,1,2, 傅伯杰,2Drought impacts on crop yield: Progress, challenges and prospect
LIU Xianfeng,1,2, FU Bojie,2通讯作者:
收稿日期:2020-08-11修回日期:2021-03-25
| 基金资助: |
Received:2020-08-11Revised:2021-03-25
| Fund supported: |
作者简介 About authors
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:
摘要
关键词：
Abstract
Keywords：
PDF (1758KB)元数据多维度评价相关文章导出EndNote|Ris|Bibtex收藏本文
本文引用格式
刘宪锋, 傅伯杰. 干旱对作物产量影响研究进展与展望. 地理学报, 2021, 76(11): 2632-2646 doi:10.11821/dlxb202111003
LIU Xianfeng, FU Bojie.
1 引言
粮食安全关乎人类生存和社会经济发展,是人类社会实现永续发展的根本保障[1]。当今世界人口增长和消费水平提升促使粮食需求保持刚性增长态势[2],如何保障国家粮食安全和实现农业系统可持续发展成为世界各国政府和学界共同面临的重大挑战。20世纪70年代以来,全球气候变暖导致的干旱等极端气候事件的频率和强度呈显著增加趋势[3],并已对全球农业生产和粮食安全造成巨大而深远的影响[4,5,6,7]。资料显示,中国农作物受干旱影响面积占农作物总受灾面积的50%以上,世界饥饿人口在经历持续减少后于2014年趋势逆转,表现出逐渐增加的态势[8],且2015—2016年强厄尔尼诺现象引发的严重干旱进一步导致全球多地出现严重粮食危机,对全球粮食供应和粮食价格产生严重影响[8,9]。地球系统模式预测,未来全球干旱风险将进一步增加[3],对农业生产的影响将进一步加深。因此,准确评估干旱对全球粮食生产的影响作为提高全球变化适应能力和实现全球粮食安全的关键环节,成为当今政府和学界亟待解决的重大科学问题。为有效应对日益严峻的全球干旱及其对粮食生产带来的不利影响,国内外****已开展大量卓有成效的研究工作。全球尺度上,Lesk等系统研究了极端干旱事件对全球主要作物产量的影响[4],Leng等则探讨了全球主要作物产量对干旱事件的敏感性[10]。区域尺度上,Li等以美国玉米产量为例指出极端湿润事件同样会造成与极端干旱事件幅度相似的减产程度,证实了水资源丰欠对作物产量有着至关重要的影响[11]。与此同时,国际上也发展了多个用于评估水资源对全球作物产量影响的作物模型比较计划,其中代表性比较计划项目有AgMIP和ISI-MIP[12,13],该计划通过多模型集合的方式有效提高了气候变化对全球粮食生产影响的模拟能力和可靠性。通过回顾已有研究发现,当前研究多从水分亏缺视角探讨干旱单一变量对全球粮食产量的影响,缺乏干旱与热浪等其他极端气候事件的复合效应研究,难以准确刻画复合极端气候事件对全球粮食生产的影响。应指出的是,以干旱和热浪耦合为主的复合极端事件对粮食系统的影响将超过任何单一事件亦或2个事件的总和,呈现出以正反馈为特征的耦合放大效应,成为威胁粮食系统可持续发展的重要风险源。然而当前学界对干旱等极端气候对作物产量影响研究的全面认识尚未完全形成,有必要对干旱对作物产量影响研究进展与发展历程进行全面梳理,以促进系统认知干旱对全球粮食产量的影响。
理解和评估极端气候事件对作物产量的影响对于减轻灾害损失和提高气候变化适应能力具有至关重要的作用[14]。联合国粮农组织发布的《世界粮食安全和营养状况》亦强调了世界应加快和扩大行动,增强人们及其生计抵御和适应气候变异和极端气候的能力,实现2030年消除饥饿和一切形式营养不良的目标[8]。从国家安全战略角度看,中国人口众多、自然灾害频发,农业系统受自然风险和影响较大,严重阻碍了农业系统的可持续发展,而提高应对极端气候对农业生产影响的能力不仅是实现中国农业系统可持续的关键环节,而且是实现总体国家安全观的重要组成部分。基于上述认识,本文首先从干旱对作物产量影响的研究内容和评估方法进行系统梳理,进而揭示国内外干旱对作物产量影响研究的发展历程和最新研究进展。在此基础上,提出目前干旱对作物产量影响研究存在的问题与挑战,并对干旱对作物产量影响的未来研究重点方向进行归纳与总结,以期通过提高农业生产对极端气候事件的抵御能力,实现农业系统可持续发展,切实保障国家粮食安全。
2 干旱对作物产量影响研究进展
