Temporal and spatial changes of water footprint of maize production in Jilin Province

2014 ◽  
Vol 14 (6) ◽  
pp. 1067-1075 ◽  
Author(s):  
Peili Duan ◽  
Lijie Qin
Keyword(s):  
Crop Production ◽  
Water Footprint ◽  
Jilin Province ◽  
Green Water ◽  
Eastern Region ◽  
Maize Production ◽  
Production Values ◽  
Spatial Changes ◽  
Different Types ◽  
Temporal And Spatial

Quantitation of the green, blue and grey water footprints (WFs) of crop production can distinguish the water types and amount in crop production, as well as the degree of freshwater pollution. This paper calculates the WF of maize production and assesses the temporal variability and spatial distribution of WFs in different types of rainfall years over Jilin Province from 1998 to 2012. The results indicated that: (1) the annual average WF of maize production was 1,067 m3/ton, which was 53% green, 24% blue and 23% grey (maize production in Jilin Province relies primarily on green water); (2) the drier the year, the higher the WF of maize production; (3) the highest WF of maize production values among 49 counties in the province were in Antu and Tumen counties, whereas the lowest values occurred in Gongzhuling and Lishu counties, whether the year was humid, average or dry; and (4) the WF of maize production was highest in the eastern region, moderate in the western region and lowest in the middle region.

scholarly journals Spatiotemporal Characteristics of the Carbon and Water FootPrints of Maize Production in Jilin Province, China

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 17
Author(s):  
Li Jia ◽  
Lijie Qin ◽  
Huiyun Zhang ◽  
Jianqin Wang ◽  
Bo Li ◽  
...  
Keyword(s):  
Water Use ◽  
Crop Production ◽  
Environmental Changes ◽  
Water Footprint ◽  
Ghg Emissions ◽  
Jilin Province ◽  
Low Carbon ◽  
Maize Production ◽  
Spatiotemporal Characteristics ◽  
The Relationship

Greenhouse gas (GHG) emissions and freshwater scarcity are central environmental concerns that are closely linked to crop production. The carbon footprint (CF) and water footprint (WF) of a crop can reflect the effects of crop production on GHG emissions and water use (WU), respectively. Studying the CFs and WFs associated with crop production will be conducive to understanding the environmental changes caused by agricultural activities, and exploring the relationship between CFs and WFs can provide a basis for strategies that reduce environmental pressures. We estimated the CF and WF of maize production in Jilin Province from 2004 to 2017 and analyzed their spatiotemporal characteristics. The results showed that the average CF and WF were 0.177 kg CO2eq/kg and 0.806 m3/kg from 2004 to 2017, respectively; 69% of the GHG emissions were due to the manufacture; transportation and application of fertilizer; and 84% of the water use was attributed to the green WF. The relationship between the CF and WF of maize production was significantly positive and indicated the possibility of simultaneous mitigation. Potential practices such as the optimization of fertilization and of agricultural machinery use and the incorporation of no-till technologies with the straw return are recommended to mitigate both GHG emissions and water use and achieve triple-win agriculture with low carbon use and water and energy savings

scholarly journals Assessment of Crop Water Footprint for Different Varieties of Groundnut (Arachis hypogaea)

2021 ◽  
Author(s):  
J. Ramachandran ◽  
R. Lalitha ◽  
S. Vallal Kannan ◽  
K. Sivasubramanian
Keyword(s):  
Water Stress ◽  
Tamil Nadu ◽  
Crop Production ◽  
Water Footprint ◽  
Management Strategies ◽  
Green Water ◽  
Blue Water ◽  
Total Water ◽  
Crop Water ◽  
Different Levels

Background: Water Footprint is a recently used indicator which helps to reduce water depletion and alleviate water stress in areas of drought and proper crop cultivation. Hence a study was taken up to assess the crop water footprint of different groundnut varieties namely TMV 7, VRI 2, VRI 3, VRI Gn 5, VRI Gn 6, CO 3, CO Gn 4, ALR 3 and TMV Gn 13 cultivated during Kharif and Rabi seasons at Tiruchirapalli district of Tamil Nadu. Methods: The total water requirement, blue and green crop evapotranspiration, blue and green crop water use and total water footprint for different varieties of groundnut were estimated using CROPWAT 8.0 Windows. A comparison was made between the water footprint of groundnut varieties and the strategies to reduce water footprint is presented. Result: The total water footprint for groundnut varieties ranged from 2603 to 4889 m3 ton-1 (CV of 26%) during kharif season, while it was ranged from 1465 to 2470 m3 ton-1 (CV of 18%) during rabi season. It was found that in all groundnut varieties the blue water footprint is higher than the green water footprint, while VRI Gn 5 variety had minimum total water footprint. It was concluded that, the groundnut production is affected by different levels of blue water stress which requires effective irrigation practices and water management strategies to enhance the crop production.

