| 典型干旱指数在黄河源区的适宜性评估 |
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| 引用本文： | 王作亮,文军,李振朝,韩博,刘蓉,王欣.典型干旱指数在黄河源区的适宜性评估[J].农业工程学报,2019,35(21):186-195. |
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| 作者姓名： | 王作亮 文军 李振朝 韩博 刘蓉 王欣 |
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| 作者单位： | 1. 北京农业信息技术研究中心，北京 100097；2. 国家农业信息化工程技术研究中心，北京 100097；3. 数字植物北京市重点实验室，北京 100097,1. 北京农业信息技术研究中心，北京 100097；2. 国家农业信息化工程技术研究中心，北京 100097；3. 数字植物北京市重点实验室，北京 100097,1. 北京农业信息技术研究中心，北京 100097；2. 国家农业信息化工程技术研究中心，北京 100097；3. 数字植物北京市重点实验室，北京 100097,1. 北京农业信息技术研究中心，北京 100097；2. 国家农业信息化工程技术研究中心，北京 100097；3. 数字植物北京市重点实验室，北京 100097,1. 北京农业信息技术研究中心，北京 100097；2. 国家农业信息化工程技术研究中心，北京 100097；3. 数字植物北京市重点实验室，北京 100097,1. 北京农业信息技术研究中心，北京 100097；2. 国家农业信息化工程技术研究中心，北京 100097；3. 数字植物北京市重点实验室，北京 100097 |
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| 基金项目： | 国家重点研发计划课题（2016YFD0300605）；国家自然科学基金（31871519）；北京市农林科学院创新能力建设专项（KJCX20180423）；北京市农林科学院科研创新平台建设（PT2019-24） |
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| 摘 要： | 光线分布和叶片光合特征在冠层内部具有极强的时空异质性，基于三维冠层模型的玉米光合模型是精确评估品种高光效的重要手段。该研究将作物三维冠层模型、光线分布模型、光合模型与光能利用模型相耦合，建立了玉米冠层光合生产模型3DMaizeCaP，设置3个不同株型的玉米品种（矮单268、京科968和郑单958），2种不同光照条件（晴天和阴天），通过大田试验与模型模拟研究揭示了玉米冠层光合速率和光能利用效率对品种和环境的响应。结果表明，矮单268、京科968和郑单958的叶片最大光合速率和暗呼吸速率均随节位下降呈线性降低的垂直分布规律，各品种中矮单268的最大光合速率最大，而暗呼吸速率最小；冠层净光合速率日变化趋势明显，矮单268在阴天和晴天下的冠层最大净光合速率（以CO2计）为21.6和26.2 μmol/(m2·s)，均显著（P<0.05）高于京科968（20.8和24.9 μmol/(m2·s)）和郑单958（19.6和24.4 μmol/(m2·s)）；矮单268的日CO2净同化量在阴天和晴天下均显著（P<0.05）高于郑单958，增幅分别高达14.8%和12.4%，各品种间株型虽有显著差异（P<0.05），但冠层日累积光截获并无显著差异（P>0.05）；单叶尺度上，各叶片中第16节位的单叶日净同化量达到最大；矮单268的光能利用效率最大，在阴天和晴天下分别为3.22和3.03 g/MJ，比京科968分别高4.5%和5.6%，比郑单958分别高7.7%和7.8%；初始光量子效率对玉米冠层光能利用效率的敏感性显著高于最大光合速率（P<0.05）。从提高玉米冠层光能利用效率考虑，建议设计株型紧凑、叶片光合性能强的玉米品种。研究可为定量研究玉米冠层光合速率提供估算方法，也可为高光效品种选育提供评价依据和鉴定技术。
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| 关 键 词： | 光合作用 作物 模型 冠层光分布 三维点云 植物功能结构模型 光响应曲线 光能利用效率 |
| 收稿时间： | 2019/6/3 0:00:00 |
| 修稿时间： | 2019/10/27 0:00:00 |
Evaluation of suitability using typical drought index in source region of the Yellow River |
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| Wang Zuoliang,Wen Jun,Li Zhenchao,Han Bo,Liu Rong and Wang Xin.Evaluation of suitability using typical drought index in source region of the Yellow River[J].Transactions of the Chinese Society of Agricultural Engineering,2019,35(21):186-195. |
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| Authors: | Wang Zuoliang Wen Jun Li Zhenchao Han Bo Liu Rong and Wang Xin |
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| Institution: | 1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. Beijing Key Laboratory of Digital Plant, Beijing 100097, China,1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. Beijing Key Laboratory of Digital Plant, Beijing 100097, China,1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. Beijing Key Laboratory of Digital Plant, Beijing 100097, China,1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. Beijing Key Laboratory of Digital Plant, Beijing 100097, China,1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. Beijing Key Laboratory of Digital Plant, Beijing 100097, China and 1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. Beijing Key Laboratory of Digital Plant, Beijing 100097, China |
