Spatiotemporal variations of agricultural water footprint and its economic benefits in Xinjiang, northwestern China.

Agriculture is the largest water user and is the main driving force behind water stress in Xinjiang, northwestern China. In this study, the water footprint (WF) (blue, green and gray WF) of main crop production and their temporal and spatial characteristics in Xinjiang were estimated in 2006, 2010, 2014 and 2018. The blue water footprint deficit (BWFd) was conducted and food productivity and economic benefits of WF were also analyzed via the water consumption per output value (food productivity and economic benefits). The results reveal that the WF increased from 22.75 to 44.16 billion m3 during 2006-2018 in Xinjiang, of which cotton, corn and wheat are main contributors of WF. In terms of different regions, corn has the largest WF in north Xinjiang and cotton has the largest WF in south and east Xinjiang. The BWFd broadened from - 11.51 to + 13.26 billion m3 in Xinjiang with the largest increased BWFd in Kashgar (from - 3.35 to 1.40 billion m3) and Aksu (from - 2.92 to 2.23 billion m3) of south Xinjiang and in Shihezi (from - 0.11 to 2.90 billion m3) of north Xinjiang. In addition, the water footprint food productivity does not well correspond with the water footprint economic benefits in prefectures of Xinjiang. It means we should consider the food yields priority and economic benefits priority to formulate a scientific and effective supervisor mode to realize the sustainable management of agricultural water in prefectures of Xinjiang.

Introduction

Water shortage, an important issue of global sustainable development[1-3], is more pronounced in the arid regions where the environment is extremely harsh and water resources are extremely scarce[4] and large amount of water resources are used for agriculture irrigation[5-7]. For example, water for agriculture was accounting for 94.4% of total amounts in Xinjiang, northwest China (from Xinjiang Water Resources Bulletin 2016). Excessive use for irrigation water will occupy the ecological water requirement, which brings a great challenge for ecology security. Therefore, we should firstly know the agriculture water requirement and then establish the balance between the irrigation water and the ecological water requirement[8,9].

To quantify the irrigation water requirement for crop production, the water footprint (WF) was introduced by Hoekstra[10] and includes blue water footprint (WFblue), green water footprint (WFgreen) and gray water footprint (WFgray): WFblue is irrigation water from the surface and ground water, WFgreen is the consumed rainwater, WFgray is the volume of freshwater used to assimilate the load of pollutants based on existing ambient water quality standards[11]. This methodology has later been extensively applied to the global- and national-scale calculation for water footprint of multiple crops[6-15]. For example, Chapagain et al.[12] calculated the global consumption water for cotton is 256 Gm3 each year during 1997–2001, of which blue, green and gray is 42%, 39% and 19%, respectively. Zhou et al.[13] estimated the China’s averaged WF per capital and found the crop consumption reduced by 23% from 625 m3/cap in 1978 to 481 m3/cap in 2008. Among crops, more than half of the total WFblue within China was from rice (51%), followed by wheat (28%). Rice (32%) and wheat (20%) together also shared half of the total WFgreen. Liu et al.[6] assessed the total food consumption grows 35.4% from 147.0 to 162.9 million in Northwest China during 2000–2016. However, the WF related to food consumption only increased from 153.8 Gm3 to 159.6 Gm3 due to the improvement of water saving efficiency.

