青藏高原季节性冻土湿度模拟及参数优化——以黑河上游为例

发布时间：2018-08-17 17:12

【摘要】：利用青藏高原东北部地区阿柔冻融观测站2013年5月至2014年11月观测资料,对通用陆面过程模式(CLM4.0)和动态陆面过程模式(DLM)青藏高原高寒地区土壤湿度模拟性能进行了评估。结果显示两种模式均能够较好的反映浅层(40 cm)土壤湿度动态变化,然而显著低估非冻结期土壤湿度;通过土壤有机质含量对土壤湿度模拟敏感性分析发现模式模拟土壤湿度偏干可能与模式中土壤有机质方案不足有关。在此基础上改进DLM模式土壤有机质和冻土液态水渗透方案,实验结果表明新参数化方案显著提高了高寒、高有机质含量地区模式土壤湿度模拟,平均偏差(BIAS)、均方根误差(RMSE),均方差(MSE)和相关系数(R)分别达到0.032 m~3·m~(-3),0.078 m~3·m~(-3),0.010 m~3·m~(-3)和0.866。
[Abstract]:Based on the observational data from May 2013 to November 2014 at Arou Freeze-thaw Observatory in the northeastern part of the Qinghai-Xizang Plateau, the soil moisture simulation performance of the general land surface process model (CLM4.0) and the dynamic land surface process model (DLM) in the alpine region of Qinghai-Xizang Plateau was evaluated. The results showed that both models could reflect the dynamic changes of soil moisture in shallow layer (40 cm), but significantly underestimated soil moisture during non-freezing period. Based on the sensitivity analysis of soil organic matter content to soil moisture simulation, it was found that the dry soil moisture simulated by the model may be related to the lack of soil organic matter scheme in the model. On this basis, the DLM model soil organic matter and frozen soil liquid water infiltration scheme was improved. The experimental results show that the new parameterization scheme can significantly improve the simulation of soil moisture in high cold and high organic content regions. The mean deviation (BIAS), root mean square error (RMSE),) (MSE) and correlation coefficient (R) were 0.032 mt3m-3 and 0.86666, respectively.
【作者单位】：中国科学院地理科学与资源研究所/资源与环境信息系统国家重点实验室;中国科学院大学;中国科学院西北生态环境资源研究院/黑河遥感试验研究站;北京市气象局气象信息中心;
【基金】：国家科技支撑项目(2013BAC03B04) 国家自然科学基金项目(41271116,31500402)
【分类号】：S152.71

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