长江经济带水资源消耗时空差异驱动效应研究

doi:10.18402/resci.2018.11.11

摘要/Abstract

摘要：

量化长江经济带水资源消耗时空差异的驱动效应,对双控行动的贯彻实施具有重要意义。本文采用LMDI方法,将用水量的时空差异分解为经济规模效应、产业结构效应和技术进步效应,用水强度的时空差异分解为产业结构效应和技术进步效应。结果显示：技术进步、产业结构调整是抑制用水量上升和促进用水强度下降的主次因素,而经济增长始终推动用水量上升;三次产业用水效率普遍提高和第一产业比重下降,有力促进了用水量和用水强度下降;与重庆相比,其他省份产业用水强度始终较大,尤其是第一、二产业,不利于用水量空间差异的缩小,长江三角洲省份产业结构更加高级缩小了用水量空间差异;与上海相比,其他省份第三产业用水强度始终较大和产业结构低级扩大了用水强度空间差异;水资源消耗时空差异之间存在相互转换的关系。因此,用水量控制应该围绕提高用水效率和优化产业结构,还需要辅助于经济、制度等手段,同时,根据三次产业特征差异而有所侧重;各省份选定参照对象后,依据空间差异驱动效应情况,提出适用的节水对策。

关键词: 长江经济带, 水资源消耗, 时空差异, 驱动效应, LMDI

Abstract:

Quantifying the driving effect of spatio-temporal difference in water consumption in the Yangtze River Economic Zone is of great significance to the implementation of the Double Control Actions. In this study, the LMDI method was used to decompose the spatio-temporal difference of water consumption into economic scale effect, industrial structure effect, and technical progress effect. The water intensity is decomposed into industrial structure effect and technical progress effect. The results illustrated that technical progress and adjustment of industrial structure are primary and secondary factors that inhibit the increase in water consumption and promote the reduction of water intensity, while economic growth has always pushed up water consumption. The general improvement of water efficiency in three industries and the decline of the proportion of the primary industry have strongly promoted the decline of water consumption and water intensity. Compared to Chongqing, the industrial water intensity of other provinces is always greater, especially the primary and secondary industries, which is not conductive to the narrowing of the spatial difference of water consumption. The more advanced industrial structure in the Yangtze River Delta Zone has reduced the spatial difference in water consumption. Compared to Shanghai, higher water intensity and low-level industrial structure of other provinces in tertiary industry enlarged the water intensity spatial difference. There is a mutual conversion relationship between the spatial and temporal difference of water consumption. Therefore, the control of water consumption should focus on the improvement of water efficiency and the optimization of industrial structure. At the same time, it should focus on the differences of three industrial characteristics. With selecting the reference object, each province should propose applicable water saving countermeasures according to the spatial difference driving effect.

Key words: Yangtze River Economic Zone, water resources consumption, spatio-temporal difference, driving effect, LMDI

张陈俊, 许静茹, 张丽娜, 庞庆华. 长江经济带水资源消耗时空差异驱动效应研究[J]. 资源科学, 2018, 40(11): 2247-2259.

Chenjun ZHANG, Jingru XU, Lina ZHANG, Qinghua PANG. Driving effect of spatial-temporal difference in water resource consumption in the Yangtze River Economic Zone[J]. Resources Science, 2018, 40(11): 2247-2259.

图/表 15

图1

图2

图3

图4

图5

图6

图7

图8

图9

图10

Table 1

Table 2

Table 3

Table 4

表5

用水总量时空差异的关系"

		$Δ W R 1 - R 0, t$	$Δ W R 1 - R 0, t - 1$	$Δ W R 1 - R 0, t$ - $Δ W R 1 - R 0, t - 1$
$Δ W t - 1, t ?; R 1$	103.00-108.38	25.10	52.05	-26.95
$Δ W t - 1, t ?; R 0$	77.90-56.33
$Δ W t - 1, t ?; R 1 - Δ W t - 1, t ?; R 0$	-26.95

表5

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组别	经济规模效应	产业结构效应	技术进步效应	总效应
上海-重庆	75.75→49.35	-31.59→-62.60	7.89→38.35	52.05→25.10
江苏-重庆	287.37→342.50	-13.99→-25.75	115.90→177.85	389.27→494.60
浙江-重庆	136.70→112.57	-17.97→-14.97	26.10→5.10	144.82→102.70
安徽-重庆	48.61→41.18	19.81→36.61	51.93→128.12	120.36→205.90
江西-重庆	12.72→-11.95	19.67→44.75	128.92→132.90	161.31→165.70
湖北-重庆	90.72→78.71	8.23→25.40	115.32→118.59	214.27→222.70
湖南-重庆	98.15→80.58	21.12→38.27	140.36→130.85	259.63→249.70
四川-重庆	88.49→91.58	17.53→39.32	46.19→51.60	152.20→182.50
贵州-重庆	-37.33→-63.10	11.46→24.39	53.71→57.62	27.83→18.90
云南-重庆	10.22→-23.83	13.35→41.82	67.21→51.91	90.78→69.90