Researches of crops water footprint requirement (WFr) in Xinjiang has increased in recent decades[5,16-18]. Shen et al.[16] calculated the WFr in Tarim Basin and Junggar Basin and found it had a rapidly increasing trend with the highest value 172.2 × 108 m3 in 2010. Wang et al.[17] pointed out the WFr of Tarim Basin was 359 × 108 m3 in 2010 and 472 × 108 m3 in 2015. Li et al.[5] found the total WFr of Xinjiang was 389.9 × 108 m3 in 2018. Zhang et al.[18] proposed that the WFr increased from 73.91 × 108 m3 in 1988 to 270.50 × 108 m3 in 2015. We can find that the WFr calculated by different groups in the same year are inconsistent because of the selected different crops and parameters (e.g., irrigation coefficient). For example, Shen et al.[16] chosen wheat, corn, cotton, oil crops and soybeans, while wheat, corn, cotton, rice and fruit trees were selected in Wang et al.[17]. The averaged irrigation coefficient in Xinjiang was used by Shen et al.[16] and Wang et al.[17], while Li et al.[5] used the irrigation coefficient of different prefectures. Several obvious deficiencies are also discovered: (1) WFgray is the important contributor to Xinjiang production due to the extensive use of chemical fertilizer[19], but their data are relative scarce for Xinjiang crops; (2) few studies estimated the difference between the actual irrigation water and WFblue to measure the extent of blue water scarcity in Xinjiang; (3) the water footprint per unit of yield (WY) received more attention to reveal water productivity from the perspective of food production, while few studies describe water productivity from the perspective of economic benefits via the water footprint per output value (WV).

In this study, we are planning to address the above three issues: (1) the WFblue, WFgreen and WFgray for main 11 crops were calculated and their temporal and spatial characteristics were investigated in 2006, 2010, 2014 and 2018; (2) the new indicator-blue water footprint deficit (BWFd)[3] were used to reveal the actual situation of water shortage in Xinjiang; (3) the WF per unit of yield (WY) and WF per unit of output value (WV) were calculated to estimate water footprint food production and economic benefits in Xinjiang. Our works could enrich indicators about water footprint of crop production and also offer an optional way for agriculture saving water in Xinjiang.

Study area

Xinjiang (34°–49°N, 73°–96°E), located in the northwestern China, covers an area of approximately 166 × 104 km2 and accounts for 1/6 of the total area in China. It has 15 prefectures including Urumqi, Changji, Shihezi, Karamay, Turpan, Hami, Altai, Tacheng, Bozhou, Yili, Aksu, Bazhou, Kezhou, Hotan and Kashgar. Based on the topography, Xinjiang is classified into three regions (north, south and east Xinjiang) (Fig. 1). North Xinjiang has eight prefectures including Urumqi, Changji, Shihezi, Karamay, Altai, Tacheng, Bozhou and Yili. South Xinjiang has five prefectures (Aksu, Bazhou, Kezhou, Hotan and Kashgar). Turpan and Hami belong to East Xinjiang.

Figure 1

Distribution of farmlands, meteorological stations and prefectures in Xinjiang, China. Map is created in ArcGIS 10.1 and data are from National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://www.geodata.cn).

The climate is characterized by a temperate continental climate with mean annual precipitation of < 200 mm and mean annual temperature of 9.1 °C. The oases are mainly situated in the piedmont plains and their water resources primarily result from rivers originating from precipitation and from glacial and snow melt water in the mountainous regions (i.e., Tianshan, Altai and Kunlun Mountains). The cultivated lands are distributed in the oasis regions. Water use for agricultural irrigation has been accounted for > 90% of freshwater use in Xinjiang, which is much higher than the average level of China. The planting area and yield of 11 main crops in Xinjiang were shown in Supplementary Table S1. The irrigation area of Xinjiang increased from 3856.91 × 103 ha to 5573.16 × 103 ha during 2006–2018 with an increase of 44.50%. Correspondingly, the crop yield increased from 3189.73 × 107 kg to 4660.45 × 107 kg in this interval with an increase of 46.10%. The crops planting area and their yield accounted for both > 80% in total.

Results

Trends of water footprint (WF)

The WF in Xinjiang increased from 22.75 to 44.16 billion m3 with a rate of 2.0 billion m3 during 2006–2018 (Fig. 2a). The increased WF comes from the growing contributions of WFblue, WFgreen and WFgray. In detail, it significantly increased from 17.84 to 34.58 billion m3 for WFblue, from 1.50 to 3.12 billion m3 for WFgreen, and from 3.41 to 6.46 billion m3 for WFgray. However, the percentages of WFblue, WFgreen and WFgray are basically stable in the study interval: the ratio of WFblue decreased from 78.42 to 78.30%, that of WFgreen increased from 6.61 to 7.06% and that of WFgray decreased from 14.98 to 14.63%.

