scholarly journals Multifractal Characteristics Analysis Based on Slope Distribution Probability in the Yellow River Basin, China

2021 ◽  
Vol 10 (5) ◽  
pp. 337
Author(s):  
Zilong Qin ◽  
Jinxin Wang ◽  
Yan Lu
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Yellow River ◽  
Multifractal Spectrum ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Distribution Probability ◽  
Multifractal Theory ◽  
The Yellow River Basin ◽  
Geomorphological Features

Multifractal theory provides a reliable method for the scientific quantification of the geomorphological features of basins. However, most of the existing research has investigated small and medium-sized basins rather than complex and large basins. In this study, the Yellow River Basin and its sub-basins were selected as the research areas, and the generalized fractal dimension and multifractal spectrum were computed and analyzed with a multifractal technique based on the slope distribution probability. The results showed that the Yellow River Basin and its sub-basins exhibit clear multifractal characteristics, which indicates that the multifractal theory can be applied well to the analysis of large-scale basin geomorphological features. We also concluded that the region with the most uneven terrain is the Yellow River Downstream Basin with the “overhanging river”, followed by the Weihe River Basin, the Yellow River Mainstream Basin, and the Fenhe River Basin. Multifractal analysis can reflect the geomorphological feature information of the basins comprehensively with the generalized fractal dimension and the multifractal spectrum. There is a strong correlation between some common topographic parameters and multifractal parameters, and the correlation coefficients between them are greater than 0.8. The results provide a scientific basis for analyzing the geomorphic characteristics of large-scale basins and for the further research of the morphogenesis of the forms.

scholarly journals CCAM: China Catchment Attributes and Meteorology dataset

2021 ◽  
Vol 13 (12) ◽  
pp. 5591-5616
Author(s):  
Zhen Hao ◽  
Jin Jin ◽  
Runliang Xia ◽  
Shimin Tian ◽  
Wushuang Yang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
River Basin ◽  
Large Scale ◽  
Yellow River ◽  
Potential Evapotranspiration ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Catchment Characteristics ◽  
The Yellow River Basin

Abstract. The absence of a compiled large-scale catchment characteristics dataset is a key obstacle limiting the development of large-sample hydrology research in China. We introduce the first large-scale catchment attribute dataset in China. We compiled diverse data sources, including soil, land cover, climate, topography, and geology, to develop the dataset. The dataset also includes catchment-scale 31-year meteorological time series from 1990 to 2020 for each basin. Potential evapotranspiration time series based on Penman's equation are derived for each basin. The 4911 catchments included in the dataset cover all of China. We introduced several new indicators that describe the catchment geography and the underlying surface differently from previously proposed datasets. The resulting dataset has a total of 125 catchment attributes and includes a separate HydroMLYR (hydrology dataset for machine learning in the Yellow River Basin) dataset containing standardized weekly averaged streamflow for 102 basins in the Yellow River Basin. The standardized streamflow data should be able to support machine learning hydrology research in the Yellow River Basin. The dataset is freely available at https://doi.org/10.5281/zenodo.5729444 (Zhen et al., 2021). In addition, the accompanying code used to generate the dataset is freely available at https://github.com/haozhen315/CCAM-China-Catchment-Attributes-and-Meteorology-dataset (last access: 26 November 2021) and supports the generation of catchment characteristics for any custom basin boundaries. Compiled data for the 4911 basins covering all of China and the open-source code should be able to support the study of any selected basins rather than being limited to only a few basins.

scholarly journals Nitrogen Fertilization Effects on Physiology of the Cotton Boll–Leaf System

Agronomy ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 271
Author(s):  
Jing Chen ◽  
Liantao Liu ◽  
Zhanbiao Wang ◽  
Hongchun Sun ◽  
Yongjiang Zhang ◽  
...  
Keyword(s):  
River Basin ◽  
Nitrogen Fertilization ◽  
Yellow River ◽  
Yellow River Basin ◽  
Growth And Yield ◽  
The Yellow River ◽  
Nitrogen Rate ◽  
The Yellow River Basin ◽  
Source Sink ◽  
Subtending Leaves

The objective of this study was to assess the impacts of nitrogen on the physiological characteristics of the source–sink system of upper fruiting branches under various amounts of nitrogen fertilization. A two-year field experiment was conducted with a Bt cotton cultivar in the Yellow River Basin of China. The growth and yield of cotton of the upper fruiting branches were compared under four nitrogen levels: Control (N0, 0 kg ha−1), low nitrogen (N1, 120 kg ha−1), moderate nitrogen (N2, 240 kg ha−1), and high nitrogen (N3, 480 kg ha−1). The results indicated that in the subtending leaves in upper fruiting branches, chlorophyll content, protein content, and peroxidase (POD) activity dramatically increased with nitrogen application, reaching the highest under the moderate nitrogen treatment. The physiological characters in the seeds had the same trends as in the subtending leaves. Furthermore, the moderate nitrogen rate (240 kg ha−1) had a favorable yield and quality. Our results supported that a moderate nitrogen rate (240 kg ha−1) could coordinate the source–sink growth of cotton in the late stage, enhance the yield and fiber quality, and decrease the cost of fertilizer in the Yellow River Basin of China and other similar ecological areas.

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