Sensitivity analysis of the De Nitrification and De Composition model for simulating regional carbon budget at the wetlandgrassland area on the Zoige Plateau, China

• Published in: 山地科学学报：英文版 Vol. 13; no. 7; pp. 1200 - 1216
• Main Author: WANG Ji-yan LI Ai-nong JIN Hua-an
• Format: Journal Article
• Language: English
• Published: 2016
• Subjects: DNDC模型; 分解模型; 土地利用类型; 模拟; 灵敏度分析; 生态系统呼吸; 碳收支; 若尔盖高原
• ISSN: 1672-6316; 1993-0321

Although mathematical models（e.g., De Nitrification and De Composition（DNDC） provide a powerful tool to study regional carbon budget, it is still difficult to obtain accurate simulation results because there exists large uncertainties in modeling regional carbon budget. Through the investigation on the sensitivity of model output parameters to the input parameters, sensitivity analysis（SA） has been proved to be able to identify the key sources of uncertainties and be helpful to reduce the model uncertainties. However, some input parameters with discrete values（e.g., land use type and soil type） and the regional effect of the sensitive parameters were rarely examined in SA. In this paper, taking the Zoige Plateau as a case area, we combined the one-factor-ata-time（OAT） with Extended Fourier Amplitude Sensitivity Test（EFAST） to conduct a SA of DNDC for simulating the regional carbon budget, including Gross Primary Productivity（GPP）, Net Primary Productivity（NPP）, Net Ecosystem Productivity（NEP）, autotrophic respiration（Ra）, soil microbial heterotrophic respiration（Rh） and ecosystem respiration（Re）. The result showed that the combination of OAT and EFAST could test the contribution of the input parameters with discrete values to the output parameters. In DNDC model, land use type and soil type had a significant impact on the regional carbon budget of the Zoige Plateau, and daily temperature was also confirmed to be one of the most important parameters for carbon budget. For the other input parameters, with the change of land use type or soil type at regional scale, the sensitive parameters of carbon budget would vary accordingly. The SA results would provide scientific evidence to optimize DNDC model and they suggested that we should pay attention to the spatial/temporal effect of SA and try to use the appropriate data in simulation of the regional carbon budget.