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 Catchment attributes and meteorology for large sample study in contiguous China

2021 ◽  
Author(s):  
Zhen Hao ◽  
Jin Jin ◽  
Runliang Xia ◽  
Shimin Tian ◽  
Wushuang Yang ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Yellow River ◽  
Potential Evapotranspiration ◽  
Sunshine Duration ◽  
Ground Surface ◽  
Yellow River Basin ◽  
Catchment Characteristics ◽  
The Difference ◽  
The Yellow River Basin

Abstract. We introduce the first large-scale catchment attributes and meteorological time series dataset of contiguous China. To develop the dataset, we compiled diverse data sources to generate basin-oriented features describing the characteristics of the catchment related to hydrological processes. The proposed dataset consists of catchment characteristics including soil, land cover, climate, topography, geology, and 29-year meteorological time series (from 1990 to 2018). The meteorological variables include precipitation, temperature, evapotranspiration, wind speed, ground surface temperature, pressure, humidity and sunshine duration. We also derived a daily potential evapotranspiration time series based on a modified Penman’s equation. The studied catchments are 4875 catchments within contiguous China derived from digital elevation models. The spatial variations of catchment characteristics are analysed and organized into a series of maps; the correlation analysis between attributes was conducted. Compared to the previously proposed datasets, we derived more catchment characteristics resulting in a total of 127 attributes, providing a complete description of the catchments. Besides, we propose Normal-Camels-YR, a hydrological dataset covering 102 basins of the Yellow River basin with normalized streamflow observations. The proposed dataset provides numerous opportunities for comparative hydrological research, such as examining the difference in hydrological behaviours across different catchments and building general rainfall-runoff modelling frameworks for many catchments instead of limited to a few. The dataset is freely available via http://doi.org/10.5281/zenodo.4704017 for community use. We will open-source the complement code for generating the dataset such that the user can generate meteorological series and catchment attributes for any watershedwithin contiguous China.

scholarly journals Water Conservation Estimation Based on Time Series NDVI in the Yellow River Basin

2021 ◽  
Vol 13 (6) ◽  
pp. 1105
Author(s):  
Yangchengsi Zhang ◽  
Jiaqiang Du ◽  
Long Guo ◽  
Zhilu Sheng ◽  
Jinhua Wu ◽  
...  
Keyword(s):  
Time Series ◽  
Water Conservation ◽  
Large Scale ◽  
Yellow River ◽  
Yellow River Basin ◽  
Support Vector ◽  
The Yellow River ◽  
Grassland Ecosystem ◽  
Line Planning ◽  
The Yellow River Basin

Accurate estimation of the water conservation is of great significance for ecological red line planning. The water conservation of the Yellow River Basin has a vital influence on the development of the environment and the supply of ecological services in China. However, the existing methods used to estimate water conservation have many disadvantages, such as requiring numerous parameters, a complex calculation model, and using data that is often difficult acquire. It is often hard to provide sufficiently precise parameters and data, resulting in a large amount of calculation time and the difficulties in the study of large scale and long time series. In this study, a time series of the Normalized Difference Vegetation Index (NDVI) was applied to estimate water conservation in two aspects using the idea of wholeness and stratification, respectively. The overall fitting results can explain nearly 30% of the water conservation by partial least squares regression and nearly 50% of it by a support vector machine. However, the results of a stratified simulation showed that water conservation and the NDVI have a certain stratified heterogeneity among different ecosystem types. The optimal fitting result was achieved in a water/wetland ecosystem with the highest coefficient of determination (R2P) of 0.768 by the stratified support vector machine (SVM) model, followed by the forest and grassland ecosystem (both R2P of 0.698). The spatial mapping results showed that this method was most suitable for grassland ecosystem, followed by forest ecosystem. According to the results generated using the NDVI time series data, it is feasible to complete a spatial simulation of water conservation. This research can provide a reference for calculating regional or large-scale water conservation and in ecological red line planning.

scholarly journals The Trend and Influencing Factors of Potential Evapotranspiration in the Yellow River

2018 ◽  
Vol 246 ◽  
pp. 01020
Author(s):  
Yanyu Dai ◽  
Fan Lu ◽  
Kui Zhu ◽  
Xinyi Song ◽  
Yiran Xu
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Potential Evapotranspiration ◽  
Great Influence ◽  
Yellow River Basin ◽  
Test Method ◽  
Trend Test ◽  
The Yellow River ◽  
Significant Downward Trend ◽  
The Yellow River Basin

Based on the Penman-Monteith formula recommended by the World Food and Agriculture Organization (FAO) and the Mann-Kendall trend test method, the variation trend of potential evapotranspiration in the Yellow River Basin from 1952 to 2014 is analyzed. The results showed that the potential evapotranspiration of 43.3% of the 90 meteorological stations in the Yellow River Basin showed a significant upward trend. 30% of the stations showed a significant downward trend, and 26.7% of the stations had no obvious trend of change. In all the secondary areas of water resources, the stations above Longyangxia are basically marked upward. The Longyangxia to the northern part of Lanzhou, the Longmen to the east of Sanmenxia and the Sanmenxia to Huayuankou are all significant descending sites. The change trend of the sites below the Huayuankou is not obvious. In other partition three kinds of sites are distributed. Through the correlation analysis, it is found that the increase of temperature has a great influence on the stations where the potential evapotranspiration is significantly increased, and the decrease of wind speed is the main reason for the significant decrease of potential evapotranspiration in some stations.

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.

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