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Spatiotemporal Variation in Total Sediment Load Concentration and Related Factors of Shoreline Waters Based on Disorder Power Index

机译:基于紊乱权力指数的沉积物荷载浓度及海岸线水域相关因素的时空变化

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摘要

Entropy is a property of a system which measures the uncertainty or disorder within the system. In hydraulics, uncertainties occur in flow variables, such as velocity, sediment concentration, wave. Using entropy, it is possible to establish connections between deterministic and probabilistic domains. To describe sediment transport distributional/autocorrelation properties, including scaling behavior both in state and in time, the well-founded physical and mathematical entropy theory is generally used wherein the spatiotemporal disorder power index (STDPI) is considered to have the maximum uncertainty. Effort has been made in this research to propose a novel entropy method capable of accurately calculating the total sediment load concentration (TSLC) in the shoreline region. Accordingly, STDPI and entropy method have been suggested for finding the TSLC to analyze the spatiotemporal patterns/reports based on a shoreline zone case study because STDPI is quite suitable for marine and hydrological ecosystem components analyses. The method makes use of the monthly data of six shoreline sections in Makran Ocean region in the time period between 1970 and 2015 and investigates the spatiotemporal patterns of the wave height and TLSC variables both of which depend on time and play important parts in terrestrial hydrological studies. These variables usually show meaningful spatiotemporal variability, but explanation of their combined performance is not an easy task. As the results show, STDPI can simulate TSLC and wave when concentration, flow conditions, and granulometry vary.
机译:熵是系统的一个属性,可以测量系统内的不确定性或无序。在液压系统中,在流量变量中发生不确定性,例如速度,沉积物浓度,波。使用熵,可以在确定性和概率域之间建立连接。为了描述沉积物传输分布/自相关性,包括在状态和及时的缩放行为,通常使用良好的物理和数学熵理论,其中认为时尚紊乱功率指数(STDPI)被认为具有最大的不确定性。在该研究中已经努力提出一种新的熵方法,能够准确地计算海岸线区域中的总沉积物负荷浓度(TSLC)。因此,已经提出了STDPI和熵方法来寻找基于海岸线区域案例研究来分析TSLC以分析时空模式/报告,因为STDPI非常适合海洋和水文生态系统组件分析。该方法在1970年至2015年期间的时间段内利用Makran海洋地区的六个海岸线部分的月度数据,并研究了波浪高度和TLSC变量的时空模式,两者都依赖于时间并在陆地水文研究中发挥重要部分。这些变量通常会显示有意义的时空变异性,但对其组合性能的说明并不是一项简单的任务。作为结果表明,STDPI可以在浓度,流动条件和粒度变化时模拟TSLC和波。

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