农作物自然灾害暴露研究进展
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摘要
随着气候变化与全球变化进程,未来农作物自然灾害损失风险不断加剧,给全球粮食安全带来极大威胁,评估农作物损失成为灾害风险研究关注的热点问题。目前暴露对风险的贡献已然超过气候变化的影响,导致在损失评估过程中如何进行农作物暴露的刻画与衡量显得尤为重要。该文综合国内外现有研究,首先梳理了不同视角下的农作物暴露定义,认为暴露需要以时空维度去理解,能够体现出其对灾情的放大或缩小影响;其次,总结了农作物暴露的三种空间维度指标与相应时间维度指标;最后,归纳了农作物种植范围、产量、经济价值以及时间维指标的常用计算方法与模型,以期能够更加系统、全面地理解暴露,满足灾害系统复杂性研究需求,为风险定量评价提供科学支持。
With the process of climate change and global change, the risk of future crop losses caused by natural disasters is increasing, which poses a great threat to global food security. The assessment of crop losses has become a hot issue in disaster risk research. The current contribution of exposure to risk has exceeded climate change's influence, which makes it particularly important to describe and measure crop exposure in its loss risk assessment. This paper firstly focuses on the definition of crop exposure from different perspectives, and it is believed that the exposure needs to be understood by space and time dimension, which can reflect its amplification or reduction effect on disaster losses. Secondly, three kinds of spatial dimension indicators and the corresponding time dimension indicators of crop exposure are summarized. Finally, it sums up the calculation methods and models of crop range, yield, economic value and time dimension indicators, to understand the exposure connotation more systematically and comprehensively, meet the needs of disaster system complexity research and provide scientific support for quantitative risk assessment.
With the process of climate change and global change, the risk of future crop losses caused by natural disasters is increasing, which poses a great threat to global food security. The assessment of crop losses has become a hot issue in disaster risk research. The current contribution of exposure to risk has exceeded climate change's influence, which makes it particularly important to describe and measure crop exposure in its loss risk assessment. This paper firstly focuses on the definition of crop exposure from different perspectives, and it is believed that the exposure needs to be understood by space and time dimension, which can reflect its amplification or reduction effect on disaster losses. Secondly, three kinds of spatial dimension indicators and the corresponding time dimension indicators of crop exposure are summarized. Finally, it sums up the calculation methods and models of crop range, yield, economic value and time dimension indicators, to understand the exposure connotation more systematically and comprehensively, meet the needs of disaster system complexity research and provide scientific support for quantitative risk assessment.
引文
[1] IPCC. Climate Change 2014-Impacts, Adaptation and Vulnerability: Rerengional Aspects[M]. UK: Cambridge University Press, 2014.
[2] LI Y, YE W, WANG M, et al. Climate change and drought: a risk assessment of crop-yield impacts[J]. Climate Research, 2009,39(1): 31-46.
[3] Burke M, Emerick K. Adaptation to climate change: Evidence from US agriculture[J]. American Economic Journal: Economic Policy, 2016,8(3): 106-40.
[4] Lesk C, Rowhani P, Ramankutty N. Influence of extreme weather disasters on global crop production[J]. Nature, 2016, 529(7584): 84.
[5] IPCC. Special Report of the Intergovernmental Panel on Climate Change[M]. US: Cambridge University Press, New York, 2012.
[6] HE C, HUANG Q, DOU Y, et al. The population in China’s earthquake-prone areas has increased by over 32 million along with rapid urbanization[J]. Environmental Research Letters, 2016,11(7): 074028.
[7] Fraser S A, Wood N J, Johnston D, et al. Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling[J]. Natural Hazards and Earth System Sciences, 2014,14(11): 2975-2991.
[8] 王尚彦.我国西部岩溶山区“小震大灾”现象的原因分析[J].科技资讯,2013(3):133-133.
[9] Shrimpton P C, Wall B F. The increasing importance of X ray computed tomography as a source of medical exposure[J]. Radiation Protection Dosimetry, 1995, 57(1/4): 413-415.
[10] 胡二邦.环境风险评价实用技术、方法和案例[M].北京:中国环境科学出版社,2009:195-196.
[11] Marder J, Eylath U, Moskovitz E, et al. The effect of heat exposure on blood chemistry of the hyper thermic rabbit[J]. Comparative Biochemistry and Physiology, 1990, 97(2): 245-247.
