Identification of Active Gully Erosion Sites in the Loess Plateau of China Using MF-DFA

Abstract

Gullies of different scales and types have developed in the Loess Plateau, China. Differences in the amount of gully erosion influence the development, evolution, morphology, and spatial distribution of these gullies. The strengths of headward erosion on the gully shoulder line are used to dictate soil and water conservation measures. In this study, six typical loess landforms in the Loess Plateau were selected as sampling sites: Shenmu, Suide, Ganquan, Yanchuan, Yijun, and Chunhua, which respectively represent loess-aeolian and dune transition zones, loess hills, loess ridge hills, loess ridges, loess long-ridge fragmented tablelands, and loess tablelands. Using 5 m resolution digital elevation model data from the National Basic Geographic Information Database, a small representative watershed was selected from each sampling site to obtain elevation data on the terrain profiles of gully shoulder lines. Multifractal detrended fluctuation analysis (MF-DFA) was used to conduct statistical and comparative analysis of the elevation fluctuation characteristics of these profiles. The results show that MF-DFA is capable of detecting active gully erosion sites. Sites of active gully erosion are concentrated in Shenmu and Suide but more widely distributed in the other five sites. The results provide a scientific basis for small watershed management planning and the design of soil and water conservation measures.

Application of fractal and multifractal analysis on Blue Nile drainage patterns in the morphostructural analysis of the Ethiopian highlands, Ethiopia

“…The higher the values of the fractal dimensions and multifractal spectra, the more complex the dataset structure is. This means that different fractal/ multifractal drainage pattern values in each SSA correspond to different shapes and densities of the drainage patterns in the study area (see Cao et al, 2020).…”

“…Costabile et al (2019) described a total of eight multifractal studies published between 1994 and 2000. They used multifractal calculations to analyze river networks, but in addition to shapes, they were also interested in catchment areas, slopes, topography, network optimization, dissipation energy, channel initiation function, and the width function. The advantages of multifractal analysis are also outlined in other previous studies (Cao et al, 2020;Gires et al, 2017;Landais et al, 2015;Li et al, 2018;Tarquis et al, 2017). Fractal and multifractal methods have been successfully applied (1) to study the spatial distribution of drainage patterns with different sizes; (2) to describe drainage patterns of different shapes; and (3) to study processes inside the drainage pattern and their areal distribution (Ariza-Villaverde et al, 2013;Bai et al, 2019;Khanbabaei et al, 2013).…”

“…Several researchers have used both fractal and multifractal analysis to create meaningful studies focusing on landscape analysis, hydrological parameters, and drainage pattern analysis, etc. (see in Cao et al, 2020;Dutta, 2017;Kusák, 2014;Lopes et al, 2011). Fractal analysis was first used by Hurst in 1951, but it only included monofractal analysis.…”

“…Dutta (2017) provided a way to automatically distinguish glacial and fluvial morphologies using the multifractal technique. The study shows that glacial landforms reveal more complex structures compared to fluvial landforms, as indicated by fractal variables such as the degree of multifractality (see in Cao et al, 2020). Our work focuses on determining the differences between morphologies of tectonic and non-tectonic drainage patterns.…”

Long‐range correlations of soil water content time series under tillage and different cover crops in a semi‐arid vineyard

“…Castellanos, Morató, Aguado, Monte, and Tarquis (2018) analysed landscapes through MFDFA of altitude of data points along transects from different directions. Cao et al (2020) also made use of elevation data of terrain profiles of gully shoulder lines to detect active gully erosion sites. It is worth noting here that, as far as we know, this non‐exhaustive list of MFDFA applications, seems to indicate the limited use of this advanced technique of data analysis in soil science to date.…”