Theoretical Method and Application of Assessment on Water Resources Carrying Capacity: A Case Study of Binzhou, Shandong

2021 ◽  
pp. 325-339
Author(s):  
Chengjie Zhang ◽  
Sheng Zheng ◽  
Yuzhe Wu
2020 ◽  
Vol 980 ◽  
pp. 429-436
Author(s):  
Li Juan Li ◽  
Shan Yong Li

In this paper, 11 indexes were selected from three aspects: water resources environment, economy and society to construct the evaluation index system, and the main component analysis method was used to comprehensively evaluate the carrying capacity of water resources in Henan province for the past three years. The research results show that: 1. During the current period, the carrying capacity of water resources in Henan Province has been steadily increasing. The cities with good carrying capacity of water resources are: Zhengzhou, Luoyang, Xinxiang and Nanyang; Cities with better water resources capacity include Kaifeng, Pingdingshan, Anyang, Jiaozuo and Xinyang; The remaining cities have general water resources carrying capacity;The contribution of each subsystem to the integrated carrying capacity of water resources is increasing year by year, among which the contribution of water resources environmental subsystem and economic subsystem is the largest and the contribution of social subsystem is relatively stable.The conclusion shows that the development level of Waterscape tourism industry in Zhengzhou, Luoyang, Kaifeng, Jiaozuo and other areas is higher, while the Waterscape tourism industry in Luohe, Xuchang, Zhoukou and other areas is lower. The development level of Waterscape tourism industry in Henan Province from the view of the overall spatial pattern is higher. The water resources management and utilization level of henan is relatively high.


2017 ◽  
Vol 7 (1) ◽  
pp. 21 ◽  
Author(s):  
Hongyan Liao ◽  
Yuabiao Zhang ◽  
Zhifeng Chen ◽  
Zexin Meng

Growing pressure on the world’s water resources is having major impacts on us. In this paper, we discuss on water resources carrying capacity. We have a case study of Shandong Province which is one of the most arid regions in China. Considering the dynamics of water supply and demand, we combine the Falkenmark indicator and the binary dynamics model to establish an evaluation model of regional water resources carrying capacity. According to the result of our model, Shandong Province is heavily exploited. The per capita water resources in Shandong province were less than 300 m3 in the past ten years. The increasing destruction and increasing waste make the situation even worse. Then ARIMA model and BP neural network is combined to propose a prediction model. We use it to predict the supply and demand of water resources in Shandong Province in the next 15 years


2015 ◽  
Vol 1092-1093 ◽  
pp. 1202-1208
Author(s):  
Ming Xia Jing

This paper predicted HuangShui River carrying capacity level of environmental resources at the end of the "twelfth five-year" period and even longer, based on the economic and social development in the base year 2011 data, to provide reference for the development of various government related department reference.


2021 ◽  
Vol 248 ◽  
pp. 03010
Author(s):  
Gao Mengmeng ◽  
Li Xiaolei ◽  
Yang Nan ◽  
Sun Xiubo ◽  
Liu Qiong ◽  
...  

Water resources play an important role in the natural environment, which is an irreplaceable resource for the survival and development of human society. Taking water resources as the research object, combined with the demand of social and economic development for water resources, this paper carried out the research on the evaluation method of cultivated land scale and urban construction scale under the constraints of water resources in Jinzhou. The results show that: the scale of cultivated land is 7215.98-7843.20km2, which is in surplus. Heishan County has the largest scale of cultivated land and Guta District has the smallest scale of cultivated land. The urban construction land scale is 229.89-279.02 km2, which is in surplus. Taihe District and Yixian County are overloaded, and the rest are surplus. The evaluation results can support the determination and decomposition of planning objectives and indicators, and provide an important scientific basis for the implementation of local land spatial planning.


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