Assessment for water resources bearing capacity based on Entropy model and EFAST weight algorithm in the Yellow River basin

Author(s):  
Libin Yang

<p>It is of great practical significance to analyze water resources load carry and clarify the bearing capacity of water resources in the Yellow River basin for the ecological protection and economic and social development with high quality of the Yellow River. The Entropy model and EFAST weight algorithm is coupled and employed to assess the water-resources bearing capacity in the Yellow River basin based on the double index of water quantity and quality. The results show that there are 78 groundwater overdraft areas existing, the total area and ultra-picks quantity of which is 2.26×10<sup>4</sup> km<sup>2</sup> and 14×10<sup>8</sup> m<sup>3</sup>, respectively. Massive cones of depression are developing like Yinchuan and Dawukou in Ningxia province; Fengdong, Xinghua, Lvqiao and Weibin in Shaanxi province; Songgu, Taiyuan and Yuncheng in Shanxi province; Wuzhi, Wenxian and Mengxian in Henan province. Moreover, 47 of 70 assessed prefecture cities are in the state of overload or severe overload, in which, there are 24 severe-overload prefecture cities and the proportion is 34.3%, and the number of overload prefecture cities is 23 accounting for 32.9%. The overload and severe-overload regions concentrate in Gansu, Ningxia, Inner Mongolia, Shaanxi, Shanxi and Henan provinces at the upper and middle Yellow River. In conclusion, the current water supply has exceeded its water-resources bearing capacity in the Yellow River basin. Strengthening water saving, the construction of main-stream controlled reservoirs and water diversion are the effective ways to relieve the overload state.</p>

2021 ◽  
Author(s):  
Zhaofeng Wang ◽  
Qingqing Chen

Abstract A better understanding on the spatial matching relationship between tourism urbanization and resources and environment carrying capacity is vital for the regional selection of the key eco-livable tourist cities in the Yellow River Basin. This paper addressed this research issue by evaluating and partitioning tourism urbanization level and resources and environment carrying capacity of the Yellow River Basin in 2005, 2011 and 2018, using GIS technology, spatial autocorrelation model and partition method. Empirical results suggest that (1) The tourism urbanization level of Shaanxi province maintains the leading position, while Shanxi province has great development potential. The high value areas of resources and environmental carrying capacity concentrated in Gansu, Inner Mongolia and Shandong provinces. (2) The spatial agglomeration degree of tourism urbanization level and resources and environment carrying capacity have been improved. (3) The resources and the environment carrying capacity exhibits a greater restrictive effect on the current high-level areas of tourism urbanization, and the spatial correspondence between them is weak. Based on the findings of this study, a series of optimization strategies and policy suggestions have been proposed for promoting the sustainable development of tourism urbanization in the Yellow River Basin.


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.


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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