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

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 220 ◽  
Author(s):  
Lin Wang ◽  
Yutong Zhang ◽  
Ling Jia ◽  
Guiyu Yang ◽  
Yizhen Yao ◽  
...  

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.

2014 ◽  
Vol 11 (1) ◽  
pp. 1047-1072 ◽  
Author(s):  
L. J. Zhang ◽  
X. A. Yin ◽  
Y. Zhi ◽  
Z. F. Yang

Abstract. China is a water-stressed country, and agriculture consumes the bulk of its water resources. Assessing the virtual water content (VWC) of crops is one important way to develop efficient water management measures to alleviate water resources conflicts among different sectors. In this research, the VWC of rice, as a major crop in China, was assessed and the spatial characteristics were analyzed. In addition to the calculation of green, blue and grey water – the direct water in VWC – the indirect water use of rice was also calculated, using the Input–Output model. The percentages of direct green, blue, grey and indirect water in the total VWC of rice in China were 43.8, 28.2, 27.6, and 0.4%. The total VWC of rice generally showed a three-tiered distribution, and decreased from southeast to northwest. The higher values of direct green water of rice were mainly concentrated in Southeast and Southwest China, while these values were relatively low in Northwest China and Inner Mongolia. The higher direct blue water values were mainly concentrated in the eastern and southern coastal regions and Northwest China, and low values were mainly concentrated in Southwest China. Grey water values were relatively high in Shanxi and Guangxi provinces and low in Northeast and Northwest China. The regions with high values for indirect water were randomly distributed but the regions with low values were mainly concentrated in Northwest and Southwest China. For the regions with relatively high total VWC the high values of blue water made the largest contribution, although for the country as a whole the direct green water is the most important contributor.


2014 ◽  
Vol 18 (6) ◽  
pp. 2103-2111 ◽  
Author(s):  
L. J. Zhang ◽  
X. A. Yin ◽  
Y. Zhi ◽  
Z. F. Yang

Abstract. China is a water-stressed country, and agriculture consumes the bulk of its water resources. Assessing the virtual water content (VWC) of crops is one important way to develop efficient water management measures to alleviate water resource conflicts among different sectors. In this research, the VWC of rice, a major crop in China, is taken as the research object. China covers a vast land area, and the VWC of rice varies widely between different regions. The VWC of rice in China is assessed and the spatial characteristics are also analysed. The total VWC is the total volume of freshwater both consumed and affected by pollution during the crop production process, including both direct and indirect water use. Prior calculation frameworks of the VWC of crops did not contain all of the virtual water content of crops. In addition to the calculation of green, blue and grey water – the direct water in VWC – the indirect water use of rice was also calculated, using an input–output model. The percentages of direct green, blue, grey and indirect water in the total VWC of rice in China were found to be 43.8, 28.2, 27.6, and 0.4%. The total VWC of rice generally showed a roughly three-tiered distribution, and decreased from southeast to northwest. The higher values of direct green water usage were mainly concentrated in Southeast and Southwest China, while the values were relatively low in Northwest China and Inner Mongolia. The higher direct blue water values were mainly concentrated in the eastern and southern coastal regions and Northwest China, and low values were mainly concentrated in Southwest China. Grey water values were relatively high in Shanxi and Guangxi provinces and low in Northeast and Northwest China. The regions with high values for indirect water were randomly distributed but the regions with low values were mainly concentrated in Northwest and Southwest China. For the regions with relatively high total VWC the high values of blue water made the largest contribution, although for the country as a whole the direct green water is the most important contributor.


2021 ◽  
Vol 10 (6) ◽  
pp. e26610615777
Author(s):  
Ana Luiza Grateki Barbosa ◽  
Daniel Brasil Ferreira Pinto ◽  
Rafael Alvarenga Almeida

Currently, the management of water resources has gained greater visibility and has become indispensable, with the need for different methodologies which consider all water used and incorporated in the processes and products. In this way, the water footprint concept has been introduced to calculate the appropriation of fresh water on the part of the humankind. Thus, the objective of this work was to determine the water footprint in some sectors of family farming in the municipality of Teófilo Otoni – MG, analyzing the agricultural production of crops cultivated exclusively by the sector in 2017 in Teófilo Otoni. The cultivation of pumpkin, banana, chayote, beans, cassava, Maize, peppers, okra, cabbage, and tangerine were studied. Thus, the total water footprint for the year 2017 was 13,996,735.05 m3.t-1, in which the green water footprint represents 86%, the blue water footprint represents 12.5% and the gray water footprint equals 1.5%. The family farming sector of Teófilo Otoni demands an average of 196.73 liters for a production of R$ 1.00.


