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基于灰色关联度模型的生态敏感区贫困化成因分析——以南水北调中线河南省水源区贾营小流域为例
贾大周1, 赵喜鹏2, 刘少博3, 郝仕龙4, 张彦鹏4
1.南阳市水利建筑勘测设计院, 河南 南阳 473068;2.杭州大地科技有限公司, 浙江 杭州 310004;3.华北水利水电大学 水利学院, 河南 郑州 450046;4.华北水利水电大学, 测绘与地理信息学院, 河南 郑州 450046
摘要:
[目的] 探究生态敏感区农村贫困化的主要影响因素,为扶贫工作提供理论基础。[方法] 以南水北调中线水源区贾营生态清洁小流域为研究对象,运用基于熵权的灰色关联度模型,计算了小流域贫困化率与影响因素的关联度,分析了小流域内影响贫困化率的主要因素。[结果] ①小流域2017年贫困化率为5.69%,是同时期河南省平均水平的2.21倍;②小流域内中游地区平均贫困化率为7.13%,明显高于上游地区(6.26%)和下游地区(5.65%);③影响小流域贫困化的主要因素为人均耕地资源占有量、劳动力占总人口比重及家庭年均饮食消费支出、初中以上学历比例、家庭年均工资性收入、地面坡度及家庭年均医疗支出等指标;④影响小流域内各个村的贫困化主要因素各有不同,呈现区域差异化。[结论] 在小流域内因地制宜地采取扶贫措施,充分利用流域内剩余劳动力和剩余劳动时间,加大教育投入力度以及处理好因残及因病致贫问题是解决小流域贫困问题的关键。
关键词:  灰色关联模型  农村贫困化率  生态清洁小流域  南水北调
DOI:10.13961/j.cnki.stbctb.2020.01.028
分类号:F323.8
基金项目:水利部黄土高原水土流失过程与控制重点实验室开放课题"豫西黄土丘陵区坡耕地水土流失控制理论与技术研究"(201604)
Analysis of Causes of Impoverishment in Ecologically Sensitive Areas Based on Grey Relational Degree Model—A Case Study at Jiaying Small Watershed in He'nan Province Water Source Area of Middle Route Rroject of South to North Water Diversion
Jia Dazhou1, Zhao Xipeng2, Liu Shaobo3, Hao Shilong4, Zhang Yanpeng4
1.Nanyang Reconnaissance and Design Institute, Nanyang, He'nan 473068, China;2.Dadi Technology Co., Ltd. Hangzhou, Zhejiang 310004, China;3.College of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, He'nan 450046, China;4.College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou, He'nan 450046, China
Abstract:
[Objective] The primary factors which are responsible for poverty in ecologically sensitive areas were studied in order to provide a theoretical basis for implementing anti-poverty measures.[Methods] This study selected an eco-clean watershed as the research target, which was located at Jiaying in the He'nan Province. In particular it was situated in the area of the water source of the Middle Route Project of South to North Water Diversion. The gray correlation model based on the entropy weight was employed to calculate the correlation degree between the poverty rate and the influencing factors in the small watershed; further, the primary factors affecting the poverty rate in the small watershed were analyzed.[Results] ①The poverty rate in Jiaying eco-clean watershed was 5.69% in 2017, which was regarded as 2.21 times higher than that of the average in the He'nan Province at the same period. ②The average poverty rate in the middle reaches of small basins was 7.13%, which was significantly higher than that in the upper (6.26%) and the lower reaches (5.65%). ③Various factors were observed to affect the poverty in small watersheds, namely:the amount of cultivated land per capita, proportion of the labor force in the total population, annual household dietary expenditures, proportion of junior middle schools, household annual average wage incomes, ground slope, and annual average medical expenditures of households. ④However, the primary factors affecting the poverty of each village in the small watershed were different, exhibiting regional differentiation.[Conclusion] The key to solve the problem of poverty in small watersheds is to take measures to alleviate the poverty according to the local specific conditions, and by rendering the complete use of the surplus labor force and the surplus working time. Further, an increase in the investment with regard to education is necessitated with appropriate solutions for tackling poverty caused by disability and disease.
Key words:  grey relational degree model  rural poverty rate  eco-clean watershed  the South to North Project