基于MRIO模型的中国省（市）区水足迹测度及空间转移格局

doi:10.31497/zrzyxb.20190504

摘要/Abstract

摘要：

基于2012年中国31个省（市）区的投入产出表,建立水资源扩展型的投入产出模型,测算了中国31个省（市）区的水足迹及水足迹贸易量,并基于省际贸易分析了省（市）区间空间转移格局。结果显示：（1）2012年,中国水足迹总量为4819.3亿m³,国际贸易净输入水足迹为261.3亿m³,省际贸易净输出水足迹为801.6亿m³,省际贸易在全国水足迹贸易中占主导地位。（2）就省（市）区而言,河北、黑龙江等19个省（市）区为净输出省份,北京、天津等12个省（市）区为净输入省份;分产业来看,第一产业水足迹净输出757.9亿m³;第二产业净输入222.2亿m³、第三产业净输出4.6亿m³。（3）省际间水足迹空间转移具有来源与去向的不一致性,同时存在省（市）区转移的地理邻近性,资源丰富省份和经济发达地区转移现象明显。

关键词: MRIO模型, 水足迹, 空间转移, 中国

Abstract:

Based on the input-output table of 31 provinces (autonomous regions and municipalities) in China in 2012, the water footprint and water footprint trade structure of the provinces in China were calculated and analyzed by establishing the I-O model of water resources expansion, and the spatial transfer pattern of the provinces was analyzed based on the interprovincial trade. The results showed that: (1) In 2012, the total amount of internal water footprint, the net input water footprint of international trade, and the net export water footprint of interprovincial trade were 4819.3×10⁸ m³, 261.3×10⁸ m³, and 801.6×10⁸ m³, respectively. Inter-provincial trade played a leading role in the national water footprint trade. (2) In terms of the provincial-level region, 19 were net output provinces, such as Hebei and Heilongjiang, 12 were net input provinces, such as Beijing and Tianjin. In the view of the industry, the net output water footprint of the primary industry, the net input of the secondary industry, and the net output of the tertiary industry were 757.9×10⁸ m³, 222.2×10⁸ m³, and 4.6×10⁸ m³, respectively. (3) The inter-provincial water footprint spatial transfer has the inconsistency between the source and the destination provinces, the geographical proximity of provincial transfer, and the phenomenon was obvious in resources-rich provinces and economically developed areas.

Key words: MRIO model, water footprint, space transfer, China

孙才志, 刘淑彬. 基于MRIO模型的中国省（市）区水足迹测度及空间转移格局[J]. 自然资源学报, 2019, 34(5): 945-956.

Cai-zhi SUN, Shu-bin LIU. Water footprint and space transfer at provincial level of China based on MRIO model[J]. JOURNAL OF NATURAL RESOURCES, 2019, 34(5): 945-956.

图/表 6

Table 1

Results of water footprint in 31 provinces of China （亿m3）"

省(市)区	内部水足迹					输出水足迹			输入水足迹
省(市)区	农村消费	城镇消费	政府消费	投资	总和	国内省外流出	出口	总和	国内省外流入	进口	总和
北京	2.3	38.3	4.0	25.8	70.4	350.5	22.6	373.1	260.5	176.4	436.9
天津	2.8	25.9	2.2	25.9	56.8	29.5	11.1	40.5	85.5	23.9	109.4
河北	23.0	56.4	8.4	90.6	178.4	172.7	9.3	182.0	119.8	12.6	132.4
山西	21.3	40.9	3.1	39.0	104.2	24.4	2.0	26.4	36.8	2.4	39.2
内蒙古	8.1	21.0	16.7	46.0	91.8	75.2	—	75.2	142.4	—	142.4
辽宁	11.7	51.1	6.4	69.4	138.6	85.2	17.8	103.0	100.3	20.7	121.0
吉林	11.2	18.9	5.2	79.3	114.6	77.8	4.3	82.1	69.6	13.0	82.6
黑龙江	23.0	78.9	13.0	106.8	221.7	386.7	18.6	405.3	235.7	45.2	280.9
上海	6.6	119.6	6.8	36.2	169.2	152.0	84.5	236.5	213.4	124.1	337.5
江苏	36.6	79.8	25.0	103.0	244.4	270.3	113.3	383.6	193.2	117.3	310.4
浙江	17.3	98.7	6.2	72.0	194.3	84.7	57.9	142.5	156.6	33.7	190.2
安徽	20.8	48.8	7.0	62.5	139.1	251.0	12.8	263.7	196.1	8.3	204.4
福建	23.3	68.3	9.9	93.8	195.3	59.3	63.9	123.1	46.8	62.0	108.8
江西	41.4	65.1	8.2	62.7	177.4	131.5	10.5	142.1	86.5	5.5	92.0
山东	16.6	43.4	11.8	74.3	146.1	23.2	30.6	53.8	61.0	58.3	119.3
河南	22.6	35.3	11.2	58.6	127.7	105.5	5.8	111.3	96.6	7.1	103.8
湖北	23.6	49.5	9.5	146.8	229.4	—	53.7	53.7	—	40.4	40.4
湖南	44.5	94.8	10.3	94.8	244.3	189.7	4.9	194.6	106.7	4.5	111.3
广东	54.7	228.6	15.4	79.8	378.4	84.4	153.9	238.4	156.7	173.7	330.3
广西	41.8	72.8	12.1	84.2	210.8	174.1	12.3	186.4	77.8	46.2	124.1
海南	4.9	13.6	1.3	17.7	37.6	91.2	2.3	93.5	61.3	7.6	68.8
重庆	8.8	32.6	3.6	54.5	99.5	98.2	0.9	99.1	97.3	1.0	98.3
四川	42.5	68.0	9.2	68.6	188.3	24.5	12.1	36.6	38.5	6.7	45.2
贵州	32.3	30.0	6.3	38.6	107.2	61.4	4.8	66.2	60.8	1.8	62.6
云南	54.6	59.4	4.5	64.7	183.1	80.3	9.0	89.3	70.8	16.3	87.2
西藏	8.9	7.7	1.4	18.8	36.7	1.7	3.3	5.0	14.1	0.1	14.2
陕西	11.3	36.6	7.2	75.7	130.8	171.0	30.5	201.5	139.0	20.9	159.9
甘肃	28.3	35.6	13.4	45.0	122.3	129.9	4.3	134.2	74.5	7.1	81.6
青海	4.0	11.7	6.8	28.5	51.0	—	16.3	16.3	—	15.1	15.1
宁夏	18.0	44.2	4.5	22.0	88.6	53.3	7.3	60.6	57.4	0.9	58.4
新疆	65.5	152.4	11.9	111.1	340.9	571.3	29.6	600.8	153.0	18.3	171.3

Table 1

图1

图2

图3

图4

图5

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