Schäfer Benjamin, Heppell Catherine M, Rhys Hefin, Beck Christian
School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, UK.
Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway.
iScience. 2021 Jul 21;24(8):102881. doi: 10.1016/j.isci.2021.102881. eCollection 2021 Aug 20.
Superstatistics is a general method from nonequilibrium statistical physics which has been applied to a variety of complex systems, ranging from hydrodynamic turbulence to traffic delays and air pollution dynamics. Here, we investigate water quality time series (such as dissolved oxygen concentrations and electrical conductivity) as measured in rivers and provide evidence that they exhibit superstatistical behavior. Our main example is time series as recorded in the River Chess in South East England. Specifically, we use seasonal detrending and empirical mode decomposition to separate trends from fluctuations for the measured data. With either detrending method, we observe heavy-tailed fluctuation distributions, which are well described by log-normal superstatistics for dissolved oxygen. Contrarily, we find a double peaked non-standard superstatistics for the electrical conductivity data, which we model using two combined -distributions.
超统计是一种来自非平衡统计物理学的通用方法，已应用于各种复杂系统，从流体动力学湍流到交通延误和空气污染动力学。在此，我们研究河流中测量的水质时间序列（如溶解氧浓度和电导率），并提供证据表明它们呈现超统计行为。我们的主要示例是英格兰东南部切斯河中记录的时间序列。具体而言，我们使用季节性去趋势化和经验模态分解从测量数据的波动中分离出趋势。使用任何一种去趋势化方法，我们都观察到重尾波动分布，对于溶解氧，对数正态超统计能很好地描述这种分布。相反，我们发现电导率数据呈现双峰非标准超统计，我们用两个组合的 - 分布对其进行建模。