2020 ◽  
Vol 15 (2) ◽  
pp. 121
Author(s):  
Fathi Alfinur Rizqi ◽  
Sri Nuryani Utami

Populasi penduduk Indonesia diperkirakan akan mencapai 350 juta pada tahun 2045, mendorong Indonesia untuk meningkatkan ketersediaan pangan 3% setiap tahunnya. Program Upaya Khusus (Upsus) Padi Jagung Kedelai (Pajale), menjadi salah satu program unggulan pemerintah dalam menjawab tantangan ini. Di sisi lain, tekanan lingkungan memberikan batas jelas untuk melaksanakan proses budidaya pertanian berkelanjutan. Sebagaimana dua tujuan dari Sustainability Development Goals (SDGs) adalah menghentikan kelaparan dan kepastian akses terhadap air. Konsep air virtual (virtual water) hadir sebagai salah satu alternatif konsep berserta alat hitung air yang diperlukan dalam sebuah proses produksi pertanian. Penelitian ini dilakukan untuk mengidentifikasi air virtual untuk komoditas padi, jagung, dan kedelai di wilayah Daerah Istimewa Yogyakarta. Analisa dalam penelitian ini menghasilkan nilai tapak air yang terdiri dari blue water, green water, dan grey water. Hasil penelitian menunjukkan, bahwa water footprint tahunan kedelai merupakan yang tertinggi dengan 2.589 m3/ton disusul padi ladang, jagung, dan padi sawah sebesar 1.280 m3/ton; 844 m3/ton; 841 m3/ton. Hasil ini disebabkan oleh tingkat produktivitas yang semakin tinggi nilainya maka akan menghasil nilai water footprint akan semakin rendah. Pelaksanaan penelitian ini mengungkap faktor yang mempengaruhi jumlah air yang diperlukan untuk memproduksi komoditas pertanian. Pemilihan lokasi, kondisi iklim, jenis tanaman, teknik budidaya hingga penggunaan pupuk merupakan faktor yang perlu diperhatikan untuk dapat menekan penggunaan air dalam proses produksi pertanian. Dengan demikian, tujuan pelaksanaan budidaya pertanian yang berkelanjutan dapat terwujud.


2021 ◽  
Author(s):  
Hamideh Nouri ◽  
Sattar Chavoshi Borujeni ◽  
Pamela Nagler ◽  
Armando Barreto Munoz ◽  
Kamel Didan ◽  
...  

<p>The concept of a sustainable green city based on Sustainable Development Goals (SDGs)–Goal 11 - sustainable cities and communities – may not be narrowed down to solely intensifying urban green spaces. Sustainability could include urban water management to alleviate possible conflict among “water‐saving” and “greening cities” strategies. Water consumption by urban greenery has a major role in urban water management, particularly in water-scarce regions where green covers are most affected by drought and aridity. More green and blue water resources are required to maintain and expand urban green spaces. Quantifying the water footprint of urban greenery helps to balance greening cities while water saving from both green and blue water resources. We employed remote sensing and artificial intelligence techniques to assess the water consumption and water footprint of a 780‐ha public green space, the Adelaide Parklands in Australia. We estimated the green and blue water footprint of this green space (containing 29 parks) during 2010-2018 on a monthly basis. Our results showed that the mean total water footprint of the Adelaide Parklands was about 7.75 gigaliter per annum over 2010-2018; it varied from 7.19 gigaliter/year in 2018 to 8.45 gigaliter/year in 2012. The blue water footprint was consistently higher than the green water footprint even in wet time of the year. We suggest implementing sponge city and water sensitive urban design (WSUD) techniques to help greening cities while reducing the water footprint of urban green spaces. These approaches have the potential to lessen the pressure on blue water resources and optimise the consumption of green water resources.</p>


Author(s):  
Cheerawit Rattanapan ◽  
◽  
Weerawat Ounsaneha

The aim of this research was to assess the water footprint level of Thai banana production. Firstly, the water consumption inventory of banana production was developed. The water consumptions in the banana farms and a case study of banana industry were collected based on the inventory. The results showed that the water consumption of banana plantation was 842.02 m3 including 443.50 m3 of green water, 398.52 m3 of blue water and not found grey water. Moreover, 1638.59 m3/rai was found in the one rai of banana plantation consisted of 863.06 m3/rai of green water and 775.53 m3/rai of blue water. From the finding of this study, the reduction approach of water footprint for banana production should be the reduction of watering the plant in the process of banana growing.


