Abstract

As water use is closely associated with economic activities, a growing population, agricultural development, and reallocation of water resources, the Heihe River Basin highlights common issues of water productivity and groundwater overexploitation. We conducted a quasi-dynamic input–output analysis to investigate the changes to water use among different sectors of Zhangye city from 2002 to 2012, and clarified the driving mechanism of these changes. Our results indicated that the direct agricultural water use coefficient (calculated with an input–output table and other water use data) was the largest among the coefficients from all the sectors; notably, the fishery sector still consumed about 1 m3 of water per unit output in 2012. We found that the water-saving technologies clearly contributed to the decrease of agricultural water from 2002 to 2007, but induced a rebound in total water use from 2007 to 2012. This study provides insights into the challenges of water resource management in the Heihe River Basin and sheds light on potential water-saving strategies for the future. This study may also enhance the policy relevance of land use governance and industrial transformation. A comprehensive exploration of the water–ecosystem economy is critical to integrated water resource management.

Introduction

Humans have inhabited inland river basins for thousands of years, but this trend has been challenged by issues relating to water scarcity in recent years. Arid and semi-arid areas occupy approximately 35% of total land areas globally. At the same time, a booming population and economic prosperity worsen the problem as they intensify water consumption and diminish water availability for ecosystems. This concern is not restricted to hydrologists and engineers; economists also share this concern, as integrated water resource management and sustainable development is crucial for rationalizing water consumption structures (Cheng & Li, 2015). To solve the problem with limited available water resources, it is essential to understand the structure of water use in economic systems. Water use is an important economic activity, but it is influenced by changes in technology, economic scales, degree of input substitution, and final demands (Cazcarro et al., 2013; Maria & Ponce-Alifonso, 2015; Colosimo & Kim, 2016).

Integrated water resource management necessitates comprehensive investigations of industrial water use structures, the export of virtual water resources, and the driving forces of these changes in regional economic systems (Hoekstra et al., 2011; Zhang et al., 2012; Deng et al., 2015). One important feature, along with the economic growth path, is structural change or industrial transformation (Lewis, 1954; Pablo & Klaus, 2008; Chen et al., 2011). Moreover, industrial transformation will always occur with the reallocation of water resources across industries or sectors (Boulding, 1973; Wu et al., 2014; Li et al., 2015). The concept of an industrial water use structure involves both the direct water use coefficient (DWUC) of each sector and the relationship between indirect water uses in all sectors. However, researchers and managers focus on the former but ignore the latter, which plays a significant role in the establishment of an evidence-based efficient water-allocation structure in economic systems (Jiang et al., 2014; Zhi et al., 2014; Feng et al., 2017).

Understanding water use for the economy and its drives is necessary for policy making aimed at water resources sustainability. Water use for most socio-economic activities varies largely due to the complex interplay of multiple factors. An input–output model can examine the direct and indirect water use associated with these factors, as well as the impact of economic growth on natural resource use. By convention, water footprint accounting is the total water use of an economic system (Yang et al., 2006; Deng et al., 2014) and virtual water refers to the total water consumption used for the production of goods or services in the regional trade process (Yang et al., 2006; Shi et al., 2015). With regard to virtual water, water use by a particular region and/or sector is interconnected or interdependent across the regions or sectors (Zhao et al., 2015). Input–output models are already used to estimate the water flow embodied in production or trade services beyond both the regional and sectoral scopes (Guan & Hubacek, 2007; Cazcarro et al., 2013).

To gauge the effects of the driving forces of water use or virtual water changes, researchers have widely adopted the index decomposition analysis (IDA) and structural decomposition analysis (SDA) (Guan & Hubacek, 2007; Wang & Wang, 2009; Wang et al., 2009). While IDA incorporates changes only in industrial water consumption, SDA developed from an input–output table can describe the water flow among production industries, consumption households and exports (Pablo & Klaus, 2008; Daniels et al., 2011; Fang & Chen, 2015). Although IDA is used to track economy-wide water consumption efficiency trends, differences still exist between the scope of SDA and of IDA in water use studies. For example, typical SDA provides more details (e.g. a Leontief effect, a technical effect, or a final-demand effect by both sector and demand/source) and can estimate the indirect effects. The analysis might be especially interesting for revealing the material implications of economic and social changes in the Heihe River Basin, characterized by water scarcity, severe rainfall and climatic irregularity.

