Analysis of Spatiotemporal Distribution of Precipitation Changes in the Source Region of the Yangtze River

2020 ◽  
Vol 09 (03) ◽  
pp. 335-343
Author(s):  
佑承 蒋
Keyword(s):  
Yangtze River ◽  
Source Region ◽  
Spatiotemporal Distribution ◽  
The Yangtze River ◽  
Precipitation Changes

scholarly journals Spatiotemporal Distribution Characteristics and Driving Forces of PM2.5 in Three Urban Agglomerations of the Yangtze River Economic Belt

2021 ◽  
Vol 18 (5) ◽  
pp. 2222
Author(s):  
Jin-Wei Yan ◽  
Fei Tao ◽  
Shuai-Qian Zhang ◽  
Shuang Lin ◽  
Tong Zhou
Keyword(s):  
Geographically Weighted Regression ◽  
Yangtze River ◽  
National Level ◽  
National Development ◽  
Urban Agglomeration ◽  
Spatiotemporal Distribution ◽  
Weighted Regression ◽  
Series Data ◽  
The Yangtze River ◽  
Urban Agglomerations

As part of one of the five major national development strategies, the Yangtze River Economic Belt (YREB), including the three national-level urban agglomerations (the Cheng-Yu urban agglomeration (CY-UA), the Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and the Yangtze River Delta urban agglomeration (YRD-UA)), plays an important role in China’s urban development and economic construction. However, the rapid economic growth of the past decades has caused frequent regional air pollution incidents, as indicated by high levels of fine particulate matter (PM2.5). Therefore, a driving force factor analysis based on the PM2.5 of the whole area would provide more information. This paper focuses on the three urban agglomerations in the YREB and uses exploratory data analysis and geostatistics methods to describe the spatiotemporal distribution patterns of air quality based on long-term PM2.5 series data from 2015 to 2018. First, the main driving factor of the spatial stratified heterogeneity of PM2.5 was determined through the Geodetector model, and then the influence mechanism of the factors with strong explanatory power was extrapolated using the Multiscale Geographically Weighted Regression (MGWR) models. The results showed that the number of enterprises, social public vehicles, total precipitation, wind speed, and green coverage in the built-up area had the most significant impacts on the distribution of PM2.5. The regression by MGWR was found to be more efficient than that by traditional Geographically Weighted Regression (GWR), further showing that the main factors varied significantly among the three urban agglomerations in affecting the special and temporal features.

scholarly journals Temperature Change and Its Elevation Dependency in the Source Region of the Yangtze River and Yellow River

2014 ◽  
Vol 6 (2) ◽  
pp. 124 ◽  
Author(s):  
Chongyi E ◽  
Hongchang Hu ◽  
Hong Xie ◽  
Yongjuan Sun
Keyword(s):  
Temperature Change ◽  
Minimum Temperature ◽  
Yangtze River ◽  
Yellow River ◽  
Source Region ◽  
Maximum Temperature ◽  
Climatic Data ◽  
The Yangtze River ◽  
Extreme Minimum Temperature ◽  
The Mean

The study of temperature change and its elevation dependency in the source region of the Yangtze River and Yellow River have been insufficient owing to the lack of adequate observation stations and long-term climatic data. In this study five temperature indices of 32 stations from 1961 to 2007 in and near the source region are used. The 32 stations all have experienced significant warming; the warming amplitudes are higher than the mean warming amplitude of the Qinghai-Tibetan plateau. The warming amplitudes and the numbers of stations showing significant warming trends in mean minimum temperature and extreme minimum temperature are higher than that of the mean maximum temperature and extreme maximum temperature. The elevation dependency of climatic warming and the amount of significant warming stations are not obvious; the influence of human activity and urbanization may be higher. The warming amplitudes of 26 stations above 3000 m tend to be uniform, and there is no significant law at 6 stations below 3000 m. On the contrary, the ratio of stations showing significant warming in minimum temperature above 4000 m is far less than that of the stations below 4000 m.

scholarly journals Impact of the Westerly Jet on Rainfall/Runoff in the Source Region of the Yangtze River during the Flood Season

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xin Lai ◽  
Yuanfa Gong ◽  
Sixian Cen ◽  
Hui Tian ◽  
Heng Zhang
Keyword(s):  
Water Vapor ◽  
Coastal Zone ◽  
Yangtze River ◽  
Source Region ◽  
Observation Data ◽  
The Yangtze River ◽  
Antecedent Rainfall ◽  
Flood Season ◽  
Westerly Jet ◽  
The Impact