Assessment of Water Footprint for Koshi River Basin (KRB), Nepal

2020 ◽  
Author(s):  
Raj Deva Singh ◽  
Kumar Ghimire ◽  
Ashish Pandey
Keyword(s):  
River Basin ◽  
Water Use ◽  
Crop Production ◽  
Agricultural Land ◽  
Water Footprint ◽  
Green Water ◽  
Blue Water ◽  
Total Water ◽  
Green And Blue Water ◽  
Koshi River Basin

<p>Nepal is an agrarian country and almost one-third of Gross Domestic Product (GDP) is dependent on agricultural sector. Koshi river basin is the largest basin in the country and serves large share on agricultural production. Like another country, Nepalese agriculture holds largest water use in agriculture. In this context, it is necessary to reduce water use pressure. In this study, water footprint of different crop (rice, maize, wheat, millet, sugarcane, potato and barley) have been estimated for the year 2005 -2014 to get the average water footprint of crop production during study period. CROPWAT model, developed by Food and Agriculture Organization (FAO 2010b).</p><p>For the computation of the green and blue water footprints, estimated values of ET (the output of CROPWAT model) and yield (derived from statistical data) are utilised. Blue and green water footprint are computed for different districts (16 districts within KRB) / for KRB in different years (10 years from 2005 to 2014) and crops (considered 7 local crops). The water footprint of crops production for any district or basin represents the average of WF production of seven crops in the respective district or basin.</p><p>The study provides a picture of green and blue water use in crop production in the field and reduction in the water footprint of crop production by selecting suitable crops at different places in the field. The Crop, that has lower water footprint, can be intensified at that location and the crops, having higher water footprint, can be discontinued for production or measure for water saving technique needs to be implemented reducing evapotranspiration. The water footprint of agriculture crop production can be reduced by increasing the yield of the crops. Some measures like use of an improved variety of seed, fertilizer, mechanized farming and soil moisture conservation technology may also be used to increase the crop yields.</p><p>The crop harvested areas include both rainfed as well as irrigated land. Agricultural land occupies 22% of the study area, out of which 94% areas are rainfed whereas remaining 6% areas are under irrigation. The study shows 98% of total water use in crop production is due to green water use (received from rainfall) and remaining 2 % is due to blue water use received from irrigation (surface and ground water as source). Potato has 22% blue water proportion and contributes 85% share to the total blue water use in the basin. Maize and rice together hold 77% share of total water use in crops production. The average annual water footprint of crop production in KRB is 1248 cubic meter/ton having the variation of 9% during the period of 2005-2014. Sunsari, Dhankuta districts have lower water footprint of crop production. The coefficient of variation of water footprint of millet crop production is lower as compared to those of other crops considered for study whereas sugarcane has a higher variation of water footprint for its production.</p>

Impact of different sowing dates on green water footprint of maize in western Jilin Province

2012 ◽  
Vol 32 (23) ◽  
pp. 7375-7382 ◽  
Author(s):  
秦丽杰 QIN Lijie ◽  
靳英华 JIN Yinghua ◽  
段佩利 DUAN Peili
Keyword(s):  
Water Footprint ◽  
Jilin Province ◽  
Green Water ◽  
Sowing Dates ◽  
Western Jilin Province ◽  
Western Jilin

scholarly journals Temporal and Spatial Changes in Crop Patterns, Use of Inputs and Hydrological Alteration in the Case of Fogera Floodplain, Ethiopia

Ecologies ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 380-396
Author(s):  
Mare Addis Desta ◽  
Gete Zeleke ◽  
William A. Payne ◽  
Wubneh Belete Abebe
Keyword(s):  
Water Flow ◽  
Crop Production ◽  
Vegetation Index ◽  
Swat Model ◽  
Temporal Trends ◽  
Primary Data ◽  
Nitrogen And Phosphorus ◽  
Flow Measurements ◽  
Spatial Changes ◽  
Temporal And Spatial