To the best of our knowledge, current research in this field has two main limitations. First, static analysis provides only ‘snapshot information’ of water use structures in one set year. Dynamic analysis of the water use and of virtual water changes over a certain period is rare, given the constraint of requiring a compilation of years for input–output tables. Second, most of the existing research provides only descriptions of ‘what it is’ rather than ‘how it is shaped’. Studies on the driving forces behind the water use and virtual water changes remain very limited at the basin level. A decomposition analysis of contributing factors to the water use or to virtual changes under the input–output framework is also absent at the basin level.

This study analyzed the mechanisms involved in the water use and the virtual water changes of Zhangye city to provide references for integrated water resource management. Zhangye city began its ‘water-saving society’ program to improve water use efficiency after 2002. Many measures were implemented such as the promotion of water-saving technology, encouragement of water reuse and recycling, the renovation of irrigation systems, and the increase of water prices. Meanwhile, the current overall water supply–demand balance in Zhangye city relied on the increased runoff from the upstream water source and more exploitation of groundwater. First, we identified the driving forces based on an exploration of the water use and of virtual water in terms of water use coefficient in each primary sector from 2002 to 2012. Second, we conducted assessments of their changes based on an input–output model and SDA. Third, we discussed how international trade and economic growth affect water use. The remainder of this study was focused on suggestions for integrated water resource management and investigating the feasibility of a virtual water strategy in this basin.

Study area

Zhangye, as a water-intensive city, is located at the middle reach of Heihe River Basin in the typical arid area in the middle of the Hexi Corridor (Figure 1). Zhangye city was selected as the first demonstrative city of the water-saving society initiative in China since 2002. It is crucial to take Zhangye city as a representative case study area to figure out the water use coefficient for each sector and correspondingly explore possible pathways to mitigate water usage pressure. As a major area of the national West Development, Zhangye city occupies 95% of cultivated land (2,668 km2), which supports 91% of its population, and generates more than 80% of the GDP of the Heihe River Basin. Zhangye city is rich in natural resources and is the main irrigation district in this basin. Zhangye city possesses 26 rivers and streams, contributing to an annual runoff of 2.66 billion m3 of water. It also has abundant groundwater reserves. It has more than 217,333 km2 of grassland and 3,867 km2 of forest land, forming forest coverage up to 9.2%. The annual sunshine duration can be up to 3,000 hours. With irrigation from the Heihe River, the flat and fertile soils produce rich crops, such as Wujiang rice and maize for seed. Zhangye city is one of the 12 key national commercial grain bases due to its abundant supply of wheat, corn, rice, oilseed, rapeseed, flax and other crops. After the government pledged to secure food production and economic growth, irrigation agriculture in Zhangye city became the largest water use sector to date. Large investments were devoted to agricultural infrastructure and laws were established to protect the water use rights of riparian farmers. To adjust to this farming layout, a major goal of their agricultural development was to transform low-value grain commodities into high-value products.

Fig. 1.

Location and administrative boundary of Zhangye.

Fig. 1.

Location and administrative boundary of Zhangye.

The rapid agricultural development in Zhangye city induced an increase in water use. According to Zhangye Water Works Authority information, water consumption was 2.32 billion m3 in 2012, including 1.51 billion m3 of surface water and 0.81 billion m3 of groundwater; 99% of water resources were consumed by socio-economic systems, of which 95% were used in the agricultural sector (Table 1). Ecological water allocation is strictly constrained by excessive water utilization from socio-economic systems. As a result, Zhangye city may be trapped in an environmental–economic dilemma, where water demand for both economic development and ecological maintenance cannot be met at the same time, given the context of water scarcity.

Table 1.

Water use in socio-economic and ecological systems in Zhangye, 2012.

  Production use
 
Household use Ecological use Total 
Agricultural sectors Industrial sectors Tertiary industry 
Surface water 1,434 23.57 6.76 25.41 20.42 1,510.16 
Groundwater 759 28.02 3.64 11.26 11.07 812.99 
Total 2,193 51.59 10.4 36.67 31.49 2,323.15 
  Production use
 
Household use Ecological use Total 
Agricultural sectors Industrial sectors Tertiary industry 
Surface water 1,434 23.57 6.76 25.41 20.42 1,510.16 
Groundwater 759 28.02 3.64 11.26 11.07 812.99 
Total 2,193 51.59 10.4 36.67 31.49 2,323.15 

Note: Measured in million m3.

