Insights into water sustainability from a grey water footprint perspective in an irrigated region of the Yellow River Basin

2021 ◽  
pp. 128329
Author(s):  
Jie Chen ◽  
Yanyan Gao ◽  
Hui Qian ◽  
Hui Jia ◽  
Qiying Zhang
Keyword(s):  
River Basin ◽  
Water Footprint ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Water Sustainability ◽  
Grey Water ◽  
The Yellow River Basin

scholarly journals Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River Basin

2014 ◽  
Vol 11 (1) ◽  
pp. 135-167 ◽  
Author(s):  
L. Zhuo ◽  
M. M. Mekonnen ◽  
A. Y. Hoekstra
Keyword(s):  
River Basin ◽  
Water Footprint ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Blue Water ◽  
Total Water ◽  
Crop Water ◽  
Input Variables ◽  
The Yellow River Basin

Abstract. Water Footprint Assessment is a quickly growing field of research, but as yet little attention has been paid to the uncertainties involved. This study investigates the sensitivity of water footprint estimates to changes in important input variables and quantifies the size of uncertainty in water footprint estimates. The study focuses on the green (from rainfall) and blue (from irrigation) water footprint of producing maize, soybean, rice, and wheat in the Yellow River Basin in the period 1996–2005. A grid-based daily water balance model at a 5 by 5 arcmin resolution was applied to compute green and blue water footprints of the four crops in the Yellow River Basin in the period considered. The sensitivity and uncertainty analysis focused on the effects on water footprint estimates at basin level (in m3 t−1) of four key input variables: precipitation (PR), reference evapotranspiration (ET0), crop coefficient (Kc), and crop calendar. The one-at-a-time method was carried out to analyse the sensitivity of the water footprint of crops to fractional changes of individual input variables. Uncertainties in crop water footprint estimates were quantified through Monte Carlo simulations. The results show that the water footprint of crops is most sensitive to ET0 and Kc, followed by crop calendar and PR. Blue water footprints were more sensitive to input variability than green water footprints. The smaller the annual blue water footprint, the higher its sensitivity to changes in PR, ET0, and Kc. The uncertainties in the total water footprint of a crop due to combined uncertainties in climatic inputs (PR and ET0) were about ±20% (at 95% confidence interval). The effect of uncertainties in ET0 was dominant compared to that of precipitation. The uncertainties in the total water footprint of a crop as a result of combined key input uncertainties were on average ±26% (at 95% confidence level). The sensitivities and uncertainties differ across crop types, with highest sensitivities and uncertainties for soybean.

scholarly journals Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River basin

2014 ◽  
Vol 18 (6) ◽  
pp. 2219-2234 ◽  
Author(s):  
L. Zhuo ◽  
M. M. Mekonnen ◽  
A. Y. Hoekstra
Keyword(s):  
River Basin ◽  
Water Footprint ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Blue Water ◽  
Crop Water ◽  
Crop Calendar ◽  
Input Variables ◽  
The Yellow River Basin

Abstract. Water Footprint Assessment is a fast-growing field of research, but as yet little attention has been paid to the uncertainties involved. This study investigates the sensitivity of and uncertainty in crop water footprint (in m3 t−1) estimates related to uncertainties in important input variables. The study focuses on the green (from rainfall) and blue (from irrigation) water footprint of producing maize, soybean, rice, and wheat at the scale of the Yellow River basin in the period 1996–2005. A grid-based daily water balance model at a 5 by 5 arcmin resolution was applied to compute green and blue water footprints of the four crops in the Yellow River basin in the period considered. The one-at-a-time method was carried out to analyse the sensitivity of the crop water footprint to fractional changes of seven individual input variables and parameters: precipitation (PR), reference evapotranspiration (ET0), crop coefficient (Kc), crop calendar (planting date with constant growing degree days), soil water content at field capacity (Smax), yield response factor (Ky) and maximum yield (Ym). Uncertainties in crop water footprint estimates related to uncertainties in four key input variables: PR, ET0, Kc, and crop calendar were quantified through Monte Carlo simulations. The results show that the sensitivities and uncertainties differ across crop types. In general, the water footprint of crops is most sensitive to ET0 and Kc, followed by the crop calendar. Blue water footprints were more sensitive to input variability than green water footprints. The smaller the annual blue water footprint is, the higher its sensitivity to changes in PR, ET0, and Kc. The uncertainties in the total water footprint of a crop due to combined uncertainties in climatic inputs (PR and ET0) were about ±20% (at 95% confidence interval). The effect of uncertainties in ET0was dominant compared to that of PR. The uncertainties in the total water footprint of a crop as a result of combined key input uncertainties were on average ±30% (at 95% confidence level).

scholarly journals Nitrogen Fertilization Effects on Physiology of the Cotton Boll–Leaf System

Agronomy ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 271
Author(s):  
Jing Chen ◽  
Liantao Liu ◽  
Zhanbiao Wang ◽  
Hongchun Sun ◽  
Yongjiang Zhang ◽  
...  
Keyword(s):  
River Basin ◽  
Nitrogen Fertilization ◽  
Yellow River ◽  
Yellow River Basin ◽  
Growth And Yield ◽  
The Yellow River ◽  
Nitrogen Rate ◽  
The Yellow River Basin ◽  
Source Sink ◽  
Subtending Leaves

The objective of this study was to assess the impacts of nitrogen on the physiological characteristics of the source–sink system of upper fruiting branches under various amounts of nitrogen fertilization. A two-year field experiment was conducted with a Bt cotton cultivar in the Yellow River Basin of China. The growth and yield of cotton of the upper fruiting branches were compared under four nitrogen levels: Control (N0, 0 kg ha−1), low nitrogen (N1, 120 kg ha−1), moderate nitrogen (N2, 240 kg ha−1), and high nitrogen (N3, 480 kg ha−1). The results indicated that in the subtending leaves in upper fruiting branches, chlorophyll content, protein content, and peroxidase (POD) activity dramatically increased with nitrogen application, reaching the highest under the moderate nitrogen treatment. The physiological characters in the seeds had the same trends as in the subtending leaves. Furthermore, the moderate nitrogen rate (240 kg ha−1) had a favorable yield and quality. Our results supported that a moderate nitrogen rate (240 kg ha−1) could coordinate the source–sink growth of cotton in the late stage, enhance the yield and fiber quality, and decrease the cost of fertilizer in the Yellow River Basin of China and other similar ecological areas.

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