中国农业水贫困评价及时空特征分析
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摘要
本文以提高农业用水有效性为指导思想,提出"农业水贫困"概念,基于农业水贫困概念界定和评价指标体系构建的基础上,利用POME-两级模糊模式识别模型测度2000—2016年中国30个省(市)农业水贫困指数,借助探索性时空数据分析(ESTDA),从时空耦合视角分析其空间格局动态性。研究发现:中国虽然存在较严重的农业水贫困问题,但是大部分省(市)的农业水贫困程度呈缓解趋势;各省(市)大部分年份的农业水贫困具有显著的空间负相关性,空间差异呈逐渐扩大趋势;相对于西南地区,华南地区和华东地区具有更加动态的局部空间结构;东北地区和西北地区的时空依赖效应较弱;农业水贫困空间格局具有较强的空间整合性,协同高增长的省(市)主要分布在华东地区和华南地区,协同低增长的省(市)主要分布在北部地区;各省(市)农业水贫困的局部空间联动性较弱,空间集聚性存在相对较高的路径锁定特征。此外,提出了降低农业水贫困的对策建议,为中国农业水资源管理和可持续发展提供借鉴。
In this paper, the concept of "agricultural water poverty" is put forward under the guided by the idea of improving the efficiency of water use in agriculture. Based on the conceptual definition and evaluation index system of agricultural water poverty, the POME-two-level fuzzy pattern recognition model was used to evaluate the agricultural water poverty index of 30 provinces(cities) in China from 2000 to 2016 under the common constraints of existing water resource endowment, water supply facilities, water resource use, ecological environment and social economy, education and people's life. Then calculated by Exploratory Time-space Data Analysis(ESTDA) to analysis its dynamic spatial and temporal pattern from the perspective of time and space coupling. The results show that: Although China has a serious problem of agricultural water poverty, the degree of agricultural water poverty in most provinces(cities) is alleviating. The agricultural water poverty of provinces(cities) in most years has a significant spatial negative correlation, and the spatial difference is gradually expanding. Compared with the southwest region,south China and east China have more dynamic local spatial structure. The spatial and temporal dependence is weak in northeast and northwest China. The spatial pattern of agricultural water poverty has strong spatial integration, the provinces(cities) that showed the same trend increased are mainly distributed in East China and South China, and the provinces(cities) that showed the same trend decreased are mainly distributed in the northern regions. The local spatial linkage of agricultural water poverty in provinces(cities) is relatively weak, and the spatial clustering has relatively high path-locking characteristics. In addition, the countermeasures and suggestions for reducing agricultural water poverty are put forward to provide reference for China's agricultural water resources management and sustainable development.
In this paper, the concept of "agricultural water poverty" is put forward under the guided by the idea of improving the efficiency of water use in agriculture. Based on the conceptual definition and evaluation index system of agricultural water poverty, the POME-two-level fuzzy pattern recognition model was used to evaluate the agricultural water poverty index of 30 provinces(cities) in China from 2000 to 2016 under the common constraints of existing water resource endowment, water supply facilities, water resource use, ecological environment and social economy, education and people's life. Then calculated by Exploratory Time-space Data Analysis(ESTDA) to analysis its dynamic spatial and temporal pattern from the perspective of time and space coupling. The results show that: Although China has a serious problem of agricultural water poverty, the degree of agricultural water poverty in most provinces(cities) is alleviating. The agricultural water poverty of provinces(cities) in most years has a significant spatial negative correlation, and the spatial difference is gradually expanding. Compared with the southwest region,south China and east China have more dynamic local spatial structure. The spatial and temporal dependence is weak in northeast and northwest China. The spatial pattern of agricultural water poverty has strong spatial integration, the provinces(cities) that showed the same trend increased are mainly distributed in East China and South China, and the provinces(cities) that showed the same trend decreased are mainly distributed in the northern regions. The local spatial linkage of agricultural water poverty in provinces(cities) is relatively weak, and the spatial clustering has relatively high path-locking characteristics. In addition, the countermeasures and suggestions for reducing agricultural water poverty are put forward to provide reference for China's agricultural water resources management and sustainable development.
