Long-term trend analysis for major climate variables in the Yellow River basin*

2007 ◽  
Vol 21 (14) ◽  
pp. 1935-1948 ◽  
Author(s):  
Z. X. Xu ◽  
J. Y. Li ◽  
C. M. Liu
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Climate Variables ◽  
Term Trend ◽  
The Yellow River Basin ◽  
Long Term Trend

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>

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 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

scholarly journals Performance of Two Long-Term Satellite-Based and GPCC 8.0 Precipitation Products for Drought Monitoring over the Yellow River Basin in China

2019 ◽  
Vol 11 (18) ◽  
pp. 4969 ◽  
Author(s):  
Wei ◽  
Jiang ◽  
Ren ◽  
Yuan ◽  
Zhang
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
Drought Monitoring ◽  
The Yellow River ◽  
Climate Data ◽  
Full Data ◽  
Global Precipitation Climatology Centre ◽  
The Yellow River Basin

This study investigated the accuracy and drought monitoring application of two newly-released long-term satellite precipitation products (i.e., the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record, PERSIANN-CDR and the Climate Hazards Group Infrared Precipitation with Station data version 2.0 CHIRPS) and the latest reanalysis precipitation product (i.e., the Global Precipitation Climatology Centre full data monthly version 2018, GPCC 8.0). Satellite- and reanalysis-based precipitation sequences and standardized precipitation indices (SPIs) were compared comprehensively with background estimates of the China Gauge-based Daily Precipitation Analysis (CGDPA) dataset at spatial and multiple temporal scales over the Yellow River Basin (YRB) in China during 1983–2016. Results indicated the PERSIANN-CDR, CHIRPS and GPCC 8.0 precipitation products generally had good consistency with CGDPA (correlation coefficient, CC > 0.78). At spatial, monthly and seasonal scales, the consistency between GPCC 8.0 and CGDPA precipitation was found to be better than that of the two satellite products. Due to their good performance at the spatiotemporal scale, the satellite with long-time record and GPCC 8.0 products were evaluated and compared with CGDPA to derive SPI-1 (1-month SPI), SPI-3 (3-month SPI), and SPI-12 (12-month SPI) for drought monitoring in the YRB. The results showed that they had good application in monitoring droughts (CC > 0.65 at spatial scale, CC > 0.84 at temporal scale). The historical drought years (i.e., 1997, 1999, and 2006) and the spatial distribution of drought area in August 1997 were captured successfully, but the performance of GPCC 8.0 was found to be the best. Overall, GPCC 8.0 is considered best suited to complement precipitation datasets for long-term hydrometeorological research in the YRB.

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