Figure 2

Total water footprint (WF) of crops in 2006–2018.

Spatial features of water footprint (WF)

In terms of three regions, WF in south Xinjiang increased from 12.05 to 22.34 billion m3 during 2006–2018 (Fig. 2b). It increased from 9.94 to 20.61 billion m3 in north Xinjiang (Fig. 2c) and increased from 0.76 to 1.21 billion m3 in east Xinjiang (Fig. 2d). All prefectures experienced an increasing trend of WF during 2006–2018. Aksu and Kashgar had the fastest increased rates (0.38 billion m3 and 0.35 billion m3 each year), while the rates of Karamay and Urumqi were relatively in low levels (6.80 × 106 m3 and − 6.20 × 105 m3 each year). Among these prefectures from 2006 to 2014, the WF all increased; from 2014 to 2018, the WF in Aksu, Altay, Kezhou, Shihezi, Tacheng and Yili also increased and decreased in other regions. In 2018, the highest WF occurred in Kashgar (8.34 billion m3) with a contribution rate of 18.88%; the lowest WF appeared in Karamay (0.16 billion m3) with a contribution rate of 0.35%.

The spatial characters of WF in 2006–2018 were shown in Fig. 3. The proportion of WF in south Xinjiang decreased from 52.95 to 50.59%, and it decreased from 3.34 to 2.73% in east Xinjiang, while it increased from 43.71 to 46.67% in north Xinjiang. In 2018, three prefectures with the highest proportion of WF in east, north and south Xinjiang were Hami (69.15%), Tacheng (23.13%) and Kashgar (37.32%), respectively.

Figure 3

Spatial distribution of water footprint (WF) in 2006–2018. Map is created in ArcGIS 10.1.

Water footprint (WF) of different crops

Cotton, corn and wheat are major contributors of WF in Xinjiang during 2006–2018. Their amounts increased of 55.19% from 23.14 to 35.91 billion m3. The WF of corn had the largest increase of 114.20% from 3.55 to 7.61 billion m3. The WF of rice had the smallest increase of 20.06% from 0.61 to 0.76 billion m3. The WF of soybeans, sugerbeet, potato, and medicago in Xinjiang decreased from 0.61 billion m3, 0.40 billion m3, 0.10 billion m3 and 1.38 billion m3 to 0.33 billion m3, 0.27 billion m3, 0.08 billion m3 and 1.24 billion m3, respectively (Fig. 4).

Figure 4

Total water footprint (WF) and contribution rate in Xinjiang during 2006–2018.

The contribution rates of WF were different in south Xinjiang, north Xinjiang and east Xinjiang (Fig. 4). In south and east Xinjiang, the largest contribution rate for WF among crops was cotton, accounting for 52.26–63.81%, while the smallest rate was potato, accounting for 0.10–0.72%. In north Xinjiang, the largest contribution rate was corn with an increase from 12.33 to 21%, while the contribution rates of wheat and vegetables respectively decreased from 16.33 and 6.81% to 12.79 and 3.61%. The smallest contribution rate was also potato, only accounting for 0.37–0.73%.

In terms of WFblue, corn is major contributor among crops and increases from 11.97 to 20.16% in north Xinjiang. Being converse with corn, the contribution rate of wheat has a decreasing trend from 14.44 to 11.08%. No obvious changes were showed in other crops. In south Xinjiang, the contribution rate of cotton increased from 55.83 to 63.02%, while that of corn and wheat decreased from 16.74 and 15.67% to 12.11 and 11.45%. In east Xinjiang, WFblue of cotton, corn and wheat decreased significantly from 60.40%, 3.63%, 12.30% to 53.44%, 1.16%, 10.10%.

In terms of WFgreen, the contribution rates of cotton and corn were increased from 32.29 and 15.18% to 39.16 and 24.16%, and it was decreasing in other crops with different rates, of which the contribution rate of wheat decreased obviously from 25.33 to 15.96% in north Xinjiang. Being consistent with changes of cotton in north Xinjiang, the contribution rate of cotton increased from 46.54 to 52.17% in south Xinjiang. Corn and wheat have decreasing trends from 19.23 and 22.71% to 16.26 and 16.80%, respectively. The observed changing trends of crops in east Xinjiang are similar with that in south Xinjiang.

