干旱对作物产量影响研究进展与展望

doi:10.11821/dlxb202111003

地理学报 ›› 2021, Vol. 76 ›› Issue (11): 2632-2646.doi: 10.11821/dlxb202111003

干旱对作物产量影响研究进展与展望

刘宪锋¹^,²(), 傅伯杰²()

1.陕西师范大学地理科学与旅游学院,西安 710119
2.中国科学院生态环境研究中心,北京 100085

收稿日期:2020-08-11 修回日期:2021-03-25 出版日期:2021-11-25 发布日期:2022-01-25
通讯作者: 傅伯杰(1958-), 男, 中国科学院院士, 研究员, 博士生导师, 中国地理学会会员(S110001618M), 主要从事地理学综合研究。E-mail: bfu@rcees.ac.cn
作者简介:刘宪锋(1986-), 男, 黑龙江人, 副教授, 硕士生导师, 中国地理学会会员(S110011521M), 主要从事气候变化与生态水文研究。E-mail: liuxianfeng7987@163.com
基金资助:
国家自然科学基金项目(41801333);国家自然科学基金项目(41991230);陕西省自然科学基金项目(2020JQ-417);陕西省社会科学基金项目(2020D039);中央高校基本科研业务费专项(GK201901009);中央高校基本科研业务费专项(GK202003068)

Drought impacts on crop yield: Progress, challenges and prospect

LIU Xianfeng¹^,²(), FU Bojie²()

1. School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
2. Research Center for Eco-Environmental Sciences, CAS, Beijing 100085, China

Received:2020-08-11 Revised:2021-03-25 Published:2021-11-25 Online:2022-01-25
Supported by:
National Natural Science Foundation of China(41801333);National Natural Science Foundation of China(41991230);Natural Science Foundation of Shaanxi Province(2020JQ-417);Social Science Foundation of Shaanxi Province(2020D039);Fundamental Research Funds for the Central Universities(GK201901009);Fundamental Research Funds for the Central Universities(GK202003068)

摘要/Abstract

摘要：

粮食安全关乎人类生存和社会发展,是总体国家安全观的重要组成部分。本文首先梳理了作物产量影响因素及干旱对作物产量的影响过程,进而从基于田间控制实验、统计模型、作物生长机理模型以及遥感反演模型等4个方面系统回顾了干旱对全球主要作物产量影响评估的最新进展,揭示出当前研究呈现出由单灾种向多灾种、由单目标向多目标、由统计模型向综合模型转变的特征。文献计量分析表明,1990—2020年干旱对作物产量影响研究发文量呈指数增长,且研究主题经历了由传统的作物水分胁迫到作物受旱影响与适应综合研究的转变过程,体现出研究视角的不断深化和综合。在学科分布上,农学、植物学和环境科学是研究干旱对作物产量影响的主要学科,建议应加强地理学多要素多尺度的系统性思维在粮食和水资源耦合系统研究中的应用。最后,在分析现有问题和挑战的基础上,将未来应关注的重要议题归纳为以下4个方面,即构建干旱对作物产量影响的多源信息数据库、阐明干旱对作物产量影响的关键过程及机理、发展耦合宏观与微观过程作物生长机理模型和搭建作物产量与粮食安全综合监测平台系统,旨在通过提高干旱对作物产量影响的监测预警和科学管控,实现农业可持续发展和全球粮食安全。

关键词: 干旱, 作物产量, 粮食安全, 研究进展, 研究展望

Abstract:

Food security, one of key components of national security, is a top priority for human survival and social development. In this study, we first sought to determine the influencing factors of crop yields and the process of drought impacts on crop yields. We then systematically reviewed the effects of droughts on major global crop yields from four aspects: field control experiments, statistical models, crop growth models, and remote sensing inversion models. Recent progress in crop yield impact assessment reveals that the current research has changed from single-hazard to multi-hazard, from single target to multiple targets, and from statistical models to a comprehensive model. A bibliometric analysis shows that the volume of research on drought impacts on crop yields has increased exponentially, and the related research theme has undergone a transformation from traditional research on crop water stress to comprehensive research on crop drought impacts and adaptation, reflecting the continuous deepening and integration of research perspectives. Agriculture, plant sciences, and environmental sciences are the three main disciplines in research on drought impacts on crop yields. We need to strengthen the application of geographical thinking, that is, systematic thinking concerning multiple factors and multiple scales to study the coupling of crop yields and water resources in the future. Finally, we suggest the following four priority areas for future research in consideration of the problems and challenges of the existing research: establishing a multi-source database of drought impact on crop yield, revealing the key process and mechanism of drought impacts on crop yields, developing a coupled macro and micro process crop growth model, and establishing a comprehensive monitoring platform system for crop yields and food security. This will help ensure sustainable agricultural development and global food security by improving monitoring, early warning, and scientific management of the impacts of droughts on crop yields.