[12] 李楚霖,杨明,易江编.金融分析及应用(第3版)[M].北京:首都经济贸易大学出版社, 2014:203-206.
[13] UNDP. Reducing Disaster Risk: A Challenge for Development-A Global Report[M]. New York, USA: UNDP, 2004.
[14] ADRC. This book, which consists of two parts, the theory of TDRM and good practices for disaster risk management, was compiled for the purpose of promoting Total Disaster Risk Management (TDRM) as a comprehensive approach to disaster risk reduction worldwide. Researchers at the Asian Disaster Reduction Center (ADRC) in consultation with UN-OCHA/Kobe further developed their theory of TDRM for this publication. The TDRM good practices were contributed by various stakeholders, including ADRC member countries[R]//2005.
[15] IPCC. Climate change 2007-impacts, adaptation and vulnerability: Working group II contribution to the fourth assessment report of the IPCC[M]. UK: Cambridge University Press, 2007.
[16] 史培军,汪明,胡小兵,等.社会-生态系统综合风险防范的凝聚力模式[J].地理学报,2014,69(6):863-876.
[17] Turner B L, Kasperson R E, Matson P A, et al. A framework for vulnerability analysis in sustainability science[J]. Proceedings of the national academy of sciences, 2003, 100(14): 8074-8079.
[18] 葛全胜,邹铭,郑景云.中国自然灾害风险综合评估初步研究[M].北京:科学出版社,2008:204-205.
[19] Pittore M, Wieland M, Fleming K. Perspectives on global dynamic exposure modelling for geo-risk assessment[J]. Natural Hazards,2017, 86(1): 7-30.
[20] Deressa T, Hassan R M, Ringler C. Measuring Ethiopian farmers’ vulnerability to climate change across regional states [R]. Ifpri Discussion Papers,2008.
[21] Gbetibouo G A, Ringler C. Hassan R. Vulnerability of the South African farming sector to climate change and variability: an indicator approach[J]. Natural Resources Forum, 2010,34(3): 175-187.
[22] Murthy C, Laxman B, Sai M S. Geospatial analysis of agricultural drought vulnerability using a composite index based on exposure, sensitivity and adaptive capacity[J]. International Journal of Disaster Risk Reduction, 2015,12: 163-171.
[23] Anandhi A, Steiner J L, Bailey N. A system’s approach to assess the exposure of agricultural production to climate change and variability[J]. Climatic Change, 2015,136(3/4): 1-13.
[24] ZHANG L, ZHANG Z, CHEN Y, et al. Exposure, vulnerability, and adaptation of major maize-growing areas to extreme temperature[J]. Natural Hazards, 2018, (2/3): 1-16.
[25] Gourdji S M, Sibley A M, Lobell D B. Global crop exposure to critical high temperatures in the reproductive period: historical trends and future projections[J]. Environmental Research Letters, 2013, 8(2): 024041.
[26] Teixeira E I, Fischer G, van Velthuizen H, et al. Global hot-spots of heat stress on agricultural crops due to climate change[J]. Agricultural and Forest Meteorology, 2013, 170: 206-215.
[27] LUO Q. Temperature thresholds and crop production: a review[J]. Climatic Change, 2011, 109(3/4): 583-598.
[28] Sánchez B, Rasmussen A, Porter J R. Temperatures and the growth and development of maize and rice: a review[J]. Global Change Biology, 2014, 20(2): 408-417.
[29] Fritz S, You L, Bun A, et al. Cropland for sub-Saharan Africa: A synergistic approach using five land cover data sets[J]. Geophysical Research Letters, 2011,38(4): 155-170.
[30] 许仲林, 彭焕华, 彭守璋.物种分布模型的发展及评价方法[J].生态学报,2015,35(2): 557-567.
[31] Elith J, Graham C H, Anderson R P, et al. Novel methods improve prediction of species’ distributions from occurrence data[J]. Ecography, 2006, 29(2): 129-151.
[32] XU Z, ZHAO C, FENG Z, et al. Estimating realized and potential carbon storage benefits from reforestation and afforestation under climate change: a case study of the Qinghai spruce forests in the Qilian Mountains, northwestern China[J]. Mitigation and adaptation strategies for global change, 2013, 18(8): 1257-1268.
[33] Walke N, Reddy G O, Maji A, et al. GIS-based multicriteria overlay analysis in soil-suitability evaluation for cotton (Gossypium spp.): A case study in the black soil region of Central India[J]. Computers & geosciences, 2012, 41: 108-118.
