Water Transfer and Water Savings through Interprovincial
Trade within China: from the Perspective of Value Chains
Xi Liu, College of Management and Economics, Tianjin University, Tianjin 300072, China
Huibin Du* , College of Management and Economics, Tianjin University, Tianjin 300072, China
Zengkai Zhang, College of Management and Economics, Tianjin University, Tianjin 300072, China
John Crittenden*, Brook Byers Institute for Sustainable Systems, School of Civil and Environmental Engineering, Georgia Institute of
Technology, Atlanta, GA, USA
Juan Moreno-Cruz, School of Economics, Georgia Institute of Technology, Atlanta, GA, USA
Guozhu Mao*, School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
Outline
1. Introduction
2. Materials and Methods
3. Results
4. Discussion
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Introduction
1.1 Background
Water resource situation in China
 Renewable internal freshwater resources per capita, ranking 105 in the world in 2014 (World Bank, 2014).
 Water demand, 22% of total water resource endowment in 2013 (China Statistical Yearbook, 2014).
 Water resources uneven distribution, south China more than 60% of that in north in 2015 (China Water
Resources Bulletin, 2015)
Challenges China faced
 Water demand increasing, 16% in the last 10 years.
 Global climate change, exacerbate the scarcity problem as the variability of water supply may change
(Kenneth and Major, 2002).
Measures for water usage sustainability
 technology efficiency improvement.
 engineering measures like “the South to North Water Diversion” project.
 virtual water trade (Zhang et al., 2011).
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Introduction
1.2 Previous studies
Virtual water trade research (proposed by Allan, 1993)
 Water resources re-allocation: virtual water trade balance or direction at global, national, regional
levels (Dalin et al., 2012; Kumar MD & Singh OP, 2005; Zhao et al., 2012), sources and destinations.
 Production fragmentation: intermediate goods trade, two thirds internationally.
trade in final goods
Commodity A
Commodity B
Country 1
Commodity C
export
Commodity C
trade in intermediate goods for the value chain related trade
final stage of production
Commodity D
export
Commodity E
Country 2
Country 3
 Without considering the production fragmentation: focus on two countries, neglecting the role of third
country in water-related policy; overestimate the responsibility for water resources usage.
Introduction
1.3 Our study
The motivation
 interregional trade in China, influenced by production fragmentation, value chain related trade being
important (Meng et al., 2012)
production
fragmentation
Multi-regional input-output (MRIO) analysis
The aim
The analysis
provincial
water uses
water uses by
trade pattern
virtual water
transfer
trade direction, major
flows by trade pattern
water savings
national and provincial
water savings
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Material and Methods
2.1 The MRIO model
 the basic equation of MRIO model
 X 1   A11
 2   21
X   A

 
 g   g1
 X   A
1 
 G 1r
A1g   X 1    r Y  EX 
G


A2 g   X 2    r Y 2 r  EX 2 



 



