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水足迹视角下陕西省种植业水资源利用评价及经济发展脱钩分析

本站小编 Free考研考试/2022-01-01

张炜,,
覃求
西安建筑科技大学管理学院 西安 710055
基金项目: 陕西省社会科学基金项目12Q023
陕西省教育厅专项科研计划项目13JK0223

详细信息
作者简介:张炜, 主要研究方向为资源环境管理和项目投资优化与决策。E-mail:352753390@qq.com
中图分类号:S271

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收稿日期:2018-05-08
录用日期:2018-09-20
刊出日期:2019-01-01

Decoupling analysis on water resources utilization of planting industry and economic development in Shaanxi Province from the perspective of water footprint

ZHANG Wei,,
QIN Qiu
School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China
Funds: Shaanxi Provincial Social Science Fund12Q023
Shaanxi Provincial Department of Education Special Research Project13JK0223

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Corresponding author:ZHANG Wei, E-mail: 352753390@qq.com


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摘要
摘要:陕西省位于"一带一路"关键地带,经济发展将处于加速转型的关键时期,期间农业水资源可利用量势必被进一步压缩,因此对陕西省各地市种植业水足迹进行量化并研究与其经济发展的协调关系,有利于明确各区域种植业生产的用水情况并为陕西省水资源管理提供参考。本研究运用水足迹理论,将灌溉水在输配水及田间灌溉过程中的损失纳入作物区域生产水足迹核算之中,通过核算2005-2016年陕西省种植业的水足迹值,定量分析了陕西省各作物耗水量的时空差异性,以及绿水足迹利用效率和各市水环境压力状况,并结合脱钩模型研究了种植业经济增长与水资源利用和水环境变化的脱钩关系。结果显示:1)各作物耗水量在研究期内差异较大,蔬菜和水果水足迹较低,分别为0.42 m3·kg-1和0.51 m3·kg-1,茶叶则高达30.29 m3·kg-1,但总体呈下降趋势;2)各地市种植业耗水量构成呈现较大差异性,关中地区粮食类作物占比为69.59%,陕北地区玉米和水果占75.16%,陕南地区则相对均衡,耗水量组成基本与水资源禀赋和作物水足迹大小相一致;3)全省绿水足迹利用效率相对较低,水环境压力指数呈现南部低,中部、北部高的特点,其中咸阳市水环境压力指数12年间平均高达4.75,是水环境压力最为严重地区;4)陕西省种植业经济增长与水资源利用和水环境压力强脱钩状态分别占比45.45%和27.27%。研究结果说明,陕西省各市种植结构相对合理,但绿水足迹利用效率和水环境压力上仍需改良,种植业经济增长与水资源利用的关系逐渐完成了由弱脱钩的初级协调到强脱钩的优质协调的转变,但仍面临着种植业经济增长与水环境压力增大的挑战。
关键词:陕西省/
水足迹/
Tapio脱钩模型/
种植业/
经济增长/
水环境压力/
作物耗水量/
水足迹利用效率
Abstract:Shaanxi Province is located in a key area of the "One Belt One Road" promoted by China. The availability of agricultural water resources is bound to be further scarce due to accelerated economic transformation as a result of the "One Belt One Road" project. To therefore quantify water footprint of the crop industry and to determine the co-ordination between planting and economic development are critical for further clarification of the water use in planting and setting up relevant reference basis for water resources management in Shaanxi Province. Thus this paper incorporated the loss of water during distribution and irrigation of crop water footprint. By accounting for the value of water footprint of the crop industry in Shaanxi Province for the period 2005-2016, we analyzed the spatial and temporal differences in water consumption by various crops in Shaanxi Province, the utilization efficiency of green water and the pressure of water environment. Combined with the Tapio model, the change in relationship between economic growth of crop farming, water resource utilization and water environment was determined. The results showed that:1) water consumption by various crops was significantly different during the study period. The water footprint of vegetables and fruits were respectively 0.42 m3·kg-1 and 0.51 m3·kg-1, while that of tea was as high as 30.29 m3·kg-1. However, there was an overall downward trend in water use. 2) The water consumption composition of planting industry in different areas was quite different, crop water consumption proportion in Guanzhong was 69.59%, grain and corn water consumption proportion in northern Shaanxi was 75.16% and that in southern Shaanxi was relative equilibrium among various corps. The water consumption composition was basically the same as water endowment and crop water footprint. 3) The use efficiency of green water footprint was relatively low. Also the pressure index of water environment was low in the south, high in the central and north. The average water environment pressure index for Xianyang was as high as 4.75 in 12 years, indicating serious water environment pressure. 4) The decoupling of economic growth of crop industry with water resource use and water environment pressure accounted respectively for 45.45% and 27.27% of total water use in the province. The research results showed that planting structure in Shaanxi Province was relatively reasonable and that green water footprint was hugely utilized. The efficiency and pressure of water environment still needed improvement. The relationship between economic growth of crop industry and water resources use was being gradually transformed from primary co-ordination of weak decoupling to quality co-ordination of strong decoupling. However, it still faced the change of industrial diversity, economic growth and environmental pressures.
Key words:Shaanxi Province/
Water footprint/
Tapio decoupling model/
Crop industry/
Economic growth/
Water environment pressure/
Crop water consumption/
Water footprint use efficiency