引文
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[17]赵雪雁,高志玉,马艳艳,等.2005~2014年中国农村水贫困与农业现代化的时空耦合研究[J].地理科学,2018,38(5):717-726.[Zhao X Y,Gao Z Y,Ma Y Y,et al.Spatio-temporal coupling between rural water poverty and agricultural modernization in China from 2005 to 2014[J].Scientia Geographica Sinica,2018,38(5):717-726.]
[18]Forouzani M,Karami E.Agricultural water poverty index and sustainability[J].Agronomy for Sustainable Development,2011,31(2):415-431.
[19]中华人民共和国国家统计局.中国统计年鉴[M].北京:中国统计出版社,2001-2017.[National Bureau of Statistics of China.China Statistical Yearbook[M].Beijing:China Statistics Press,2001-2017.]
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[24]杨羽頔,孙才志.环渤海地区陆海统筹度评价与时空差异分析[J].资源科学,2014,36(4):691-701.[Yang Y D,Sun C Z.Assessment of land-sea coordination in the Bohai Sea Ring Area and spatial-temporal differences[J].Resources Science,2014,36(4):691-701.]
[25]Jaynes E T.Information theory and statistical mechanics[J].Physical Review,1957,106(4):620-630.
[26]陈守煜,于雪峰.相对隶属度与两级模糊识别模型及其在水工评价中应用[J].大连理工大学学报,2004(2):288-291.[Chen SY.Relative membership degree and new two-level fuzzy pattern recognition model and their application to hydraulic engineering[J].Journal of Dalian University of Technology,2004(2):288-291.]
[27]关伟,张华,许淑婷.基于DEA-ESDA模型的辽宁省能源效率测度及时空格局演化分析[J].资源科学,2015,37(4):764-773.[Guan W,Zhang H,Xu S T.Spatial and temporal pattern evolution of energy efficiency in Liaoning Based on the DEA-ESDAModel[J].Resources Science,2015,37(4):764-773.]
[28]Ye X Y,Rey S J.A framework for exploratory space-time analysis of economic data[J].The Annals of Regional Science,2013,50(1):315-339.
[29]高长春,刘贤赵,李朝奎,等.近20年来中国能源消费碳排放时空格局动态[J].地理科学进展,2016,35(6):747-757.[Gao C C,Liu X Z,Li C K,et al.Spatiotemporal dynamics of emissions by energy consumption in China from 1995 to 2014[J].Progress in Geography,2016,35(6):747-757.]
[30]Rey S J,Ye X Y.Comparative Spatial Dynamics of Regional Systems[A].Páez A,Gallo J,Buliung R N,et al.Progress in Spatial Analysis:Methods and Applications[M].Berlin:Springer,2010.
[31]Rey S J.Spatial empirics for economic growth and convergence[J].Geographical Analysis,2001,33(3):195-214.
[32]Mehta L.The manufacture of popular perceptions of scarcity:dams and water-related narratives in Gujarat,India[J].World Development,2004,29(12):2025-2041.
[33]Noemdoe S,Jonker L,Swatuk L A.Perceptions of water scarcity:the case of Genadendal and outstations[J].Physics&Chemistry of the Earth,2006,31(15):771-778.
[34]Rey S J,Murray,A T,Anselin L.Visualizing regional income distribution dynamics[J].Letters in Spatial and Resource Sciences,2011,4(1):81-90.
[2]Sullivan Caroline.The water poverty index:development and application at the community scale[J].Natural Resources Forum,2003,27(3):189-199.
[3]Adkins P,Dyck L.Canadian Water Sustainability Index[R].Otta-411wa:Project Report,2007.