More than half of the world’s population consumes rice. Recently, the area sown with modern rice varieties has expanded, and the use of chemical fertilizers and pesticides has increased in various countries. Wetland hydrology is also influenced by chemical and physical characteristics. Hence, this research focused on temporal and spatial changes in crop patterns, input usage, and hydrology in the Ethiopian Fogera floodplain, with the following objectives: (a) What are the spatial and temporal trends in crop production patterns? (b) What input changes have occurred to produce rice and other crops? (c) What hydrological changes have occurred in the area with intensification of production systems? Primary data were gathered through a questionnaire, focus group discussions, interviews, and field observations. Secondary data were obtained from Landsat imageries, the SWAT model, water flow measurements, and normalized difference vegetation index (NDVI). NDVI results indicated that the area cultivated for rice is increasing while the area of other crops is decreasing. Agricultural inputs are used in rice systems but were not used before the introduction of rice. Recession farming activities have also diminished wetland areas. Water flow showed a decrease, whereas Nitrogen and Phosphorus showed an increase with Pearson’s correlation values −0.069 and −0.072, respectively. Flow of water was negatively correlated with N and P water concentration, whereas N and P contents were positively correlated. In conclusion, growth of intensive rice systems has had negative environmental consequences on wetland ecology. Therefore, policies to regulate and manage wetland uses are recommended.

Mean annual green water footprint of national consumption per capita (1996-2005)

2018 ◽  
Author(s):  
Najet Guefradj
Keyword(s):  
Industrial Production ◽  
Agricultural Production ◽  
Crop Production ◽  
Water Footprint ◽  
Green Water ◽  
Domestic Water ◽  
The Mean ◽  
Per Capita ◽  
Table Data ◽  
National Consumption

This layer represents estimation of the mean annual green water footprint of national consumption for the period 1996-2005. The water footprint is a measure of human’s appropriation of freshwater resources. The green water footprint is the volume of green water (rainwater) consumed, which is particularly relevant in crop production. Estimation are given in cubic meter per capita per year. In the table, data are also available disaggregated per sectors: agricultural production, industrial production and domestic water use. Methodology and results can be found in the main report: http://temp.waterfootprint.org/Reports/Report50-NationalWaterFootprints-Vol1.pdf . For more information, visit the Water Footprint Network website: http://temp.waterfootprint.org/?page=files/WaterStat Agriculture Supply Use/Reuse

scholarly journals Spatiotemporal variations of agricultural water footprint and its economic benefits in Xinjiang, northwestern China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yinbo Li ◽  
Mingjiang Deng
Keyword(s):  
Sustainable Management ◽  
Crop Production ◽  
Water Footprint ◽  
Economic Benefits ◽  
Northwestern China ◽  
Agricultural Water ◽  
Food Productivity ◽  
North Xinjiang ◽  
Temporal And Spatial ◽  
Temporal And Spatial Characteristics

AbstractAgriculture is the largest water user and is the main driving force behind water stress in Xinjiang, northwestern China. In this study, the water footprint (WF) (blue, green and gray WF) of main crop production and their temporal and spatial characteristics in Xinjiang were estimated in 2006, 2010, 2014 and 2018. The blue water footprint deficit (BWFd) was conducted and food productivity and economic benefits of WF were also analyzed via the water consumption per output value (food productivity and economic benefits). The results reveal that the WF increased from 22.75 to 44.16 billion m3 during 2006–2018 in Xinjiang, of which cotton, corn and wheat are main contributors of WF. In terms of different regions, corn has the largest WF in north Xinjiang and cotton has the largest WF in south and east Xinjiang. The BWFd broadened from − 11.51 to + 13.26 billion m3 in Xinjiang with the largest increased BWFd in Kashgar (from − 3.35 to 1.40 billion m3) and Aksu (from − 2.92 to 2.23 billion m3) of south Xinjiang and in Shihezi (from − 0.11 to 2.90 billion m3) of north Xinjiang. In addition, the water footprint food productivity does not well correspond with the water footprint economic benefits in prefectures of Xinjiang. It means we should consider the food yields priority and economic benefits priority to formulate a scientific and effective supervisor mode to realize the sustainable management of agricultural water in prefectures of Xinjiang.