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图12005—2016年陕西省各地级市种植业各种作物耗水量平均组成
Figure1.Average proportions of water consumptions of different crops in planting industry in various cities of Shaanxi Province during 2005 to 2016


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图22005—2016年陕西省作物耗水量变化趋势
Figure2.Trends of water consumption of different crops in Shaanxi Province during 2005 to 2016


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图32008年、2012年和2016年陕西省水资源环境压力空间变化
Figure3.Spatial variation of environmental pressure on water resources in Shaanxi Province in 2008, 2012 and 2016


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表1陕西省2005—2016年间灌溉水利用系数
Table1.Irrigation water utilization coefficients in Shaanxi Province from 2005 to 2016
年份Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
灌溉水利用系数
Irrigation water utilization coefficient
0.48 0.50 0.51 0.52 0.53 0.54 0.54 0.55 0.55 0.55 0.56 0.56


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表2Tapio指数脱钩程度判断表[29]
Table2.Tapio index decoupling degree judgment table
脱钩类型
Decoupling type
脱钩状态
Decoupling state
Δ种植业总产值(ΔTPO)
Δ total planting output value
Δ水足迹/Δ灰水足迹
(ΔWF/ΔWFgrey) Δ water footprint /Δ green water footprint
脱钩指数(DE)
Decoupling index
负脱钩
Negative decoupling
弱负脱钩Weak negative decoupling < 0 < 0 0 < DE < 0.8
强负脱钩Strong negative decoupling < 0 > 0 DE < 0
增长负脱钩Expansive negative decoupling > 0 > 0 DE > 1.2
脱钩
Decoupling
衰退脱钩Recessive decoupling < 0 < 0 DE > 1.2
强脱钩Strong decoupling > 0 < 0 DE < 0
弱脱钩Weak decoupling > 0 > 0 0 < DE < 0.8
耦合
Coupling
衰退型耦合Recessive coupling < 0 < 0 0.8 < DE < 1.2
扩张性耦合Expansion coupling > 0 > 0 0.8 < DE < 1.2


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表32005—2016年陕西省各地级市作物绿水足迹平均相对占比
Table3.Average relative proportions of crop green water footprints in various cities in Shaanxi Province during 2005 to 2016
%
区域
Area
小麦
Wheat
水稻
Rice
玉米
Maize
大豆
Soybean
棉花
Cotton
油菜
Rape
花生
Peanut
麻类
Hemp
烟草
Tobacco
蔬菜
Vegetable
茶树
Tea
水果
Fruit
西安Xi’an 15.47 20.28 33.88 33.92 28.61 20.98 24.06 47.68 52.24
铜川Tongchuan 14.58 28.09 37.31 36.26 21.09 44.08 76.94
渭南Weinan 17.70 28.11 42.17 48.29 39.46 24.30 27.23 61.87 100.00 53.93 61.39
宝鸡Baoji 21.81 43.98 48.52 42.70 29.01 30.82 89.10 45.30 70.80
咸阳Xianyang 16.09 35.60 36.74 29.12 21.48 26.32 47.04 62.86 43.02 64.02
延安Yan’an 13.68 22.95 27.26 38.56 29.03 18.25 20.84 50.90 82.17 36.41 66.17
榆林Yulin 10.80 19.05 22.10 31.43 23.35 15.94 15.22 36.04 45.93 26.21 42.93
安康Ankang 35.78 43.45 62.11 52.80 44.40 40.42 59.77 84.13 100.00 65.03 57.63 44.99
汉中Hanzhong 26.58 37.60 68.34 68.52 59.83 40.75 59.29 80.43 100.00 63.86 65.11 49.81
商洛Shangluo 22.88 27.18 60.63 51.91 44.00 24.38 40.22 73.42 73.56 55.62 61.30 64.74
“—”表示研究期内作物种植较少, 统计时不做考虑。“—” means that the crop area is too little not to be calculated.


