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A fundamental theorem for eco-environmental surface modelling and its applications

Authors :
Wenjiao Shi
Shengnan Ma
Changqing Yan
Hongsheng Huang
Ming Lu
Yang Yang
Ying’an Wang
Xiaozhe Yin
Xiaofang Sun
Chuanfa Chen
Saibo Li
Na Zhao
John Wilson
Yuzhu Wang
Mingwei Zhao
Bin Fan
Wei Zhou
Qiquan Li
Lili Zhang
Yifu Wang
Wei Wang
Zhengyi Bao
Chenliang Wang
Ufra Naseer
Yu Liu
Shihai Wang
Miaomiao Zhao
Yinjun Song
Yapeng Zhao
Zong Wang
Zhang Bin
Yi Liu
Qing Wang
Yimeng Jiao
Zhengping Du
Yimin Lu
Tianxiang Yue
Yong-Zhong Tian
Dunjiang Song
Zemeng Fan
Source :
Science China Earth Sciences. 63:1092-1112
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

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.

Details

ISSN :
18691897 and 16747313
Volume :
63
Database :
OpenAIRE
Journal :
Science China Earth Sciences
Accession number :
edsair.doi...........4ab7b756bf8c3a0b10ef4d2a93af6dfa