Data and methodology

Data

Water use data from various sectors were obtained from the Zhangye Water Resource Bulletin and the First Census for Water published by the Zhangye Water Works Authority. The procedures used for extracting useful information included three steps. First, we calculated the water use coefficients of each sector based on the first water resource survey conducted in Zhangye city in 2011. According to the Ministry of Water Resources, the first water resource survey was conducted over 2010–2012. Thus, 31 December 2011 was set as the standard time point and the year 2011 was defined as the census period. The scope of the census covers all rivers, lakes, water structures, major water factories for socio-economic use, and water-related institutions. Second, total water-consumption data over 2002–2012 were collected from the Zhangye Water Works Authority and their affiliated water plants. We then divided the total water use between 48 sectors in 2012 according to the water use coefficients of industries in 2011. Finally, we calculated the industrial water use in 2002 and 2007 based on previously published research and the Water Resource Bulletin.

Our study used input–output table data from 2002, 2007 and 2012, which were published by the Statistics Bureau of Gansu. The data originated from the Statistics Yearbook of Gansu Province published by the National Bureau of Statistics of China from 2002 to 2012, including the provincial accounting statistics and census of business accounting statistics of China. The sectoral data in the Zhangye input–output tables are formatted to provincial standards in 2002, 2007 and 2012. Sectoral inputs and outputs were adjusted according to the Zhangye Statistics Yearbooks.

Methodology

The input–output model and the SDA model are often used in quantitative analysis of annual water use changes, the contributions of key economic sectors, and the factors leading to those changes, which together form a decomposition analysis of water use changes (Figure 2). The input–output model illustrates the monetary trade of products and services among different industrial sectors in an economic system (Leontief, 1941, 1970). The water use for each sector was calculated as follows (Zhang et al., 2011). To calculate the water use, the water use coefficient of each sector should be computed, which is defined as the water necessary to produce each monetary unit (yuan) of goods or services in a region. Notably, in this study, direct water use refers to the water circulated in the water use and indirect water use refers to the water contained in products and services.

Fig. 2.

The flow chart of model analysis.

Fig. 2.

The flow chart of model analysis.

We introduce the DWUC as:  
formula
(1)
where is the total output from sector ; (m3) is the direct water use by sector j for the production of products. We assume is the total water use by sector j for the production of products. Total water use includes direct and indirect water uses. Indirect water use is derived from the indirect use of products during production.
The first round of the indirect water use coefficient (IWUC) is:  
formula
(2)
The matrix form is . We assume the IWUC of the th round is . Then the th round of IWUC is:  
formula
(3)
The matrix form is formatted as follows:  
formula
(4)
Therefore, the total water consumption is estimated as:  
formula
(5)
We change the form of the matrices and w to square matrices , respectively, which have the same diagonal elements as . The remaining elements are all 0. In such a form, we get:  
formula
(6)

Weighted decomposition method

According to SDA theories, there are ways to arrive at decomposition:  
formula
(7)
 
formula
(8)
 
formula
(9)
 
formula
(10)
 
formula
(11)
 
formula
(12)
where t is the report period, and 0 represents the base period. We then get:  
formula
(13)
where wi represents the weight.
SDA is conducted based on the data at the start period (2002) and at the end period (2012). The contributions of the above three factors are determined as follows:  
formula
(14)
 
formula
(15)
 
formula
(16)
 
formula
(17)
where represent the structural effect, the technological effect and the demand effect, respectively.
By assigning different values to , we get different decomposition methods. Specifically, we get the weighted decomposition method when the following formula is satisfied:  
formula
(18)

We arrive at new decomposition methods by assigning other values to .

