标题：A fundamental theorem for eco-environmental surface modelling and its applications
作者：Yue, Tianxiang; Zhao, Na; Liu, Yu; Wang, Yifu; Zhang, Bin; Du, Zhengping; Fan, Zemeng; Shi, Wenjiao; Chen, Chuanfa; Zhao, Mingwei; 更多 作者机构：[Yue, Tianxiang; Zhao, Na; Du, Zhengping; Fan, Zemeng; Shi, Wenjiao; Wang, Shihai; Song, Yinjun; Wang, Chenliang; Zhou, Wei; Liu, Yi; Wang, Zong; Bao, 更多
通讯作者地址：Yue, TX; Fan, ZM (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijin 更多
来源：SCIENCE CHINA-EARTH SCIENCES
关键词：HASM; FTEEM; Spatial upscaling; Spatial downscaling; Spatial; interpolation; Data fusion; Model-data assimilation; Model coupling
摘要：We propose a fundamental theorem for eco-environmental surface modelling (FTEEM) in order to apply it into the fields of ecology and environmental science more easily after the fundamental theorem for Earth's surface system modeling (FTESM). The Beijing-Tianjin-Hebei (BTH) region is taken as a case area to conduct empirical studies of algorithms for spatial upscaling, spatial downscaling, spatial interpolation, data fusion and model-data assimilation, which are based on high accuracy surface modelling (HASM), corresponding with corollaries of FTEEM. The case studies demonstrate how eco-environmental surface modelling is substantially improved when both extrinsic and intrinsic information are used along with an appropriate method of HASM. Compared with classic algorithms, the HASM-based algorithm for spatial upscaling reduced the root-mean-square error of the BTH elevation surface by 9 m. The HASM-based algorithm for spatial downscaling reduced the relative error of future scenarios of annual mean temperature by 16%. The HASM-based algorithm for spatial interpolation reduced the relative error of change trend of annual mean precipitation by 0.2%. The HASM-based algorithm for data fusion reduced the relative error of change trend of annual mean temperature by 70%. The HASM-based algorithm for model-data assimilation reduced the relative error of carbon stocks by 40%. We propose five theoretical challenges and three application problems of HASM that need to be addressed to improve FTEEM.