In terms of WFgray, the contribution rate of cotton was decreasing from 47.30 to 37.90%, while that of corn increased significantly from 11.86 to 23.91% in north Xinjiang. The contribution rates of other crops were basically stable. The contribution rate of cotton was increasing from 50.35 to 51.65% in south Xinjiang. In east Xinjiang, the changeable trends of the contribution rate of crops were the same as those in south Xinjiang.

Based on the above analysis, the main contributions of WF come from cotton, corn and wheat in Xinjiang during 2006–2018. The increasing contributions of WF in north Xinjiang were from WFblue and WFgray of corn and WFgreen of cotton and corn, while those in south Xinjiang and east Xinjiang were from WFblue, WFgreen and WFgray of cotton. The contribution rate of WFblue was much higher than that of WFgreen and WFgray, which suggests these planting crops were mainly depended on irrigation water in Xinjiang.

Blue water footprint deficit (BWFd)

During 2006–2010, the BWFd increased from − 11.51 to − 6.28 billion m3 due to the expansion of planting areas. Although the water-saving technologies are beginning to be applied (e.g., dropper technology) in Xinjiang, this was not enough to offset the rapid increase of water demand due to the expansion of irrigation farmland since 2010. The rapid expanded irrigation farmland results in the larger BWFd from − 6.28 billion m3 in 2010 to 13.26 billion m3 in 2018, leading to more severe shortage of blue water in Xinjiang.

Regarding the different prefectures in three regions (Fig. 5), the BWFd in south Xinjiang was lower than that in north Xinjiang. In south Xinjiang, the largest increases of BWFd were showed in Kashgar (from − 3.35 billion m3 in 2006 to 1.40 billion m3 in 2018) and Aksu (from − 2.92 billion m3 in 2006 to 2.23 billion m3 in 2018). Bazhou has been in the state of BWFd with an increasing trend from 0.06 billion m3 in 2006 to 2.16 billion m3 in 2018. The increased BWFd was also found in Kezhou from − 0.07 billion m3 in 2006 to 0.02 billion m3 in 2018. Hotan has been in the condition of the blue water surplus during 2006–2018. In north Xinjiang, the blue water surpluses were found in Urumqi and Altai during 2006–2018. The blue water surplus was found in Yili before 2014, while the state of blue water deficit was found in Bozhou and Shihezi since 2010. Tacheng and Changji were always in the blue water deficit in the studied interval. The largest increasing BWFd was showed in Tacheng from 0.65 billion m3 in 2006 to 2.32 billion m3 in 2018. In east Xinjiang, the blue water surplus was found in Turpan, while Hami was in the deficit condition of BWFd during 2006–2018.

Figure 5

Blue water footprint deficit (BWFd) in prefectures of Xinjiang.

Water footprint productivity

Water footprint per unit of yield (WY)

