| Cite this article: | 刘雯昱,陈晓宏.华南地区省际用水效率时空差异及驱动因子研究[J].灌溉排水学报,0,():-. |
| Liu Wenyu,Chen Xiaohong.华南地区省际用水效率时空差异及驱动因子研究[J].灌溉排水学报,0,():-. |
|
| |
|
|
| This article has been：Browse 1957Times Download 0Times |
|
|
|
| DOI： |
|
| Study on Temporal-Spatial Difference and affecting factors of Interprovincial Water Use Efficiency in South China |
|
Liu Wenyu, Chen Xiaohong
|
|
Center for Water Resources and Environment, Sun Yat-sen University,Guangzhou
|
| Abstract: |
| 【Objective】In order to identify the temporal and spatial difference and the main influencing factors of water use efficiency between provinces in South China. Although the amount of water resources in South China is richer than that in other parts of the country, the people's consciousness of saving water is relatively weak. Therefore, it is very important to formulate targeted measures to effectively improve the water use efficiency in South China.【Method】A comprehensive evaluation index system of water use efficiency is constructed from five aspects: life, agriculture, industry, ecology and economy. The water use efficiency of South China is comprehensively evaluated by administrative regions, and the temporal difference and change trend of water use efficiency in South China from 2000 to 2018 are analyzed. The inter-provincial spatial variation trend of each index is analyzed by using Thiel coefficient, and the main driving factors of water use efficiency in South China are explored by Grey correlation method.【Conclusion】As regard to water use efficiency level, from 2000 to 2018, Fujian Province is the highest, far higher than Hainan, Guangdong Province, and Guangxi Autonomous Region is the worst. As for the spatial difference of index, the spatial difference of water consumption of ten thousand yuan GDP and ten thousand yuan industrial added value are the largest, and the spatial difference of irrigation water efficiency and comprehensive per capita water consumption are the smallest. In terms of driving factors, the four provinces are mostly affected by water consumption and drainage, and also affected by economy and total water resources,etc. |
| Key words: South China; Water Use Efficiency; Topsis analysis; Information weight; Thiel coefficient; Grey correlation method |
|
|
|
|
|
|
