Analysis of long-term water balance in the source area of the Yellow River basin

2008 ◽  
Vol 22 (11) ◽  
pp. 1618-1629 ◽  
Author(s):  
Yoshinobu Sato ◽  
Xieyao Ma ◽  
Jianqing Xu ◽  
Masayuki Matsuoka ◽  
Hongxing Zheng ◽  
...  
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Yellow River ◽  
Source Area ◽  
Yellow River Basin ◽  
The Yellow River ◽  
The Yellow River Basin

scholarly journals Evaluation of Evapotranspiration Estimates in the Yellow River Basin against the Water Balance Method

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1884 ◽  
Author(s):  
Guojie Wang ◽  
Jian Pan ◽  
Chengcheng Shen ◽  
Shijie Li ◽  
Jiao Lu ◽  
...  
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Land Surface ◽  
Yellow River ◽  
Yellow River Basin ◽  
Balance Method ◽  
The Yellow River ◽  
Water Balance Method ◽  
Global Land ◽  
The Yellow River Basin

Evapotranspiration (ET), a critical process in global climate change, is very difficult to estimate at regional and basin scales. In this study, we evaluated five ET products: the Global Land Surface Evaporation with the Amsterdam Methodology (GLEAM, the EartH2Observe ensemble (E2O)), the Global Land Data Assimilation System with Noah Land Surface Model-2 (GLDAS), a global ET product at 8 km resolution from Zhang (ZHANG) and a supplemental land surface product of the Modern-ERA Retrospective analysis for Research and Applications (MERRA_land), using the water balance method in the Yellow River Basin, China, including twelve catchments, during the period of 1982–2000. The results showed that these ET products have obvious different performances, in terms of either their magnitude or temporal variations. From the viewpoint of multiple-year averages, the MERRA_land product shows a fairly similar magnitude to the ETw derived from the water balance method, while the E2O product shows significant underestimations. The GLEAM product shows the highest correlation coefficient. From the viewpoint of interannual variations, the ZHANG product performs best in terms of magnitude, while the E2O still shows significant underestimations. However, the E2O product best describes the interannual variations among the five ET products. Further study has indicated that the discrepancies between the ET products in the Yellow River Basin are mainly due to the quality of precipitation forcing data. In addition, most ET products seem to not be sensitive to the downward shortwave radiation.

Application of a Coupled Atmospheric and Hydrological Modelling System (AHMS) to the Yellow River Basin, China

2020 ◽  
Author(s):  
Cong Jiang ◽  
Eric J. R. Parteli ◽  
Yaping Shao
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
Hydrological Modelling ◽  
The Yellow River ◽  
Hydrological Process ◽  
Daily Streamflow ◽  
The Yellow River Basin ◽  
Modelling System

<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>

scholarly journals Changes of Soil Moisture from Multiple Sources during 1988–2010 in the Yellow River Basin, China

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Dan Lou ◽  
Guojie Wang ◽  
Chan Shan ◽  
Daniel Fiifi T. Hagan ◽  
Waheed Ullah ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Soil Drying ◽  
Interannual Variations ◽  
Multiple Sources ◽  
The Yellow River Basin

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.

scholarly journals Geological model of the Yellow River basin for the long-term groundwater simulation

2009 ◽  
Vol 60 (1-2) ◽  
pp. 117-130
Author(s):  
Hirofumi Muraoka ◽  
Koji Mori ◽  
Shiro Tamanyu ◽  
Takemasa Ishii ◽  
Youhei Uchida
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Geological Model ◽  
Groundwater Simulation ◽  
The Yellow River Basin
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