Analysis and prediction of grain water footprint in Heilongjiang province based on time series model
LI Tong1, DONG Weihong2*, ZHANG Qichen2, WEN Chuanlei2
1. College of New Energy and Environment, Jilin University, Changchun, Jilin 130021, China; 2. Institute of Water Resources and Environment, Jilin University, Changchun, Jilin 130021, China
Abstract：The water footprint of main grain crops in Heilongjiang province from 2000 to 2017 was calculated by using CROPWAT 8.0 model, and the water footprint of grain crops in the province from 2018 to 2022 was predicted by using autoregression moving average(ARIMA)model. From 2000 to 2017, the total water footprint of grain crops increased by 2.84 times. Specially, the water footprint of maize fluctuated in between 0.47 and 1.07 m3/kg, while the water footprints of soybean, wheat and rice were in 1.35-2.39 m3/kg, 1.12-2.99 m3/kg, and 1.76-1.41 m3/kg, respectively. The proportion of green water footprint of wheat was the highest(72.74%), followed by corn(66.26%)and soybean(64.59%). The proportion of green water footprint of rice was the lowest(46.99%). The proportion of grey water of the four crops was all lower than 1.12%. As a simple prediction method, ARIMA model can predict the change of water footprint of grain crops in a fair accuracy. The predicted results show that the water footprint of grain crops in Heilongjiang province will increase year by year, but the water footprint of corn per unit mass will decrease yearly, the water footprint of rice and soybean per unit mass will rise year by year, and the water footprint of wheat per unit mass will remain unchanged basically. Considering the relative shortage of water resources in the province and the total water footprint of grain crops to increase year by year, it is suggested that agricultural management of the province should be strengthened to improve water use efficiency of crops.
李桐,董维红*,张琦琛,温传磊. 基于时间序列模型的黑龙江省粮食水足迹分析与预测[J]. 排灌机械工程学报, 2020, 38(11): 1152-1159.
LI Tong,DONG Weihong*,ZHANG Qichen,WEN Chuanlei. Analysis and prediction of grain water footprint in Heilongjiang province based on time series model. Journal of Drainage and Irrigation Machinery Engin, 2020, 38(11): 1152-1159.
