The effect of development in water-saving irrigation techniques on spatial-temporal variations in crop water footprint and benchmarking

Wang, Wei; Zhuo, La; Li, Meng; Liu, Yilin; Wu, Pute

doi:10.1016/j.jhydrol.2019.123916

Cited by 53 publications

(33 citation statements)

References 40 publications

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“…The water footprint studies in China have primarily calculated water footprints at the River Basin level, the provincial level, and the urban level, such as Deng (2014), Wang and Li (2016), Li (2017), and Feng (2018) that calculated and analyzed the water footprint of Shanghai and Chongqing, Weihe River Basin, the urban agglomeration in the middle reaches of the Yangtze River, Shanxi, and other places, respectively [30][31][32][33]. Regarding the literature on the influencing factors of the water footprint, scholars have found various factors affecting the water footprint, including economic development level, industrial structure, urbanization, technological innovation, consumption level, water resources endowment, water use efficiency, human capital, foreign trade, and climate conditions (Zhang et al, 2015, Paolo et al, 2016, Ali et al, 2016, Zhu et al, 2016, Xie et al, 2019 [34][35][36][37][38][39][40][41]. Closely related to this paper is that Lv (2017, 2018) measured the inward foreign direct investment (IFDI) in China by using the foreign capital dependence for empirical research, and the results showed that China's IFDI (Inward Foreign Direct Investment) promotes the improvement of water footprint.…”

Section: Water Footprint Measurement and Its Influencing Factors (Nonmentioning

confidence: 99%

Empirical Study of the Impact of Outward Foreign Direct Investment on Water Footprint Benefit in China

Kan

Huang

2019

Sustainability

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How to enhance the water footprint benefit in conjunction with outward foreign direct investment (OFDI) is of great significance to reconcile the contradiction between supply and demand of water resources. This paper examines the effect of OFDI on the water footprint benefit using system GMM (Generalized Method of Moments) on a dynamic panel data. The results revealed that, in general, OFDI was not conducive to enhancing social, spatial, and environmental benefits of China’s water footprint, but was conducive for improving water footprint economic benefits. The results also showed that different types of OFDI exert differential effects on water footprint benefits. Specifically, the market-seeking and resource-seeking types of OFDI are not conducive for enhancing social and spatial benefits of China’s water footprint, but have improved (although not significantly) economic benefits of the water footprint. However, the market-seeking type of OFDI is conducive for improving environmental benefits of the water footprint, while the resource-seeking OFDI is not conducive for improving environmental benefits of the water footprint. In addition, the technology-seeking OFDI is conducive to the social, economic, spatial, and environmental benefits of China’s water footprint. Furthermore, the path-wise OFDI (investing in developing countries) is not conducive to enhancing social, spatial, and environmental benefits of China’s water footprint, but has improved (although not significantly) the economic benefits of China’s water footprint. On the other hand, the inverse OFDI (investing in developed countries) is conducive to China’s water footprint including its social, economic, spatial, and environmental benefits. The findings from this study have relevant policy implications and can help provide some policy prescriptions for an economy such as China to engage in OFDI and enhance water footprint benefits. For instance, in addition to expanding market-seeking and resource- seeking OFDI, China should actively increase the scale of technology-seeking OFDI. In addition, while continuing to expand path-wise OFDI, China should further increase the scale of inverse OFDI. By taking advantage of the complementary and synergetic effects of different types of OFDI, an economy can capture the whole effects of OFDI to reap the water footprint’s full social, economic, spatial, and environmental benefits.

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Section: Water Footprint Measurement and Its Influencing Factors (Nonmentioning

confidence: 99%

Empirical Study of the Impact of Outward Foreign Direct Investment on Water Footprint Benefit in China

Kan

Huang

2019

Sustainability

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“…The dates of planting of crops referred to Chen et al (1995). The harvest indexes were taken from Xie et al (2011) and Zhang and Zhu (1990). Crop growth periods and maximum root depths were taken from Allen et al (1998) and Hoekstra and Chapagain (2007).…”

Section: Data Sourcesmentioning

confidence: 99%

Physical versus economic water footprints in crop production: a spatial and temporal analysis for China