A gg   X g   G Y gr  EX g 
  r

A12
A22
Ag 2
final uses
intermediate inputs
 the exports from s to r, Tsr
T
sr
Y
sr
T _ f sr
A L Y A L
sr
rr
T _ i sr
rr
sr
G
rr
A
rt
B Y A
tr
rr
G
sr
t r
B
rt
Y A
tr
t r
G
sr
G
B Y
tu
rt
t
u r
T _ d sr
in final goods
②intermediate
goods for the
final stage of production
t
T _ g sr
T _v
①trade
G
 Asr B rt EX t
sr
③
value chain related trade
 gross output generated from province s
G
G
G
sr
sr
sr
X s  LssY ss  Lss EX s  Lss  T _ f sr  Lss  T _ i sr  Lss  T _ v sr
①local
activities ② foreign countries export ③ other provinces
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Material and Methods
Induced by local
economic activity
A region’s
gross water
uses
 gross water use of province s
W F X
s
s
Induced by
trade
s
 F L Y  F L EX  F L
s
ss
ss
s
ss
s
s
ss
G
T _ f
sr
sr
F L
s
ss
G
T _ i
sr
sr
F L
s
ss
G
T _ v
sr
sr
Induced by
international
trade
Induced by
inter-provincial
trade
Trade in final goods
(T_f)
Trade in intermediate goods for
the final stage of production
(T_i)
Value chain-related trade
(T_v)
 virtual water transfer
Intermediate goods trade
(1) virtual water embodied in exports from province s to r: VW sr  F s LssT _ f sr  F s LssT _ i sr  F s LssT _ v sr
(2) balance of embodied virtual water use from province s to r:
BVW sr  VW sr  VW rs
  F s LssT _ f sr  F r LrrT _ f rs    F s LssT _ i sr  F r LrrT _ i rs    F s LssT _ v sr  F r LrrT _ v rs 
G
G
G
r s
r s
r s
BVW s  VW sr  VW rs  BVW sr
BVW> 0, the production fragmentation contributes to an increase in the water use of province s.
BVW< 0, the production fragmentation promotes a decrease in the water use of province s
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Material and Methods
 national water saving effects
(1) balance of avoided water use (BAW)
BAW sr = VW sr − WAI sr + VW rs − WAI rs
rr
rr
rr
= Fs Lss − Fr L T_f sr + Fs Lss − Fr L T_i sr + Fs Lss − Fr L T_v sr exports from s to r
rr
rr
rr
+ Fr L − Fs Lss T_f rs + Fr L − Fs Lss T_i sr + Fr L − Fs Lss T_v sr imports of s from r
(2) national water saving effects of province s
 G

