scholarly journals Long‐term hydrological assessment of remote sensing precipitation from multiple sources over the lower Yangtze River basin, China

2021 ◽  
Vol 28 (3) ◽  
Author(s):  
Dehua Zhu ◽  
Abro M. Ilyas ◽  
Gaoxu Wang ◽  
Biqiu Zeng
Keyword(s):  
Remote Sensing ◽  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Multiple Sources ◽  
Lower Yangtze

scholarly journals Analysis of long-term terrestrial water storage variations in the Yangtze River basin

2013 ◽  
Vol 17 (5) ◽  
pp. 1985-2000 ◽  
Author(s):  
Y. Huang ◽  
M. S. Salama ◽  
M. S. Krol ◽  
R. van der Velde ◽  
A. Y. Hoekstra ◽  
...  
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Water Storage ◽  
The Yangtze River ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
The Yangtze River Basin ◽  
Lower Yangtze ◽  
Gauging Station

Abstract. In this study, we analyze 32 yr of terrestrial water storage (TWS) data obtained from the Interim Reanalysis Data (ERA-Interim) and Noah model from the Global Land Data Assimilation System (GLDAS-Noah) for the period 1979 to 2010. The accuracy of these datasets is validated using 26 yr (1979–2004) of runoff data from the Yichang gauging station and comparing them with 32 yr of independent precipitation data obtained from the Global Precipitation Climatology Centre Full Data Reanalysis Version 6 (GPCC) and NOAA's PRECipitation REConstruction over Land (PREC/L). Spatial and temporal analysis of the TWS data shows that TWS in the Yangtze River basin has decreased significantly since the year 1998. The driest period in the basin occurred between 2005 and 2010, and particularly in the middle and lower Yangtze reaches. The TWS figures changed abruptly to persistently high negative anomalies in the middle and lower Yangtze reaches in 2004. The year 2006 is identified as major inflection point, at which the system starts exhibiting a persistent decrease in TWS. Comparing these TWS trends with independent precipitation datasets shows that the recent decrease in TWS can be attributed mainly to a decrease in the amount of precipitation. Our findings are based on observations and modeling datasets and confirm previous results based on gauging station datasets.

Lead pollution recorded in sediments of three lakes located at the middle and lower Yangtze River basin, China

2009 ◽  
Vol 208 (1-2) ◽  
pp. 145-150 ◽  
Author(s):  
Shuchun Yao ◽  
Bin Xue ◽  
Weilan Xia ◽  
Yuxing Zhu ◽  
Shijie Li
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Lead Pollution ◽  
Lower Yangtze

scholarly journals Analysis of long-term terrestrial water storage variations in Yangtze River basin

2012 ◽  
Vol 9 (10) ◽  
pp. 11487-11520 ◽  
Author(s):  
Y. Huang ◽  
M. S. Salama ◽  
M. S. Krol ◽  
R. van der Velde ◽  
A. Y. Hoekstra ◽  
...  
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Precipitation Amount ◽  
Temporal Analysis ◽  
Reanalysis Data ◽  
Full Data ◽  
Global Precipitation Climatology Centre ◽  
Lower Yangtze ◽  
Gauging Station

Abstract. In this study, we analyze 32 yr of TWS data obtained from Interim Reanalysis Data (ERA-Interim) and Noah model from Global Land Data Assimilation System (GLDAS-Noah) for the period between 1979 and 2010. The accuracy of these datasets is validated against 26 yr (1979–2004) of runoff dataset from Yichang gauging station and compared to 32 yr of independent precipitation data obtained from Global Precipitation Climatology Centre Full Data Reanalysis Version 6 (GPCC) and NOAA's PRECipitation REConstruction over Land (PREC/L). Spatial and temporal analysis of the TWS data shows that TWS in the Yangtze River basin is decreasing significantly since the year 1998. The driest period of the basin is noted from 2005 to 2010, especially in the middle and lower Yangtze reaches. The TWS changed abruptly into persistently high negative anomalies in the middle and lower Yangtze reaches in 2004. From both basin and annual perspectives, 2006 is detected as the major inflection point at which the system exhibits a persistent decrease in TWS. Comparing these TWS trends to independent precipitation datasets shows that the recent decrease in TWS can mainly be attributed to a decrease in precipitation amount. Our finding is based on observation and modeling data sets and confirms previous results based on gauging station datasets.

scholarly journals “3S” TECHNOLOGIES AND APPLICATION FOR DYNAMIC MONITORING SOIL AND WATER LOSS IN THE YANGTZE RIVER BASIN, CHINA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1563-1567
Author(s):  
C. Li ◽  
J. Yao ◽  
R. Li ◽  
Y. Zhu ◽  
H. Yao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
River Basin ◽  
Yangtze River ◽  
Soil Loss ◽  
Yangtze River Basin ◽  
Dynamic Monitoring ◽  
The Yangtze River ◽  
Soil And Water Loss ◽  
The Yangtze River Basin ◽  
Remote Sensing Interpretation

Abstract. For China, which has many big rivers, there is an urgent need for efficient dynamic monitoring technology of water and soil loss. However, there are some problems in the current 3S (RS, GIS and GPS) technology for dynamic monitoring water and soil loss. This paper takes the Yangtze River Basin as an example to innovate and optimize the key technologies of the remote sensing interpretation of the water and soil loss dynamic monitoring of the Yangtze River Basin, and overcome the major technical difficulties in the remote sensing interpretation of the dynamic monitoring of water and soil loss. The key technologies include: 1) The establishment of a field investigation platform based on Internet and UAV (Unmanned Aerial Vehicle) for remote sensing interpretation; 2) Near real-time evaluating key factors of soil and water loss based on UAV photogrammetry and digital terrain analysis; 3) Geometric and Radiometric Simultaneous Correction Model (GRSCM) framework for remote sensing images pre-processing; 4) An object-oriented land use change update quality control method supported by multi-PC and GIS; and an object-oriented remote sensing image classification system based on random forest, deep learning and transfer learning; 5) Improvement of quantitative change detection method for image vegetation and three-dimensional topography. The results have been successfully applied in the remote sensing interpretation of the dynamic monitoring of water and soil loss in the national key prevention and control area of the Yangtze River Basin. They have been provided a scientific reference for the development planning of The Yangtze River Economic Zone.

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