2000—2014年中国粮食主产区植被水分利用效率时空演变特征研究
|
摘要
【目的】实现在气候变化背景下对粮食产区农业水资源的优化配置和水分的高效利用。【方法】利用Python、ArcGIS软件和MODIS遥感估算的MOD17和MOD16数据产品,研究了中国粮食主产区(东北、内蒙古、华北、南部)2000—2014年植被生态系统水分利用效率(water use efficiency,WUE)的时空分布规律。【结果】①年WUE(以碳计,下同)整体呈上升趋势,增速为0.013 g/(mm·m2·a)(P<0.01),2个转折点分别出现在2003、2010年;②年内WUE的变化主要呈M型的双峰模式,峰值出现在4—5月、9—10月,而季节尺度上WUE的变化具有显著差异;③不同时间尺度的WUE空间分布上具有明显的异质性;④2000—2014年来全区年WUE整体呈上升趋势,其中呈上升趋势的面积占84.01%,但上升幅度以轻度、中度为主;⑤各季WUE整体呈上升趋势,但是不同季节WUE发生上升的区域位置、面积和显著性的大小都不同。【结论】在气候变化背景下,2000—2014年中国粮食主产区植被生态系统WUE呈上升趋势,且年内呈M型的双峰结构,季节和空间尺度上的分布具有显著差异。
【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】① The annual WUE in major crop production areas from2000 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. ② The 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. ③ The spatial distribution of WUE also varied seasonally. ④ From 2000—2014, the overall WUE showed an increase, with areas seeing increase and significant increase(P<0.05) accounting for 84.01% and39.91% 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.
【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】① The annual WUE in major crop production areas from2000 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. ② The 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. ③ The spatial distribution of WUE also varied seasonally. ④ From 2000—2014, the overall WUE showed an increase, with areas seeing increase and significant increase(P<0.05) accounting for 84.01% and39.91% 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.
引文
[1]康银红.气候变化对干旱半干旱地区玉米水分利用效率影响的预测研究[D].杨凌:西北农林科技大学, 2010.
[2]谢锐敏,崔宁博,李卓,等.中国粮食主产区主要气象因子时空演变特征及其对参考作物蒸散量影响[J].灌溉排水学报, 2017, 36(9):81-89.
[3]刘宪锋,胡宝怡,任志远.黄土高原植被生态系统水分利用效率时空变化及驱动因素[J].中国农业科学, 2018, 51(2):302-314.
[4]张春敏,梁川,龙训建,等.江河源区植被水分利用效率遥感估算及动态变化[J].农业工程学报, 2013, 29(18):146-155.
[5] ZHU Xianjin, YU Guirui, WANG Qiufeng, et al. Spatial variability of water use efficiency in China's terrestrial ecosystems[J]. Global&Planetary Change, 2015, 129:37-44.
[6] LIU Yibo, XIAO Jingfeng, JU Weimin, et al. Water use efficiency of China’s terrestrial ecosystems and responses to drought[J]. Scientific Reports,2015, 5:13799.
[7]李肖娟,张福平,王虎威,等.黑河流域植被水分利用效率时空变化特征及其与气候因子的关系[J].中国沙漠, 2017, 37(4):733-741.
[8]仇宽彪,成军锋.陕西省植被水分利用效率及与气候因素的关系[J].水土保持研究, 2015, 22(6):256-260.
[9]徐晓桃.黄河源区NPP及植被水分利用效率时空特征分析[D].兰州:兰州大学, 2008.
[10]刘彦随,翟荣新.中国粮食生产时空格局动态及其优化策略探析[J].地域研究与开发, 2009, 28(1):1-5.
[11]李世奎.中国农业气候区划[J].自然资源学报, 1987(1):71-83.
[12] ZHAO Maosheng, HEINSCH F A, NEMANI R R, et al. Improvements of the MODIS terrestrial gross and net primary production global data set[J].Remote Sensing of Environment, 2005, 95(2):164-176.
[13] TURNER D P, RITTS W D, COHEN W B, et al. Evaluation of MODIS NPP and GPP products across multiple biomes[J]. Remote Sensing of Environment, 2006, 102(3):282-292.
[14] MU Q, ZHAO M, RUNNING S W. Improvements to a MODIS global terrestrial evapotranspiration algorithm[J]. Remote Sensing of Environment,2011, 115(8):1781-1800.
[15] MU Qiaozhen, ZHAO Maosheng, KIMBALL J S, et al. A Remotely Sensed Global Terrestrial Drought Severity Index[J]. Bulletin of the American Meteorological Society, 2013, 94(1):83-98.
[16]张特,刘冀,董晓华,等.基于MOD16的澴河流域蒸散发时空分布特征[J].灌溉排水学报, 2018, 37(8):121-128.
[17]吴桂平,刘元波,赵晓松,等.基于MOD16产品的鄱阳湖流域地表蒸散量时空分布特征[J].地理研究, 2013, 32(4):617-627.
[18] SUN Ge, CALDWELL P, NOORMETS A, et al. Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model[J]. Journal of Geophysical Research Biogeosciences, 2015, 116(G3):2011.
[19] LIANG Wei, YANG Yuting, FAN Dongmei, et al. Analysis of spatial and temporal patterns of net primary production and their climate controls in China from 1982 to 2010[J]. Agricultural&Forest Meteorology, 2015, 204:22-36.