[4]GinéGarriga R,Pérez Foguet A,Molina J L,et al.Application of Bayesian networks to assess water poverty[C]//II International Conference on Sustainability Measurement and Modelling.Centro Internacional de Métodos Numéricos en Ingeniería(CIMNE),2009.
[5]Lawrence P R,Meigh J,Sullivan C.The water poverty index:an international comparison[M].Keele,Straffordshire,UK:Department of Economics,Keele University,2002.
[6]Nadeem A M,Cheo R,Huang S.Multidimensional analysis of water poverty and subjective well-being:a case study on local household variation in Faisalabad,Pakistan[J].Social Indicators Research,2018,138(2):1-18.
[7]Jemmali H.Mapping water poverty in Africa using the improved multidimensional index of water poverty[J].International Journal of Water Resources Development,2017,33(4):1-18.
[8]Jemmali H.Water poverty in Africa:a review and synthesis of issues,potentials,and policy implications[J].Social Indicators Research,2018,136(1):335-358.
[9]曹建廷.水匮乏指数及其在水资源开发利用中的应用[J].中国水利,2005,(9):22-24.[Cao J T.Water poverty index:a concise tool to evaluate the progresses in water resource utilization[J].China Water Resources,2005,(9):22-24.]
[10]何栋材,徐中民,王广玉.水贫困测量及应用的国际研究进展[J].干旱区地理,2009,32(2):296-303.[He D C,Xu Z M,Wang G Y.Progresses in the international research on water poverty measure and application[J].Arid Land Geography,2009,32(2):296-303.]
[11]孙才志,王雪妮.基于WPI-ESDA模型的中国水贫困评价及空间关联格局分析[J].资源科学,2011,33(6):1072-1082.[Sun CZ,Wang X N.Research on the assessment and spatial correlation pattern of water poverty in China based on WPI-ESDA model[J].Resources Science,2011,33(6):1072-1082.]
[12]孙才志,王雪妮,邹玮.基于WPI-LSE模型的中国水贫困测度及空间驱动类型分析[J].经济地理,2012,32(3):9-15.[Sun CZ,Wang X N,Zou W.Measurement and spatial driving type analysis for water poverty in China based on WPI-LSE Model[J].Economic Geography,2012,32(3):9-15.]
[13]Sun C Z,Wu Y J,Zou W,et al.A rural water poverty analysis in China using the DPSIR-PLS model[J].Water Resources Management an International Journal Published for the European Water Resources Association,2018,32(6):1933-1951.
[14]王雪妮,孙才志,邹玮.中国水贫困与经济贫困空间耦合关系研究[J].中国软科学,2011,(12):180-192.[Wang X N,Sun C Z,Zou W.Coupling relation analysis between water poverty and economic poverty in China[J].China Soft Science,2011,(12):180-192.]
[15]孙才志,汤玮佳,邹玮.中国水贫困与城市化、工业化进程的协调关系研究[J].中国软科学,2013,(7):86-100.[Sun C Z,Tang W J,Zou W.Research on the coordinating relation among rural water poverty,urbanization and industrialization process in China[J].China soft Science,2013,(7):86-100.]
[16]杨玉蓉,谭勇,皮灿,等.湖南农村水贫困时空分异及其驱动机制[J].地域研究与开发,2014,33(1):23-27.[Yang Y R,Tan Y,Pi C,et al.Spatial-temporal pattern of rural water poverty and its driving factors in the Hilly Area of Hunan Province[J].Areal Research and Development,2014,33(1):23-27.]
[17]赵雪雁,高志玉,马艳艳,等.2005~2014年中国农村水贫困与农业现代化的时空耦合研究[J].地理科学,2018,38(5):717-726.[Zhao X Y,Gao Z Y,Ma Y Y,et al.Spatio-temporal coupling between rural water poverty and agricultural modernization in China from 2005 to 2014[J].Scientia Geographica Sinica,2018,38(5):717-726.]