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| Abstract: | Abstract: As the most important catchment of the Yellow River, the drought of the source region of the Yellow River has a significant impact on water resources regulation and ecological environment protection. Although, as a foundation of drought estimates, drought index is capable of describing the intensity, range and starting and ending time of the drought, due to differences of the methodology and background in drought indexes, widely used drought index based on meteorological measurements cannot precisely depict the temporal and intensity characteristic of the drought, evaluating the performance of drought index is essential for drought monitoring and diagnosis. Therefore, soil moisture anomaly percentage index (SMAPI) from a well-instrumented regional-scale soil moisture and temperature monitoring network was identified as the reference of drought index to evaluate five droughts indices-the palmer drought severity index (PDSI), the self-calibrating palmer drought severity index (SC-PDSI), standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and monthly land water storage anomaly from gravity recovery and climate experiment (GRACE). The time series of SMAPI showed that during the whole study period there were five stages which were respectively from July 2008 to August 2009 (the first stage), September 2009 to March 2011 (the second stage), April 2011 to December 2011(the third stage), January 2012 to June 2016 (the fourth stage) and from July 2016 to June 2017 (the fifth stage). Results indicated against the first stage, two distinct features of SMAPI were presented with an initial increasing trend and increasing again after a decreasing trend at the end of the first stage. At this stage, a slight drought event occurred in the cold winter of 2008 (SMAPI=-17%). Against the second stage, except August of 2010, the SMAPI showed a slowly drying trend, especially at the end of 2010, that all SMAPI of different soil depths decreased to approximately -20% indicates during this period there was a stable drought event. Against the third stage, the study area presented a clear wetting process, and in the fall of 2011 occurring an extremely wetting event, which was the most humid month overall phases (SMAPI at 0.05 m was equal to 52%). The drought event with the longest duration was from January 2012 to June 2016 (the fourth stage), and in accordance with minimum SMAPI (SMAPI at 0.05 m, 0.10 m, and 0.20 m were equal to -47%, -43%, -41%, respectively) at three soil depths, the severest drought occurred in August 2015. The drought began to mitigate in the last stage, and concurrent SMAPI increased to larger than 5% in January 2017. The estimation of the five indexes indicated SC-PDSI had a similar trend with PDSI, but SC-PDSI showed a more stable characteristic in comparison of PDSI, and thus SC-PDSI performed the optimum effect in the Yellow River source region, but according to an existing classification of drought, it would generally overestimate the intensity of drought event, and the future work should thus need to define a new classification of drought for SC-PDSI. Against an identical time-scale parameter k, the time series of SPI and SPEI showed similar characteristics, but SPI was more suitable for assessing the intensity of drought in this study region. But when air temperature was less than 0, it would result in a large error in study area. Terrestrial water storage anomaly from gravity recovery and climate experiment, as a space-borne remote sensing observation product, showed a significant agreement with the SMAPI (correlation coefficient was 0.37, P<0.01). Relevant research should primarily focus on improving the existing drought assessment approach or developing a more suitable drought index for the source catchment of the Yellow River in future. |
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| Keywords: | photosynthesis crops models canopy light distribution 3-D point cloud plant structural-functional model light response curve radiation use efficiency |
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