scholarly journals REGIONAL AGRICULTURAL WATER FOOTPRINT AND CROP WATER CONSUMPTION STUDY IN YELLOW RIVER BASIN, CHINA

2019 ◽  
Vol 17 (3) ◽  
Author(s):  
J YIN
Keyword(s):  
River Basin ◽  
Water Consumption ◽  
Water Footprint ◽  
Yellow River ◽  
Yellow River Basin ◽  
Agricultural Water ◽  
Crop Water ◽  
Crop Water Consumption

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 Study on Agricultural Water Consumption by Food Demand Model in Yellow River Basin

2006 ◽  
Vol 14 ◽  
pp. 277-282
Author(s):  
Masufumi SONODA ◽  
Akio ONISHI ◽  
Akihiro SHIRAKAWA ◽  
Hidefumi IMURA
Keyword(s):  
River Basin ◽  
Water Consumption ◽  
Yellow River ◽  
Yellow River Basin ◽  
Food Demand ◽  
Demand Model ◽  
Agricultural Water

scholarly journals A STUDY ON AGRICULTURAL WATER CONSUMPTION BY FOOD DEMAND MODEL IN YELLOW RIVER BASIN

2006 ◽  
Vol 34 ◽  
pp. 525-535
Author(s):  
Masufumi SONODA ◽  
Akio ONISHI ◽  
Hiroaki SHIRAKAWA ◽  
Hidefumi IMURA
Keyword(s):  
River Basin ◽  
Water Consumption ◽  
Yellow River ◽  
Yellow River Basin ◽  
Food Demand ◽  
Demand Model ◽  
Agricultural Water

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 How High-Quality Urbanization Affects Utilization Efficiency of Agricultural Water Resources in the Yellow River Basin under Double Control Action?

2020 ◽  
Vol 12 (7) ◽  
pp. 2869
Author(s):  
Xiling Zhang ◽  
Yusheng Kong ◽  
Xuhui Ding
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
Utilization Efficiency ◽  
The Yellow River ◽  
Agricultural Water ◽  
High Quality ◽  
Water Utilization ◽  
Urban Rural ◽  
The Yellow River Basin

To promote the high-quality development of the Yellow River Basin, the total amount and intensity of agricultural water must be controlled. Further speaking, an urbanization development system should be established that is compatible with water resources and the water environment. We adopted the stochastic frontier analysis model to measure the agricultural water utilization efficiency of the Yellow River Basin from 2007 to 2017. We also adopted the dynamic panel difference generalized method of moments (GMM) and system GMM models to verify the driving factors, in which population urbanization, economic urbanization, and equilibrium urbanization levels were selected as the key variables. The results show that the overall efficiency of agricultural water utilization maintained a steady upward trend during the research period. The spatial differentiation was generally characterized by higher efficiency levels in the eastern region and lower levels in the western region. The variation coefficient of water utilization efficiency showed a downward trend in general, which indicates a space spillover effect. Agricultural water utilization efficiency continued to converge from 2007 to 2017, and the upper reaches area converged relatively more quickly. Regarding the influencing factors, the population urbanization, economic urbanization, balanced urbanization, crop planting ratio, and rice planting ratio had negative effects on agricultural water utilization efficiency. Urbanization did not positively affect agricultural water use efficiency as the related theories, so urbanization quality and urban–rural integration should be paid more attention. However, technology innovation was significantly positive in agricultural water utilization efficiency. The influencing factors of per capita water availability and annual precipitation did not pass the significance test. Therefore, the government should vigorously promote the development of high-quality new-type urbanization, scientifically formulate the scale and speed of urbanization, strengthen the urban, rural, and industrial integration, and promote the adjustment of planting structures and agricultural deep processing.

scholarly journals Spatio-Temporal Variations of Crop Water Footprint and Its Influencing Factors in Xinjiang, China during 1988–2017

2020 ◽  
Vol 12 (22) ◽  
pp. 9678
Author(s):  
Aihua Long ◽  
Pei Zhang ◽  
Yang Hai ◽  
Xiaoya Deng ◽  
Junfeng Li ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Consumption ◽  
Water Footprint ◽  
Policy Decision ◽  
Temporal Variations ◽  
Added Value ◽  
Local Policy ◽  
Agricultural Water ◽  
Crop Water ◽  
Factors Influencing

Scientifically determining agricultural water consumption is fundamental to the optimum allocation and regulation of regional water resources. However, traditional statistical methods used for determining agricultural water consumption in China do not reflect the actual use of water resources. This paper determined the variation in the crop water footprint (CWF) to reflect the actual agricultural water consumption in Xinjiang, China, during the past 30 years, and the data from 15 crops were included. In addition, the STIRPAT (stochastic impacts by regression on population, affluence and technology) model was used to determine the factors influencing the CWF. The results showed that the CWF in Xinjiang increased by 256% during the 30-year period. Factors such as population, agricultural added value, and effective irrigated area were correlated with an increase in the CWF. This study also showed that the implementation of national and regional policies significantly accelerated the expansion of agricultural production areas and increased the amount of agricultural water used. The objectives of this paper were to identify the factors influencing the CWF, give a new perspective for further analysis of the relationship between agricultural growth and water resources utilization, and provide a reference for local policy decision-makers in Xinjiang.

scholarly journals A Decoupling Analysis of the Crop Water Footprint Versus Economic Growth in Beijing, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Kai Huang ◽  
Mengqi Wang ◽  
Zhongren Zhou ◽  
Yajuan Yu ◽  
Yixing Bi
Keyword(s):  
Economic Growth ◽  
Water Use ◽  
Water Consumption ◽  
Crop Production ◽  
Water Footprint ◽  
Social Economy ◽  
Agricultural Water ◽  
Crop Water ◽  
Entire Study ◽  
Agricultural Water Use

Beijing, the capital of China, is experiencing a serious lack of water, which is becoming a main factor in the restriction of the development of the social economy. Due to the low economic efficiency and high consumption proportion of agricultural water use, the relationship between economic growth and agricultural water use is worth investigating. The “decoupling” index is becoming increasingly popular for identifying the degree of non-synchronous variation between resource consumption and economic growth. However, few studies address the decoupling between the crop water consumption and agricultural economic growth. This paper involves the water footprint (WF) to assess the water consumption in the crop production process. After an evaluation of the crop WF in Beijing, this paper applies the decoupling indicators to examine the occurrence of non-synchronous variation between the agricultural gross domestic product (GDP) and crop WF in Beijing from 1981 to 2013. The results show that the WF of crop production in 2013 reduced by 62.1% compared to that in 1980 — in total, 1.81 × 109 m3. According to the decoupling states, the entire study period is divided into three periods. From 1981 to 2013, the decoupling states represented seventy-five percent of the years from 1981 to 1992 (Period I) with a moderate decoupling degree, more than ninety percent from 1993 to 2003 (Period II) with a very strong decoupling degree and moved from non-decoupling to strong decoupling from 2004 to 2013 (Period III). Adjusting plantation structure, technology innovation and raising awareness of water-saving, may promote the decoupling degree between WF and agricultural GDP in Beijing.

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