[34] Mendas A,Delali A. Integration of MultiCriteria Decision Analysis in GIS to develop land suitability for agriculture: Application to durum wheat cultivation in the region of Mleta in Algeria. Computers and Electronics in Agriculture, 2012, 83: 117-126.
[35] YOU L, Wood S, Wood-Sichra U. Generating plausible crop distribution maps for Sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach[J]. Agricultural Systems, 2009, 99(2): 126-140.
[36] Fischer G, Shah M, Tubiello F N, et al. Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990-2080[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2005, 360(1463): 2067-2083.
[37] YAN Y, ZHAO J, DENG H, et al. Predicting China’s cultivated land resources and supporting capacity in the twenty-first century[J]. The International Journal of Sustainable Development and World Ecology, 2006, 13(3): 229-241.
[38] WEI X, Declan C, Erda L, et al. Future cereal production in China: the interaction of climate change, water availability and socio-economic scenarios[J]. Global Environmental Change, 2009, 19(1): 34-44.
[39] Lobell D B, B?nziger M B, Magorokosho C, et al. Nonlinear heat effects on African maize as evidenced by historical yield trials[J]. Nature Climate Change, 2010, 1(1): 42-45.
[40] Lobell D B, Schlenker W, Costa-Roberts J. Climate trends and global crop production since 1980[J]. Science, 2011, 333(6042): 616-620.
[41] Roudier P, Sultan B, Quirion P. et al. The impact of future climate change on West African crop yields: What does the recent literature say?[J] Global Environmental Change,2011, 21(3): 1073-1083.
[42] 王文佳,冯浩.国外主要作物模型研究进展与存在问题[J].节水灌溉, 2012 (8): 63-68.
[43] Asseng S, Ewert F, Rosenzweig C, et al. Uncertainty in simulating wheat yields under climate change[J]. Nature Climate Change, 2013, 3(9): 827.
[44] Martre P, Wallach D, Asseng S, et al. Multimodel ensembles of wheat growth: many models are better than one[J]. Global change biology, 2015, 21(2): 911-925.
[45] R?tter R P, Carter T R, Olesen J E, et al. Crop-climate models need an overhaul[J]. Nature Climate Change, 2011, 1(4): 175.
[46] 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[J]. Proceedings of the National Academy of Sciences, 2014,111(9): 3268-3273.
[47] Mendelsohn R, Nordhaus W D, Shaw D. The impact of global warming on agriculture: a Ricardian analysis[J]. The American economic review, 1994:753-771.
[48] Gbetibouo G A, Hassan R. Measuring the economic impact of climate change on major South African field crops: a Ricardian approach[J]. Global and Planetary Change, 2005, 47(2/4): 143-152.
[49] Darwin R. The impact of global warming on agriculture: A Ricardian analysis: Comment[J]. American Economic Review, 1999, 89(4): 1049-1052.
[50] Darwin R F, Lewandrowski J, McDonald B, et al. Global Climate Change: Analyzing Environmental Issues and Agricultural Trade within a Global Context″[M]// Sullivan, J. (ed.), Environmental Policies: Implications for Agricultural Trade, Foreign Agricultural Economic Report Number 252. United States Department of Agriculture, Economic Research Service, Washington, D.C.,2014.
[51] Darwin R. A farmer’s view of the Ricardian approach to measuring agricultural effects of climatic change[J]. Climatic Change, 1999, 41(3/4): 371-411.
[52] YOU L, Wood S, Wood-Sichra U, et al. Generating global crop distribution maps: From census to grid[J]. Agricultural Systems, 2014, 127: 53-60.
[53] WU W, Shibasaki R, YANG P, et al. Global-scale modelling of future changes in sown areas of major crops[J]. Ecological Modelling, 2007, 208(2/4): 378-390.
[54] RANG Z, Jagadish S V K, ZHOU Q, et al. Effect of high temperature and water stress on pollen germination and spikelet fertility in rice[J]. Environmental and Experimental Botany, 2011, 70(1): 58-65.
[55] Jha U C, Bohra A, Singh N P. Heat stress in crop plants: its nature, impacts and integrated breeding strategies to improve heat tolerance[J]. Plant Breeding, 2014, 133(6): 679-701.
[56] LIU G, ZHANG L, HE B, et al. Temporal changes in extreme high temperature, heat waves and relevant disasters in Nanjing metropolitan region, China[J]. Natural hazards, 2015, 76(2): 1415-1430.
