新疆水资源与农业种植系统耦合协调及时空差异研究——以粮食和棉花种植系统为例

doi:10.12118/j.issn.1000-6060.2022.315

Abstract

Abstract:

This study takes the grain and cotton cropping systems as an example to measure the development level of the water resource and agricultural cropping systems in Xinjiang, China to study its water resource endowment and agriculture industry development, respectively. Additionally, the two systems are combined to further analyze the coupling coordination and spatiotemporal differences of the water resources-agriculture cropping composite system (abbreviated composite system) in Xinjiang. Therefore, data related to water resources and agriculture cropping of 14 prefectures in Xinjiang from 2005 to 2019 were selected to measure the comprehensive development index of water resources, agriculture cropping, and composite systems using the entropy method. On the basis of the comprehensive development index of the composite system, this study further explores the coupling coordination trend and spatiotemporal evolution law of the composite system using the coupling coordination degree model and exploratory spatial data analysis, respectively. The following results are presented. (1) The comprehensive development index of the composite system in Xinjiang is spatially characterized by “high in the middle and low on both sides”. Among them, the level of comprehensive development index of the water resources system is higher than that of the agriculture cropping system and the growth trend of the agricultural plantation system is fast. Comparing the results of the composite development index of water resources and agriculture cropping systems from 2005 to 2019, this study found that the former has been developing at a higher level than the latter during the study period. However, the latter showed a faster growth trend than the former, resulting in a gradual reduction in the gap between the two systems. (2) The overall level of coupling coordination of composite systems in Xinjiang shows a development trend of “high in the north and low in the south, but the gap is gradually decreasing”. Additionally, the agriculture cropping system has gradually become a shortcoming that hinders the development of the coupling coordination of composite systems due to the differences among regions. (3) A significant spatial clustering characteristic of the coupling coordination degree of the composite system is also observed in Xinjiang, but its positive correlation shows a changing trend from strong to weak. The spatial clustering type is mainly “high-high and low-low” clustering, and the coupling coordination degree of the composite system shows spillover effects and is easily influenced by the neighboring areas. The results of this study have theoretical and practical implications for the sustainable use of water resources, the development of the agriculture cropping industry, and the benign coordination of the two in Xinjiang.

Key words: water resources-agriculture cropping composite system, coupling coordination degree, exploratory spatial data analysis, spatiotemporal differences, Xinjiang

ZHANG Ning,WANG Zichen,YANG Xiao,CHEN Tong,XING Fei. Coupling coordination and spatiotemporal differences between water resources and agriculture cropping system in Xinjiang: A case of grain and cotton cropping systems[J].Arid Land Geography, 2023, 46(3): 349-359.