Key words: drought, crop yield, food security, research progress, research prospect

刘宪锋, 傅伯杰. 干旱对作物产量影响研究进展与展望[J]. 地理学报, 2021, 76(11): 2632-2646.

LIU Xianfeng, FU Bojie. Drought impacts on crop yield: Progress, challenges and prospect[J]. Acta Geographica Sinica, 2021, 76(11): 2632-2646.

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参考文献 81

[1]	Wang Hao, Yang Guiyu, Yang Zhaohui. Thinking of agriculture development in China based on regional water resources and land cultivation. Bulletin of the Chinese Academy of Sciences, 2013, 28(3):329-336, 321.
	[王浩, 杨贵羽, 杨朝晖. 水土资源约束下保障粮食安全的战略思考. 中国科学院院刊, 2013, 28(3):329-336, 321.]
[2]	Yu Chaoqing. The coupled effects of water and nitrogen on China's food and environmental securities. Scientia Sinica: Terrae, 2019, 49(12):2018-2036. doi: 10.1360/SSTe-2019-0041
	[喻朝庆. 水—氮耦合机制下的中国粮食与环境安全. 中国科学: 地球科学, 2019, 49(12):2018-2036.]
[3]	Liu Xianfeng, Zhu Xiufang, Pan Yaozhong, et al. Agricultural drought monitor: Progress, challenges and prospect. Acta Geographica Sinica, 2015, 70(11):1835-1848. doi: 10.11821/dlxb201511012
	[刘宪锋, 朱秀芳, 潘耀忠, 等. 农业干旱监测研究进展与展望. 地理学报, 2015, 70(11):1835-1848.]
[4]	Lesk C, Rowhani P, Ramankutty N. Influence of extreme weather disasters on global crop production. Nature, 2016, 529(7584):84-87. doi: 10.1038/nature16467
[5]	Wu Jianjun, Geng Guangpo, Zhou Hongkui, et al. Global vulnerability to agricultural drought and its spatial characteristics. Scientia Sinica: Terrae, 2017, 47(6):733-744. doi: 10.1360/N072016-00098
	[武建军, 耿广坡, 周洪奎, 等. 全球农业旱灾脆弱性及其空间分布特征. 中国科学: 地球科学, 2017, 47(6):733-744.]
[6]	Shi Wenjiao, Tao Fulu, Zhang Zhao. Identifying contributions of climate change to crop yields based on statistical models: A review. Acta Geographica Sinica, 2012, 67(9):1213-1222.
	[史文娇, 陶福禄, 张朝. 基于统计模型识别气候变化对农业产量贡献的研究进展. 地理学报, 2012, 67(9):1213-1222.]
[7]	Yao Yubi, Yang Jinhu, Xiao Guoju, et al. Research advances in the impacts of climate warming on rainfed agriculture and agro-ecology in Northwest China. Chinese Journal of Ecology, 2018, 37(7):2170-2179.
	[姚玉璧, 杨金虎, 肖国举, 等. 气候变暖对西北雨养农业及农业生态影响研究进展. 生态学杂志, 2018, 37(7):2170-2179.]
[8]	Food and Agriculture Organization of the United Nations. The state of food security and nutrition in the world, 2018.
[9]	Liu Xianfeng, Zhu Xiufang, Pan Yaozhong, et al. The spatial-temporal changes of cold surge in Inner Mongolia during recent 53 years. Acta Geographica Sinica, 2014, 69(7):1013-1024. doi: 10.11821/dlxb201407013
	[刘宪锋, 朱秀芳, 潘耀忠, 等. 近53年内蒙古寒潮时空变化特征及其影响因素. 地理学报, 2014, 69(7):1013-1024.]
[10]	Leng G Y, Hall J. Crop yield sensitivity of global major agricultural countries to droughts and the projected changes in the future. Science of the Total Environment, 2019, 654:811-821. doi: 10.1016/j.scitotenv.2018.10.434
[11]	Li Y, Guan K Y, Schnitkey G D, et al. Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States. Global Change Biology, 2019, 25(7):2325-2337. doi: 10.1111/gcb.2019.25.issue-7
[12]	Rosenzweig C, Jones J W, Hatfield J L, et al. The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies. Agricultural and Forest Meteorology, 2013, 170:166-182. doi: 10.1016/j.agrformet.2012.09.011
[13]	Warszawski L, Frieler K, Huber V, et al. The inter-sectoral impact model intercomparison project (ISI-MIP): Project framework. PNAS, 2014, 111(9):3228-3232. doi: 10.1073/pnas.1312330110 pmid: 24344316