[57] Porch T G, Jahn M. Effects of high-temperature stress on microsporogenesis in heat-sensitive and heat-tolerant genotypes of Phaseolus vulgaris[J]. Plant Cell and Environment, 2001, 24:723-731.
[58] 张彬,芮雯奕,郑建初, 等.水稻开花期花粉活力和结实率对高温的响应特征[J].作物学报, 2007, 33(7): 1177-1181.
[59] Porter J R,Gawith M. Temperatures and the growth and development of wheat: a review[J]. European Journal of Agronomy, 1999, 10(1): 23-36.
[60] 史培军.再论灾害研究的理论与实践[J].自然灾害学报, 1996, 5(4).
[61] 金菊良,郦建强,周玉良,等.旱灾风险评估的初步理论框架[J]. 灾害学, 2014, 29(3): 1-10.
[62] 王连喜,肖玮钰,李琪,等.中国北方地区主要农作物气象灾害风险评估方法综述[J]. 灾害学, 2013, 28(2): 114-119.
[63] Watson I. State of the Art in Storm-Surge Protection: The Netherlands Delta Project. Journal of Coastal Research, 1990,6(3): 739-764.
[64] 胡月,张继权,刘兴朋,等.荷兰防洪综合管理体系及经验启示.国际城市规划, 2011,26(4): 37-41.
[2] LI Y, YE W, WANG M, et al. Climate change and drought: a risk assessment of crop-yield impacts[J]. Climate Research, 2009,39(1): 31-46.
[3] Burke M, Emerick K. Adaptation to climate change: Evidence from US agriculture[J]. American Economic Journal: Economic Policy, 2016,8(3): 106-40.
[4] Lesk C, Rowhani P, Ramankutty N. Influence of extreme weather disasters on global crop production[J]. Nature, 2016, 529(7584): 84.
[5] IPCC. Special Report of the Intergovernmental Panel on Climate Change[M]. US: Cambridge University Press, New York, 2012.
[6] HE C, HUANG Q, DOU Y, et al. The population in China’s earthquake-prone areas has increased by over 32 million along with rapid urbanization[J]. Environmental Research Letters, 2016,11(7): 074028.
[7] Fraser S A, Wood N J, Johnston D, et al. Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling[J]. Natural Hazards and Earth System Sciences, 2014,14(11): 2975-2991.
[8] 王尚彦.我国西部岩溶山区“小震大灾”现象的原因分析[J].科技资讯,2013(3):133-133.
[9] Shrimpton P C, Wall B F. The increasing importance of X ray computed tomography as a source of medical exposure[J]. Radiation Protection Dosimetry, 1995, 57(1/4): 413-415.
[10] 胡二邦.环境风险评价实用技术、方法和案例[M].北京:中国环境科学出版社,2009:195-196.
[11] Marder J, Eylath U, Moskovitz E, et al. The effect of heat exposure on blood chemistry of the hyper thermic rabbit[J]. Comparative Biochemistry and Physiology, 1990, 97(2): 245-247.
[12] 李楚霖,杨明,易江编.金融分析及应用(第3版)[M].北京:首都经济贸易大学出版社, 2014:203-206.
[13] UNDP. Reducing Disaster Risk: A Challenge for Development-A Global Report[M]. New York, USA: UNDP, 2004.
[14] ADRC. This book, which consists of two parts, the theory of TDRM and good practices for disaster risk management, was compiled for the purpose of promoting Total Disaster Risk Management (TDRM) as a comprehensive approach to disaster risk reduction worldwide. Researchers at the Asian Disaster Reduction Center (ADRC) in consultation with UN-OCHA/Kobe further developed their theory of TDRM for this publication. The TDRM good practices were contributed by various stakeholders, including ADRC member countries[R]//2005.
[15] IPCC. Climate change 2007-impacts, adaptation and vulnerability: Working group II contribution to the fourth assessment report of the IPCC[M]. UK: Cambridge University Press, 2007.
[16] 史培军,汪明,胡小兵,等.社会-生态系统综合风险防范的凝聚力模式[J].地理学报,2014,69(6):863-876.
[17] Turner B L, Kasperson R E, Matson P A, et al. A framework for vulnerability analysis in sustainability science[J]. Proceedings of the national academy of sciences, 2003, 100(14): 8074-8079.
[18] 葛全胜,邹铭,郑景云.中国自然灾害风险综合评估初步研究[M].北京:科学出版社,2008:204-205.
