新一轮东北振兴背景下的辽宁省水资源利用效率及其空间关联格局研究

doi:10.18402/resci.2016.07.14

摘要/Abstract

摘要：

水足迹从消费角度建立了水资源利用与人类消费模式的联系,衡量人类对水资源系统的直接占用,是当前测度人类生活和生产活动对水资源生态环境系统影响的最有效的指标之一。本文基于2004-2013年辽宁省14个城市的水足迹面板数据,利用随机前沿分析SFA和数据包络分析SBM方法分别计算了辽宁省14个城市的水资源利用绝对效率和相对效率;通过基尼系数和变异系数来分析水资源效率的动态变化结果显示水资源利用效率差异在不断缩小,且有收敛趋势;借助核密度估计模型,分析了水资源利用效率的动态演变规律。结果表明,近10年间,沈阳、大连、鞍山及盘锦的水资源绝对效率和相对效率水平均较高,阜新和朝阳绝对效率和相对效率均位于全省最低水平;地理位置分布整体呈现中部内陆至南部沿海向东西两侧逐渐递减的特征;辽宁省水资源利用相对效率处在逐渐提高的状态,各城市相对效率值差距在不断缩小。利用聚类分析对水资源利用效率进行时空分异研究,构建了空间权重矩阵,显示辽宁省水资源利用效率存在空间自相关关系;空间集聚分析显示,高高集聚区域主要分布在辽宁省经济水平相对发达的城市,如大连、鞍山、盘锦等地区;低低集聚主要集中在经济欠发达的城市,如阜新、朝阳、葫芦岛;高低集聚和低高集聚一般分布在高高集聚和低低集聚之间。因此,可以通过提高低低集聚地区的水资源利用效率促进提高周围地区水资源利用效率,有利于辽宁省水资源利用效率的整体提高。

关键词: 水足迹, SFA, SBM, 水资源利用效率, 空间自相关, 辽宁

Abstract:

Water footprint from the perspective of consumption has established the water resource utilization and human consumption patterns,it measures water resources system of human occupied directly and it is one of the most effective indicators to measure the impact of human life and production activities on the water resources ecological environment system currently. Based on panel date for water footprints of 14 cities in Liaoning province from 2004 to 2013. We then established the water resources utilization absolute and relative efficiency of every city in using stochastic frontier analysis,date envelopment analysis modeling,the Gini coefficient and variable coefficient. We found that the difference reduced and converged for water resource utilization efficiency. The water resource utilization absolute and relative efficiency of Shenyang,Dalian,Anshan and Panjin are on a higher level,while Fuxin and Chaoyang are the lowest. The characteristic of geographical location is distributed across the central inland to southern coastal region and spreads east and west,gradually diminishing in entirety. The water resources utilization relative efficiency of Liaoning is in state of a gradual increase,the gap in water resource utilization absolute efficiency of every city is shrinking. Using cluster analysis to study the spatial-temporal differentiation of water resource utilization efficiency,based on the spatial weighting matrix,we found spatial autocorrelation of water resources utilization efficiency. High-high correlation pattern areas are mainly distributed at the economic level in relatively developed cities in Liaoning,such as Dalian,Anshan,Panjin and other regions. Low-low correlation pattern areas tended to be less developed cities,such as Fuxin,Chaoyang and Huludao. High-low and low-high correlation pattern areas occur between high-high and low-low correlation pattern areas. Enhancing the water resource utilization efficiency of low-low correlation pattern areas will promote the water resource utilization efficiency of surrounding areas,and this is conducive to increasing the overall water resource utilization efficiency across Liaoning.

Key words: water footprint, SFA, SBM, water resources utilization efficiency, spatial auto-correlation, Liaoning

盖美, 吴慧歌, 曲本亮. 新一轮东北振兴背景下的辽宁省水资源利用效率及其空间关联格局研究[J]. 资源科学, 2016, 38(7): 1336-1349.