组别	产业结构效应			技术进步效应
组别	第一产业	第二产业	第三产业	第一产业	第二产业	第三产业
上海-重庆	-38.68→-54.88	4.06→-21.25	3.03→13.53	18.91→32.45	3.45→27.14	-14.47→-21.24
江苏-重庆	-23.92→-23.26	13.56→-8.05	-3.63→5.56	123.29→127.22	-2.07→69.25	-5.32→-18.61
浙江-重庆	-23.90→-17.03	8.49→-7.56	-2.56→9.62	59.20→29.89	-26.91→-11.73	-6.19→-13.06
安徽-重庆	25.95→41.12	-4.81→-7.90	-1.33→3.38	50.41→71.39	3.12→53.67	-1.60→3.06
江西-重庆	26.77→48.08	-6.79→-2.61	-0.31→-0.72	100.36→86.31	25.19→35.58	3.37→11.01
湖北-重庆	10.77→28.53	-2.14→-10.62	-0.41→7.49	89.86→68.49	23.24→43.54	2.23→6.56
湖南-重庆	27.04→43.81	-5.82→-14.02	-0.10→8.48	121.10→85.84	9.23→44.88	10.03→0.13
四川-重庆	23.99→41.17	-5.43→-4.85	-1.03→3.00	44.31→44.62	1.45→1.06	0.43→5.92
贵州-重庆	16.02→28.06	-2.42→-10.20	-2.14→6.54	33.21→28.73	8.24→24.52	12.25→4.36
云南-重庆	15.57→44.00	-0.52→-6.41	-1.70→4.23	71.67→47.74	-8.80→3.22	4.34→0.94

组别	产业结构效应	技术进步效应	总效应
江苏-上海	250.97→73.88	42.82→-2.90	293.79→70.98
浙江-上海	172.71→40.90	-72.32→-30.03	100.39→10.87
安徽-上海	366.97→129.13	14.71→8.97	381.68→138.10
江西-上海	556.88→165.11	302.50→13.88	859.38→178.99
湖北-上海	359.65→104.00	176.44→5.77	536.09→109.77
湖南-上海	472.95→124.10	189.55→1.63	662.50→125.74
重庆-上海	115.96→42.19	-28.60→-25.62	87.36→16.58
四川-上海	303.46→96.63	0.24→-26.32	303.70→70.31
贵州-上海	405.70→121.94	184.30→2.81	589.99→124.75
云南-上海	444.39→138.11	59.91→-27.77	504.30→110.33

组别	产业结构效应			技术进步效应
组别	第一产业	第二产业	第三产业	第一产业	第二产业	第三产业
江苏-上海	246.55→63.92	18.89→15.35	-14.48→-5.39	26.98→-11.54	-17.25→3.59	33.09→5.05
浙江-上海	168.82→38.44	17.13→6.56	-13.24→-4.10	-3.50→-16.51	-96.37→-20.86	27.56→7.34
安徽-上海	415.92→122.70	-35.55→14.46	-13.40→-8.02	-30.00→-24.84	3.86→15.86	40.86→17.95
江西-上海	625.59→159.58	-55.59→17.39	-13.12→-11.86	105.10→-21.18	127.88→8.79	69.52→26.27
湖北-上海	397.27→100.16	-25.29→10.90	-12.33→-7.06	35.75→-22.69	81.01→7.02	59.67→21.45
湖南-上海	525.05→121.49	-38.14→8.21	-13.96→-5.59	70.60→-23.27	26.98→8.47	91.97→16.43
重庆-上海	139.79→37.43	-13.18→13.66	-10.66→-8.89	-68.36→-22.13	-11.19→-17.45	50.95→13.96
四川-上海	350.79→95.57	-34.32→9.84	-13.01→-8.78	-46.09→-29.66	-4.76→-16.01	51.09→19.35
贵州-上海	467.93→123.27	-34.32→3.91	-27.91→-5.25	-12.70→-31.78	52.79→10.40	144.21→24.18
云南-上海	476.07→138.55	-13.74→6.29	-17.93→-6.73	47.73→-31.46	-59.91→-13.17	72.09→16.85