Analysis of Streamflow Complexity Based on Entropies in the Weihe River Basin, China

Abstract

The study on the complexity of streamflow has guiding significance for hydrologic simulation, hydrologic prediction, water resources planning and management. Utilizing monthly streamflow data from four hydrologic control stations in the mainstream of the Weihe River in China, the methods of approximate entropy, sample entropy, two-dimensional entropy and fuzzy entropy are introduced into hydrology research to investigate the spatial distribution and dynamic change in streamflow complexity. The results indicate that the complexity of the streamflow has spatial differences in the Weihe River watershed, exhibiting an increasing tendency along the Weihe mainstream, except at the Linjiacun station, which may be attributed to the elevated anthropogenic influence. Employing sliding entropies, the variation points of the streamflow time series at the Weijiabu station were identified in 1968, 1993 and 2003, and those at the Linjiacun station, Xianyang station and Huaxian station occurred in 1971, 1993 and 2003. In the verification of the above points, the minimum value of t-test is 3.7514, and that of Brown–Forsythe is 7.0307, far exceeding the significance level of 95%. Also, the cumulative anomaly can detect two variation points. The t-test, Brown–Forsythe test and cumulative anomaly test strengthen the conclusion regarding the availability of entropies for identifying the streamflow variability. The results lead us to conclude that four entropies have good application effects in the complexity analysis of the streamflow time series. Moreover, two-dimensional entropy and fuzzy entropy, which have been rarely used in hydrology research before, demonstrate better continuity and relative consistency, are more suitable for short and noisy hydrologic time series and more effectively identify the streamflow complexity. The results could be very useful in identifying variation points in the streamflow time series.

Chaos arising from the hydrological behaviour of a floodplain river during the last century

“…As regards the longitudinal dimension of the Paraná River, a spatial difference was found in the characterisation of the hydrological behaviour as it was observed in other rivers (Kedra, 2014;Ma, Kang & Song, 2020). The Hurst exponent revealed a latitudinal gradient from less to more persistence system dynamic.…”

“…In floodplain systems, such as the Paraná River, ecological functioning, biodiversity patterns, and cycles of biological communities mainly depend on the hydrological regime (Junk, Bayley & Sparks, 1989;Neiff, 1990;Bunn & Arthington, 2002;Thomaz et al , 2007). Investigating the complexity of the hydrological processes is fundamental for developing a proper planning and managing of rivers (Ma et al , 2020), and for understanding the underlying processes of diversity assembly (Devercelli et al , 2016). Medvinskyet al (2001 pointed out the importance of chaotic regimes in the organization of aquatic ecosystems.…”

“…As a general overview, there are many factors influencing the complexity and chaotic dynamic of rivers, and they vary in the longitudinal gradient (Ma et al , 2020). Some factors are inherent to the configuration of rivers, such as geomorphology, topography, sediment transport, inflow composition, and vegetation (Tabacchi et al , 1998;Poff, Olden, Pepin, & Bledsoe, 2006); while other factors are external to the configuration of rivers, such as meteorological factors (precipitation, temperature, atmospheric pressure) and anthropic interventions (McManamay, Bevelhimer & Kao, 2014).…”

Multiscale Analysis of Runoff Complexity in the Yanhe Watershed

“…Frequent and intense human activities, such as afforestation and deforestation, grassland conversion, urbanization, and dam construction, determine rainfall redistribution and alter surface runoff, infiltration, groundwater recharge, instream flow, and evapotranspiration processes [ 6 , 7 ]. Runoff, the key component of the hydrological cycle, is directly or indirectly influenced by numerous types of positive and negative feedbacks at various scales, such as rainfall, climate change, human activities, and other surface factors [ 8 , 9 ], so that the runoff of a watershed is a complex system that is nonlinear, nonstationary, and uncertain [ 10 , 11 ]. Complexity is an essential and core feature of a hydrological system [ 12 ].…”

Multiscale Complexity Analysis of Rainfall in Northeast Brazil

“…These studies include fractal and multifractal methods [22][23][24][25], chaos theory [26,27], information measures [28][29][30], and complex networks [31][32][33] that have been extensively used to assess the degree of nonlinearity and the complexity of rainfall dynamics. Recently, entropy measures have attracted considerable attention as a tool to analyze the irregularity and the rate of information flow in order to access different regimes in hydrological temporal series [34][35][36][37][38].…”