An Expression for Velocity Lag in Sediment-Laden Open-Channel Flows Based on Tsallis Entropy Together with the Principle of Maximum Entropy

Zhu, Zhongfan; Yu, Jingshan; Dou, Jie; Peng, Danling

doi:10.3390/e21050522

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…Currently, much research has been conducted on the “production-living-ecological” function. These studies are based on land functions, with the value of ecosystem services [ 1 , 2 , 3 ], landscape ecology [ 4 , 5 , 6 ], land use change [ 7 , 8 , 9 , 10 ], and balanced development of land use benefits [ 11 , 12 ] as concerns. With the expansion of the research content of “production-living-ecological space”, the research of “production-living-ecological space” has been enriched under different research scales, such as national, provincial, municipal, and township.…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Evolution and Prediction of the Coordination Level of “Production-Living-Ecological” Function Coupling in the Yellow River Basin, China

Zhang

Wang

et al. 2022

IJERPH

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To clarify the evolution of “production-living-ecological” function coupling in the Yellow River Basin, coordinating the spatial allocation of resources, development management and layout optimization, is an important means for achieving ecological protection and high-quality development in the region. In this paper, we conducted an empirical analysis and ARIMA prediction of the coupled production-living-ecological function coordination level in the Yellow River Basin of China from 2008 to 2018, and found that: (1) In terms of temporal evolution, the production-living-ecological function and coupling coordination level of each province and region in the Yellow River Basin generally shows a sharp and then slow upward trend, with the living functions changing more than the production and ecological functions; (2) in terms of spatial pattern, the production and living functions of each province and region show the trend of functional level increasing from east to west over time; the ecological functions, contrary to production and living functions, show a “high-low” aggregation, midstream shows “low-low” aggregation, and downstream shows “low-high” aggregation; (3) According to the regression results of the spatial Dubin model, the environmental governance level, technological research and development level, and social security level and resource dependence degree have positive promoting and spillover effects on the coupling coordination level of the “production-living-ecological” function in the region. However, population density and carbon emission intensity will hinder the development of regional coupling coordination level; (4) from the ARIMA prediction, the coupling coordination level of “production-living-ecological” in the Yellow River Basin continues the development trend of 2008–2018 in the short term, the overall coordination level is at a high level, and the variability of coupling coordination level among provinces and regions is further reduced. Finally, corresponding development countermeasures and suggestions are given to different provinces and regions based on the spatial and temporal evolution characteristics, influencing factors and development trend of the “production-living-ecological” function in the Yellow River basin.

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Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Evolution and Prediction of the Coordination Level of “Production-Living-Ecological” Function Coupling in the Yellow River Basin, China

Zhang

Wang

et al. 2022

IJERPH

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“…This theory, built on the mathematical concept of entropy, represents the quantitative measure of the information content associated with a signal. It has been widely used in different sectors of hydraulics and hydrology to derive models of rainfall-runoff, infiltration, and soil moisture [22][23][24][25][26][27] as well as distribution of velocity, sediment concentration, and shear stress in open-channel flows [28][29][30][31][32][33][34][35][36][37][38][39]. Among the different applications, information theory has also been employed for the optimization, design, and management of several gauge stations including networks of water quality and groundwater [40,41], rainfall [42,43], streamflow, and water level [44][45][46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

Mirauda

Ostoich

2020

Sustainability

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Surface water quality has a vital role when defining the sustainability of the ecological environment, public health, and the social and economic development of whole countries. Unfortunately, the rapid growth of the worldwide population together with the current climate change have mostly determined fluvial pollution. Therefore, the employment of effective methodologies, able to rapidly and easily obtain reliable information on the quality of rivers, is becoming fundamental for an efficient use of the resource and for the implementation of mitigation measures and actions. The Water Quality Index (WQI) is among the most widely used methods to provide a clear and complete picture of the contamination status of a river stressed by point and diffuse sources of natural and anthropic origin, leading the policy makers and end-users towards a more and more correct and sustainable management of the water resource. The parameter choice is one of the most important and complex phases and recent statistical techniques do not seem to show great objectivity and accuracy in the identification of the real water quality status. The present paper offers a new approach, based on entropy theory and known as the Maximum Information Minimum Redundancy (MIMR) criterion, to define the optimal subset of chemical, physical, and biological parameters, describing the variation of the river quality level in space and time and thus identifying its pollution sources. An algorithm was implemented for the MIMR criterion and applied to a sample basin of Northeast Italy in order to verify its reliability and accuracy. A comparison with the Principal Component Analysis (PCA) showed how the MIMR is more suitable and objective to obtain the optimal quality parameters set, especially when the amount of investigated variables is small, and can thus be a useful tool for fast and low-cost water quality assessment in rivers.

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“…The concept of entropy has been analytically used by various existing methods as a robust theory for estimating the shear stress. However, the entropic approach has been given considerable attention mainly for its ability to evaluate the velocities in open channels [21][22][23][24][25][26][27][28][29][30][31][32], whereas very few studies have been carried out on its application in predicting the shear stress distribution [33][34][35][36][37][38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

Modeling Bed Shear Stress Distribution in Rectangular Channels Using the Entropic Parameter

Mirauda

Russo

2020

Entropy

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The evaluation of bed shear stress distribution is fundamental to predicting the transport of sediments and pollutants in rivers and to designing successful stable open channels. Such distribution cannot be determined easily as it depends on the velocity field, the shape of the cross section, and the bed roughness conditions. In recent years, information theory has been proven to be reliable for estimating shear stress along the wetted perimeter of open channels. The entropy models require the knowledge of the shear stress maximum and mean values to calculate the Lagrange multipliers, which are necessary to the resolution of the shear stress probability distribution function. This paper proposes a new formulation which stems from the maximization of the Tsallis entropy and simplifies the calculation of the Lagrange coefficients in order to estimate the bed shear stress distribution in open-channel flows. This formulation introduces a relationship between the dimensionless mean shear stress and the entropic parameter which is based on the ratio between the observed mean and maximum velocity of an open-channel cross section. The validity of the derived expression was tested on a large set of literature laboratory measurements in rectangular cross sections having different bed and sidewall roughness conditions as well as various water discharges and flow depths. A detailed error analysis showed good agreement with the experimental data, which allowed linking the small-scale dynamic processes to the large-scale kinematic ones.

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An Expression for Velocity Lag in Sediment-Laden Open-Channel Flows Based on Tsallis Entropy Together with the Principle of Maximum Entropy

Cited by 6 publications

References 39 publications

Spatial and Temporal Evolution and Prediction of the Coordination Level of “Production-Living-Ecological” Function Coupling in the Yellow River Basin, China

Spatial and Temporal Evolution and Prediction of the Coordination Level of “Production-Living-Ecological” Function Coupling in the Yellow River Basin, China

MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

Modeling Bed Shear Stress Distribution in Rectangular Channels Using the Entropic Parameter

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