The WY has two trends in the study interval: an increased trend from 0.69 m3/kg in 2006 to 0.81 m3/kg in 2014 and then decreased to 0.80 m3/kg in 2018 (Fig. 6). In terms of WYgreen, WYblue and WYgray, they all increased during 2006–2018. Specifically, WYgreen increased from 0.05 to 0.06 m3/kg, WYblue increased from 0.54 to 0.63 m3/kg, and WYgray increased from 0.10 to 0.12 m3/kg. Being inconsistent with the changeable trends of WYgreen, WYblue and WYgray, their ratios changed from 6.68 to 7.88%, from 78.77 to 76.31%, and from 14.55 to 15.81%, respectively. In north Xinjiang, the WY increased from 0.53 to 0.73 m3/kg, of which the ratio of WYgreen decreased from 11.51 to 9.10%, WYblue increased from 73.98 to 77.06%, and WYgray decreased from 14.51 to 13.83%. In south Xinjiang, the WY decreased from 0.91 to 0.88 m3/kg, of which the ratio of WYgreen increased from 2.84 to 5.23%, WYblue decreased from 81.52 to 79.57%, and that of WYgray remained at around 15%. In east Xinjiang, the WY decreased from 0.81 to 0.70 m3/kg, of which the ratio of WYgreen increased from 2.00 to 5.92%, WYblue decreased from 87.21 to 76.26%, and WYgray increased from 10.77 to 17.81%. In terms of prefectures (Fig. 6), WY of Shihezi was the largest (2.07 m3/kg), while that of Urumqi was the smallest (0.21 m3/kg) in 2018. During 2006–2018, the larger increases of WY were showed in Altai (from 0.39 to 0.89 m3/kg) and Shihezi (from 1.10 to 2.07 m3/kg), while the obviously decreased WY were presented in Karamay (from 3.76 to 1.09 m3/kg) and Turpan (from 0.73 to 0.41 m3/kg).

Figure 6

Spatial distribution and structure of water footprint per unit of yield (WY). Map is created in ArcGIS 10.1.

In terms of crops, the averaged WY from high to low in turn were cotton (0.44 m3/kg), corn (0.13 m3/kg), wheat (0.12 m3/kg), vegetable (0.05 m3/kg), oil crops (0.04 m3/kg), medicago (0.03 m3/kg), rice (0.02 m3/kg), bean (0.02 m3/kg), melons (0.02 m3/kg), sugarbeet (0.01 m3/kg) and potato (0.002 m3/kg) (Fig. 7). In terms of the changing trends for crops, the largest decrease of 68.18% from 0.02 to 0.01 m3/kg was showed in soybean, while the smallest decrease of of 5.71% from 0.12 to 0.11 m3/kg was found in wheat. Corn has the largest increase from 0.11 to 0.16 m3/kg.

Figure 7

Water footprint per unit of yield (WY) in different crops.

Water footprint per output value (WV)

The WV reduced from 4225.03 m3/104 Yuan in 2006 to 2387.72 m3/104 Yuan in 2018 (Fig. 8). The ratio of WVblue dropped from 78.77 to 76.31%, while the ratios of WVgreen and WVgray increased from 6.68 and 14.55% to 7.88 and 15.81%, respectively. These changes are consistent with the trends of WY (Fig. 6). The similar trends of WV are found in south and north Xinjiang. Specifically, the WV reduced from 4302.50 m3/104 Yuan to 2169.12 m3/104 Yuan in south Xinjiang with a rate of 49.58%, and it reduced from 4031.39 m3/104 Yuan to 2038.82 m3/104 Yuan in north Xinjiang with a rate of 49.42%. Being converse with the trend of south and north Xinjiang, the WV increased from 761.29 m3/104 Yuan to 1047.82 m3/104 Yuan in east Xinjiang characterized by a rate of 37.64%. All prefectures (except Hami) have a decreasing trend of WV. The largest decline from 5271.64 m3/104 Yuan to 2010.34 m3/104 Yuan was observed in Shihezi. The second largest decline from 4908.22 to 2044.67 m3/104 Yuan was in Kashgar.

Figure 8

Spatial distribution and structure of water footprint per unit of GDP (WV). Map is created in ArcGIS 10.1.

Regarding the contribution rate in three regions (Fig. 8), the rate slightly decreased for WVgreen from 9.46 to 8.42% and increased for WVgray from 14.21 to 15.31% in north Xinjiang. The ratio of WVblue remained stable at around 76%. In south Xinjiang, the ratio of WVblue decreased from 80.74 to 78.73%. The ratio of WVgreen increased from 3.58% in 2006 to 9.86% in 2010 and then decreased to 6.37% in 2018. The ratio of WYgray decreased from 15.68 to 14.89%. In east Xinjiang, the ratios of WVgreen and WVgray increased from 1.53 and 6.12% to 11.68 and 17.64%, respectively. The ratio of WVblue decreased from 86.99 to 76.23% during 2006–2018.