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表42005—2016年陕西省各地级市各种作物年平均灰水足迹总量
Table4.Annual average gray water footprint of different crops in various areas of Shaanxi Province during 2005 to 2016 ×108 m3·a-1
区域
Area
小麦
Wheat
水稻
Rice
玉米
Maize
大豆
Soybean
棉花
Cotton
油菜
Rape
花生
Peanut
麻类
Hemp
烟草
Tobacco
蔬菜
Vegetable
茶树
Tea
水果
Fruit
陕西Shannxi 21.11 1.85 26.19 1.94 1.25 2.74 0.40 0.01 0.37 16.30 2.76 47.15
西安Xi’an 3.86 0.02 4.15 0.08 0.06 0.06 0.00 0.00 0.00 2.18 0.00 2.10
铜川Tongchuan 0.51 0.00 0.62 0.05 0.00 0.09 0.00 0.00 0.01 0.17 0.00 2.25
渭南Weinan 5.46 0.00 4.54 0.13 1.16 0.26 0.13 0.00 0.01 1.94 0.00 6.66
宝鸡Baoji 3.69 0.01 3.01 0.11 0.00 0.16 0.00 0.00 0.05 1.61 0.00 2.60
咸阳Xianyang 4.17 0.00 3.89 0.06 0.01 0.34 0.00 0.00 0.03 2.96 0.00 11.25
延安Yan’an 0.12 0.01 1.65 0.26 0.02 0.04 0.02 0.00 0.03 0.70 0.00 11.63
榆林Yulin 0.07 0.04 3.08 0.67 0.00 0.00 0.07 0.00 0.00 0.70 0.00 7.80
安康Ankang 1.12 0.47 1.89 0.14 0.00 0.65 0.07 0.00 0.12 1.97 0.86 1.18
汉中Hanzhong 0.84 1.28 1.61 0.16 0.00 1.08 0.05 0.00 0.04 1.77 1.44 1.49
商洛Shangluo 1.28 0.01 1.74 0.28 0.00 0.06 0.06 0.00 0.08 0.64 0.45 0.18


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表52005—2016年陕西省水资源利用与种植业生产总值脱钩状态
Table5.Decoupling of water resources utilization and crop production in Shaanxi Province during 2005 to 2016
年份
Year
种植业
总产值
TPO (×108 )
水足迹
WF (×108 m3)
灰水足迹
WFgrey (×108 m3)
Δ总产值
ΔTPO (%)
Δ水足迹
ΔWF (%)
水足迹脱钩指数
DE(WF, TPO)
脱钩状态
Decoupling state
Δ灰水足迹
ΔWFgrey (%)
水环境
脱钩指数DE(WFgrey, TPO)
脱钩状态
Decoupling state
2005 472.90 496.71 108.04 10.68 3.14 0.29 弱Weak 2.64 0.25 强Strong
2006 523.42 512.31 110.89 20.24 -6.17 -0.30 强Strong -2.13 -0.11 强Strong
2007 629.34 480.71 108.53 23.28 3.55 0.15 弱Weak 4.89 0.21 弱Weak
2008 775.85 497.77 113.84 6.15 -1.57 -0.25 强Strong 5.28 0.86 扩张性耦合Expansion coupling
2009 823.60 489.98 119.85 34.44 5.12 0.15 弱Weak 11.25 0.33 弱Weak
2010 1 107.24 515.07 133.33 22.89 -6.15 -0.27 强Strong -7.55 -0.33 强Strong
2011 1 360.66 483.38 123.27 12.17 4.29 0.35 弱Weak 1.56 0.13 弱Weak
2012 1 526.28 504.10 125.20 12.35 7.92 0.64 弱Weak 2.55 0.21 弱Weak
2013 1 714.79 544.00 128.39 9.10 -4.14 -0.46 强Strong 1.00 0.11 弱Weak
2014 1 870.78 521.48 129.68 2.13 1.10 0.52 弱Weak 1.12 0.53 弱Weak
2015 1 910.71 527.22 131.13 6.12 3.26 0.53 强Strong 1.16 0.19 强Strong
2016 2 027.56 544.43 132.66
TPO: total planting output value; WF: water footprint; WFgrey: grey water footprint; ΔTPO: change rate of TPO; ΔWF: change rate of WF; DE(WF, TPO): decoupling index of WF; ΔWFgrey: change rate of WFgrey; DE(WFgrey, TPO): decoupling index of water environment.


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表6不同****对陕西区域小麦水足迹研究比较
Table6.Comparison of different scholars' researches on wheat water footprint in Shaanxi region
作者
Author
研究区域
Study area
研究期
Study period
作物水足迹组成
Water footprint composition
水足迹
Water footprint (m3·kg-1)
参考文献
Reference
张炜等
Zhang Wei, et al.
陕西省
Shaanxi Province
2005—2016 绿水、蓝水(灰水) Green water, blue water (grey water) 2.75 (3.21)
史利洁等
Shi Lijie, et al.
陕西省
Shaanxi Province
2000—2012 绿水、蓝水Green water, blue water 1.29 [9]
刘帝等
Liu Di, et al.
陕西省关中地区
Guanzhong Region, Shaanxi Province
1998, 2005, 2010 绿水、蓝水Green water, blue water 0.96 [31]
冯东溥等
Feng Dongpu, et al.
陕西省宝鸡峡灌区
Baoji Gorge Irrigation District, Shaanxi Province
1994—2010 绿水、蓝水(灰水) Green water, blue water (grey water) 0.68 (1.04) [32]
括号内数据为包含灰水足迹下的作物水足迹。Values in brackets are water footprint containing grey water footprint.


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