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安 敏, 方 雪, 何伟军, 黄 进, 文法广, 童 星, 宋孟斐.淮河生态经济带用水转移网络特征及影响因素分析水资源与水工程学报[J].,2022,33(1):46-53
淮河生态经济带用水转移网络特征及影响因素分析
Water transfer network characteristics and its influencing factors in the Huaihe River Eco-economic Belt
  
DOI:10.11705/j.issn.1672-643X.2022.01.07
中文关键词:  区域用水关联关系  社会网络分析  水资源管理  淮河生态经济带
英文关键词:regional water use correlation  social network analysis (SNA)  water resources management  the Huaihe River Eco-economic Belt
基金项目:国家自然科学基金项目(71874101、72004116、72104127); 湖北省人文社会科学重点研究基地项目(2021-SDSG-05); 2021年湖北省教育厅科学研究计划项目中青年人才项目(Q20211211); 水库移民研究中心湖北省高校人文社科重点研究基地开放基金项目(2020KF05)
作者单位
安 敏1,2, 方 雪1, 何伟军1, 黄 进1, 文法广3, 童 星1, 宋孟斐1 (1.三峡大学 水库移民研究中心 湖北 宜昌 443002 2.三峡大学 经济与管理学院湖北 宜昌 443002 3.山东大学 数学学院 山东 济南 250100) 
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中文摘要:
      稀缺背景下相邻区域用水关系呈现出越来越复杂的关联特征,厘清地区间内部用水关系并揭露其用水空间联动格局,能为优化区域水资源协同治理政策提供可靠的参考依据。根据淮河生态经济带28个城市2005-2018年的相关用水数据,运用社会网络分析(SNA)方法刻画了淮河生态经济带城市间用水空间关联网络结构及其转移特征,并使用二次指派程序(QAP)方法揭示了其用水空间关联网络构建的影响因素。结果表明:淮河生态经济带城市间用水关联关系呈现出较为复杂的网络结构,网络密度在样本考察期内轻微减小,但整体网络结构稳定,宿州、周口、徐州、蚌埠4个城市位于用水空间关联网络的核心地位,主导着网络中水资源的流动;块模型分析表明,用水空间关联网络可划分为经纪人、双向溢出、主受益、净收益4个板块,板块之间的空间溢出效应呈现出链条状的趋势;地理位置临近性、人均水资源量以及城镇化率是用水空间关联网络形成的重要影响因素。研究结果对提升区域间水资源交换效率,缓解缺水地区水资源困境具有战略意义。
英文摘要:
      Under the background of water scarcity, the water use relationship between adjacent regions presents more and more complex correlation characteristics. Clarifying the internal water use relationship among regions and revealing the spatial linkage pattern of water use can provide a reliable reference for optimizing the coordinated governance policy of regional water resources. Based on the relevant water use data of 28 cities in the Huaihe River Eco-economic Belt from 2005 to 2018, social network analysis (SNA) was used to describe the structure and transfer characteristics of water use spatial association network among cities in the Huaihe River Eco-economic Belt, and its influencing factors were revealed by quadratic assignment procedure (QAP). The results show that the water use relationships among the cities in the Huaihe River Eco-economic Belt presented a complex network structure. The network density decreased slightly during the sample investigation period, but the overall network structure was stable. Cities of Suzhou, Zhoukou, Xuzhou and Bengbu were at the core of the water use network, leading the flow of water resources in the related network. The block model analysis showed that the spatial correlation network of water use could be divided into four modules, namely broker, two-way spillover, main beneficiary and net beneficiary, and the spatial spillover effect between modules showed a chain-like trend. Geographical spatial proximity, per capita water resources and urbanization rate were important factors affecting the formation of water spatial correlation network. The research results are of strategic significance to the promotion of water resources exchange efficiency among regions and alleviation of water resources dilemma in water shortage areas.
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