Grey Footprint of Winter Wheat-Summer Maize Rotation System in North China Plain and Its Variability in County Scale

Yu, 张宇 Zhang; Yunkai, 李云开 Li; Zhiyun, 欧阳志云 Ouyang; Jianguo, 刘建国 Liu

doi:10.5846/stxb201405211051

Cited by 5 publications

(6 citation statements)

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“…By calculating the results, it was found that the main factors that contributed to a high WF grey for wheat in North China were the high leaching nitrogen application rates. This finding is in agreement with the result of high nitrogen application proposed by Zhang et al [9]. The main factors determining high WF grey in Northwest China were large leaching nitrogen application rates, as shown in Figure 5a.…”

Section: Grey Water Footprint Influencing Factorssupporting

confidence: 92%

“…Grain crops have the highest WFgrey caused by nitrogen loads among crops, which is followed by vegetables. Domestic WFgrey studies focused on the calculation and evaluation of agricultural WFgrey caused by pollution of chemical fertilizers and pesticides at regional scales [9,10]. Zhang et al [9] used fixed leaching rates to calculate the WFgrey of the winter wheat-summer maize rotation, caused by the nitrogen fertilizer application in the North China Plain from 1986 to 2010, and analyzed the temporal and spatial differences.…”

Section: Introductionmentioning

confidence: 99%

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Spatial Characteristics and Implications of Grey Water Footprint of Major Food Crops in China

Wang

Zhang

Liu

et al. 2019

Water

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The estimated, effective increase of agricultural fertilizer applied in China by 10.57 Mts from 2006 to 2016 is a crucial factor affecting the water environment. Based on analyzing the nitrate-leaching rate, the nitrogen-fertilizer application rate, and crop yield in wheat and maize key cultivation divisions in China, this paper applied the grey water footprint analytical method to estimate THE grey water footprint and its proportion to total water footprint and analyzed the spatial differences from 2012 to 2016. Results showed that the grey water footprint of wheat was higher in North and Northwest China with an increasing trend, while that of maize was higher in Southwest and Northwest China because of high nitrogen application rates and low yields in these regions. Except for the Southwestern division, wheat's grey water footprint was about 1.3 times higher than the blue water footprint, while, for maize, it was two to three times higher. When analyzing and planning water demand for crop irrigation, the water required for nonpoint source pollution due to chemical fertilizers should be considered. Focusing blue water (irrigation) alone, while neglecting green water and ignoring grey water footprints, it might lead to overestimation of available agricultural water resources and failure to meet the goals of sustainable use of water resources.

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Section: Grey Water Footprint Influencing Factorssupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Spatial Characteristics and Implications of Grey Water Footprint of Major Food Crops in China

Wang

Zhang

Liu

et al. 2019

Water

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“…These products included eight food crops and cash crops. Their VW c values are listed in Table 1 [38][39][40][41]. The virtual water content of livestock products (VW a ) refers to the water consumption in the life cycle of livestock production during feeding.…”

Section: Virtual Water Content Of Agriculture and Livestock Productsmentioning

confidence: 99%

Risk Assessment and Pressure Response Analysis of the Water Footprint of Agriculture and Livestock: A Case Study of the Beijing–Tianjin–Hebei Region in China

Cao

2019

Sustainability

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Excessive water consumption, associated with regional agriculture and livestock development and rapid urbanization, has caused significant stress to the ecological health and sustainable use of water resources. We used the water footprint theory to quantify the spatiotemporal characteristics and variation in the water footprint of agriculture and livestock (WF-AL) in the Beijing–Tianjin–Hebei region of China (2000–2016). We predicted the spatial distribution and sustainability of regional water resources at different levels of annual precipitation. Results showed that the average county WF-AL rose from 8.03 × 108 m3 in 2000 to 10.89 × 108 m3 in 2016. There was spatial heterogeneity compared to the average city WF-AL. The WF-AL varied between the mountains and the plains. The scale of the WF-AL was one of the main reasons for differences in the consumption and distribution of water resources. The development of regional water resources deteriorated from a stable state to an unstable state from 2000 to 2016. Only 5.8% of the areas maintained a stable state of water resources. Even in the predicted wet years, no improvements were found in the instability of water resources in four areas centered on the counties of Xinji, Daming, Luannan, and Weichang. To achieve a medium and long-term balance between WF-AL development and water resource recovery, the WF-AL should be limited and combined with reservoir and cross-regional water transfer.

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“…Nitrogen (the most substantial component of the fertilizers) is used as the case pollutant to account for AGNPS pollution [25][26][27]. In this study, a chemical fertilizer application was deployed as the main pollutant; nitrogen loss was adopted as the main pollutant indicator; and, however, pesticide application was not considered due to its complexity [28,29].…”

Section: Export Coefficient Modelmentioning

confidence: 99%

“…E is the export coefficient for nutrient source i; A is the area of catchment occupied by crop i, where the main crops in the HLRA include rice, corn, soybean and wheat; I is the input of nutrients to source i; and P is the input of nutrients out of rainfall (omitted here) [19]. Nitrogen (the most substantial component of the fertilizers) is used as the case pollutant to account for AGNPS pollution [25][26][27]. In this study, a chemical fertilizer application was deployed as the main pollutant; nitrogen loss was adopted as the main pollutant indicator; and, however, pesticide application was not considered due to its complexity [28,29].…”

Section: Export Coefficient Modelmentioning

confidence: 99%

Decoupling Agricultural Nonpoint Source Pollution from Crop Production: A Case Study of Heilongjiang Land Reclamation Area, China

Yang

Liu

2017

Sustainability

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Abstract:Modern agriculture often leads to nonpoint source pollution. From the perspective of a decoupling analysis, this research evaluates the relationship between crop production and agricultural nonpoint source pollution (via fertilizer application), using the Heilongjiang land reclamation area as a case study. As it is the largest commodity grain base and green food base in China, more than 80% of water pollution in this area comes from fertilizer application. This study adopts an export coefficient model to hindcast nitrogen loss delivered to surface water via fertilizer application and conduct a further analysis of decoupling agricultural nonpoint source pollution from crop production. The results indicated that weak decoupling frequently occurred. However, this tendency was not steady in the period 2001-2012, and weak decoupling was typical in each branch based on the average value. Regarding the example of decoupling agricultural nonpoint source pollution from rice production, weak decoupling occurred more often, but this tendency was not steady over time. In addition, expansive coupling occurred in 2006, 2010 and 2012, and there were no definite signs of it improving. All branches, except for the Suihua branch, reached the degree of weak decoupling. A basic fact is that a decoupling tendency and environmental deterioration coexist in both the past and present. The decoupling analysis will contribute to localized strategies for sustainable agricultural development.

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Grey Footprint of Winter Wheat-Summer Maize Rotation System in North China Plain and Its Variability in County Scale

Cited by 5 publications

References 0 publications

Spatial Characteristics and Implications of Grey Water Footprint of Major Food Crops in China

Spatial Characteristics and Implications of Grey Water Footprint of Major Food Crops in China

Risk Assessment and Pressure Response Analysis of the Water Footprint of Agriculture and Livestock: A Case Study of the Beijing–Tianjin–Hebei Region in China

Decoupling Agricultural Nonpoint Source Pollution from Crop Production: A Case Study of Heilongjiang Land Reclamation Area, China

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