2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Peni Faridah Khaerani

AbstrakKebutuhan akan susu semakin meningkat seiring dengan perkembangan jumlah penduduk, tingkat pendapatan, dan selera masyarakat. Dengan semakin meningkatnya kebutuhan akan susu, permintaan akan populasi sapi perah pun akan meningkat pula. Konsumsi produk hewani berkontribusi lebih dari seperempat water footprint manusia. Air yang dibutuhkan untuk menghasilkan pakan merupakan faktor utama di balik water footprint produk hewani Penelitian ini bertujuan untuk mengetahui besaran water footprint dalam produksi susu sapi serta untuk merumuskan upaya-upaya yang bisa dilakukan untuk mengurangi besarnya water footprint produksi susu sapi. Penelitian ini menggunakan desain penelitian kuantitatif dominant kualitatif. Data dikumpulkan melalui observasi, pengukuran langsung dan wawancara semi-terstruktur pada setiap tahap budidaya. Hasil penelitian menunjukkan bahwa, nilai water footprint  produksi susu sapi adalah 606,88 m3/ton, dengan nilai masing-masing komponennya adalah 233,0 m3/ton untuk green water, 178,1 m3/ton untuk blue water serta 195,78 m3/ton untuk grey water. Upaya-upaya yang dapat dilakukan untuk mengurangi water footprint produksi susu sapi : dengan meningkatkan produktivitas air pada tahap budidaya rumput gajah serta melakukan pengolahan limbah dan menerapkan  metode livestock integrated farming pada tahap budidaya ternak sapi perah.Kata Kunci : Water footprint, produksi susu sapi, upaya-upaya untuk mengurangi water footprintAbstractThe need for milk is increasing in line with population growth, income levels, and public taste. With the increasing demand for milk, dairy cow population demand will increase as well. Consumption of animal products contribute more than a quarter of the human water footprint. Water needed to produce food is a major factor behind the water footprint of animal products This study aims to determine the amount of water footprint in cow milk production as well as to formulate measures that can be done to reduce the amount of water footprint of milk production of cows. This study uses a quantitative dominant qualitative research design. Data were collected through observation, direct measurement  and semi-structured interviews at each stage of cultivation. The results showed that, the value of milk production water footprint is 606.88 m3/ton, with the value of each component is 233,0 m3/ton for green water, 178,1 m3/ton  for blue water and 195.78 m3/ton for grey water. Efforts that can be done to reduce the water footprint of milk production : increasing the productivity of water at the stage of elephant grass cultivation and doing the waste water treatment and apply livestock integrated farming method in dairy cattle farming stage.Keywords: Water footprint, milk production, efforts to reduce the water footprint


2013 ◽  
Vol 6 (1) ◽  
pp. 645-684 ◽  
Author(s):  
S. Multsch ◽  
Y. A. Al-Rumaikhani ◽  
H.-G. Frede ◽  
L. Breuer

Abstract. The water footprint accounting method addresses the quantification of water consumption in agriculture, whereby three types of water to grow crops are considered, namely green water (consumed rainfall), blue water (irrigation from surface or groundwater) and grey water (water needed to dilute pollutants). Most of current water footprint assessments focus on global to continental scale. We therefore developed the spatial decision support system SPARE:WATER that allows to quantify green, blue and grey water footprints on regional scale. SPARE:WATER is programmed in VB.NET, with geographic information system functionality implemented by the MapWinGIS library. Water requirement and water footprints are assessed on a grid-basis and can then be aggregated for spatial entities such as political boundaries, catchments or irrigation districts. We assume in-efficient irrigation methods rather than optimal conditions to account for irrigation methods with efficiencies other than 100%. Furthermore, grey water can be defined as the water to leach out salt from the rooting zone in order to maintain soil quality, an important management task in irrigation agriculture. Apart from a thorough representation of the modelling concept we provide a proof of concept where we assess the agricultural water footprint of Saudi Arabia. The entire water footprint is 17.0 km3 yr−1 for 2008 with a blue water dominance of 86%. Using SPARE:WATER we are able to delineate regional hot spots as well as crop types with large water footprints, e.g. sesame or dates. Results differ from previous studies of national-scale resolution, underlining the need for regional water footprint assessments.