[19] Pittore M, Wieland M, Fleming K. Perspectives on global dynamic exposure modelling for geo-risk assessment[J]. Natural Hazards,2017, 86(1): 7-30.
[20] Deressa T, Hassan R M, Ringler C. Measuring Ethiopian farmers’ vulnerability to climate change across regional states [R]. Ifpri Discussion Papers,2008.
[21] Gbetibouo G A, Ringler C. Hassan R. Vulnerability of the South African farming sector to climate change and variability: an indicator approach[J]. Natural Resources Forum, 2010,34(3): 175-187.
[22] Murthy C, Laxman B, Sai M S. Geospatial analysis of agricultural drought vulnerability using a composite index based on exposure, sensitivity and adaptive capacity[J]. International Journal of Disaster Risk Reduction, 2015,12: 163-171.
[23] Anandhi A, Steiner J L, Bailey N. A system’s approach to assess the exposure of agricultural production to climate change and variability[J]. Climatic Change, 2015,136(3/4): 1-13.
[24] ZHANG L, ZHANG Z, CHEN Y, et al. Exposure, vulnerability, and adaptation of major maize-growing areas to extreme temperature[J]. Natural Hazards, 2018, (2/3): 1-16.
[25] Gourdji S M, Sibley A M, Lobell D B. Global crop exposure to critical high temperatures in the reproductive period: historical trends and future projections[J]. Environmental Research Letters, 2013, 8(2): 024041.
[26] Teixeira E I, Fischer G, van Velthuizen H, et al. Global hot-spots of heat stress on agricultural crops due to climate change[J]. Agricultural and Forest Meteorology, 2013, 170: 206-215.
[27] LUO Q. Temperature thresholds and crop production: a review[J]. Climatic Change, 2011, 109(3/4): 583-598.
[28] Sánchez B, Rasmussen A, Porter J R. Temperatures and the growth and development of maize and rice: a review[J]. Global Change Biology, 2014, 20(2): 408-417.
[29] Fritz S, You L, Bun A, et al. Cropland for sub-Saharan Africa: A synergistic approach using five land cover data sets[J]. Geophysical Research Letters, 2011,38(4): 155-170.
[30] 许仲林, 彭焕华, 彭守璋.物种分布模型的发展及评价方法[J].生态学报,2015,35(2): 557-567.
[31] Elith J, Graham C H, Anderson R P, et al. Novel methods improve prediction of species’ distributions from occurrence data[J]. Ecography, 2006, 29(2): 129-151.
[32] XU Z, ZHAO C, FENG Z, et al. Estimating realized and potential carbon storage benefits from reforestation and afforestation under climate change: a case study of the Qinghai spruce forests in the Qilian Mountains, northwestern China[J]. Mitigation and adaptation strategies for global change, 2013, 18(8): 1257-1268.
[33] Walke N, Reddy G O, Maji A, et al. GIS-based multicriteria overlay analysis in soil-suitability evaluation for cotton (Gossypium spp.): A case study in the black soil region of Central India[J]. Computers & geosciences, 2012, 41: 108-118.
[34] Mendas A,Delali A. Integration of MultiCriteria Decision Analysis in GIS to develop land suitability for agriculture: Application to durum wheat cultivation in the region of Mleta in Algeria. Computers and Electronics in Agriculture, 2012, 83: 117-126.
[35] YOU L, Wood S, Wood-Sichra U. Generating plausible crop distribution maps for Sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach[J]. Agricultural Systems, 2009, 99(2): 126-140.
[36] Fischer G, Shah M, Tubiello F N, et al. Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990-2080[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2005, 360(1463): 2067-2083.
[37] YAN Y, ZHAO J, DENG H, et al. Predicting China’s cultivated land resources and supporting capacity in the twenty-first century[J]. The International Journal of Sustainable Development and World Ecology, 2006, 13(3): 229-241.
[38] WEI X, Declan C, Erda L, et al. Future cereal production in China: the interaction of climate change, water availability and socio-economic scenarios[J]. Global Environmental Change, 2009, 19(1): 34-44.
[39] Lobell D B, B?nziger M B, Magorokosho C, et al. Nonlinear heat effects on African maize as evidenced by historical yield trials[J]. Nature Climate Change, 2010, 1(1): 42-45.
[40] Lobell D B, Schlenker W, Costa-Roberts J. Climate trends and global crop production since 1980[J]. Science, 2011, 333(6042): 616-620.