The averaged WV for crops were showed from high to low: cotton (1532.91 m3/104 Yuan), corn (447.35 m3/104 Yuan), wheat (440.76 m3/104 Yuan), vegetable (160.04 m3/104 Yuan), oil crops (123.32 m3/104 Yuan), medicago (104.37 m3/104 Yuan), bean (60.33 m3/104 Yuan), rice (55.83 m3/104 Yuan), melons (52.01 m3/104 Yuan), sugarbeet (30.03 m3/104 Yuan) and potato (10.56 m3/104 Yuan) (Fig. 9). The WV of cotton had a tendency of decreasing, increasing and then decreasing. The WV of other crops decreased continuously. Being consistent with the ratios of WYgreen, WYblue and WYgray, the ratio of WVblue was the highest (mean 40.78%) in cotton, while the lowest (mean 0.25%) was found in potato.

Figure 9

Water footprint per unit of GDP (WV) in different crops.

Discussion

Water footprint and blue water footprint deficit

The main crop acreage in Xinjiang quickly amplified from 3.86 × 106 ha in 2006 to 5.57 × 106 ha in 2018, of which the yield of main crops increased from 3.19 × 1010 kg in 2006 to 4.66 × 1010 kg in 2018. It would inevitably result in a rise of WF from 22.75 to 44.16 billion m3 (Fig. 2). The rapid expansion of agricultural planting scale is the fundamental reason for the large increase of crops WF in Xinjiang[8,20,21]. The WF were showed from high to low in Xinjiang: WFblue > WFgray > WFgreen. It means that WFblue is the most important water consumption and the role of WFgray should be concerned in next researches because of WFgray > WFgreen. In terms of the changeable rates, their increasing trend is also WFblue (160.20 million m3/yr) > WFgray (26.91 million m3/ yr) > WFgreen (1.10 million m3/yr).

In terms of the increased rates of WF in three regions, they were significantly different: south Xinjiang (0.79 billion m3/yr) > north Xinjiang (0.82 billion m3/yr) > east Xinjiang (0.03 billion m3/yr) (Fig. 3). The WF in south Xinjiang (22.34 billion m3 in 2018) is consistently higher than that in north Xinjiang (20.61 billion m3 in 2018) in the studied interval, the gap between them was further shrinking from 2.11 billion m3 in 2006 to 1.73 billion m3 in 2018 due to its better agricultural development conditions, faster agricultural infrastructure construction and better large-scale operation foundation in north Xinjiang[16]. Correspondingly, the increased rate is WFblue > WFgray > WFgreen in three regions. For WFblue and WFgray, the rates are south Xinjiang > north Xinjiang > east Xinjiang. It means that the crop irrigation water consumption and fertilizer consumption in south Xinjiang were higher than those in north Xinjiang. For WFgreen, the rates are north Xinjiang > south Xinjiang > east Xinjiang. The increasing rates are consistent with significantly increasing precipitation in Xinjiang during 2006–2018[22], which lead to higher effective precipitation (90–95%) in the conditions of the small amount of deep seepage and the majority surface-soil interception[8]. The expanded planting area also plays an significant role in an increase of WFgreen, which makes the area of crops can withstand precipitation increase and then makes the utilization of effective precipitation increase correspondingly[18,19]. In addition, the replacement of natural oases by many expansion of planting areas results in the conversion of ecological environmental water into artificial consumption in terms of water consumption[8].

In Xinjiang, the BWFd had an increased level from − 0.18 billion to 25.56 billion m3 during 2006–2018. The BWFd of north Xinjiang (8.24 billion m3) and south Xinjiang (4.65 billion m3) were totally higher than that in east Xinjiang (0.38 billion m3). In terms of prefectures (Fig. 5), Aksu (2.23 billion m3), Bazhou (2.16 billion m3) and Kashgar (1.40 billion m3) experience the heaviest blue water deficit in south Xinjiang, while Bozhou (1.31 billion m3), Shihezi (2.90 billion m3), Tacheng (2.32 billion m3) and Changji (2.07 billion m3) experience the heaviest blue water deficit in north Xinjiang in 2018. This means these prefectures are the agricultural water-saving core area. Combined with the crop structures in prefectures, it is vital to optimize the planting structures of crops and to improve the irrigation coefficient and related management level with the purpose of slowing down the growth rate of WF in the blue-water-deficit prefectures of Xinjiang.