Based on runoff data collected at the Zhimenda station, reanalysis data from the National Centers of Environmental Prediction/National Centers of Atmospheric Research (NCEP/NCAR), and observation data from ground stations in China, this study analyzes the characteristics of changes in runoff in the source region of the Yangtze River (SRYR) during the flood season (from July to September), the relationship between runoff and antecedent rainfall, and the impact of the westerly jet (WJ) on rainfall in the coastal zone of the SRYR. The results show the following. The runoff in the SRYR displays a significant interannual and interdecadal variability. The runoff in the SRYR during the flood season is most closely related to 15-day (June 16 to September 15) antecedent rainfall in the coastal zone of the SRYR. In turn, the antecedent rainfall in the coastal zone of the SRYR is mainly affected by the intensity of the simultaneous WJ over a key region (55–85°E, 45–55°N). When the intensity of the WJ over the key region is greater (less) than normal, the jet position moves northward (southward), and the easterly (westerly) wind anomalies over the region to the west of the SRYR become unfavorable (favorable) to the transport of water vapor from high-latitude regions to the SRYR. In addition, the southerly wind over the equatorial region cannot (can) easily advance northward, which is unfavorable (favorable) to the northward transport of water vapor from the low-latitude ocean. Hence, these conditions result in a decrease (increase) in the water vapor content in the SRYR. Furthermore, the convergence (divergence) anomalies in the upper level and the divergence (convergence) anomalies in the lower level result in the descending (ascending) motion over the SRYR. These factors decrease (increase) the rainfall, thereby decreasing (increasing) the runoff in the SRYR during the flood season.

scholarly journals Contribution of glacial melt to river runoff as determined by stable isotopes at the source region of the Yangtze River, China

2015 ◽  
Vol 47 (2) ◽  
pp. 442-453 ◽  
Author(s):  
Zhaofei Liu ◽  
Zhijun Yao ◽  
Rui Wang
Keyword(s):  
Yangtze River ◽  
Meteoric Water ◽  
Stream Water ◽  
Source Region ◽  
Upstream Region ◽  
The Yangtze River ◽  
Hydrograph Separation ◽  
Water Line ◽  
Total Runoff ◽  
Meteoric Water Line

The primary objective of this study was to quantify the contribution of glacial melt to total runoff in the Gaerqu River catchment, which is located in the source region of the Yangtze River, China. The isotope hydrograph separation method was used to separate glacier melt runoff from total runoff in the catchment. The degree-day method was used to investigate temporal variations in glacial melt runoff. The results showed that the contribution of glacial melt runoff to total runoff was 15.0%. The uncertainty of the separation was ± 3.7% at the confidence level of 95%. Glacial melt runoff was mainly generated in June, July, and August. The runoff coefficient was 0.23 for the catchment. Precipitation-induced runoff constituted 19.9% of the total precipitation, meaning that precipitation loss was >80% across the study period (a hydrological year). The Local Meteoric Water Line (LMWL) of the catchment was fitted as δ2H = 7.75 δ18O + 5.93. This line has a smaller slope and intercept than the Global Meteoric Water Line. The regression-lines for the δ18O and δ2H values of stream water indicated that evaporation was greater over the entire catchment than it was for the upstream region alone.

Runoff dominated by supra-permafrost water in the source region of the Yangtze river using environmental isotopes

2020 ◽  
Vol 582 ◽  
pp. 124506 ◽  
Author(s):  
Zongxing Li ◽  
Zongjie Li ◽  
Qi Feng ◽  
Baijuan Zhang ◽  
Juan Gui ◽  
...  
Keyword(s):  
Yangtze River ◽  
Source Region ◽  
Environmental Isotopes ◽  
The Yangtze River

Monitoring permafrost changes in the Yangtze River source region of the Qinghai-Tibetan Plateau using differential SAR interferometry

2020 ◽  
Author(s):  
Lingxiao Wang ◽  
Lin Zhao ◽  
Huayun Zhou ◽  
Shibo Liu ◽  
Xiaodong Huang ◽  
...  
Keyword(s):  
Active Layer ◽  
Yangtze River ◽  
Ground Deformation ◽  
Source Region ◽  
Deformation Monitoring ◽  
Tibet Plateau ◽  
Permafrost Degradation ◽  
The Yangtze River ◽  
Ground Ice

<p>Qinghai-Tibet Plateau (QTP) has the largest high-altitude permafrost zone in the middle and low latitudes. Substantial hydrologic changes have been observed in the Yangtze River source region and adjacent areas in the early 21st century. Permafrost on the QTP has undergone degradation under global warming. The ground leveling observation site near Tangula (33°04′N, 91°56′E) located in the degraded alpine meadow indicates that the ground has subsided 50mm since 2011. The contribution of permafrost degradation and loss of ground ice to the hydrologic changes is however still lacking. This study monitors the permafrost changes by applying the Small BAseline Subset InSAR (SBAS-InSAR) technique using C-band Sentinel-1 datasets during 2014-2019. The ground deformation over permafrost terrain is derived in spatial and temporal scale, which reflects the seasonal freeze-thaw cycle in the active layer and long-term thawing of ground ice beneath the active layer. Results show the seasonal thaw displacement exhibits a strong correlation with surficial geology contacts. The ground leveling data is used to validate the ground deformation monitoring results. Then, the ground deformation characteristics are analyzed against the landscape units. Last, the long-term inter-annual displacement value is used to estimate the water equivalent of ground ice melting.</p>

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