[14]	Piao S L, Zhang X P, Chen A P, et al. The impacts of climate extremes on the terrestrial carbon cycle: A review. Science China Earth Sciences, 2019, 62(10):1551-1563. doi: 10.1007/s11430-018-9363-5
[15]	Prado K, Maurel C. Regulation of leaf hydraulics: From molecular to whole plant levels. Frontiers in Plant Science, 2013, 4:255. DOI: 10.3389/fpls.2013.00255. doi: 10.3389/fpls.2013.00255
[16]	Çakir R. Effect of water stress at different development stages on vegetative and reproductive growth of corn. Field Crops Research, 2004, 89(1):1-16. doi: 10.1016/j.fcr.2004.01.005
[17]	Hussain H A, Men S, Hussain S, et al. Interactive effects of drought and heat stresses on morpho-physiological attributes, yield, nutrient uptake and oxidative status in maize hybrids. Scientific Reports, 2019, 9(1):3890. DOI: 10.1038/s41598-019-40362-7. doi: 10.1038/s41598-019-40362-7 pmid: 30846745
[18]	Yao Ning, Song Libing, Liu Jian, et al. Effects of water stress at different growth stages on the development and yields of winter wheat in arid region. Scientia Agricultura Sinica, 2015, 48(12):2379-2389.
	[姚宁, 宋利兵, 刘健, 等. 不同生长阶段水分胁迫对旱区冬小麦生长发育和产量的影响. 中国农业科学, 2015, 48(12):2379-2389.]
[19]	Wang Shuji, Kang Shaozhong, Li Tao. Suitable water deficit mode for winter wheat basing objective of water saving as well as high yield and quality. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(12):111-118.
	[王书吉, 康绍忠, 李涛. 基于节水高产优质目标的冬小麦适宜水分亏缺模式. 农业工程学报, 2015, 31(12):111-118.]
[20]	Song Libing, Yao Ning, Feng Hao, et al. Effects of water stresses at different growth stages on development and yields of summer maize in arid region. Journal of Maize Sciences, 2016, 24(1):63-73.
	[宋利兵, 姚宁, 冯浩, 等. 不同生育阶段受旱对旱区夏玉米生长发育和产量的影响. 玉米科学, 2016, 24(1):63-73.]
[21]	Wang Mixia, Kang Shaozhong, Cai Huanjie, et al. The effect of regulated deficit irrigation on ecological characteristics and yield of corn. Journal of Northwest Agriculture University, 2000, 28(1):31-36.
	[王密侠, 康绍忠, 蔡焕杰, 等. 调亏对玉米生态特性及产量的影响. 西北农业大学学报, 2000, 28(1):31-36.]
[22]	Ma L S, Li Y J, Wu P T, et al. Coupling evapotranspiration partitioning with water migration to identify the water consumption characteristics of wheat and maize in an intercropping system. Agricultural and Forest Meteorology, 2020, 290:108034. DOI: 10.1016/j.agrformet.2020.108034. doi: 10.1016/j.agrformet.2020.108034
[23]	Chen S, Jiang T C, Ma H J, et al. Dynamic within-season irrigation scheduling for maize production in Northwest China: A method based on weather data fusion and yield prediction by DSSAT. Agricultural and Forest Meteorology, 2020, 285-286:107928. doi: 10.1016/j.agrformet.2020.107928
[24]	Kisekka I, Schlegel A, Ma L, et al. Optimizing preplant irrigation for maize under limited water in the High Plains. Agricultural Water Management, 2017, 187:154-163. doi: 10.1016/j.agwat.2017.03.023
[25]	Lei Tingwu, Xiao Juan, Zhan Weihua, et al. Effect of water quality in furrow irrigation on corn yield and soil salinity. Journal of Hydraulic Engineering, 2004, 35(9):118-122.
	[雷廷武, 肖娟, 詹卫华, 等. 沟灌条件下不同灌溉水质对玉米产量和土壤盐分的影响. 水利学报, 2004, 35(9):118-122.]
