摘要
基于非期望产出的SBM模型,比较了2009—2017年黄河流域农业用水效率动态变化和农业用水优化路径。结果表明,黄河流域农业用水效率高于全国水平,但其下降幅度更大;黄河中上游、中下游地区和流域整体效率均值分别为0.722、0.855、0.781,中上游地区效率低且下降更为显著;青海、山东、陕西和四川效率值为1,山西用水效率较高但存在潜在的下降风险,甘肃、宁夏、河南效率较低,内蒙古农业用水效率最低,节水潜力最大。根据农业用水效率及污染程度聚类结果,甘肃、宁夏和内蒙古属于低效率-低污染类型,河南属于低效率-高污染类型,青海、山西、陕西和四川属于高效率-低污染类型,山东属于高效率-高污染类型,不同类型地区采取不同的农业用水优化政策。
Based on the SBM-Undesirable model,the dynamic changes of agricultural water-use efficiency and the optimization path of agriculturalwater-use in the Yellow river basin from 2009 to 2017 were studied.The results showed that the agricultural water-use efficiency of the Yellow river basin was higher than the national level,but the water-use efficiency of it has dropped by a larger mar⁃gin;the average efficiency of the yellow river upper and middle reaches,the middle and lower reaches and the overall basin were 0.722,0.855,0.781,respectively,the efficiency in the upper and middle reaches were low and the decline ismore significant;The ef⁃ficiency of Qinghai,Shandong,Shaanxi and Sichuan were 1,the water-use efficiency of Shanxi was higher,but there was a potential risk of decline.Gansu,Ningxia,and Henan have lower efficiency.Inner Mongolia has the lowest agricultural water-use efficiency and the greatest water-saving potential.According to the clustering results of agricultural water-use efficiency and pollution degree,Gan⁃su,Ningxia and Inner Mongolia belong to the low-efficiency-low-pollution type,Henan was the low-efficiency-high-pollution type,Qinghai,Shanxi,Shaanxi and Sichuan were the high-efficiency-low-pollution type of area,and Shandong belonged to the high-effi⁃ciency-high-pollution type,different types of areas should adopt different agricultural water-use optimization policies.
作者
李鸿雁
付俊怡
张兴华
LI Hong-yan;FU Jun-yi;ZHANG Xing-hua(School of Economics and Management,Ningxia University,Yinchuan 750021,China;School of Agriculture,Ningxia University,Yinchuan 750021,China)
出处
《湖北农业科学》
2021年第20期171-178,共8页
Hubei Agricultural Sciences
基金
国家自然科学基金项目(71863030)
宁夏大学社科重大项目(SKZX2017004)
宁夏大学理论经济学一流学科(NXYLXK2017B04)。