Author(s):  
Maite M. Aldaya ◽  
M. Ramón Llamas ◽  
Arjen Y. Hoekstra

This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Environmental Science. Please check back later for the full article. The water footprint concept broadens the scope of traditional national and corporate water accounting as it has been previously known. It highlights the ways in which water consuming and polluting activities relate to the structure of the global economy, opening a window of opportunity to increase transparency and improve water management along whole-production and supply chains. This concept adds a new dimension to integrated water resources management in a globalized world. The water footprint is a relatively recent indicator. Created in 2002, it aims to quantify the effect of consumption and trade on the use of water resources. Specifically, the water footprint is an indicator of freshwater use that considers both direct and indirect water use of a consumer or producer. For instance, the water footprint of a product refers to the volume of freshwater used to produce the product, tracing the origin of raw material and ingredients along their respective supply chains. This novel indirect component of water use in supply chains is, in many cases, the greatest share of water use, for example, in the food and beverage sector and the apparel industry. Water footprint assessment shows the full water balance, with water consumption and pollution components specified geographically and temporally and with water consumption specified by type of source (e.g., rainwater, groundwater, or surface water). It introduces three components: 1. The blue water footprint refers to the consumption of blue water resources (i.e., surface and groundwater including natural freshwater lakes, manmade reservoirs, rivers, and aquifers) along the supply chain of a product, versus the traditional and restricted water withdrawal measure. 2. The green water footprint refers to consumption through transpiration or evaporation of green water resources (i.e., soilwater originating from rainwater). Green water maintains natural vegetation (e.g., forests, meadows, scrubland, tundra) and rain-fed agriculture, yet plays an important role in most irrigated agriculture as well. Importantly, this kind of water is not quantified in most traditional agricultural water use analyses. 3. The grey water footprint refers to pollution and is defined as the volume of freshwater that is required to assimilate the load of pollutants given natural concentrations for naturally occurring substances and existing ambient water-quality standards. The water footprint concept has been incorporated into public policies and international standards. In 2011, the Water Footprint Network adopted the Water Footprint Assessment Manual, which provides a standardized method and guidelines. In 2014, the International Organization for Standardization adopted a life cycle-based ISO 14046 standard for the water footprint; it offers guidelines to integrate water footprint analysis in life-cycle assessment for products. In practice, water footprint assessment generally results in increased awareness of critical elements in a supply chain, such as hotspots that deserve most attention, and what can be done to improve water management in those hotspots. Water footprint assessment, including the estimation of virtual water trade, applied in different countries and contexts, is producing new data and bringing larger perspectives that, in many cases, lead to a better understanding of the drivers behind water scarcity.


2013 ◽  
Vol 6 (4) ◽  
pp. 1043-1059 ◽  
Author(s):  
S. Multsch ◽  
Y. A. Al-Rumaikhani ◽  
H.-G. Frede ◽  
L. Breuer

Abstract. The agricultural water footprint addresses the quantification of water consumption in agriculture, whereby three types of water to grow crops are considered, namely green water (consumed rainfall), blue water (irrigation from surface or groundwater) and grey water (water needed to dilute pollutants). By considering site-specific properties when calculating the crop water footprint, this methodology can be used to support decision making in the agricultural sector on local to regional scale. We therefore developed the spatial decision support system SPARE:WATER that allows us to quantify green, blue and grey water footprints on regional scale. SPARE:WATER is programmed in VB.NET, with geographic information system functionality implemented by the MapWinGIS library. Water requirements and water footprints are assessed on a grid basis and can then be aggregated for spatial entities such as political boundaries, catchments or irrigation districts. We assume inefficient irrigation methods rather than optimal conditions to account for irrigation methods with efficiencies other than 100%. Furthermore, grey water is defined as the water needed to leach out salt from the rooting zone in order to maintain soil quality, an important management task in irrigation agriculture. Apart from a thorough representation of the modelling concept, we provide a proof of concept where we assess the agricultural water footprint of Saudi Arabia. The entire water footprint is 17.0 km3 yr−1 for 2008, with a blue water dominance of 86%. Using SPARE:WATER we are able to delineate regional hot spots as well as crop types with large water footprints, e.g. sesame or dates. Results differ from previous studies of national-scale resolution, underlining the need for regional estimation of crop water footprints.


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