Application of Fractal Theory in the River Regime in the Lower Yellow River

Tian, Shi Min; Su, Xiao Hui; Wang, Wei Hong; Lai, Rui Xun

doi:10.4028/www.scientific.net/amm.190-191.1238

Cited by 9 publications

(3 citation statements)

References 18 publications

(20 reference statements)

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“…Based on the previous literature, we found that the capacity dimensions of river networks ranged from 1.83 to 1.93 in mountainous areas [4,5,53,54], while in low mountainous areas the capacity dimensions of river networks ranged from 1.49 to 1.81 [19,20,54]. Besides this, the capacity dimensions of river networks in the Lower Yellow River were found to range from 1.10 to 1.18 [55], and then weakened dramatically to 1.05-1.35, due to the influence of the Xiaolangdi Reservoir [56].…”

Section: Multifractal Analysis Of River Network From Other Areasmentioning

confidence: 90%

Multifractal Analysis of River Networks in an Urban Catchment on the Taihu Plain, China

Xiang

Yuan

et al. 2019

Water

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Multifractal analysis was successfully used to investigate the structure of river networks. In this paper, we performed a multifractal analysis of river networks in an urban catchment that is located on the Taihu Plain in the lower part of the Yangtze River Delta, China. Spatial and temporal variations in the river networks during the period 1960–2010 were investigated. The generalized multifractal dimensions (Dq) and the multifractal spectrum (f(α)) were calculated using a box-counting method. The results indicate that: (i) the river networks in Wuchengxiyu (WXCY), Yangchengdianmao (YCDM), and Hangjiahu (HJH) had obvious multifractal features with capacity dimensions between 1.90 and 1.91 during the period 1960–2010. The multifractal spectrums are asymmetrical inverted-hook-shaped curves with a dominant left arm. The variation in the singularity component (∆α) changed the most in WCXY (an increase of ~ 7.9%), and the height variation in the multifractal spectrum (∆f) increased by ~ 17.5% in HJH; (ii) the changes in ∆α and ∆f of the tributaries in the three areas during the period 1960–2010 were consistent with those of the overall river network, demonstrating the decisive role that the tributaries play in the complexity of the river networks; (iii) compared to the natural factors, the influences of urbanization on the river networks significantly changed with a higher urbanization level; and (iv) there were no border effects. Further applications of multifractal theory in analyses of the relationship between a flood-forming regime and the multifractal structures of river networks will attract more attention. Generally, this approach, when successfully applied to studies of changes in river networks, is of theoretical significance for better describing and quantifying the evolution of river networks’ structures.

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Section: Multifractal Analysis Of River Network From Other Areasmentioning

confidence: 90%

Multifractal Analysis of River Networks in an Urban Catchment on the Taihu Plain, China

Xiang

Yuan

et al. 2019

Water

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“…Yu et al (2011) took Bengbu to Fushan reach as an example, and analysed the incoming water and sediment, bed-building discharge, and riverbed stability coefficient. For other rivers, Tian et al (2012) used the fractal theory to analyse the evolution of the lower Yellow River. Batalla et al (2018) studied the morphology of theÑuble River channel changing over the years based on aviation images, and quantitatively analysed the channel morphology index.…”

Section: Introductionmentioning

confidence: 99%

The middle Huaihe River stability analysis and optimization of hydrological chaos forecasting model

Duan

Wang

et al. 2020

Geomatics, Natural Hazards and Risk

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Based on the monthly flow time series data of main hydrological stations in the middle Huaihe River from 1985 to 2015, the river stability of Zhengyangguan-Bengbu and Bengbu-Fushan reaches is scientifically judged by nonequilibrium thermodynamics. The results show that the river pattern is in a stable state, and there is no transformation possible in a short time; the evolution of riverbed tends to be stable, and the influence of riverbed boundary conditions is greater than that of incoming water and sediment conditions. Based on fully understanding the stability of the middle Huaihe River, to improve the intelligence of hydrological forecasting, the chaotic characteristics of monthly flow time series are identified, then the artificial neural network forecasting model is optimized by chaos theory and optimization algorithms. Our findings suggest that the nonequilibrium thermodynamic analysis methods of river stability can provide a new idea for the study of river characteristics, and the forecasting model combined with chaos theory and optimization methods provide an effective technical means to improve the hydrological forecasting accuracy of the middle Huaihe River.

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“…Because of flood season randomness, certainty, and fuzziness, the flood season division method is varied according to its characteristics. The current flood season staging methods mainly include the change point analysis method [14], fuzzy set analysis method [15], system clustering method [16], and Fisher most segmentation method [17]. These methods have shortcomings, such as single selection index or cumbersome calculation.…”

Section: Introductionmentioning

confidence: 99%

Considering Abrupt Change in Rainfall for Flood Season Division: A Case Study of the Zhangjia Zhuang Reservoir, Based on a New Model

Zhang

2018

Water

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The traditional flood season division method is cumbersome. In order to make the flood season division elaborate, the Mann–Kendall and cumulative sum of rank difference (CSD) methods were used to detect the abrupt change year of precipitation (p) over the study area from 1969 to 2015. The year of change was determined to be 1995. Taking the 1995 year as a demarcation point of the data, the discriminant model and Fisher optimal partition method were applied for flood division, and a comparison of the results from the two approaches were compared. The discriminant model was found to perform slightly better than the Fisher approach. It was found that abrupt rainfall change has a certain influence on flood season division. The main flood season in the Zhangjia Zhuang reservoir during 1969–2015 was 16 days longer than during 1996–2015, but three days shorter than between 1969–1995. For the Zhangjia Zhuang Reservoir, the flood water level limit can increase up to 2 m according to the results of the flood season division and designed rainfall after abrupt change; in addition, the water storage capacity is 469 million m³ more than that of the traditional reservoir operation mode.

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Application of Fractal Theory in the River Regime in the Lower Yellow River

Cited by 9 publications

References 18 publications

Multifractal Analysis of River Networks in an Urban Catchment on the Taihu Plain, China

Multifractal Analysis of River Networks in an Urban Catchment on the Taihu Plain, China

The middle Huaihe River stability analysis and optimization of hydrological chaos forecasting model

Considering Abrupt Change in Rainfall for Flood Season Division: A Case Study of the Zhangjia Zhuang Reservoir, Based on a New Model

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