Results

Changes in the DWUC

The DWUC is necessary for water use accounting. The DWUC is an indicator of sectoral water use intensity, which refers to the amount of direct water intake necessary for the production of one monetary unit. However, the DWUC does not reflect the total water embodied in the final outputs because a large amount of water is used in the upstream production chain in many economic systems. The total water use of the economic system in 2012 is 2,245 million m3, which increased by 12.6% from 1,994 million m3 in 2002. The DWUC of the agricultural sector was more than 5,897 m3/104 yuan in 2002. DWUC averaged across all sectors and all years is 2,418 m3/104 yuan. However, the DWUCs are below 30 m3/104 yuan for almost half of the sectors, including mineral mining, manufacturing, electric power, construction industry, transportation, warehousing, and the service industry in Zhangye city. Therefore, agriculture is the largest direct consumer. The DWUC of the agricultural sector is about twice as high as the average value, because more than 90% of the total water use was utilized for agriculture but the agriculture produces less than one third of the city's total output. The service industry consumed the least water resources, which decreases from 17.86 m3/104 yuan in 2002 to 1.81 m3/104 yuan in 2012. The DWUC changes in agriculture during 2007–2012 and 2002–2007 are about 400 m3/104 yuan and 2,184 m3/104 yuan, respectively (Table 2). Consequently, the DWUC change in agriculture during 2002–2007 is evident relative to the change during 2007–2012.

Table 2.

DWUCs in 2002, 2007, and 2012 (m3/104yuan).

Sector 2002
 
2007
 
2012
 
II II II 
Agriculture 189,038.00 5,897.59 205,303.00 3,713.60 207,324.00 3,313.00 
Forestry 17,107.00 8,542.04 17,623.00 7,541.00 16,952.00 6,985.00 
Animal husbandry 1,101.00 898.42 454.00 623.20 1,714.00 912.80 
Fisheries 2,871.00 12,940.16 2,871.00 11,370.71 2,387.00 9,260.30 
Mineral mining 401.82 54.20 266.00 15.77 355.00 6.84 
Manufacturing industry 3,752.62 92.60 3,825.00 43.03 4,904.00 27.78 
Electric power 285.00 41.78 607.00 34.28 691.92 18.61 
Construction industry 467.00 110.40 563.00 42.60 583.00 18.10 
Transportation and warehousing postal 120.81 11.50 100.00 8.27 89.00 7.28 
Service industry 369.00 17.86 445.00 10.95 457.00 1.81 
Sector 2002
 
2007
 
2012
 
II II II 
Agriculture 189,038.00 5,897.59 205,303.00 3,713.60 207,324.00 3,313.00 
Forestry 17,107.00 8,542.04 17,623.00 7,541.00 16,952.00 6,985.00 
Animal husbandry 1,101.00 898.42 454.00 623.20 1,714.00 912.80 
Fisheries 2,871.00 12,940.16 2,871.00 11,370.71 2,387.00 9,260.30 
Mineral mining 401.82 54.20 266.00 15.77 355.00 6.84 
Manufacturing industry 3,752.62 92.60 3,825.00 43.03 4,904.00 27.78 
Electric power 285.00 41.78 607.00 34.28 691.92 18.61 
Construction industry 467.00 110.40 563.00 42.60 583.00 18.10 
Transportation and warehousing postal 120.81 11.50 100.00 8.27 89.00 7.28 
Service industry 369.00 17.86 445.00 10.95 457.00 1.81 

I: Direct water use amount (m3); II: Direct water use coefficient (m3/104 yuan).

Changes in virtual water

Virtual water is commonly known as the water used in the production of traded goods and services. Virtual water trading through import from water-abundant areas often relieves regional water shortages. The calculation of virtual water is primarily based on the data from sectoral trade and water use. In this study, we calculated virtual water based on the import and export information of input–output table and water use coefficient for each sector. Our results showed that sectoral virtual water inflow and outflow brought about by the trade of goods and services differ greatly. For example, in 2012, Zhangye city received 82.56 billion yuan from selling agricultural products to other areas, which is equal to an export of 1,405 million m3 of virtual water. Thus, sustainable use of water resources in Zhangye city is important for the import rather than the export of water-intensive products. The current trade trends are likely to exacerbate the demand–supply imbalance of water resources. The virtual water change in agriculture has been abrupt, with an increase in the export of virtual water from 847 million m3 in 2002 to 1,253 million m3 in 2007 (Figure 3).

Fig. 3.

Net exports of virtual water of 10 sectors in the year of 2002, 2007 and 2012. (Legend 1. Agriculture; 2. Forestry; 3. Animal husbandry; 4. Fisheries; 5. Mineral mining; 6. Manufacturing; 7. Electric power; 8. Construction industry; 9. Transportation and warehousing postal; 10. Service industry.)