[26]	Prasad A K, Chai L, Singh R P, et al. Crop yield estimation model for Iowa using remote sensing and surface parameters. International Journal of Applied Earth Observation and Geoinformation, 2006, 8(1):26-33. doi: 10.1016/j.jag.2005.06.002
[27]	Lobell D B, Schlenker W, Costa-Roberts J. Climate trends and global crop production since 1980. Science, 2011, 333(6042):616-620. doi: 10.1126/science.1204531 pmid: 21551030
[28]	Lobell D B, Cahill K N, Field C B. Historical effects of temperature and precipitation on California crop yields. Climatic Change, 2007, 81(2):187-203. doi: 10.1007/s10584-006-9141-3
[29]	Lobell D B, Roberts M J, Schlenker W, et al. Greater sensitivity to drought accompanies maize yield increase in the US Midwest. Science, 2014, 344(6183):516-519. doi: 10.1126/science.1251423 pmid: 24786079
[30]	Madadgar S, AghaKouchak A, Farahmand A, et al. Probabilistic estimates of drought impacts on agricultural production. Geophysical Research Letters, 2017, 44(15):7799-7807. doi: 10.1002/2017GL073606
[31]	Peña-Gallardo M, Vicente-Serrano S M, Quiring S, et al. Response of crop yield to different time-scales of drought in the United States: Spatio-temporal patterns and climatic and environmental drivers. Agricultural and Forest Meteorology, 2019, 264:40-55. doi: 10.1016/j.agrformet.2018.09.019
[32]	Harrison M T, Tardieu F, Dong Z S, et al. Characterizing drought stress and trait influence on maize yield under current and future conditions. Global Change Biology, 2014, 20(3):867-878. doi: 10.1111/gcb.12381 pmid: 24038882
[33]	Jin Z N, Ainsworth E A, Leakey A D B, et al. Increasing drought and diminishing benefits of elevated carbon dioxide for soybean yields across the US Midwest. Global Change Biology, 2018, 24(2):e522-e533.
[34]	Yu Huiqian, Zhang Qiang, Sun Peng, et al. Impacts of drought intensity and drought duration on winter wheat yield in five provinces of North China Plain. Acta Geographica Sinica, 2019, 74(1):87-102. doi: 10.11821/dlxb201901007
	[余慧倩, 张强, 孙鹏, 等. 干旱强度及发生时间对华北平原五省冬小麦产量影响. 地理学报, 2019, 74(1):87-102.]
[35]	Huang Jianxi, Zhang Jie, Liu Junming, et al. Correlation analysis between drought and winter wheat yields based on remotely sensed drought severity index. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(3):166-173.
	[黄健熙, 张洁, 刘峻明, 等. 基于遥感DSI指数的干旱与冬小麦产量相关性分析. 农业机械学报, 2015, 46(3):166-173.]
[36]	Guo E L, Liu X P, Zhang J Q, et al. Assessing spatiotemporal variation of drought and its impact on maize yield in Northeast China. Journal of Hydrology, 2017, 553:231-247. doi: 10.1016/j.jhydrol.2017.07.060
[37]	Liu Wei, Li Yijun, He Liang, et al. Effect of growing season drought on spring maize yields in Northeast China based on standardized precipitation index. Transactions of the Chinese Society of Agricultural Engineering, 2018, 34(22):121-127.
	[刘维, 李祎君, 何亮, 等. 基于SPI判定的东北春玉米生长季干旱对产量的影响. 农业工程学报, 2018, 34(22):121-127.]
[38]	Zhu Ran, Fang Yiping. Impact of drought on crops yield and its spatial difference in the mid-mountain of the Koshi basion. Arid Zone Research, 2019, 36(1):237-243.
	[朱冉, 方一平. 柯西河流域干旱对作物产量的影响及其空间差异. 干旱区研究, 2019, 36(1):237-243.]
[39]	Schauberger B, Archontoulis S, Arneth A, et al. Consistent negative response of US crops to high temperatures in observations and crop models. Nature Communications, 2017, 8:13931. DOI: 10.1038/ncomms13931. doi: 10.1038/ncomms13931 pmid: 28102202
