Abstract
Multifractal theory provides an effective method for the scientific quantification of the river network features. This method has been applied to estimate river network structure in previous research, but there are few temporal and spatial analysis studied for large river basins based on multifractals. In this study, the Yellow River Basin and its nine provinces were selected as the study area, and the generalized fractal dimension and multifractal spectrum of the study area during the period 2000–2020 were calculated and analyzed. We analyzed the response relationship between the river network changes and the urbanization process. Results indicated that the river network of the study area exhibited obvious multifractal properties, which were mainly affected by dense river networks. The complexity of the studied river network has shown a tendency to decrease over time. The rate of change in the river network structure has a high positive correlation with urbanization, that is, the higher the rate of urbanization, the greater the impact on the river network structure. Additionally, the changes of the river network structure are more affected by urbanization during the rapid urbanization stage. We applied multifractal analysis to study the river network structure changes, which is of great significance for scientifically quantifying fluvial characteristics and studying the development and evolution of river networks.
Highlights
Before conducting a multifractal analysis, it is necessary to assess whether the studied river network has multifractal properties
The logarithmic curve of the partition function M (e, q) and the box size e in the Yellow River Basin were calculated for the 2000s, 2010s, and the 2020s
We analyzed the multifractal characteristics of nine provinces in the Yellow River Basin and discussed the urbanization driving changes in the river network structure
Summary
The structure of a river network is one of the most basic components of basin geomorphology, and it is affected by many factors. Accurate and quantitative expression of river network structures is very important for studying river network sedimentation processes [1], extreme hydrological events in river basins [2], and river network development [3]. Some traditional statistical methods can reveal some characteristics of river network structure, such as river density [4,5], branch ratio [6], and total length, owing to the high complexity of a river network structure, these methods usually cannot well describe certain key features of river networks [7]. The fractal theory provides an effective means of quantitatively describing the characteristics of river networks
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