甘肃省农业用水效率评价
Evaluation of Agricultural Water Use Efficiency in Gansu Province
摘要: 在使用Super-SBM模型计算甘肃省14个市州农业用水效率的基础上,通过Malmquist指数分析了1999~2018年甘肃省农业用水效率变化特征,并采用Tobit模型分析了农业用水效率的影响因素,研究发现,从全省14个市州的农业用水效率均值来看,1999~2018年的农业用水效率呈波动上升趋势,其中8个市州的均值达到了DEA有效,嘉峪关市和甘南藏族自治州农业用水效率最高,各市州农业水资源利用效率呈现明显差异。从全要素生产率指数(TFP)看,甘肃省农业用水效率在大部分年份是提高的,且驱动甘肃省农业用水全要素生产率提高的核心因素是技术进步。从影响因素评价来看,人均GDP、城镇化率和节水灌溉面积占比与农业用水效率具有显著的正相关关系,而有效灌溉面积占比对农业用水效率具有显著的负向影响。
Abstract: Based on the calculation of agricultural water use efficiency in 14 cities and states in Gansu Province using the Super-SBM model, the variation characteristics of agricultural water use efficiency in Gansu Province from 1999 to 2018 were analyzed by the Malmquist Index, and the influencing factors of agricultural water use efficiency were analyzed by using the Tobit model, and it was found that from the average agricultural water efficiency of 14 cities and states in the province, the agricultural water use efficiency from 1999 to 2018 showed a fluctuating upward trend, and the average value of 8 cities and states reached DEA effectiveness, Jiayuguan City and Gannan Tibetan Autonomous Prefecture have the highest agricultural water use efficiency, and the utilization efficiency of agricultural water resources in various cities and prefectures shows obvious differences. From the perspective of total factor productivity index (TFP), the agricultural water efficiency of Gansu Province has improved in most years, and the core factor driving the improvement of total factor productivity of agricultural water in Gansu Province is technological progress. From the evaluation of influencing factors, the proportion of per capita GDP, urbanization rate and water-saving irrigation area had a significant positive correlation with agricultural water use efficiency, while the proportion of effective irrigation area had a significant negative impact on agricultural water use efficiency.
文章引用:杨婷, 陈兴鹏. 甘肃省农业用水效率评价[J]. 可持续发展, 2022, 12(2): 444-455. https://doi.org/10.12677/SD.2022.122048

参考文献

[1] 靳京, 吴绍洪, 戴尔阜. 农业资源利用效率评价方法及其比较[J]. 资源科学, 2005, 27(1): 146-152.
[2] 王学渊, 赵连阁. 中国农业用水效率及影响因素——基于1997-2006年省区面板数据的SFA分析[J]. 农业经济问题, 2008, 29(3): 10-18+110.
[3] 谢高地, 齐文虎, 章予舒, 等. 主要农业资源利用效率研究[J]. 资源科学, 1998, 20(5): 7-11.
[4] Cao, Y., Zhang, W. and Ren, J. (2020) Efficiency Analysis of the Input for Water-Saving Agriculture in China. Water, 12, Article No. 207. [Google Scholar] [CrossRef
[5] Fang, J. (2020) Analysis of Water Use Efficiency and Influencing Factors of Agricultural Total Factors in Beijing- Tianjin-Hebei Region. IOP Conference Series: Earth and Environmental Science, 440, Article ID: 052008. [Google Scholar] [CrossRef
[6] Liu, Y., Geng, J., Zhang, L., et al. (2020) Analysis of Ag-ricultural Water Use Efficiency in Shandong Province Based on DEA and Malmquist Model. IOP Conference Series: Earth and Environmental Science, 585, Article ID: 012090.
[7] Wang, S., Zhou, L., Wang, H., et al. (2018) Water Use Efficiency and Its Influencing Factors in China: Based on the Data Envelopment Analysis (DEA)—Tobit Model. Water, 10, Article No. 832. [Google Scholar] [CrossRef
[8] 罗凯, 唐德善, 唐彦. 基于熵权——正态云模型的农业用水效率评价[J]. 中国农村水利水电, 2020(10): 159-163.
[9] 郑海霞, 封志明, 张陆彪, 等. 甘肃省县域农业资源利用效率综合评价——基于遗传投影寻踪方法[J]. 经济地理, 2006, 26(4): 632-635.
[10] 赵敏, 刘姗. 基于双前沿面SBM-DEA模型的农业用水效率评价[J]. 水利经济, 2020, 38(1): 54-60+67+87.
[11] 许朗, 黄莺. 农业灌溉用水效率及其影响因素分析——基于安徽省蒙城县的实地调查[J]. 资源科学, 2012, 34(1): 105-113.
[12] 佟金萍, 马剑锋, 王圣, 等. 长江流域农业用水效率研究:基于超效率DEA和Tobit模型[J]. 长江流域资源与环境, 2015, 24(4): 603-608.
[13] Huang, Y.J., Huang, X.K., Xie, M.N., et al. (2021) A Study on the Ef-fects of Regional Differences on Agricultural Water Resource Utilization Efficiency Using Super-Efficiency SBM Mode. Scientific Reports, 11, Article No. 9953. [Google Scholar] [CrossRef] [PubMed]
[14] 董毅明, 廖虎昌. 基于DEA的西部省会城市水资源利用效率研究[J]. 水土保持通报, 2011, 31(4): 134-139.
[15] 陆泉志, 陆桂军, 范稚莲, 等. 广西农业水资源利用效率及其影响因素研究——基于Global超效率DEA与Tobit模型[J]. 节水灌溉, 2018(8): 54-58+65.
[16] 李青松, 张凤太, 苏维词, 等. 长江经济带农业用水绿色效率测度及影响因素分析——基于超效率EBM-Geodetector模型[J/OL]. 中国农业资源与区划, 2021.
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