Food productivity and economic benefits of water footprint

The issues of food safety have received increasing attention in the context of the explosive growth of population in Xinjiang and the availability of fresh water is the biggest challenge to food production. GDP is mainly affected by the fluctuating crop prices and the labor cost. From different angles (food productivity and economic productivity) of water footprint, it provides an alternative way for Xinjiang agriculture to save water.

As shown in Figs. 6, 7, 8, 9, three types were found in the relationship between WY and WV. Firstly, WY and WV mutual matched among different crops. In 2018, the maximum WY (0.49 m3/kg) and WV (2490.35 m3/104 Yuan) are found in cotton, and the minimum WY (0.0030 m3/kg) and WV (15.30 m3/104 Yuan) are showed in potato. The similar correspondences were also found among other crops. Secondly, WY and WV matched in different regions. In 2006, WY from large to small was 0.91 m3/kg in south Xinjiang, 0.81 m3/kg in east Xinjiang, and 0.53 m3/kg in north Xinjiang, while WV was 4302.50 m3/104 Yuan in south Xinjiang, 4031.39 m3/104 Yuan in north Xinjiang, 761.29 m3/104 Yuan in east Xinjiang. The consistent correspondent relationships were found in other years. Thirdly, WY and WV mismatched in different prefectures. In 2018, the WV was largest in Shihezi (2.07 m3/kg), while the largest WV was in Aksu (3284.26 m3/104 Yuan). This means water footprint food productivity in Aksu was lower than that in Shihezi, but the water footprint economic productivity was reversed. Two aspects should be proposed based on the above analysis: (1) food productivity is well corresponded with economic benefits among crops and three regions, which means WV or WY plays a equivalent role in government and farmers’ decisions about crop planting structures in Xinjiang; (2) different policies should be made from different perspectives (food productivity and economic benefits) in prefectures of Xinjiang, being consistent with the results of Zhangjiakou City[3].

Next works

Xinjiang WF experienced a continuous increasing trend during 2006- 2018. The rapid expansion of agricultural planting scale is the fundamental cause for a significant increase of WF for crops in Xinjiang. Under the condition of available water shortage in Xinjiang, we focus on a scientific view for the adjustment and transformation of crop structures to reasonably allocate water resources in Xinjiang. However, two following aspects should be done in future: (1) the spatial–temporal matching characteristics between water footprint and socioeconomic factors in each prefecture are needed to analyse using mathematical models (e.g., Gini coefficient and imbalance index[23]); (2) the specific planting area of crops are available via the remote sensing and the field investigation. Emphasizing comprehensive consideration of a variety of social and economic factors and detailed planting distribution of crops, we can provide a detailed plan to put forward suitable measures and policies to adjust the crop structure for sustainable agricultural development in prefectures of Xinjiang.

Data sources and methods

Data sources

Total 66 meteorological stations for Xinjiang were collected from China Meteorological Administration (http://data.cma.cn/). The selected parameters include the maximum temperature, the minimum temperature, mean monthly temperature, mean monthly precipitation, wind speed, air pressure, relative humidity and sunlight duration. The land use/cover data were downloaded from National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://www.geodata.cn). The NLCD maps (1 km) were produced by visual interpretation of Landsat Thematic Mapper (TM) images[24]. Socioeconomic data (crop types, planting areas, crops yields and regional GDP) were compiled from Xinjiang Statistics Yearbook (China). Irrigation water consumption for prefectures in Xinjiang were obtained from Xinjiang Water Resources Bulletin (2006, 2010, 2014 and 2018).

