sensitive to ecophysiological parameters than Korean pine. Leaf carbon to nitrogen ratio, fine root carbon to nitrogen ratio, specific leaf area (SLA), and water interception coef?cient were among the highly sensitive parameters affecting the modeled NPP; while fine root carbon to new leaf carbon allocation, new stem carbon to new leaf carbon allocation and SLA were the highly sensitive parameters influencing ET. In addition, fraction of leaf N in Rubisco, leaf and fine root turnover, ratio of all sided to projected leaf area are also critical parameters affecting the output of Biome-BGC simulations. The degree of sensitivity of the critical parameters varied with species and sites, highlighting the need to adopt local parametrization of Biome-BGC model in simulating regional forest carbon and water fluxes. For other non-sensitive parameters, model default value can be readily used.