[40]	Zhao C, Piao S L, Wang X H, et al. Plausible rice yield losses under future climate warming. Nature Plants, 2017, 3(1):16202. DOI: 10.1038/nplants.2016.202. doi: 10.1038/nplants.2016.202
[41]	Zhao C, Liu B, Piao S L, et al. Temperature increase reduces global yields of major crops in four independent estimates. PNAS, 2017, 114(35):9326-9331. doi: 10.1073/pnas.1701762114
[42]	Asseng S, Cammarano D, Basso B, et al. Hot spots of wheat yield decline with rising temperatures. Global Change Biology, 2017, 23(6):2464-2472. doi: 10.1111/gcb.13530
[43]	Liu B, Asseng S, Müller C, et al. Similar estimates of temperature impacts on global wheat yield by three independent methods. Nature Climate Change, 2016, 6(12):1130-1136. doi: 10.1038/nclimate3115
[44]	Lobell D B, Bänziger M, Magorokosho C, et al. Nonlinear heat effects on African maize as evidenced by historical yield trials. Nature Climate Change, 2011, 1(1):42-45.
[45]	Moore F C, Lobell D B. The fingerprint of climate trends on European crop yields. PNAS, 2015, 112(9):2670-2675. doi: 10.1073/pnas.1409606112
[46]	Gammans M, Mérel P, Ortiz-Bobea A. Negative impacts of climate change on cereal yields: Statistical evidence from France. Environmental Research Letters, 2017, 12(5):54007. DOI: 10.1088/1748-9326/aa6b0c. doi: 10.1088/1748-9326/aa6b0c
[47]	Zandalinas S I, Mittler R, Balfagon D, et al. Plant adaptations to the combination of drought and high temperatures. Physiologia Plantarum, 2018, 162(1):2-12. doi: 10.1111/ppl.2018.162.issue-1
[48]	Vogel E, Donat M G, Alexander L V, et al. The effects of climate extremes on global agricultural yields. Environmental Research Letters, 2019, 14(5):54010. DOI: 10.1088/1748-9326/ab154b. doi: 10.1088/1748-9326/ab154b
[49]	Liu X F, Pan Y Z, Zhu X F, et al. Drought evolution and its impact on the crop yield in the North China Plain. Journal of Hydrology, 2018, 564:984-996. doi: 10.1016/j.jhydrol.2018.07.077
[50]	Tao F L, Rötter R P, Palosuo T, et al. Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments. Global Change Biology, 2018, 24(3):1291-1307. doi: 10.1111/gcb.2018.24.issue-3
[51]	Müller C, Elliott J, Chryssanthacopoulos J, et al. Global gridded crop model evaluation: Benchmarking, skills, deficiencies and implications. Geoscientific Model Development, 2017, 10(4):1403-1422. doi: 10.5194/gmd-10-1403-2017
[52]	Charles B C, Elijah P, Vernon R N C. Climate change impact on maize (Zea mays L.) yield using crop simulation and statistical downscaling models: A review. Scientific Research and Essays, 2017, 12(18):167-187. doi: 10.5897/SRE
[53]	Peng B, Guan K Y, Tang J Y, et al. Towards a multiscale crop modelling framework for climate change adaptation assessment. Nature Plants, 2020, 6(4):338-348. doi: 10.1038/s41477-020-0625-3 pmid: 32296143
[54]	Sun Yangyue, Shen Shuanghe. Research progress in application of crop growth models. Chinese Journal of Agrometeorology, 2019, 40(7):444-459.
	[孙扬越, 申双和. 作物生长模型的应用研究进展. 中国农业气象, 2019, 40(7):444-459.]
[55]	Wang Q F, Wu J J, Li X H, et al. A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model. International Journal of Biometeorology, 2017, 61(4):685-699. doi: 10.1007/s00484-016-1246-4