scholarly journals Crop Production Allocations for Saving Water and Improving Calorie Supply in China

2021 ◽  
Vol 5 ◽  
Author(s):  
Yilin Liu ◽  
La Zhuo ◽  
Xi Yang ◽  
Xiangxiang Ji ◽  
Zhiwei Yue ◽  
...  
Keyword(s):  
Water Resources ◽  
Crop Production ◽  
Water Footprint ◽  
Water Saving ◽  
Reference Level ◽  
Blue Water ◽  
Maize Production ◽  
Food Quantity ◽  
Citrus Production ◽  
Agricultural Water Resources

The limited available water resources and competition among different water use sectors have become the main constraints of food security and sustainability. Faced with the inability to expand the area of cultivated land due to urbanization and population growth, one of the biggest challenges and risks for developing countries is to ensure the supply of food quantity and quality under extremely limited water resources. To achieve water-saving and improve calorie supply by adjusting crop production allocations, three objectives—of minimum blue water footprint, maximum calorie production, and each crop production no less than the reference level of nine main crops in China—were achieved using a non-dominated sorting genetic algorithm II. The results display that compared with the reference year, model Maize+ (maize production increased) had significant blue water saving (~32%), the blue water footprint of crop production in all provinces reduced, and its calorie production increased by 4%. This solution is not realistic for China because wheat and rice production need to be reduced by 82 and 80%, respectively. However, model Citrus– (citrus production decreased) reduced the blue water footprint of crop production (~16%), and increased calorie production (~12%). Compared with other solutions, it is a sustainable crop production structure that is easier to realize because it is better at meeting the production of each crop. Therefore, China can appropriately increase the planting area of maize and reduce the planting of citrus and other crops that consume more blue water and produce fewer calories to ensure the security and sustainability of food supplies. However, the improvement of water saving-technology, rationalization of agricultural water resources management, crop production allocations mentioned in this study, and other efforts are necessary to achieve this goal.

Temporal and spatial changes of blue water and green water in the Taihang Mountain Region, China, in the past 60 years

2019 ◽  
Vol 64 (16) ◽  
pp. 2040-2056 ◽  
Author(s):  
Junkai Du ◽  
Yangwen Jia ◽  
Chunfeng Hao ◽  
Yaqin Qiu ◽  
Cunwen Niu ◽  
...  
Keyword(s):  
Mountain Region ◽  
Green Water ◽  
Blue Water ◽  
The Past ◽  
Spatial Changes ◽  
Temporal And Spatial ◽  
Taihang Mountain

scholarly journals Assessing Temporal and Spatial Inequality of Water Footprint Based on Socioeconomic and Environmental Factors in Jilin Province, China

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 521 ◽  
Author(s):  
Jianqin Wang ◽  
Lijie Qin ◽  
Hongshi He
Keyword(s):  
Water Resources ◽  
Environmental Factors ◽  
Natural Water ◽  
Water Footprint ◽  
Developing Economies ◽  
Spatial Inequality ◽  
Jilin Province ◽  
Impact Factors ◽  
Rational Allocation ◽  
Temporal And Spatial

Freshwater resources are limited and uneven in their spatiotemporal distribution, and substantial increases in water demand from rapidly developing economies and concentrated populations place pressure on the available water. Research on the inequality of water footprint (WF) could provide countermeasures for the rational use and allocation of water resources. We evaluated the temporal and spatial inequality of WF using the Gini coefficient and imbalance index based on socioeconomic and environmental factors in Jilin Province. The results showed that from 2008 to 2015, the overall inequality of WF in Jilin Province was “relative equality”, and the inequalities between the WF and population, cultivated area were “high equality”; between the WF and gross domestic product (GDP) was “relative equality”; and between the WF and natural water endowment was “high inequality”. With respect to space, the differences of WF inequality were significant. In the west, the WF inequality changed greatly, from “relative equality” to “relative inequality” driven by population, GDP, cultivated area, and natural water endowment. In the middle, the WF inequality showed large internal differences with “high inequality” or “high equality” caused by GDP and natural water endowment. In the east, the WF inequality was relatively stable, at “high equality” or “neutral” affected by natural water endowment and population. The varied impact factors reflected the differences in natural resources and socioeconomic conditions in the various regions, and the results might provide a theoretical basis for guiding the rational allocation of water resources.

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