[41] Roudier P, Sultan B, Quirion P. et al. The impact of future climate change on West African crop yields: What does the recent literature say?[J] Global Environmental Change,2011, 21(3): 1073-1083.
[42] 王文佳,冯浩.国外主要作物模型研究进展与存在问题[J].节水灌溉, 2012 (8): 63-68.
[43] Asseng S, Ewert F, Rosenzweig C, et al. Uncertainty in simulating wheat yields under climate change[J]. Nature Climate Change, 2013, 3(9): 827.
[44] Martre P, Wallach D, Asseng S, et al. Multimodel ensembles of wheat growth: many models are better than one[J]. Global change biology, 2015, 21(2): 911-925.
[45] R?tter R P, Carter T R, Olesen J E, et al. Crop-climate models need an overhaul[J]. Nature Climate Change, 2011, 1(4): 175.
[46] 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[J]. Proceedings of the National Academy of Sciences, 2014,111(9): 3268-3273.
[47] Mendelsohn R, Nordhaus W D, Shaw D. The impact of global warming on agriculture: a Ricardian analysis[J]. The American economic review, 1994:753-771.
[48] Gbetibouo G A, Hassan R. Measuring the economic impact of climate change on major South African field crops: a Ricardian approach[J]. Global and Planetary Change, 2005, 47(2/4): 143-152.
[49] Darwin R. The impact of global warming on agriculture: A Ricardian analysis: Comment[J]. American Economic Review, 1999, 89(4): 1049-1052.
[50] Darwin R F, Lewandrowski J, McDonald B, et al. Global Climate Change: Analyzing Environmental Issues and Agricultural Trade within a Global Context″[M]// Sullivan, J. (ed.), Environmental Policies: Implications for Agricultural Trade, Foreign Agricultural Economic Report Number 252. United States Department of Agriculture, Economic Research Service, Washington, D.C.,2014.
[51] Darwin R. A farmer’s view of the Ricardian approach to measuring agricultural effects of climatic change[J]. Climatic Change, 1999, 41(3/4): 371-411.
[52] YOU L, Wood S, Wood-Sichra U, et al. Generating global crop distribution maps: From census to grid[J]. Agricultural Systems, 2014, 127: 53-60.
[53] WU W, Shibasaki R, YANG P, et al. Global-scale modelling of future changes in sown areas of major crops[J]. Ecological Modelling, 2007, 208(2/4): 378-390.
[54] RANG Z, Jagadish S V K, ZHOU Q, et al. Effect of high temperature and water stress on pollen germination and spikelet fertility in rice[J]. Environmental and Experimental Botany, 2011, 70(1): 58-65.
[55] Jha U C, Bohra A, Singh N P. Heat stress in crop plants: its nature, impacts and integrated breeding strategies to improve heat tolerance[J]. Plant Breeding, 2014, 133(6): 679-701.
[56] LIU G, ZHANG L, HE B, et al. Temporal changes in extreme high temperature, heat waves and relevant disasters in Nanjing metropolitan region, China[J]. Natural hazards, 2015, 76(2): 1415-1430.
[57] Porch T G, Jahn M. Effects of high-temperature stress on microsporogenesis in heat-sensitive and heat-tolerant genotypes of Phaseolus vulgaris[J]. Plant Cell and Environment, 2001, 24:723-731.
[58] 张彬,芮雯奕,郑建初, 等.水稻开花期花粉活力和结实率对高温的响应特征[J].作物学报, 2007, 33(7): 1177-1181.
[59] Porter J R,Gawith M. Temperatures and the growth and development of wheat: a review[J]. European Journal of Agronomy, 1999, 10(1): 23-36.
[60] 史培军.再论灾害研究的理论与实践[J].自然灾害学报, 1996, 5(4).
[61] 金菊良,郦建强,周玉良,等.旱灾风险评估的初步理论框架[J]. 灾害学, 2014, 29(3): 1-10.
[62] 王连喜,肖玮钰,李琪,等.中国北方地区主要农作物气象灾害风险评估方法综述[J]. 灾害学, 2013, 28(2): 114-119.
[63] Watson I. State of the Art in Storm-Surge Protection: The Netherlands Delta Project. Journal of Coastal Research, 1990,6(3): 739-764.
[64] 胡月,张继权,刘兴朋,等.荷兰防洪综合管理体系及经验启示.国际城市规划, 2011,26(4): 37-41.