[56]	Wang Yakai, Liu Mengyu, Dong Baodi, et al. Simulation of drought impact on yield of rainfed wheat and maize in the piedmont plain of Mt. Taihang, China. Agricultural Research in the Arid Areas, 2019, 37(2):185-194.
	[王亚凯, 刘孟雨, 董宝娣, 等. 干旱对太行山山前平原雨养农田产量影响的模拟研究. 干旱地区农业研究, 2019, 37(2):185-194.]
[57]	Xu Jianwen, Ju Hui, Mei Xurong, et al. Simulation on potential effects of drought on winter wheat in Huang-Huai-Hai plain from 1981 to 2020. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(6):150-158.
	[徐建文, 居辉, 梅旭荣, 等. 近30年黄淮海平原干旱对冬小麦产量的潜在影响模拟. 农业工程学报, 2015, 31(6):150-158.]
[58]	Zhang Jianping, Zhao Yanxia, Wang Chunyi, et al. Evaluation technology on drought disaster to yields of winter wheat based on WOFOST crop growth model. Acta Ecologica Sinica, 2013, 33(6):1762-1769. doi: 10.5846/stxb
	[张建平, 赵艳霞, 王春乙, 等. 基于WOFOST作物生长模型的冬小麦干旱影响评估技术. 生态学报, 2013, 33(6):1762-1769.]
[59]	Blanc E, Caron J, Fant C, et al. Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields. Earth's Future, 2017, 5(8):877-892.
[60]	Rosenzweig C, Elliott J, Deryng D, et al. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. PNAS, 2014, 111(9):3268-3273. doi: 10.1073/pnas.1222463110 pmid: 24344314
[61]	Li Sijia, Sun Yannan, Li Meng, et al. Research on the progress of domestic and foreign crop yield estimation by RS. World Agriculture, 2013, 409:125-127, 131.
	[李思佳, 孙艳楠, 李蒙, 等. 国内外农作物遥感估产的研究进展. 世界农业, 2013, 409:125-127, 131.]
[62]	Li Weiguo, Li Hua. Progress and countermeasures of rice yield estimation by satellite remote sensing. Jiangsu Agricultural Sciences, 2010(5):444-445.
	[李卫国, 李花. 水稻卫星遥感估产研究现状与对策. 江苏农业科学, 2010(5):444-445.]
[63]	Lobell D B, Sibley A, Ivan Ortiz-Monasterio J. Extreme heat effects on wheat senescence in India. Nature Climate Change, 2012, 2(3):186-189. doi: 10.1038/nclimate1356
[64]	Lobell D B, Azzari G. Satellite detection of rising maize yield heterogeneity in the US Midwest. Environmental Research Letters, 2017, 12(1):14014. DOI: 10.1088/1748-9326/aa5371. doi: 10.1088/1748-9326/aa5371
[65]	Azzari G, Jain M, Lobell D B. Towards fine resolution global maps of crop yields: Testing multiple methods and satellites in three countries. Remote Sensing of Environment, 2017, 202:129-141. doi: 10.1016/j.rse.2017.04.014
[66]	Wu Bingfang, Meng Jihua, Li Qiangzi, et al. Latest development of crop watch: An global crop monitoring system with remote sensing. Advances in Earth Science, 2010, 25(10):1013-1022.
	[吴炳方, 蒙继华, 李强子, 等. 全球农情遥感速报系统crop watch新进展. 地球科学进展, 2010, 25(10):1013-1022.]
[67]	Wu Bingfang, Zhang Miao, Zeng Hongwei, et al. Twenty years of crop watch: Progress and prospect. Journal of Remote Sensing, 2019, 23(6):1053-1063.
	[吴炳方, 张淼, 曾红伟, 等. 全球农情遥感速报系统20年. 遥感学报, 2019, 23(6):1053-1063.]
[68]	Chen Zhongxin, Ren Jianqiang, Tang Huajun, et al. Progress and perspectives on agricultural remote sensing research and applications in China. Journal of Remote Sensing, 2016, 20(5):748-767.
	[陈仲新, 任建强, 唐华俊, 等. 农业遥感研究应用进展与展望. 遥感学报, 2016, 20(5):748-767.]
[69]	Li Qiangzi, Yan Nana, Zhang Feifei, et al. Drought monitoring and its impacts assessment in southwest China using remote sensing in the spring of 2010. Acta Geographica Sinica, 2010, 65(7):771-780.
	[李强子, 闫娜娜, 张飞飞, 等. 2010年春季西南地区干旱遥感监测及其影响评估. 地理学报, 2010, 65(7):771-780.]