Fig. 3.

Net exports of virtual water of 10 sectors in the year of 2002, 2007 and 2012. (Legend 1. Agriculture; 2. Forestry; 3. Animal husbandry; 4. Fisheries; 5. Mineral mining; 6. Manufacturing; 7. Electric power; 8. Construction industry; 9. Transportation and warehousing postal; 10. Service industry.)

Drivers of water use changes

The impact of the individual drivers on the water use changed in Zhangye city from 2002 to 2007 and from 2007 to 2012; the impacts were categorized into technological effects, economic effects, efficiency effects, and scale effects. Technological effects contributed to water use changes and water use reduction in agriculture. Normally, technological improvement reduces the water use of a product. However, the impact of technological contributions on water consumption for the most water-intensive industry weakened from 1.2 × 108 m3 over 2002–2007 to 0.6 × 108 m3 over 2007–2012. In the second-most intensive industry, the impact of the contribution of water-saving technology increased from 0.25 × 108 m3 over 2002–2007 to 0.3 × 108 m3 over 2007–2012 (Figure 4). However, the contribution of water-saving technology to the third-most intensive industry is not evident. Based on our results, we found that promoting the contribution of technology efficiency alongside the technological improvement in the agriculture industry is extremely challenging.

Fig. 4.

Contributions of structural effects, efficiency effects, scale effects, and technological effects to total water use changes during 2002–2007 (top) and 2007–2012 (bottom).

Fig. 4.

Contributions of structural effects, efficiency effects, scale effects, and technological effects to total water use changes during 2002–2007 (top) and 2007–2012 (bottom).

The effects of economic system efficiency, mathematically reflected by changes in the Leontief inverse matrix, represent the influence of inter-sectoral interdependence based on the supply and demand present in the economic system. Results showed that the economic system efficiency increases water use across sectors and periods, but most notably in the agricultural sector.

Structural effects denote the impact of sectoral distribution changes with regard to final demand. The structural effect of the primary industry is prominent over 2007–2012. The farming practices that emphasize developing seed production of hybrid maize in Zhangye city are typically associated with increased structural effects. After high-water-intensity crops were substituted with seed maize, the irrigating quota per unit area decreased in Zhangye city, but the total quota of some sub-zones increased because of the expansion of sowing areas. This situation was promoted by the farmers' pursuit of higher expected returns, which drove them to choose higher-profit crops or enlarge their sowing areas by using extra water.

Scale effects denote the total final demand changes’ impact on the water use. Results revealed that the scale effect of the primary industry stimulated the increase of total water use. However, the water use change over 2002–2007 was 2 × 108 m3, about twice that of the change over 2007–2012. This reduction is attributed to the difficulty in continuously improving the efficiency of water-saving technology. Meanwhile, the conserved water was used to reclaim the land. Cultivated land expansion led to the increase of total final demand for goods and services, dramatically altering the water use changes. These conclusions are also demonstrated by the land use change data from the Data Center of the Chinese Academy of Sciences (Table 3). Thus, the structure and scale of oasis agriculture development should be considered in the integrated management of the Heihe River Basin.

Table 3.

Land use/cover changes in Heihe River Basin during 2000–2012.

Land use type 2000
 
2012
 
Change of area during 2000–2012 
Area (hm2Percentage (%) Area (hm2Percentage (%) 
Cultivated land 5,307 4.15 5,807 4.55 500 
Forest land 5,883 4.61 5,878 4.60 −5 
Grassland 30,237 23.67 30,437 23.83 200 
Water area 1,517 1.19 1,490 1.17 −27 
Built-up area 470 0.37 520 0.41 50 
Unused land 84,316 66.01 83,598 65.45 −718 
Total area 127,730 127,730  
Land use type 2000
 
2012
 
Change of area during 2000–2012 
Area (hm2Percentage (%) Area (hm2Percentage (%) 
Cultivated land 5,307 4.15 5,807 4.55 500 
Forest land 5,883 4.61 5,878 4.60 −5 
Grassland 30,237 23.67 30,437 23.83 200 
Water area 1,517 1.19 1,490 1.17 −27 
Built-up area 470 0.37 520 0.41 50 
Unused land 84,316 66.01 83,598 65.45 −718 
Total area 127,730 127,730  

Source: Data Center of the Chinese Academy of Sciences.