Methods

Experimental design

The water requirements of 11 crops in their growing period were firstly calculated using the CROPWAT 8.0 and then the temporal and spatial features of water footprint of crop production were estimated in 2006, 2010, 2014 and 2018. Combined with the irrigation water consumption, the blue water footprint deficits were calculated to reveal the situation of blue water. Finally, water footprint per unit of yield and water footprint per unit of GDP were estimated to depict water productivity from the perspective of food production and economic benefits in Xinjiang.

Data processing

Water footprint (WF) for crop production

It consists of blue water footprint (WFblue), green water footprint (WFgreen) and gray water footprint (WFgray). The total WF of 11 major crops in Xinjiang is evaluated based on the calculation method of water footprint showed in[25]:where WFblue is surface and ground water consumed (evaporated) by the production of a commodity; WFgreen is the consumption of green water during the growing period of crops, green water is actually the total amount of rain evaporation. WFgray is a product refers to the amount of fresh water required to assimilate contaminants according to existing environmental water quality standards.

Green water footprint (WFgreen) and blue water footprint (WFblue)

To calculate WFgreen and WFblue, reference crop evapotranspiration (ET0) was calculated through meteorological elements and crop evapotranspiration (ETc) was calculated through crop regulation coefficient (Kc)[26]. Crop evapotranspiration includes evaporation of soil surface and transpiration of crop. The specific formula is as follows[26].

In this equation, ETcrop is crop evapotranspiration (mm/day); ETblue is the evapotranspiration of crop blue water; ETgreen represents the evapotranspiration of green water; Kc is the crop regulation coefficient (dimensionless); ET0 is the reference crop evapotranspiration (mm/day); factor 10 is the conversion of the depth unit mm to the volume unit m3 of water; A is the crop planting area; is the total evapotranspiration in the growing period of crops from the sowing date (the first day) to the harvest date, lgP represents the number of days in the growing period.

ETgreen was determined by comparing the potential evapotranspiration and effective precipitation (Pe) during the growing period of crops, when ETc > Pe, ETgreen = Pe, ETblue = ETc-Pe; When ETc < Pe, ETgreen = ETc, ETblue = 0.

Gray water footprint (WFgray)

In this study, we adopts the groundwater quality standard (GB/T14848-93) and water quality standard for irrigation (GB5084-2005) in China, that is, nitrate (N) is less than 0.02 g/L, farmland irrigation water salinity in general should not be higher than 1.7 g/L. We selected Cmax = 1.7 g/L, the ambient background concentration of nitrogen is assumed to be 0, and the specific calculation formula of gray water is as follows[27]:

where WFgray is the gray water footprint (m3); AR is the pure amount of nitrogen fertilizer, kg; Ə is the nitrogen leaching rate, %; Cmax is the maximum environmental allowable concentration of nitrogen fertilizer (kg/m3); Cnat is the initial concentration of pollutants in water (kg/m3).

Blue water footprint deficit (BWFd)

Due to water shortage and imperfect water supply infrastructures, crops can’t always be fully irrigated in Xinjiang, WFblue may not record the extent of blue water scarcity. In order to distinguish the actual blue water footprint consumption (WFblue′) from the crops requirement of blue water footprint, we used the blue water footprint deficit (BWFd) introduced by Ma et al.[3] in this study, which refers to the difference between WFblue′ and WFblue.

When BWFd < 0, it means a situation of blue water surplus. When BWFd > 0, it means a situation of blue water shortage.where Wi refers to the irrigation water, ƞ is the effective utilization coefficient in each prefecture.

Water footprint per unit of yield (WY)

The WF per unit of yield (WY) is the WF divided by the crop yield (Y) and includes WFblue per unit of yield (WYblue), WFgreen per unit of yield (WYgreen) and WFgray per unit of yield (WYgray)[3].

Water footprint per unit of GDP (WV)

The WF per unit of GDP (WV) is the WF divided by GDP[3]. It also includes three parts (WVblue, WVgreen and WVgray), which reflects the economic benefits of WF.

Data analysis

According to the calculated results, we analyzed the temporal and spatial features of WF, BWFd, WY and WV in 2006, 2010, 2014 and 2018. The characters in these data among crops were also noted.

Supplementary Information.