Loading…
The Blue, Green and Grey Water Consumption for Crop Production in Heilongjiang
Under the pressure of population growth and dietary structure change, Global consumption of freshwater resources has grown more than six fold in the past century, future demand for fresh water and food will increase significantly in the coming decades. It is necessary to research these to preserve f...
Saved in:
Published in: | Energy procedia 2019-01, Vol.158, p.3908-3914 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Under the pressure of population growth and dietary structure change, Global consumption of freshwater resources has grown more than six fold in the past century, future demand for fresh water and food will increase significantly in the coming decades. It is necessary to research these to preserve food security in China. The water footprint theory provides methods and ideas to solve such problems. This paper takes Wheat, Maize, Rice, Alfalfa, Soybean, Sunflower, Alfalfa, Sugarbet, Tobacco, Vegetable, Sweet melon, Grass and Sorghum as the main research crops, measures water footprint of crops in cities and 10 climatological stations of Heilongjiang province by CROPWAT. The results showed that there are regional differences in water footprints quantity and types of the 13 crops, the areas with large amount of grey water footprint are mainly located in southwestern, southern and central Heilongjiang, which shows that these areas have a greater water demand for environmental restoration. The gray water footprint of maize is highest in 13 crops. And the total water footprint of grass is highest in 13 crops. Almost all crops have more green water footprint and fewer grey water footprint. By focusing on these issues, decoupling analysis of agricultural water use and crop production helps to build an “ecological, intelligent, low-carbon” agricultural production system. |
---|---|
ISSN: | 1876-6102 1876-6102 |
DOI: | 10.1016/j.egypro.2019.01.853 |