Yang

Zhuo

Xie

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. A core goal of sustainable agricultural water resources management is to implement a lower water footprint (WF), i.e. higher water productivity, and to maximize economic benefits in crop production. However, previous studies mostly focused on crop water productivity from a single physical perspective. Little attention is paid to synergies and trade-offs between water consumption and economic value creation of crop production. Distinguishing between blue and green water composition, grain and cash crops, and irrigation and rainfed production modes in China, this study calculates the production-based WF (PWF) and derives the economic value-based WF (EWF) of 14 major crops in 31 provinces for each year over 2001–2016. The synergy evaluation index (SI) of PWF and EWF is proposed to reveal the synergies and trade-offs of crop water productivity and its economic value from the WF perspective. Results show that both the PWF and EWF of most considered crops in China decreased with the increase in crop yield and prices. The high (low) values of both the PWF and EWF of grain crops tended to cluster obviously in space and there existed a huge difference between blue and green water in economic value creation. Moreover, the SI revealed a serious incongruity between PWFs and EWFs both in grain and cash crops. Negative SI values occurred mostly in north-west China for grain crops, and overall more often and with lower values for cash crops. Unreasonable regional planting structure and crop prices resulted in this incongruity, suggesting the need to promote regional coordinated development to adjust the planting structure according to local conditions and to regulate crop prices rationally.

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“…Scholars have studied the impact of climate change (Bocchiola et al, 2013) [1], policy change (Fulton et al, 2014) [2], human capital (Ali et al, 2016) [3], gross national income (Miglietta et al, 2017) [4], water harvesting technology (Mohammad et al, 2018) [5], agricultural expansion (Nouri et al, 2019) [6], and trade openness (Mourad et al, 2019) [7] on a country's water footprint. In the context of the Chinese economy, scholars have found that population factors [8], economic development levels (Zhao et al, 2014) [9], water-conservation technology (Zhi et al, 2014) [10], international trade (Yang et al, 2015) [11], inward and outward foreign direct investment (Zhang et al, 2015;Kan and Huang, 2019) [12,13], climatic conditions (Yang et al, 2016) [14], consumption levels [15], industrial structure (Xie et al, 2019) [16], water-use efficiency (Kan and Lv, 2019) [17], geographical location [18], and shale-gas development (Xu et al, 2019) [19] are important influencing factors on the water footprint. The studies have not explicitly examined urbanization as an influencing factor on the water footprint.…”

Section: The Influencing Factors On Water Footprintmentioning

confidence: 99%

An Empirical Study of the Impact of Urbanization on Industry Water Footprint in China

Kan

Huang

2020

Sustainability

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How to advance new urbanization initiatives and reduce the water footprint of industries is one urgent issue about urbanization that needs to be resolved. Based on spatial dynamic panel data, we used the system GMM (Generalized Method of Moments) to study the impact of urbanization on the industrial water footprint. The results show that, overall, urbanization increases the industrial water footprint, industrial virtual water footprint, and industrial gray water footprint in China. There are sectoral and regional differences in the impact of urbanization. Specifically, urbanization reduces the agricultural water footprint and agricultural virtual water footprint but raises the agricultural gray water footprint. Urbanization increases the manufacturing water footprint, manufacturing virtual water footprint, and gray water footprint. Urbanization reduces the virtual water footprint of the service industry but increases the water footprint and gray water footprint in the service industry. At the regional level, urbanization increases the industrial water footprint and gray water footprint across the three major regions. In the eastern region, urbanization has little effect on increasing the industrial water footprint, and reduces the industrial virtual water footprint, whereas in the central and western regions urbanization increases the industrial virtual water footprint. In all three regions, urbanization reduces the agricultural water footprint, increases the manufacturing and service water footprints, reduces the virtual water footprints of agriculture and services, and increases the gray water footprint of agriculture, manufacturing, and services. In the eastern region, the reducing effect of urbanization is the greatest and the increasing effect of urbanization is the smallest. Additionally, in the eastern region, urbanization has reduced the virtual water footprint of manufacturing, whereas in the central and western regions urbanization has increased the virtual water footprint of manufacturing.Sustainability 2020, 12, 2263 157 consumption, and the per capita water consumption of 15 provinces was higher than the national 158 average. In terms of sectors, Xinjiang had the largest total agricultural water consumption, Beijing 159 had the least total agricultural water consumption, and the total agricultural water consumption of 160 14 provinces was higher than the national average level. Jiangsu had the largest total manufacturing 161 water consumption, Tibet had the least total manufacturing water consumption, and the total 162 manufacturing water consumption of 12 provinces was higher than the national average level. 163Guangdong had the largest total service water consumption, Tibet had the least total service water 164 consumption, and the total service water consumption of 14 provinces was higher than the national 165 average. 166

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The effect of development in water-saving irrigation techniques on spatial-temporal variations in crop water footprint and benchmarking

Cited by 53 publications

References 40 publications

Empirical Study of the Impact of Outward Foreign Direct Investment on Water Footprint Benefit in China

Empirical Study of the Impact of Outward Foreign Direct Investment on Water Footprint Benefit in China

Physical versus economic water footprints in crop production: a spatial and temporal analysis for China

An Empirical Study of the Impact of Urbanization on Industry Water Footprint in China

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