GAI Mei,WU Huige,QU Benliang. Water resource utilization efficiency and disparities in spatial correlation pattern research in Liaoning under the background of new round revitalization of Northeast China[J]. Resources Science, 2016, 38(7): 1336-1349.

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	农畜产品水足迹	工业水足迹	生活水足迹	生态水足迹	总水足迹
沈阳	38.114	3.099	6.374	1.696	49.283
大连	30.470	3.993	3.254	0.675	38.392
鞍山	18.271	3.084	1.775	0.064	23.194
抚顺	11.901	2.133	1.493	0.276	15.803
本溪	8.365	2.231	0.833	0.118	11.547
丹东	12.452	1.168	0.991	0.034	14.645
锦州	15.764	1.387	1.147	0.028	18.326
营口	12.002	0.834	0.977	0.016	13.829
阜新	9.891	0.774	0.745	0.072	11.482
辽阳	9.416	1.941	1.141	0.013	12.511
盘锦	6.711	0.683	0.709	0.018	8.121
铁岭	15.401	0.944	0.946	0.024	17.315
朝阳	17.023	0.952	0.962	0.068	19.005
葫芦岛	14.078	0.792	0.991	0.023	15.884
辽宁省	219.859	24.015	22.338	3.125	269.337

年份	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	平均值
沈阳	0.852 7	0.854 2	0.855 7	0.857 1	0.858 6	0.860 0	0.861 4	0.862 8	0.864 2	0.865 6	0.859 2
大连	0.986 2	0.986 4	0.986 5	0.986 6	0.986 8	0.986 9	0.987 0	0.987 2	0.987 3	0.987 4	0.986 8
鞍山	0.975 7	0.975 9	0.976 2	0.976 4	0.976 6	0.976 9	0.977 1	0.977 3	0.977 6	0.977 8	0.976 7
抚顺	0.455 2	0.460 7	0.466 1	0.471 5	0.476 8	0.482 1	0.487 3	0.492 5	0.497 6	0.502 6	0.479 2
本溪	0.428 4	0.434 2	0.439 9	0.445 5	0.451 1	0.456 6	0.462 1	0.467 5	0.472 9	0.478 2	0.453 6
丹东	0.377 7	0.384 0	0.390 2	0.396 4	0.402 4	0.408 4	0.414 4	0.420 3	0.426 1	0.431 9	0.405 2
锦州	0.400 4	0.406 4	0.412 4	0.418 3	0.424 2	0.430 0	0.435 7	0.441 4	0.447 0	0.452 6	0.426 8
营口	0.453 4	0.458 9	0.464 4	0.469 8	0.475 1	0.480 4	0.485 6	0.490 8	0.495 9	0.501 0	0.477 6
阜新	0.168 2	0.176 5	0.184 8	0.193 0	0.201 2	0.209 2	0.217 2	0.225 0	0.232 8	0.240 6	0.204 8
辽阳	0.426 6	0.432 4	0.438 1	0.443 8	0.449 4	0.454 9	0.460 4	0.465 8	0.471 2	0.476 5	0.451 9
盘锦	0.961 1	0.963 1	0.964 4	0.968 2	0.970 1	0.971 4	0.980 5	0.985 4	0.987 8	0.988 9	0.974 1
铁岭	0.334 1	0.340 8	0.347 4	0.354 0	0.360 5	0.366 9	0.373 3	0.379 6	0.385 9	0.392 1	0.363 5
朝阳	0.180 4	0.188 7	0.196 9	0.204 9	0.212 9	0.220 9	0.228 7	0.236 5	0.244 2	0.251 8	0.216 6
葫芦岛	0.309 0	0.315 9	0.322 8	0.329 6	0.336 4	0.343 1	0.349 7	0.356 2	0.362 7	0.369 1	0.339 4

