scholarly journals Simulation of Water Cycle Changes in the Yellow River Basin under Changing Conditions

10.29007/cxp9 ◽  
2018 ◽  
Author(s):  
Yongnan Zhu ◽  
Zhaohui Lin ◽  
Yong Zhao ◽  
Lizhen Wang

This study analyzed the combined effects of climate change and land use changes in the Yellow River Basin over the last 45 years. Based on the China Land-use Data for Hundred Years dataset (CLDH), East Asia daily precipitation data, and 6-h NCEP/NCAR reanalysis data, the Coupled Land Surface and Hydrology Model System (CLHMS) was applied to simulate the water cycle processes in the Yellow River under changing conditions from 1962 to 2006. During the study period, the evaporation, infiltration, and surface runoff in the Yellow River Basin all showed a decreasing trend. Comparative tests indicated that climate change was a major factor impacting water cycle variations.

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1884 ◽  
Author(s):  
Guojie Wang ◽  
Jian Pan ◽  
Chengcheng Shen ◽  
Shijie Li ◽  
Jiao Lu ◽  
...  

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.


2010 ◽  
Vol 136 (1) ◽  
pp. 106-115 ◽  
Author(s):  
Yaqin Qiu ◽  
Yangwen Jia ◽  
Jincheng Zhao ◽  
Xuehong Wang ◽  
Jeff Bennett ◽  
...  

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Zhiyong Wu ◽  
Heng Xiao ◽  
Guihua Lu ◽  
Jinming Chen

The water resources in the Yellow River basin (YRB) are vital to social and economic development in North and Northwest China. The basin has a marked continental monsoon climate and its water resources are especially vulnerable to climate change. Projected runoff in the basin for the period from 2001 to 2030 was simulated using the variable infiltration capacity (VIC) macroscale hydrology model. VIC was first calibrated using observations and then was driven by the precipitation and temperature projected by the RegCM3 high-resolution regional climate model under the IPCC scenario A2. Results show that, under the scenario A2, the mean annual temperature of the basin could increase by 1.6°C, while mean annual precipitation could decrease by 2.6%. There could be an 11.6% reduction in annual runoff in the basin according to the VIC projection. However, there are marked regional variations in these climate change impacts. Reductions of 13.6%, 25.7%, and 24.6% could be expected in the regions of Hekouzhen to Longmen, Longmen to Sanmenxia, and Sanmenxia to Huayuankou, respectively. Our study suggests that the condition of water resources in the YRB could become more severe in the period from 2001 to 2030 under the scenario A2.


Water ◽  
2017 ◽  
Vol 9 (2) ◽  
pp. 116 ◽  
Author(s):  
Bin Li ◽  
Changyou Li ◽  
Jianyu Liu ◽  
Qiang Zhang ◽  
Limin Duan

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