[20] LENHART T, ECKHARDT K, FOHRER N, et al. Comparison of two different approaches of sensitivity analysis[J]. Physics&Chemistry of the Earth,2002, 27(9):645-654.
[21] LIU Y, ZHOU Y, JU W, et al. Impacts of droughts on carbon sequestration by China’s terrestrial ecosystems from 2000 to 2011[J]. Biogeosciences,2014, 11(10):2 583-2 599.
[22]李小利,张文英,王春晖.滴灌施肥对华北小麦-玉米产量和水分利用效率的影响[J].灌溉排水学报, 2018, 37(4):18-28.
[23]冯保清,雷慧闽,吕华芳.位山灌区冬小麦及夏玉米群体水分利用效率分析[J].灌溉排水学报, 2013, 32(3):29-32.
[24] XUE BaoLin, GUO Qinghua, ALVAREZ OTTO, et al. Global patterns, trends, and drivers of water use efficiency from 2000 to 2013[J]. Ecosphere,2016, 6(10):1-18.
[2]谢锐敏,崔宁博,李卓,等.中国粮食主产区主要气象因子时空演变特征及其对参考作物蒸散量影响[J].灌溉排水学报, 2017, 36(9):81-89.
[3]刘宪锋,胡宝怡,任志远.黄土高原植被生态系统水分利用效率时空变化及驱动因素[J].中国农业科学, 2018, 51(2):302-314.
[4]张春敏,梁川,龙训建,等.江河源区植被水分利用效率遥感估算及动态变化[J].农业工程学报, 2013, 29(18):146-155.
[5] ZHU Xianjin, YU Guirui, WANG Qiufeng, et al. Spatial variability of water use efficiency in China's terrestrial ecosystems[J]. Global&Planetary Change, 2015, 129:37-44.
[6] LIU Yibo, XIAO Jingfeng, JU Weimin, et al. Water use efficiency of China’s terrestrial ecosystems and responses to drought[J]. Scientific Reports,2015, 5:13799.
[7]李肖娟,张福平,王虎威,等.黑河流域植被水分利用效率时空变化特征及其与气候因子的关系[J].中国沙漠, 2017, 37(4):733-741.
[8]仇宽彪,成军锋.陕西省植被水分利用效率及与气候因素的关系[J].水土保持研究, 2015, 22(6):256-260.
[9]徐晓桃.黄河源区NPP及植被水分利用效率时空特征分析[D].兰州:兰州大学, 2008.
[10]刘彦随,翟荣新.中国粮食生产时空格局动态及其优化策略探析[J].地域研究与开发, 2009, 28(1):1-5.
[11]李世奎.中国农业气候区划[J].自然资源学报, 1987(1):71-83.
[12] ZHAO Maosheng, HEINSCH F A, NEMANI R R, et al. Improvements of the MODIS terrestrial gross and net primary production global data set[J].Remote Sensing of Environment, 2005, 95(2):164-176.
[13] TURNER D P, RITTS W D, COHEN W B, et al. Evaluation of MODIS NPP and GPP products across multiple biomes[J]. Remote Sensing of Environment, 2006, 102(3):282-292.
[14] MU Q, ZHAO M, RUNNING S W. Improvements to a MODIS global terrestrial evapotranspiration algorithm[J]. Remote Sensing of Environment,2011, 115(8):1781-1800.
[15] MU Qiaozhen, ZHAO Maosheng, KIMBALL J S, et al. A Remotely Sensed Global Terrestrial Drought Severity Index[J]. Bulletin of the American Meteorological Society, 2013, 94(1):83-98.
[16]张特,刘冀,董晓华,等.基于MOD16的澴河流域蒸散发时空分布特征[J].灌溉排水学报, 2018, 37(8):121-128.
[17]吴桂平,刘元波,赵晓松,等.基于MOD16产品的鄱阳湖流域地表蒸散量时空分布特征[J].地理研究, 2013, 32(4):617-627.
[18] SUN Ge, CALDWELL P, NOORMETS A, et al. Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model[J]. Journal of Geophysical Research Biogeosciences, 2015, 116(G3):2011.
[19] LIANG Wei, YANG Yuting, FAN Dongmei, et al. Analysis of spatial and temporal patterns of net primary production and their climate controls in China from 1982 to 2010[J]. Agricultural&Forest Meteorology, 2015, 204:22-36.
[20] LENHART T, ECKHARDT K, FOHRER N, et al. Comparison of two different approaches of sensitivity analysis[J]. Physics&Chemistry of the Earth,2002, 27(9):645-654.
[21] LIU Y, ZHOU Y, JU W, et al. Impacts of droughts on carbon sequestration by China’s terrestrial ecosystems from 2000 to 2011[J]. Biogeosciences,2014, 11(10):2 583-2 599.
[22]李小利,张文英,王春晖.滴灌施肥对华北小麦-玉米产量和水分利用效率的影响[J].灌溉排水学报, 2018, 37(4):18-28.
[23]冯保清,雷慧闽,吕华芳.位山灌区冬小麦及夏玉米群体水分利用效率分析[J].灌溉排水学报, 2013, 32(3):29-32.
[24] XUE BaoLin, GUO Qinghua, ALVAREZ OTTO, et al. Global patterns, trends, and drivers of water use efficiency from 2000 to 2013[J]. Ecosphere,2016, 6(10):1-18.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |