scholarly journals Exploring the Clustering Property and Network Structure of a Large-Scale Basin’s Precipitation Network: A Complex Network Approach

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1739
Author(s):  
Yiran Xu ◽  
Fan Lu ◽  
Kui Zhu ◽  
Xinyi Song ◽  
Yanyu Dai
Keyword(s):  
Network Theory ◽  
Large Scale ◽  
Yellow River ◽  
Environmental Gradients ◽  
Small World ◽  
Yellow River Basin ◽  
Vertex Degree ◽  
Clustering Coefficient ◽  
Recent Developments ◽  
Precipitation Network

Understanding of the spatial connections in rainfall is a challenging and essential groundwork for reliable modeling of catchment processes. Recent developments in network theory offer new avenues to understand of the spatial variability of rainfall. The Yellow River Basin (YRB) in China is spatially extensive, with pronounced environmental gradients driven primarily by precipitation and air temperature on broad scales. Therefore, it is an ideal region to examine the availability of network theory. The concepts of clustering coefficient, degree distribution and small-world network are employed to investigate the spatial connections and architecture of precipitation networks in the YRB. The results show that (1) the choice of methods has little effect on the precipitation networks, but correlation thresholds significantly affected vertex degree and clustering coefficient values of precipitation networks; (2) the spatial distribution of the clustering coefficient appears to be high–low–high from southeast to northwest and the vertex degree is the opposite; (3) the precipitation network has small-world properties in the appropriate threshold range. The findings of this paper could help researchers to understand the spatial rainfall connections of the YRB and, therefore, become a foundation for developing a hydrological model in further studies.

scholarly journals Evaluation of Environmental and Ecological Impacts of the Leading Large-Scale Reservoir on the Upper Reaches of the Yellow River

2019 ◽  
Vol 11 (14) ◽  
pp. 3818
Author(s):  
Jun Qiu ◽  
Tie-Jian Li ◽  
Fang-Fang Li
Keyword(s):  
Flood Control ◽  
Large Scale ◽  
Yellow River ◽  
Yellow River Basin ◽  
Water Area ◽  
Economic Benefits ◽  
Control Area ◽  
Ecological Impacts ◽  
The Yellow River ◽  
Water Demands

Large-scale reservoirs have played a significant role in meeting various water demands and socio-economic development, while they also lead to undeniable impacts on the environment and ecology. The Longyangxia reservoir located on the Yellow River is the first large-scale reservoir on the upper Yellow River with a control area of 18% of the entire Yellow River Basin. Since it was put into operation in 1987, it has made great contributions to the national economy for over 30 years. In this study, the socio-economic benefits of the Longyangxia reservoir in power generation, water supply, flood control, and ice prevention are investigated. More importantly, its impacts on the ecology and environment are also presented and analyzed, such as the impacts on river morphology, flow regimes, peak flow, fish, phytoplankton, and zooplankton. It can be concluded that the construction of the Longyangxia reservoir contributes greatly to socio-economic benefits, the water area nearby has formed a new ecological environment, and the trophic level of the aquatic environment has probably increased.

Research on the Structure of Peer-to-Peer Overlay Based on the Complex Network Theory

2012 ◽  
Vol 263-266 ◽  
pp. 1096-1099
Author(s):  
Zhi Yong Jiang
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Degree Distribution ◽  
Path Length ◽  
Small World ◽  
Peer To Peer ◽  
Clustering Coefficient ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
The Mean

Relationship between nodes in peer-to-peer overlay, currently becomes a hot topic in the field of complex network. In this paper a model of peer-to-peer overlay was purposed. And then the paper focused on figuring out the mean-shortest path length (MSPL), clustering coefficient (CC) and the degree of every node which allowed us to discover the degree distribution. The results show that the degree distribution function follows approximately power law distribution and the network possesses notable clustering and small-world properties.

scholarly journals Complex network theory, streamflow, and hydrometric monitoring system design

2015 ◽  
Vol 19 (7) ◽  
pp. 3301-3318 ◽  
Author(s):  
M. J. Halverson ◽  
S. W. Fleming
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Small World ◽  
Detection Algorithm ◽  
Clustering Coefficient ◽  
Network Stability ◽  
Meteorological Forcing ◽  
Complex Network Theory ◽  
Scale Free ◽  
Seasonal Flow

Abstract. Network theory is applied to an array of streamflow gauges located in the Coast Mountains of British Columbia (BC) and Yukon, Canada. The goal of the analysis is to assess whether insights from this branch of mathematical graph theory can be meaningfully applied to hydrometric data, and, more specifically, whether it may help guide decisions concerning stream gauge placement so that the full complexity of the regional hydrology is efficiently captured. The streamflow data, when represented as a complex network, have a global clustering coefficient and average shortest path length consistent with small-world networks, which are a class of stable and efficient networks common in nature, but the observed degree distribution did not clearly indicate a scale-free network. Stability helps ensure that the network is robust to the loss of nodes; in the context of a streamflow network, stability is interpreted as insensitivity to station removal at random. Community structure is also evident in the streamflow network. A network theoretic community detection algorithm identified separate communities, each of which appears to be defined by the combination of its median seasonal flow regime (pluvial, nival, hybrid, or glacial, which in this region in turn mainly reflects basin elevation) and geographic proximity to other communities (reflecting shared or different daily meteorological forcing). Furthermore, betweenness analyses suggest a handful of key stations which serve as bridges between communities and might be highly valued. We propose that an idealized sampling network should sample high-betweenness stations, small-membership communities which are by definition rare or undersampled relative to other communities, and index stations having large numbers of intracommunity links, while retaining some degree of redundancy to maintain network robustness.

scholarly journals Drought Evaluation with CMORPH Satellite Precipitation Data in the Yellow River Basin by Using Gridded Standardized Precipitation Evapotranspiration Index

2019 ◽  
Vol 11 (5) ◽  
pp. 485 ◽  
Author(s):  
Fei Wang ◽  
Haibo Yang ◽  
Zongmin Wang ◽  
Zezhong Zhang ◽  
Zhenhong Li
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Large Scale ◽  
Drought Index ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Precipitation Data ◽  
Standardized Precipitation Evapotranspiration Index ◽  
The Yellow River Basin

The traditional station-based drought index is vulnerable because of the inadequate spatial distribution of the station, and also, it does not fully reflect large-scale, dynamic drought information. Thus, large-scale drought monitoring has been widely implemented by using remote sensing precipitation products. Compared with station data, remote sensing precipitation products have the advantages of wide coverage and dynamic, continuous data, which can effectively compensate for the deficiency in the spatial distribution of the ground stations and provide a new data source for the calculation of a drought index. In this study, the Gridded Standardized Precipitation Evapotranspiration Index (GSPEI) was proposed based on a remote sensing dataset produced by the Climate Prediction Center morphing technique (CMORPH), in order to evaluate the gridded drought characteristics in the Yellow River basin (YRB) from 1998 to 2016. The optimal Ordinary Kriging interpolation method was selected to interpolate meteorological station data to the same spatial resolution as CMORPH data (8 km), in order to compare the ground-based meteorological parameters to remote sensing-based data. Additionally, the gridded drought trends were identified based on the Modified Mann–Kendall (MMK) trend test method. The results indicated that: (1) the GSPEI was suitable for drought evaluation in the YRB using CMORPH precipitation data, which were consistent with ground-based meteorological data; (2) the positive correlation between GSPEI and SPEI was high, and all the correlation coefficients (CCs) passed the significance test of α = 0.05, which indicated that the GSPEI could better reflect the gridded drought characteristics of the YRB; (3) the drought severity in each season of the YRB was highest in summer, followed by spring, autumn, and winter, with an average GSPEI of −1.51, −0.09, 0.30, and 1.33, respectively; and (4) the drought showed an increasing trend on the monthly scale in March, May, August, and October, and a decreasing trend on the seasonal and annual scale.

Measurement and Analysis Topological Characteristics of Video-Sharing Network

2014 ◽  
Vol 575 ◽  
pp. 863-868
Author(s):  
Wen Li Ji ◽  
Xi Xi Cao
Keyword(s):  
Social Networking ◽  
Social Networking Sites ◽  
Large Scale ◽  
Small World ◽  
Clustering Coefficient ◽  
Online Social Networking ◽  
Social Characteristic ◽  
Video Sharing ◽  
The Social ◽  
Measurement And Analysis

Recently the fast-growing business of the Internet are Online Social networking services, Online Social networking sites also become the most popular sites. In order to establish future social network which is optimized, and to eventually exploit the user base for commercial purposes, in-depth understanding the social characteristic of these networks is important. In this paper, we present a large-scale measurement study and analysis on the social structure of YouKu. Our results validate the power-law, small-world and clustering coefficient properties, present the correlation and difference among four centrality properties. Finally we discuss the utilization of these structural properties for the commercial purposes.

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 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 Towards Understanding the Social Characteristic of YouKu: Measurement and Analysis

2012 ◽  
Vol 6-7 ◽  
pp. 1112-1117
Author(s):  
Yong Jun Li ◽  
Chun You ◽  
Xu Dong Bao
Keyword(s):  
Social Networking ◽  
Large Scale ◽  
Small World ◽  
Clustering Coefficient ◽  
The Internet ◽  
Social Characteristic ◽  
Social Networking Services ◽  
The Social ◽  
Measurement And Analysis ◽  
Current Systems

Online Social networking services are among the most popular sites and become the fast-growing business in the Internet. In-depth understanding the social characteristic of these networks can serve to optimize current systems, to design future social network based systems, and to eventually exploit the user base for commercial purposes. In this paper, we present a large-scale measurement study and analysis on the social structure of YouKu. Our results validate the power-law, small-world and clustering coefficient properties, present the correlation and difference among four centrality properties. Finally we discuss the utilization of these structural properties for the commercial purposes.

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