Complexity Analysis of Environmental Time Series
环境时间序列的复杂性分析AI 解读 ↓
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环境时间序列的复杂性分析
- 研究问题
- 如何刻画邻近森林流域中水、物质通量及养分浓度序列的复杂动态，并考察这些特征在变量和流域之间是否具有共性？
- 方法与思路
- 作者对长期双周数据进行补缺、去趋势和去年度周期，再计算序数模式熵、复杂度、费舍尔信息及可见图指标，并与随机过程比较。
- 材料陈述的贡献
- 摘要称，多种复杂性工具共同构成系统动态的表征，为比较变量和流域间的普适性提供基础；摘要未报告普适性已被证实。
- 阅读关注点
- 应核对 SSA 预处理对动态指标的影响、序数模式参数和参考过程设定，以及区分确定性混沌与结构化噪声的证据强度。
- 阅读边界
- 这是 arXiv 预印本，同行评审及接收状态未核实。摘要未给出指标结果或显著性，不能认定发现混沌、普适规律或因果机制。
原文摘要
Small, forested catchments are prototypes of terrestrial ecosystems and have been studied in several disciplines of environmental sciences since several decades. Time series of water and matter fluxes and nutrient concentrations from these systems exhibit a bewildering diversity of spatio-temporal patterns, indicating the intricate nature of processes acting on a large range of time scales. Nonlinear dynamics is an obvious framework to investigate catchment time series. We analyze selected long-term data from three headwater catchments in the Bramke valley, Harz mountains, Lower Saxony in Germany at common biweekly resolution for the period 1991 to 2023. For every time series, we perform gap filling, detrending and removal of the annual cycle using Singular System Analysis (SSA), and then calculate metrics based on ordinal pattern statistics: the permutation entropy, permutation complexity and Fisher information, as well as their generalized versions (q-entropy and α-entropy). Further, the position of each variable in Tarnopolski diagrams is displayed and compared to reference stochastic processes, like fractional Brownian motion, fractional Gaussian noise, and \b{eta} noise. Still another way of distinguishing deterministic chaos and structured noise, and quantifying the latter, is provided by the complexity from ordinal pattern positioned slopes (COPPS). We also construct Horizontal Visibility Graphs and estimate the exponent of the decay of the degree distribution. Taken together, the analyses create a characterization of the dynamics of these systems which can be scrutinized for universality, either across variables or between the three geographically very close catchments.