The long-term spatial and temporal variations of sediment loads and their causes of the Yellow River Basin

CATENA ◽  
2022 ◽  
Vol 209 ◽  
pp. 105850
Author(s):  
Junjie Wang ◽  
Bing Shi ◽  
Enjin Zhao ◽  
Qingyun Yuan ◽  
Xuguang Chen
2014 ◽  
Vol 955-959 ◽  
pp. 3269-3273
Author(s):  
Xin Ling Cai ◽  
Qian Li ◽  
Lin Hu ◽  
Xiao Meng Zhao

Based on the daily rainfall data of 145 meteorological stations in the Yellow River basin, the spatial and temporal variations characteristic of erosive rainfall was analyzed by using statistical methods. The results show that the trend of the erosion precipitation, extreme precipitation and annual precipitation is significantly reduced. The erosion precipitation, extreme precipitation and annual precipitation are decrease from southeast to northwest. The long-term trends of different intensities rainfall is non-uniformity in space nearly 50 years. The erosion precipitation and annual precipitation are increasing in most areas of the upper reaches of the Yellow River basin, and are decreasing in the others areas, especially decreasing significantly in the water and soil loss of serious erosion in the Loess Plateau.


2013 ◽  
Vol 33 (24) ◽  
Author(s):  
袁丽华 YUAN Lihua ◽  
蒋卫国 JIANG Weiguo ◽  
申文明 SHEN Wenming ◽  
刘颖慧 LIU Yinghui ◽  
王文杰 WANG Wenjie ◽  
...  

2020 ◽  
Author(s):  
Cong Jiang ◽  
Eric J. R. Parteli ◽  
Yaping Shao

<p>The Yellow River Basin (795,000 km<sup>2</sup>) in Northern China has been greatly affected by intensive human activity and climate change over the past decades. In this study, a coupled atmospheric and hydrological modelling system is applied to investigating the long-term hydrological cycle and short-term forecasting of hydrological events in the Yellow River Basin. This modelling system (AHMS) combines a hydrological model (HMS) with the Weather Research and Forecast model (WRF) and the Noah land surface scheme (NoahMP-LSM), which has been recently improved to account for topographic influences in the infiltration scheme and to allow for interactions between the unsaturated and saturated zones by applying the Darcy-flux boundary condition. Here, simulations are performed using the offline AHMS mode over the Yellow River Basin by considering a time span of 25 years (1979-2003) and a spatial resolution of 20 km. The NCEP reanalysis dataset and observed precipitation data for the referred period are used as meteorological forcing data. The most important parameters affecting the hydrological process are identified by means of a parametric sensitivity analysis. Specifically, these main parameters are the Manning's roughness coefficient of channel, the soil infiltration capacity and the hydraulic conductivity of riverbed. To calibrate the values of these parameters for the Yellow River Basin, model predictions for daily streamflow are compared with the corresponding observational data at four hydrological gauging stations including Tangnaihe (TNH), Lanzhou (LZ), Toudaoguai (TDG) and Huanyuankou (HYK) on the mainstream of the Yellow River. Quantitative agreement is found between these observations and the simulation results for all stations. The progress achieved in the present work paves the way for a sediment flux model over the Yellow River Basin and demonstrates the good performance of AHMS for long-term hydrological simulations. </p><p></p>


2008 ◽  
Vol 22 (11) ◽  
pp. 1618-1629 ◽  
Author(s):  
Yoshinobu Sato ◽  
Xieyao Ma ◽  
Jianqing Xu ◽  
Masayuki Matsuoka ◽  
Hongxing Zheng ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Dan Lou ◽  
Guojie Wang ◽  
Chan Shan ◽  
Daniel Fiifi T. Hagan ◽  
Waheed Ullah ◽  
...  

Soil moisture is a key variable in terrestrial water cycle, playing a key role in the exchange of water and energy in the land-atmosphere interface. The spatiotemporal variations of soil moisture from multiple sources during 1988–2010 are evaluated against in situ observations in the Yellow River basin, China, including the Essential Climate Variable satellite’s passive microwave product (SMECV), ERA-Interim reanalysis (SMERA), the National Centers for Environmental Prediction/Department of Energy’s Reanalysis-2 (SMNCEP), and the Variable Infiltration Capacity model products (SMVIC). The seasonal soil moisture dynamics of SMECV and SMVIC appear to be consistent with SMin  situ, with significant soil drying in spring and wetting in summer. SMERA and SMNCEP, however, fail to capture the soil drying before rainy seasons. Remarkably, SMECV shows large agreement with SMin  situ in terms of the interannual variations and the long-term drying trends. SMVIC captures the interannual variations but fails to have the long-term trends in SMin  situ. As for SMERA and SMNCEP, they fail to capture both the interannual variations and the long-term soil drying trends in SMin  situ.


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