Figures/Tables 9

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References 21

[1]	雒新萍, 刘晓洁. 中国典型农作物需水量及生产水足迹区域差异[J]. 节水灌溉, 2020(1): 88-93.
	[ Luo Xinping, Liu Xiaojie. Regional differences on typical crop water requirement and water footprint in China from a production perspective[J]. Water Saving Irrigation, 2020(1): 88-93. ]
[2]	郎婷婷, 郝蒙蒙, 吴风华, 等. 基于DSSAT模型的京津冀地区主要农作物用水分析[J]. 干旱地区农业研究, 2019, 37(5): 235-242, 248.
	[ Lang Tingting, Hao Mengmeng, Wu Fenghua, et al. Study on water requirements of major crops in Beijing-Tianjin-Hebei region using DSSAT model[J]. Agricultural Research in the Arid Areas, 2019, 37(5): 235-242, 248. ]
[3]	金涛. 中国粮食作物种植结构调整及其水土资源利用效应[J]. 自然资源学报, 2019, 34(1): 14-25. doi: 10.31497/zrzyxb.20190102
	[ Jin Tao. The adjustment of China’s grain cropping structure and its effect on the consumption of water and land resources[J]. Journal of Natural Resources, 2019, 34(1): 14-25. ] doi: 10.31497/zrzyxb.20190102
[4]	张家欣, 邓铭江, 李鹏, 等. 虚拟水流视角下西北地区农业水资源安全格局与调控[J]. 中国工程科学, 2022, 24(1): 131-140.
	[ Zhang Jiaxin, Deng Mingjiang, Li Peng, et al. Security pattern and regulation of agricultural water resources in northwest China from the perspective of virtual water flow[J]. Strategic Study of CAE, 2022, 24(1): 131-140. ]
[5]	吴勇, 张赓, 陈广锋, 等. 中国节水农业成效、形势机遇与展望[J]. 中国农业资源与区划, 2021, 42(11): 1-6.
	[ Wu Yong, Zhang Geng, Chen Guangfeng, et al. Achievements, situation and opportunities of water saving agricultural in China and projections for future development[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2021, 42(11): 1-6. ]
[6]	方芳, 马琼. 虚拟水价值视角下新疆主要农作物种植偏好及布局研究[J]. 节水灌溉, 2019, 44(7): 95-100.
	[ Fang Fang, Ma Qiong. Study on planting preference and layout of main crops in Xinjiang from the perspective of virtual water value[J]. Water Saving Irrigation, 2019, 44(7): 95-100. ]
[7]	许航, 李韬, 宋健峰. 旱区农业灌溉用水反弹效应及其区域差异——以西北五省(区)为例[J]. 资源科学, 2021, 43(9): 1808-1820. doi: 10.18402/resci.2021.09.08
	[ Xu Hang, Li Tao, Song Jianfeng. Estimation, driving factors, and regional differences of agricultural irrigation water rebound effect in arid areas: Examples of five provinces in northwestern China[J]. Resources Science, 2021, 43(9): 1808-1820. ] doi: 10.18402/resci.2021.09.08
[8]	孙才志, 张灿灿, 郜晓雯. 中国“四化”建设对水足迹强度的影响分析[J]. 自然资源学报, 2020, 35(4): 767-778. doi: 10.31497/zrzyxb.20200402
	[ Sun Caizhi, Zhang Cancan, Gao Xiaowen. Impact of China’s “four modernizations” on water footprint intensity[J]. Journal of Natural Resources, 2020, 35(4): 767-778. ] doi: 10.31497/zrzyxb.20200402
[9]	杨晶. 乡村振兴战略推进下农业水资源节水激励机制研究[J]. 农业经济, 2020, 40(7): 12-14.
	[ Yang Jing. Study on the incentive mechanism of agricultural water resources saving under the promotion of rural revitalization strategy[J]. Agricultural Economy, 2020, 40(7): 12-14. ]
[10]	罗巍, 杨玄酯, 杨永芳, 等. 黄河流域水-能源-粮食纽带关系协同演化及预测[J]. 资源科学, 2022, 44(3): 608-619. doi: 10.18402/resci.2022.03.14
	[ Luo Wei, Yang Xuanzhi, Yang Yongfang, et al. Co-evolution of water-energy-food nexus in the Yellow River Basin and forecast of future development[J]. Resources Science, 2022, 44(3): 608-619. ] doi: 10.18402/resci.2022.03.14
[11]	李鸿飞, 何颖茹, 毕晓莉. 黄河流域兰州段生态环境与高质量发展耦合协调关系研究[J]. 干旱区地理, 2022, 45(4): 1244-1253.
	[ Li Hongfei, He Yingru, Bi Xiaoli. Coupling coordination relationship between ecological environment and high-quality development in Lanzhou section of Yellow River Basin[J]. Arid Land Geography, 2022, 45(4): 1244-1253. ]
[12]	赵胡兰, 杨兆萍, 韩芳, 等. 新疆旅游产业—经济发展—生态环境耦合态势分析及预测[J]. 干旱区地理, 2020, 43(4): 1146-1154.
	[ Zhao Hulan, Yang Zhaoping, Han Fang, et al. Analysis and forecast of coupling situation among tourism industry-economic development-ecological environment in Xinjiang[J]. Arid Land Geography, 2020, 43(4): 1146-1154. ]
[13]	金梦婷, 徐丽萍, 李鹏辉. 南北疆区域经济差异化三维生态足迹自然资本利用的时空演变[J]. 生态学报, 2020, 40(13): 4327-4339.
	[ Jin Mengting, Xu Liping, Li Penghui. Spatial and temporal evolution of natural capital utilization in the three-dimensional ecological footprint under the regional economic differentiation in north and south Xinjiang[J]. Acta Ecologica Sinica, 2020, 40(13): 4327-4339. ]
[14]	D’Odorico P, Davis K F, Rosa L. The global food-energy-water nexus[J]. Reviews of Geophysics, 2018, 56(3): 456-531. doi: 10.1029/2017RG000591
[15]	尚杰, 于浩然, 杨旭. 农业用水效率时空差异与影响因素分析[J]. 中国农业科技导报, 2022, 24(3): 11-19. doi: 10.13304/j.nykjdb.2021.0346
	[ Shang Jie, Yu Haoran, Yang Xu. Spatial temporal differences and influencing factors of agricultural water use efficiency[J]. Journal of Agricultural Science and Technology, 2022, 24(3): 11-19. ] doi: 10.13304/j.nykjdb.2021.0346
[16]	刘楚杰, 李晓云, 聂媛. 基于重心模型的粮食生产与水资源时空耦合分析[J]. 农业现代化研究, 2021, 42(6): 1026-1036.
	[ Liu Chujie, Li Xiaoyun, Nie Yuan. The spatio-temporal coupling analysis of grain production and water resources based on the barycenter model[J]. Research of Agricultural Modernization, 2021, 42(6): 1026-1036. ]
[17]	张继红, 刘云鹤, 王全九, 等. 典型作物Logistic模型生长参数空间分布及其地区水热相关性[J]. 干旱地区农业研究, 2021, 39(5): 199-209.
	[ Zhang Jihong, Liu Yunhe, Wang Quanjiu, et al. Typical crops’ spatial variability of Logistic model parameters and its correlation with regional water and heat[J]. Agricultural Research in the Arid Areas, 2021, 39(5): 199-209. ]
[18]	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. doi: 10.13249/j.cnki.sgs.2018.05.009
	[ Zhao Xueyan, Gao Zhiyu, Ma Yanyan, 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. ] doi: 10.13249/j.cnki.sgs.2018.05.009
[19]	屠爽爽, 郑瑜晗, 龙花楼, 等. 乡村发展与重构格局特征及振兴路径——以广西为例[J]. 地理学报, 2020, 75(2): 365-381. doi: 10.11821/dlxb202002011
	[ Tu Shuangshuang, Zheng Yuhan, Long Hualou, et al. Spatio-temporal pattern of rural development and restructuring and regional path of rural vitalization in Guangxi, China[J]. Scientia Geographica Sinica, 2020, 75(2): 365-381. ] doi: 10.11821/dlxb202002011
[20]	田丰, 武建军, 刘雷震, 等. 1901—2015年华北平原干旱时空转移特征及热点区域探测[J]. 干旱区资源与环境, 2020, 34(6): 87-96.
	[ Tian Feng, Wu Jianjun, Liu Leizhen, et al. Spatiotemporal transferring characteristics of drought and its hotpots detection in North China Plain during 1901—2015[J]. Journal of Arid Land Resources and Environment, 2020, 34(6): 87-96. ]
[21]	徐依婷, 穆月英, 侯玲玲. 水资源稀缺性、灌溉技术采用与节水效应[J]. 农业技术经济, 2022, 41(2): 47-61.
	[ Xu Yiting, Mu Yueying, Hou Lingling. Water scarcity, adoption of irrigation technologies and water conservation[J]. Journal of Agrotechnical Economics, 2022, 41(2): 47-61. ]

