Literature DB >> 29193107

Characteristics of the water footprint of rice production under different rainfall years in Jilin Province, China.

Hongying Li1, Lijie Qin1, Hongshi He1,2.   

Abstract

BACKGROUND: Rice is a special crop, and its production differs from that of other crops because it requires a thin layer of water coverage for a long period. The calculation of the water footprint of rice production should differ from that of other crops owing to the rice growing process. This study improved the calculation of blue and grey water footprints of rice production and analyzed the variations in the water footprints for rice production under different rainfall years in Jilin Province.
RESULTS: In the drought year, the green water footprint was the lowest and the blue water footprint was the highest among the three years, while in the humid year, the green water footprint was the highest and the blue water footprint was not the lowest. The areas with higher water footprints were found in the east and west regions of Jilin Province, while the areas with lower water footprints were found in the middle east and middle regions of Jilin Province.
CONCLUSION: Blue water was the primary water resource for rice production, although more precipitation provided the highest green water in the humid year; also, the spatial distributions of water footprints were not the same under different rainfall years.
© 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Entities:  

Keywords:  Jilin Province; calculation of water footprint; different rainfall years; rice production; water footprint

Mesh:

Substances:

Year:  2018        PMID: 29193107     DOI: 10.1002/jsfa.8799

Source DB:  PubMed          Journal:  J Sci Food Agric        ISSN: 0022-5142            Impact factor:   3.638


  2 in total

1.  China's industrial gray water footprint assessment and implications for investment in industrial wastewater treatment.

Authors:  Yuanyi Huang; Beihai Zhou; Ruru Han; Xiaohui Lu; Shuo Li; Nan Li
Journal:  Environ Sci Pollut Res Int       Date:  2019-12-27       Impact factor: 4.223

2.  Crop Mapping Using the Historical Crop Data Layer and Deep Neural Networks: A Case Study in Jilin Province, China.

Authors:  Deyang Jiang; Shengbo Chen; Juliana Useya; Lisai Cao; Tianqi Lu
Journal:  Sensors (Basel)       Date:  2022-08-05       Impact factor: 3.847

  2 in total

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