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| DOI：10.13522/j.cnki.ggps.20180428 |
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| Spatiotemporal Variation of Water Use Efficiency of Crops in Main Agricultural Production Regions of China from 2000 to 2014 |
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FAN Tianyi , ZHANG Xiang
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1.State Key Lab. Of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; 2. Hubei Provincial Collaborative Innovation Center for Water Resources Security, Wuhan University, Wuhan 430072, China
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| Abstract: |
| 【Objective】Climate change will alert hydrological cycling. This paper analyzes the spatiotemporal change in crop production in main agricultural production areas in China in attempts to analyze the optimal reallocation of water resources for crop production and improve water use efficiency under globally changing climate.【Method】The analysis was based on data from 2000—2014. Python and ArcGIS were used to calculate the spatiotemporal variation of water use efficiency (WUE) of the crops in the ecosystems within the major agricultural production areas (Northeast, Inner Mongolia, North, South); we also estimated the MOD17 (GPP) and MOD16 (ET) using the MODIS remote sensing data. 【Result】①The annual WUE in major crop production areas from 2000 to 2014 in China was rising at an annual rate of 0.013 g/（mm·m2） (P<0.01), with two turning points occurring in 2003 and 2010 respectively. ②The intra-annual change in WUE was a M-type bimodal mode, with two peaks occurring in April to May and September to October, respectively. The seasonal WUE distribution differed significantly. ③The spatial distribution of WUE also varied seasonally. ④From 2000—2014, the overall WUE showed an increase, with areas seeing increase and significant increase (P<0.05) accounting for 84.01% and 39.91% of the total areas respectively. ⑤The WUE over the whole season was also in rise, although varying with location and time.【Conclusion】Under climate change, the WUE of the vegetation ecosystems in the main agricultural production areas from 2000 to 2014 in China had been rising with the intra-annual change being a M-type bimodal mode, and its distribution at seasonal and spatial scales varied considerably. |
| Key words: remote sensing; the main grain production regions; water use efficiency; spatiotemporal variation |
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