子系统	一级指标	二级指标	数据来源	属性	权重
水资源	水资源禀赋	人均水资源量/m³	统计年鉴获取	+	0.13
	水资源禀赋	人均用水量/m³	统计年鉴获取	-	0.09
	水资源利用	第一产业用水占比/%	第一产业用水量/总用水量	-	0.12
		生活用水占比/%	生活用水量/总用水量	+	0.10
		生态环境用水占比/%	生态环境用水量/总用水量	+	0.11
		万元GDP用水量/m³·(10⁴元)^-1	地区GDP/总用水量	-	0.12
		地下水供水占比/%	地下水供水量/总用水量	-	0.11
		中水利用量/10⁹ m³	统计年鉴获取	+	0.09
		水资源开发利用率/%	总用水量/水资源总量	-	0.12
农业种植	种植投入	第一产业固定资产投资/10⁴元	统计年鉴获取	+	0.10
		化肥施用强度/t·hm^-2	化肥施用量/耕地面积	-	0.10
		劳均农作物播种面积/hm²·人^-1	农作物播种面积/农业从业人员数	+	0.12
		农业机械化水平/kW·hm^-2	农业机械化总动力/耕地面积	+	0.11
		有效灌溉面积/10³ hm²	统计年鉴获取	+	0.12
		水土流失治理面积/10³ hm²	统计年鉴获取	+	0.09
	种植产出	劳均农业总产值/10⁴元·人^-1	农业总产值/农业从业人员数	+	0.13
		单位面积粮食产量/kg·hm^-2	统计年鉴获取	+	0.13
		单位面积棉花产量/kg·hm^-2	统计年鉴获取	+	0.11

协调程度	耦合协调度（D）	协调适配阶段
失调衰退区间	[0.0, 0.1]	极度失调衰退
	(0.1, 0.2]	严重失调衰退
	(0.2, 0.3]	中度失调衰退
	(0.3, 0.4]	轻度失调衰退
协调过渡区间	(0.4, 0.5]	濒临失调衰退
	(0.5, 0.6]	勉强协调发展
协调发展区间	(0.6, 0.7]	初级协调发展
	(0.7, 0.8]	中级协调发展
	(0.8, 0.9]	良好协调发展
	(0.9, 1.0]	优质协调发展

年份	Moran’s I	P值	Z值	sd
2005	0.419	0.010	2.894	0.173
2006	0.348	0.018	2.471	0.173
2007	0.288	0.031	1.971	0.171
2008	0.235	0.032	1.977	0.169
2009	0.280	0.030	2.127	0.171
2010	0.257	0.032	1.997	0.171
2011	0.334	0.016	2.465	0.169
2012	0.258	0.040	2.030	0.167
2013	0.236	0.040	1.973	0.163
2014	0.312	0.018	2.362	0.165
2015	0.300	0.022	2.365	0.161
2016	0.287	0.020	2.301	0.160
2017	0.326	0.018	2.461	0.165
2018	0.322	0.023	2.102	0.166
2019	0.311	0.016	2.357	0.165

Coupling coordination and spatiotemporal differences between water resources and agriculture cropping system in Xinjiang: A case of grain and cotton cropping systems

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