Reducing Agricultural Water Footprints at the Farm Scale: A Case Study in the Beijing Region

Huang, Jing; Xu, Chenghua; Ridoutt, Bradley G.; Chen, Fu

doi:10.3390/w7126674

Cited by 25 publications

(11 citation statements)

References 31 publications

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“…The ET 0 was calculated by the SIMETAW model, which was developed based on the FAO Penman-Monteith equation [28], and has widely used in NCD [29][30][31][32]. Aridity Index (AI) is an index for assessing drought risk in the crop growing period, which considers the total precipitation and evapotranspiration.…”

Section: Calculation Of Et 0 and Aridity Indexmentioning

confidence: 99%

Spatio-Temporal Analysis of Meteorological Elements in the North China District of China during 1960–2015

Yang

Yin

et al. 2018

Water

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Abstract:The North China District (NCD) is one of the main grain production regions in China. The double cropping system of irrigation has been leading to the groundwater table decline at the speed of 1-2 m per year. Climate change leads to uncertainty surrounding the future of the NCD agricultural system, which will have great effects on crop yields and crop water demands. In this research, the Meteorological dataset from 54 weather station sites over the period 1960-2015 were collected to quantify the long-term spatial and temporal trends of meteorological data, including daily minimum temperature (T min ), maximum temperature (T max ), precipitation, solar radiation, reference evapotranspiration (ET 0 ), and aridity index (AI). The results show that the long-term wheat and maize growing season and annual average air temperatures (T min and T max ) showed strong north to south increasing trends throughout the NCD. The average annual precipitation was 632.9 mm across the NCD, more than 70% of which was concentrated in the maize growing season. The regional average annual ET 0 was 1026.1 mm, which was 531.2 and 497.4 mm for the wheat and maize growing season, respectively. The regional precipitation decreased from northwest to southeast in each growing season and annual timescale. The funnel areas have lower precipitation and higher ET 0 than the regional average, which may lead to the mining of the groundwater funnel area. The regional average annual AI is 0.63, which lies in the humid class. For temporal analysis, the regional average trends in annual T min , T max , solar radiation, ET 0 , precipitation, and AI were 0.37 • C/10a, 0.15 • C/10a, −0.28 MJ/day/m 2 /10a, −2.98 mm/10a, −12.04 mm/10a, and 0.005/10a, respectively. The increasing trend of temperature and the decreasing trend of solar radiation may have a negative effect on the regional food security. The funnel area AI showed a significant increasing trend for the winter wheat growing season and a decreasing trend for maize, which indicated that more irrigation will be needed for the maize growing season and the winter fallow policy may lead to the increasing trend precipitation being wasted. Analyzing the growing season and the annual meteorological elements of the spatiotemporal trends can help us better understand the influence of climate change on the natural resources and agricultural development in both the past and the future, and will provide us with invaluable information for the modification of cropping patterns to protect the regional and national water and food security.

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Section: Calculation Of Et 0 and Aridity Indexmentioning

confidence: 99%

Spatio-Temporal Analysis of Meteorological Elements in the North China District of China during 1960–2015

Yang

Yin

et al. 2018

Water

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“…Water footprint accounting is a suitable procedure to assess the relationship between water use and crop yield [20]. A 33.3% reduction in water volume relative to current practice did not result in a major decline in maize yield, but water footprint was decreased by 23.9% [21].Water footprint (WF) studies are primarily concerned with reducing the global average of freshwater consumption [22]. The water footprint is expected to increase by up to 22% as a result of climatic changes and change in land use by 2090 [23].…”

Section: Water Footprintmentioning

confidence: 99%

Water Footprint as a Tool of Water Resources Management – Review

et al. 2021

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Water is essential for live, freshwater supplies around the world are under significant pressure because of increasing consumption and pollution. Egypt suffers from water scarcity due to the increase in the population and the lack of integrated management of water resources, resulting in a gap between the available water resources and the required water consumption. Many studies were done to improve irrigated agriculture's efficiency on water consumption and crop yields for saving water in irrigated agriculture to achieve water management sustainability. Therefore, the aim of this work is reviewing of the previous studies of crop water footprint accounting as a diagnostic tool to identify the hotspots of irrigated agricultural systems Water footprint as one of the tools of integrated water management. The water footprint (WF), which is an indicator that includes both direct and indirect water use, is a metric for determining how much freshwater a product consumes during its life cycle. It helps in providing water quantities to obtain the highest water efficiency to obtain the highest return of one cubic meter of water. And, it also helps to improve the strategies of sustainable agricultural and the structure of international trade. Water footprint necessitates the need to integrate water resources management policies agricultural and trade policies to feed in a comprehensive country water accounting system.

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“…Also, the effects of subsurface drip irrigation and mulching on crop water productivities had been reported as most favorable for various crops across the varying soil types and climates (Hou et al, 2016, Pendergast et al, 2019. The optimal deficiency of irrigation water and fertilizer could be found the most successful strategies for the water footprint reduction (Bhattarai et al, 2004, 2006, Huang et al, 2015, Haoru et al, (2021 . The various irrigation strategies like optimal inputs of irrigation water and fertilizer inputs, aerated irrigation, subsurface drip irrigation and mulching are well proven for reducing water footprints of most of the crops under various soils types and climates except few cases.…”

Section: Introductionmentioning

confidence: 99%

Simulating the Water Footprints of Sweet Corn (Zea Mays L.) Under Various Irrigation Water Management Strategies Using Aqucrop Mode

2022

IRJMETS

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The field experiment was conducted during winter season for the consecutive 2 years (2020-21 and 2021-22) at Instructional Farm of CAET, JAU, Junagadh to determine the inputs and outputs model parameters for calibrating, validating and testing of AquaCrop model. The LAI, biomass and yield of fresh green cob and fodder were observed from each of 2 replications of each of 32 treatment. The AquaCrop model simulated the sweet corn cob yield which had been agreed reasonably well with observed data for various irrigation and fertigation level under mulch and no mulch.

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Reducing Agricultural Water Footprints at the Farm Scale: A Case Study in the Beijing Region

Cited by 25 publications

References 31 publications

Spatio-Temporal Analysis of Meteorological Elements in the North China District of China during 1960–2015

Spatio-Temporal Analysis of Meteorological Elements in the North China District of China during 1960–2015

Water Footprint as a Tool of Water Resources Management – Review

Simulating the Water Footprints of Sweet Corn (Zea Mays L.) Under Various Irrigation Water Management Strategies Using Aqucrop Mode

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