BAW s   BAW sr  / 2
 r s

(3) gross balance of avoided water use, total national water savings
G
G
BAW  BAW sr
s rs
BAW> 0, the inter-provincial trade contributes to an increase in the national water use.
BAW< 0, the inter-provincial trade promotes a decrease in the national water use.
Material and Methods
2.2 Data sources
 Source materials: The 2010 multi-regional input-output (MRIO) table, 26 provinces, 4 cityregions
 Water use data: China Statistical Yearbook, 2011; China Urban-Rural Construction Statistical
Yearbook 2010.
 Sectoral water use data: secondary industry sectors, sectoral ratios in Chinese Economic
Census Yearbook 2008; service sectors, the intermediate input from water production and
supply sector to different service sectors.
 Scope: Blue water, excluding green water and gray water for data unavailability
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Results
3.1 Province’s water uses and its decomposition
Large water consumers:
 Developed regions: Jiangsu (55.4),
Guangdong (47.3 billion m3)
 Less developed and large agriculture
provinces: Xinjiang (53.5), Hunan
(32.6) and Heilongjiang (32.6 billion
m3)
Different water uses per GDP generation:
 Average level: 9.32 m3/102 $
 Developed regions: more efficient,
9.06/6.96
 Large agricultural provinces: less
efficient, 66.67/13.77/21.26.
Figure 1. The total water uses and its decomposition by five use patterns of
30 provinces
Figure 2 The fraction of water and GDP of different industries in top 10
water consumers
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Results
3.1 Province’s water uses and its decomposition
Qinhai, 84%
Gansu, 76%
Figure 1. The total water uses and its decomposition by five use patterns of
30 provinces
Water use decomposition:
 National: export, 9%; interprovincial, 34%..
 Domestic water uses: the dominate type, >50% in
22 provinces.
 Export to foreign countries: Zhejiang, 23%;
Guangdong, 21%; Shanghai, 21%; Jiangsu, 21%.
 Other provinces’ water uses: Hebei, 55
%; Jilin, 54%; Anhui, 49% etc.
 Final goods trade: Ningxia, 28%; Hebei, 23%;
Anhui, 22%.
 Intermediate goods trade: Jilin, Hebei etc. >30%.
 The water use structure is related to their position
in production network.
Results
3.2 The province’s virtual water trade and water scarcity
Net virtual transfer:
 Net virtual water exporters: northwest, southwest
and central regions like Xinjiang, Heilongjiang,
Anhui etc.
 Net virtual water importers: developed regions like
Shanghai, Guangdong etc. .
 Virtual water balance V.S. water scarcity: “stressed
water supply (water resources and net) water
exporter” like Xinjiang, Heilongjiang, Anhui, Inner
Mongolia, Ningxia, Jiangsu, Gansu, Hebei.
Water stress index: no stress, <0.2; water stress, >0.2 (Zhao
et al., 2015)
Figure 3. The four types of provinces based on net water
transfer and water stress condition
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Results
3.3 Effects of different trade patterns on province’s virtual water trade
From
Xinjiang,
Heilongjiang
etc.,
agriculture products
contributes most
67.3%
61.2%
From Guangxi,
Jiangxi, Hunan
etc.
34.5% industry: 36.9%
Primary
1.8 and 2.4 times of Shanghai
Net virtual transfer via different trade patterns:
 Final goods trade: Tianjin, Shanghai, Hunan,
Anhui, Heilongjiang and Xinjiang.
 Intermediate products for the final stage of
production: Beijing and Shandong.
 Value chain related trade: Zhejiang, Guangdong,
Hubei and Guangxi.
 The major trade pattern in net water transfer
differs due to the water use efficiency, trade
structure and also its position in the value chain.
Figure 4 The decomposition of water uses embodied in the trade of six largest net
water inflow and outflow regions (unit: billion m3)
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Results
3.4 Major virtual water flows under different trade patterns
(a) final goods trade
(b) intermediate goods trade for the final stage of production
(c) the value chain related trade
Figure 5 The 20 largest net water flows under different trade patterns
Spatial distribution of virtual water flows:
 Final goods trade: northwest, central regions to east coast, Xinjiang and Shanghai.
 Immediate goods trade for the final stage of production: Shandong.
 Value chain related trade: Guangdong, Zhejiang, Shandong, 61%, 59%, 47% for exports.
 Flow direction: northwest, northeast, central regions to north coast and east coast; southwest, central regions to south
coast.
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Results
3.5 Regional virtual water trade under different trade patterns
(a) final goods trade
(b) intermediate goods trade for the final stage of production (c) the value chain related trade
Figure 6 The eight regions’ bilateral water trade under three trade patterns
 Coast regions: east coast, final goods import (51%); south coast and north coast, value chain related trade (44%, 60%).
 Central regions: Yangtze River (central), final goods trade (44%), Yellow River (central) import virtual water.
 Northeast, southwest and northwest regions: value chain related trade (38%, 60%); final goods trade (43%).
 Reasons for the transfer direction: uneven development and economic structure; policies.
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Results
3.6 Water savings
National water savings, more water used by 13.9 billion m3:
 Final goods trade: 39.0% of total interregional trade, BAE (-0.8 billion m3), Guangdong (-1.1 billion m3) and
Shandong (-2.1 billion m3)
 Intermediate goods trade for the final stage of production: 28.7% of the total interregional trade, BAE (5.0
billion m3)
 Value chain related trade: 32.3% of the total interregional trade, BAE (9.6 billion m3), contributes the most.
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Results
(0.5, 7.0)
(2.0, 12.0)
(5.9, 21.6)
3.6 Water savings
Figure 7 The distribution of total BAW and BVW of 30 provinces in China (billion m3)
Large national and provincial water saving potential lies in:
 Xinjiang: Shanghai, Tianjin, Jiangsu and Henan in the final goods export; agriculture sector.
 Heilongjiang: Shandong, Jilin and Liaoning in the value chain related trade export; agriculture, electricity
and heat generation and crude oil and nature gas extraction sector.
 Anhui: Shaanxi, Shanghai and Zhejiang in the final goods export; agriculture, electricity and heat generation,
metals smelting and pressing, chemical industry and food, beverage and tobacco sector.
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Discussion
 virtual water trade may aggravate the water stress situation in some virtual water exporters, such
as Xinjiang (final goods trade), Inner Mongolia (value chain related trade): improving the direct
water use efficiency, optimizing its production process to save water indirectly and adjusting its
goods outflow strategy
 virtual water flows from west to east, where the environmental externalities of virtual water
transfer should be paid attention to: water compensation scheme taking all the participants into
consideration.
 national and provincial water savings: in Xinjiang, Heilongjiang, Anhui etc. in different trade
patterns and sectors. And water use efficiency is of great importance to save total water uses,
especially agriculture products, electricity and heat generation sector.
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