[70]	Huang Jianxi, Ma Hongyuan, Tian Liyan, et al. Comparison of remote sensing yield estimation methods for winter wheat based on assimilating time-sequence LAI and ET. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(4):197-203.
	[黄健熙, 马鸿元, 田丽燕, 等. 基于时间序列LAI和ET同化的冬小麦遥感估产方法比较. 农业工程学报, 2015, 31(4):197-203.]
[71]	Burke M, Lobell D B. Satellite-based assessment of yield variation and its determinants in smallholder African systems. PNAS, 2017, 114(9):2189-2194. doi: 10.1073/pnas.1616919114
[72]	Guan K Y, Berry J A, Zhang Y G, et al. Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence. Global Change Biology, 2016, 22(2):716-726. doi: 10.1111/gcb.2016.22.issue-2
[73]	Peng B, Guan K Y, Zhou W, et al. Assessing the benefit of satellite-based solar-induced chlorophyll fluorescence in crop yield prediction. International Journal of Applied Earth Observation and Geoinformation, 2020, 90:102126. DOI: 10.1016/j.jag.2020.102126. doi: 10.1016/j.jag.2020.102126
[74]	Song Changqing, Zhang Guoyou, Cheng Changxiu, et al. Nature and basic issues of Geography. Scientia Geographica Sinica, 2020, 40(1):6-11. doi: 10.13249/j.cnki.sgs.2020.01.002
	[宋长青, 张国友, 程昌秀, 等. 论地理学的特性与基本问题. 地理科学, 2020, 40(1):6-11.]
[75]	Smajgl A, Ward J. The Water-food-energy Nexus in the Mekong Region: Assessing Development Strategies Considering Cross-sectoral and Transboundary Impacts. New York: Springer Science & Business Media, 2013.
[76]	Kreibich H, Blauhut V, Aerts J C J H, et al. How to improve attribution of changes in drought and flood impacts. Hydrological Sciences Journal, 2019, 64(1):1-18. doi: 10.1080/02626667.2018.1558367
[77]	Yang Yang, Shen Shuanghe, Ma Yihao, et al. Advances in the effects of drought on crop growth and research on drought resistance techniques. Bulletin of Science and Technology, 2020, 36(1):8-15.
	[杨阳, 申双和, 马绎皓, 等. 干旱对作物生长的影响机制及抗旱技术的研究进展. 科技通报, 2020, 36(1):8-15.]
[78]	Yi Zihao, Zhu Defeng, Wang Yaliang, et al. Advances of rice growth response to drought and its compensatory effects. China Rice, 2020, 26(4):1-6, 9.
	[易子豪, 朱德峰, 王亚梁, 等. 水稻生长对干旱的响应及其补偿效应研究进展. 中国稻米, 2020, 26(4):1-6, 9.]
[79]	Wang Ying, Jia Lili, Shi Yan. Ripple effect of drought disaster on maize supply chain of Heilongjiang province based on inoperability input-output model. Journal of Catastrophology, 2020, 35(3):24-28.
	[王英, 贾丽丽, 史岩. 基于IIM的干旱灾害对黑龙江省玉米供应链的级联影响研究. 灾害学, 2020, 35(3):24-28.]
[80]	Zhang Junhua, Liu Jianli, Zhang Jiabao. Advances on crop models. Soils, 2012, 44(1):1-9.
	[张均华, 刘建立, 张佳宝. 作物模型研究进展. 土壤, 2012, 44(1):1-9.]
[81]	Wang S, Fu B J, Bodin Ö, et al. Alignment of social and ecological structures increased the ability of river management. Science Bulletin, 2019, 64(18):1318-1324. doi: 10.1016/j.scib.2019.07.016

研究手段	尺度	优点	缺点
控制实验	点、样地	① 能够提供详细的资料 ② 实验结果精度较高 ③ 实验数据能够建模或调参	① 实验样地小,扩展性差 ② 试验周期长、人为影响大 ③ 实验与真实环境存在差异
统计模型	点、行政区	① 能够充分利用历史产量数据 ② 可开展不同时空尺度的研究 ③ 操作简单、重复性强	① 机理描述不足 ② 受统计方法影响较大 ③ 指标选取不确定性大
过程模型	点、空间像元	① 综合考虑作物生长过程 ② 能够开展定量模拟实验 ③ 能够结合气候模拟数据开展预测	① 内部过程简化 ② 模型参数较多 ③ 模型模拟空间分辨率较低
遥感观测	空间像元	① 能够提供空间分布信息 ② 反演结果时空分辨率高 ③ 空间范围大、重访周期短	① 存在长势与产量脱钩问题 ② 产量反演指标敏感性低 ③ 无法表征作物品种信息

干旱对作物产量影响研究进展与展望

Drought impacts on crop yield: Progress, challenges and prospect

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