Sustainable use of water resources under environmental restriction along the Yellow River in Ningxia and Inner Mongolia autonomous regions

2004 ◽  
Author(s):  
Haiying Wang ◽  
Chuansheng Wang ◽  
Fei You ◽  
Dongqian Xue
Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 748
Author(s):  
Ming Li ◽  
Qingsong Tian ◽  
Yan Yu ◽  
Yueyan Xu ◽  
Chongguang Li

The sustainable and efficient use of water resources has gained wide social concern, and the key point is to investigate the virtual water trade of the water-scarcity region and optimize water resources allocation. In this paper, we apply a multi-regional input-output model to analyze patterns and the spillover risks of the interprovincial virtual water trade in the Yellow River Economic Belt, China. The results show that: (1) The agriculture and supply sector as well as electricity and hot water production own the largest total water use coefficient, being high-risk water use sectors in the Yellow River Economic Belt. These two sectors also play a major role in the inflow and outflow of virtual water; (2) The overall situation of the Yellow River Economic Belt is virtual water inflow, but the pattern of virtual water trade between eastern and western provinces is quite different. Shandong, Henan, Shaanxi, and Inner Mongolia belong to the virtual water net inflow area, while the virtual water net outflow regions are concentrated in Shanxi, Gansu, Xinjiang, Ningxia, and Qinghai; (3) Due to higher water resource stress, Shandong and Shanxi suffer a higher cumulative risk through virtual water trade. Also, Shandong, Henan, and Inner Mongolia have a higher spillover risk to other provinces in the Yellow River Economic Belt.


Water Policy ◽  
2021 ◽  
Author(s):  
Huiliang Wang ◽  
Shuoqiao Huang ◽  
Danyang Di ◽  
Yu Wang ◽  
Fengyi Zhang

Abstract To analyze the spatial distribution characteristics of water resource value in the agricultural system of the Yellow River Basin, this paper takes the Yellow River Basin as its research object and studies the spatial distribution characteristics and influencing factors of water resource value in the agricultural system using the emergy theory and method, the spatial autocorrelation analysis method, and the spatial regression model. The results show that (1) the value of water resources in the agricultural system ranges from 0.64 to 0.98$/m3, and the value in the middle and lower reaches of the basin is relatively high; (2) the Moran index of the water resource value in the agricultural system is 0.2772, showing a positive spatial autocorrelation feature. Here, ‘high-high (high value city gathering)’ is the main aggregation mode, which is mainly concentrated in the middle and lower reaches of the basin. (3) The spatial error model, moreover, has the best simulation effect. The cultivated land area, total agricultural output value, agricultural labor force, and total mechanical power have a significant positive impact on the agricultural production value of water resources in the Yellow River Basin; the altitude, annual average temperature, and agricultural water consumption have a negative impact. Overall, this study shows that guiding the distribution of water resources according to their value and increasing agricultural water use in the middle and lower reaches of the basin will help improve the overall agricultural production efficiency of water resources in the basin.


Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 974 ◽  
Author(s):  
Xuan Zhang ◽  
Jungang Luo ◽  
Jin Zhao ◽  
Jiancang Xie ◽  
Li Yan ◽  
...  

In order to not only solve the technical problems of quantifying the degree and range of the effect that is caused by the water quality of upstream on that of downstream portions of a river, and of dividing the responsibility of transboundary water pollution, but also to tackle the difficulty in adapting to dynamic changes of the traditional water quality model in terms of practical application, pollutant discharge and water consumption were taken as the main influence factors to build the transboundary water quality transfer effect model. Supported by a comprehensive integration platform, the transboundary water quality transfer effect simulation system of the Yellow River mainstream was constructed. The simulation results show that the concentration decreases exponentially along the range. Gansu, Ningxia, and Inner Mongolia had a more significant effect of exceeding standard water consumption on pollution, while Ningxia, Inner Mongolia, Shaanxi, and Shanxi had a more distinct contribution to the over standard pollution discharge effect. The proposed model and simulation system can provide new methods and instruction for quantifying the degree and range of transboundary water pollution, as well as dividing the responsibility for water environment compensation.


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.


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