Journal of Geographical Sciences ›› 2019, Vol. 29 ›› Issue (9): 1441-1461.doi: 10.1007/s11442-019-1670-6

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Analyses of geographical observations in the Heihe River Basin: Perspectives from complexity theory

GAO Jianbo1,2, FANG Peng2,3, YUAN Lihua1,4   

  1. 1 State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science,Beijing Normal University, Beijing 100875, China
    2 Institute of Complexity Science and Big Data Technology, Guangxi University, Nanning 530004, China
    3 Wuhan National Laboratory for Optoelectronics, Key Laboratory of Information Storage System, Engineering Research Center of Data Storage Systems and Technology, Ministry of Education of China, School of Com-puter Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
    4 Center for GeoData and Analysis, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2018-10-30 Accepted:2019-03-20 Online:2019-09-25 Published:2019-12-11
  • About author:Gao Jianbo, Professor, specialized in complexity theory. E-mail:
  • Supported by:
    National Natural Science Foundation of China(No.71661002);National Natural Science Foundation of China(No.41671532);National Key R&D Program of China(No.2017YFB0504102);The Fundamental Research Funds for the Central Universities


Since 2005, dozens of geographical observational stations have been established in the Heihe River Basin (HRB), and by now a large amount of meteorological, hydrological, and ecological observations as well as data pertaining to water resources, soil and vegetation have been collected. To adequately analyze these available data and data to be further collected in future, we present a perspective from complexity theory. The concrete materials covered include a presentation of adaptive multiscale filter, which can readily determine arbi- trary trends, maximally reduce noise, and reliably perform fractal and multifractal analysis, and a presentation of scale-dependent Lyapunov exponent (SDLE), which can reliably dis- tinguish deterministic chaos from random processes, determine the error doubling time for prediction, and obtain the defining parameters of the process examined. The adaptive filter is illustrated by applying it to obtain the global warming trend and the Atlantic multidecadal os- cillation from sea surface temperature data, and by applying it to some variables collected at the HRB to determine diurnal cycle and fractal properties. The SDLE is illustrated to deter- mine intermittent chaos from river flow data.

Key words: Heihe River basin, geographical observation, complexity theory, adaptive multiscale filter, fractal analysis, scale-dependent Lyapunov exponent