[18]Forouzani M,Karami E.Agricultural water poverty index and sustainability[J].Agronomy for Sustainable Development,2011,31(2):415-431.
[19]中华人民共和国国家统计局.中国统计年鉴[M].北京:中国统计出版社,2001-2017.[National Bureau of Statistics of China.China Statistical Yearbook[M].Beijing:China Statistics Press,2001-2017.]
[20]中华人民共和国国家统计局.中国水利统计年鉴[M].北京:中国统计出版社,2001-2017.[National Bureau of Statistics of the People’s Republic of China.China water statistical yearbook[M].Beijing:China Statistics Press,2001-2017.]
[21]国家环境保护总局.中国环境统计年鉴[M].北京:中国统计出版社,2001-2017.[State Environmental Protection Administration.China Environment Year Book[M].Beijing:China Statistics Press,2001-2017.]
[22]国家统计局.中国区域经济统计年鉴[M].北京:中国统计出版社,2001-2017.[National Bureau of Statistics.China Statistical Yearbook for Regional Economy[M].Beijing:China Statistics Press,2001-2017.]
[23]中华人民共和国水利部.中国水资源公报[M].北京:中国水利水电出版社,2000-2016.[The Ministry of Water Resources.China Water Resources Bulletin[M].Beijing:China Water Conservancy and Hydropower Press,2000-2016.]
[24]杨羽頔,孙才志.环渤海地区陆海统筹度评价与时空差异分析[J].资源科学,2014,36(4):691-701.[Yang Y D,Sun C Z.Assessment of land-sea coordination in the Bohai Sea Ring Area and spatial-temporal differences[J].Resources Science,2014,36(4):691-701.]
[25]Jaynes E T.Information theory and statistical mechanics[J].Physical Review,1957,106(4):620-630.
[26]陈守煜,于雪峰.相对隶属度与两级模糊识别模型及其在水工评价中应用[J].大连理工大学学报,2004(2):288-291.[Chen SY.Relative membership degree and new two-level fuzzy pattern recognition model and their application to hydraulic engineering[J].Journal of Dalian University of Technology,2004(2):288-291.]
[27]关伟,张华,许淑婷.基于DEA-ESDA模型的辽宁省能源效率测度及时空格局演化分析[J].资源科学,2015,37(4):764-773.[Guan W,Zhang H,Xu S T.Spatial and temporal pattern evolution of energy efficiency in Liaoning Based on the DEA-ESDAModel[J].Resources Science,2015,37(4):764-773.]
[28]Ye X Y,Rey S J.A framework for exploratory space-time analysis of economic data[J].The Annals of Regional Science,2013,50(1):315-339.
[29]高长春,刘贤赵,李朝奎,等.近20年来中国能源消费碳排放时空格局动态[J].地理科学进展,2016,35(6):747-757.[Gao C C,Liu X Z,Li C K,et al.Spatiotemporal dynamics of emissions by energy consumption in China from 1995 to 2014[J].Progress in Geography,2016,35(6):747-757.]
[30]Rey S J,Ye X Y.Comparative Spatial Dynamics of Regional Systems[A].Páez A,Gallo J,Buliung R N,et al.Progress in Spatial Analysis:Methods and Applications[M].Berlin:Springer,2010.
[31]Rey S J.Spatial empirics for economic growth and convergence[J].Geographical Analysis,2001,33(3):195-214.
[32]Mehta L.The manufacture of popular perceptions of scarcity:dams and water-related narratives in Gujarat,India[J].World Development,2004,29(12):2025-2041.
[33]Noemdoe S,Jonker L,Swatuk L A.Perceptions of water scarcity:the case of Genadendal and outstations[J].Physics&Chemistry of the Earth,2006,31(15):771-778.
[34]Rey S J,Murray,A T,Anselin L.Visualizing regional income distribution dynamics[J].Letters in Spatial and Resource Sciences,2011,4(1):81-90.
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