Policy implications

More than 90% of the water use in Zhangye city comes from the Heihe River. As a result of ecological challenges aggravated by water shortages and overexploitation of groundwater, water resource reallocation between the midstream and the downstream area of Heihe River Basin has been implemented since 2001. Zhangye city has taken many measures to reduce water use in several key economic sectors and to ensure enough water flow to the lower basin since 2002. Therefore, in the economic system, water consumption should be reduced and, conversely, water use efficiency ought to be increased. However, in this study, we investigated the feedback between land-use dynamics and water-saving measures, with a strong focus on water use in irrigation. The water productivity increased from 8 yuan/m3 in 2002 to 15 yuan/m3 in 2012, but the total water use of the economic system increased by about 200 million m3. A rebound effect of these water-saving measures occurred in Zhangye city, which indicates that there was no other use of water-saving measures in the economic system. Water authorities should strengthen water management measures, such as implementing total quantity control and raising water use efficiency. The water market should be constructed to balance the water supply and demand beyond allocating water resources by the traditional planned economy. At the same time, integrated water resources management also should be implemented to regulate the expansion of cultivated land. Water and land resources competition and environmental degradation bring about severe pressure for effective management of natural resources. In particular, managers must consider the ensuing trade-offs between economic, environmental, and social factors and their spatio-temporal variability when implementing management policies.

Discussion and conclusions

Water use of economic systems is associated with the use of both internal and external water resources, which are consumed by the inhabitants of Zhangye city through final and intermediate products. The agricultural sector consumes the largest part of water resources in Zhangye city, which account for 90% of the total amount of water usage during 2002–2012. Net virtual water is a water supplement that satisfies the local final demand by importing commodities from the external markets. Local water resources are burdened by exporting high water-intensity commodities. Therefore, the trade structure should be adjusted to reduce the proportion of agricultural products. Arid regions greatly benefit from importing ‘virtual water’ in the form of food trade, but the situation in Zhangye city differs, since the region exports virtual water through the trade of agricultural products. Our study reveals that the strategies using virtual water in this region are unavailable, because water demands of the secondary and tertiary industries are weak and structurally unreasonable. Therefore, the profit from, and the demand for, seed maize encouraged famers and firms to expand their scale of production when water saving was negligible. The net water export of agricultural products was about 1,400 million m3 in 2012, which increased by about 600 million m3 from 2002 to 2012. Consequently, it is reasonable to consider reducing areas of high water-intensity crops as a possible and effective measure to mitigate the water crisis in Zhangye city.

Our decomposition analysis indicates that technological effects are most able to offset water use increases in Zhangye city. This conclusion coincides with the government's efforts to build a water-saving society in Zhangye city since 2002. However, the scale effects of the agricultural sector promoted water consumption from 2002 to 2012. As a result, water managers have long lamented their powerlessness over land-use forms that have detrimental impacts on the availability of ecological water use. Our study describes a more precise economic structure for water resource consumption and regional economic analysis at the midstream region of Heihe River Basin and identifies the water use co-evolution path in their socio-economic system from 2002 to 2012. Structural effects contribute to water savings in Zhangye city, but how to promote these structural changes should be explored further.

Some comprehensive studies have been conducted to identify the water needs of the physical environment, but long-term economic impacts of water use are unknown. Research should focus not only on the total amount of water consumption in economic systems, but also on its structures and processes. As a result of these current research priorities, stakeholders continue to have narrow sector perspectives, blocking information that should inform many decisions concerning water use.

The virtual water strategy is an effective tool for promoting regional water security and acceptable living standards by allocating water resources optimally on a larger scale in water-scarce areas. However, the core concept of virtual water promotes water use efficiency and drives water resources to flow to industry and service sectors. This said, rapid industrialization would become a significant competitor to the agricultural sector and water productivity would increase under industrial transformation. It is imperative for integrated water resource management in this basin to promote water use efficiency.

Acknowledgements

This research was financially supported by projects of the National Natural Science Foundation (NSFC) of China (91325302, 91425303, and 41671526) and Director Innovation Fund sponsored by the Institute of Geographical Sciences and Natural Resources Research.

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