估计变量	系数	标准差	t统计值
β₀	-35.708 4	6.734 6	-5.302 2
β₁	0.003 4	0.001 3	2.525 2***
β₂	0.045 9	0.115 2	0.398 3**
β₃	0.017 7	0.000 7	26.197 2*
σ²	5 686.339 5	0.121 0	4.442 4
γ	0.961 7	0.010 9	88.394 0***
η	0.010 1	0.007 0	1.444 3***
对数似然函数		-608.097 6
单边似然比检验		159.532 7

年份	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	平均值
沈阳	0.808 8	0.768 9	0.695 2	0.761 0	0.784 8	0.795 6	0.859 9	1.000 0	1.000 0	1.000 0	0.847 4
大连	1.000 0	0.993 3	1.000 0	1.000 0	1.000 0	1.000 0	1.000 0	1.000 0	1.000 0	1.000 0	0.999 3
鞍山	1.000 0	1.000 0	1.000 0	1.000 0	1.000 0	1.000 0	1.000 0	1.000 0	0.995 2	1.000 0	0.999 5
抚顺	0.604 1	0.569 4	0.565 6	0.597 2	0.637 0	0.626 0	0.647 8	0.673 4	0.655 1	0.673 2	0.624 9
本溪	0.578 1	0.564 7	0.582 9	0.622 8	0.634 1	0.642 5	0.658 5	0.677 8	0.664 3	0.662 6	0.628 8
丹东	0.526 4	0.524 4	0.536 2	0.561 3	0.547 1	0.548 1	0.552 1	0.557 5	0.552 8	0.561 2	0.546 7
锦州	0.516 2	0.527 4	0.488 8	0.499 6	0.527 5	0.541 3	0.570 4	0.558 4	0.527 6	0.529 4	0.528 7
营口	0.627 6	0.592 6	0.625 0	0.557 5	0.544 6	0.545 0	0.586 6	0.593 1	0.607 5	0.668 5	0.594 8
阜新	0.307 6	0.340 7	0.279 7	0.3281	0.315 6	0.345 7	0.364 8	0.378 4	0.360 3	0.379 9	0.340 1
辽阳	0.623 1	0.553 4	0.561 2	0.615 0	0.629 4	0.615 2	0.631 2	0.648 0	0.617 4	0.650 7	0.614 5
盘锦	1.000 0	0.874 4	0.855 4	0.860 4	0.766 9	0.790 9	1.000 0	0.968 8	0.962 9	1.000 0	0.908 0
铁岭	0.466 3	0.444 5	0.425 4	0.451 1	0.443 2	0.434 1	0.428 4	0.444 1	0.443 2	0.448 6	0.442 9
朝阳	0.207 6	0.244 7	0.211 4	0.226 9	0.243 5	0.251 0	0.266 4	0.268 3	0.260 1	0.267 9	0.280 5
葫芦岛	0.418 6	0.499 1	0.467 3	0.456 7	0.454 6	0.450 5	0.478 5	0.477 1	0.456 3	0.454 0	0.461 3

年份	SFA			年份	SBM
年份	Moran’s I		Z（I）	P	Moran’s I	Z（I）	P
2004	0.130 3	1.114 9	0.132 4	2004	0.189 8	1.437 5	0.075 5
2005	0.130 4	1.115 2	0.132 4	2005	0.236 5	1.688 4	0.045 7
2006	0.130 5	1.115 9	0.132 2	2006	0.346 2	2.279 9	0.011 3
2007	0.130 8	0.117 4	0.131 9	2007	0.273 1	1.885 2	0.029 7
2008	0.131 3	1.120 1	0.131 3	2008	0.241 3	1.714 6	0.043 2
2009	0.131 4	0.120 4	0.131 3	2009	0.226 6	1.634 6	0.051 1
2010	0.131 4	1.120 8	0.131 2	2010	0.190 6	1.439 5	0.075 0
2011	0.131 6	1.121 8	0.131 0	2011	0.147 2	1.205 2	0.114 1
2012	0.131 7	1.122 0	0.130 9	2012	0.167 8	1.300 0	0.096 8
2013	0.131 8	1.122 5	0.130 8	2013	0.214 7	1.568 4	0.058 4