干旱是以长期降水亏缺为主要特征的极端气候事件,进而导致土壤水分亏缺、蒸散发量减少,地表温度升高,进一步加剧土壤水分亏缺,形成正反馈过程[3]。干旱对作物产量的影响主要包括以下两个方面：一是当土壤水分含量低于作物生长所需水量时,作物生长状况受到限制,并出现作物长势下降,导致作物产量减少或失收[10];二是干旱条件下作物通过调节叶片气孔开度,在减少水分蒸腾的同时也减少了CO2的输入量,从而降低作物光合作用速率,影响有机质合成,并最终对作物产量产生影响[15]。干旱被认为是对全球作物产量影响最为显著的扰动事件之一,然而由于干旱本身的复杂性增加了干旱对作物产量影响评估的难度,主要表现为不同作物物候期的干旱对作物产量影响是不同的,且不同强度、不同持续时间、不同干旱指数评估结果也存在较大差异,造成了当前学界对作物产量影响评估的不确定性。需要说明的是,作物生长和发育还受到诸多交互过程的控制,如施肥、耕作、灌溉、作物品种等人工管理方面,以及高温热浪、洪涝、低温、病虫害等其他极端事件干扰均会对作物产量产生显著作用,进一步加大了作物产量影响评估的复杂性（图1）。图1
新窗口打开|下载原图ZIP|生成PPT图1干旱对作物产量影响传递过程和影响因素
Fig. 1Drought propagation and influencing factors of drought impact on crop yield
2.1 干旱对作物产量影响评估
目前干旱对作物产量影响研究的手段主要有样地控制实验、统计模型分析、过程机理模型模拟以及多源遥感数据反演等4种方式,不同方法之间存在紧密的联系,其中统计模型分析方法作为最常用的分析工具,亦被广泛应用于其他3种方法之中,在实际评估过程中不同方法呈现出综合利用的趋势（图2）。图2
新窗口打开|下载原图ZIP|生成PPT图2干旱对作物产量影响研究方法
Fig. 2Approaches to drought impact on crop yield
2.1.1 基于控制实验的作物产量影响评估 基于控制实验的方法主要是通过人为控制作物生长季田间水分含量,并通过与对照组实验进行比较,直接测量出不同作物产量对外界气候条件变化的响应特征,该方法对于提高作物生长机理的认识和提高作物模拟能力具有重要意义。Çakir等通过田间灌溉和控水实验揭示了水分亏缺对玉米长势和产量的显著影响[16];Hussain等则研究了干旱和热胁迫共同发生对玉米形态学特征、产量和营养物质的影响[17];Prado等从分子水平到植株水平系统总结了水分的调控作用[15]。在国内,姚宁等[18]和王书吉等[19]分别利用遮雨棚人工控水试验,探究了不同生长阶段水分胁迫对冬小麦产量和蛋白质形成的影响,指出返青期和灌浆期是冬小麦田间水分管理的关键时期;宋利兵等通过田间控水实验发现灌浆期受旱可导致玉米明显减产[20];王密侠等则探究了玉米不同生育期实行不同水分调亏等级对作物产量的影响及节水策略[21];而Ma等则通过田间实验探究了作物单作和轮作2种方式对水分利用的影响[22]。在研究手段上,学界逐渐由单独的控制实验过渡到水分控制和作物模型相结合的方向,例如Chen等基于田间观测实验和作物生长模型改进了玉米生长期灌溉制度,提高了玉米产量的预测精度[23];Kisekka等则通过2006—2009年田地实验修正了CERES-Maize模型,并对Kansas玉米灌溉策略进行研究[24]。此外,另有****亦探讨了不同灌溉水质对玉米产量的可能影响[25]。
需要说明的是,基于控制实验的方法通过直接测量获得的产量数据具有较高的精度,因而实验数据可用于作物模型模拟的验证数据。然而该方法易受实验操作、作物品种等外界条件的影响而导致结果存在较大不确定性,主要表现为实验周期长、控制情景与真实自然界存在差异,实验结果的可重复性不强,且实验结论的尺度上推受限等。同时,当前控制实验方法尚未形成统一的实验标准与操作规范,从而导致不同地区实验结果的可比性较差。虽然20世纪80年代末期发展起来的开放式CO2增肥试验（Free-Air CO2 Enrichment）技术能够较为真实的模拟未来CO2增加的微域环境,探讨作物在不同CO2浓度施肥效应下的响应特征,然而当前学界对模拟真实水分条件的田间作物生长实验相对匮乏,限制了干旱对作物产量影响评估精度的提高。
2.1.2 基于统计模型的作物产量影响评估 基于统计模型的作物产量影响评估主要通过建立历史观测的产量数据与气候数据之间的关系,揭示作物产量对气候要素的响应规律,并利用这些关系和规律来建立模型预测未来作物产量,已成为研究干旱对作物产量影响最常用的方法。当前国内外****利用该方法已开展了不同空间尺度不同历史时期干旱对作物产量影响评估工作[26,27,28],其中Lesk等在全球尺度上系统分析了极端气候事件对全球作物产量的影响,指出干旱和热浪导致全球作物产量减少9%~10%[4];Lobell等则指出美国玉米产量对干旱的敏感性在增加[29];Leng等探讨了不同等级干旱对作物产量影响的风险[10],Madadgar等则采用联合分布函数方法分析了干旱对作物产量影响的概率[30];另有研究分别从不同干旱强度的损失概率差异[10]、作物对不同时间尺度干旱响应差异[31],以及未来情景下干旱胁迫对作物产量的影响等方面开展研究[32],并指出干旱频率和强度的增加会抵消掉二氧化碳施肥效应对大豆产量的贡献[33]。在国内,余慧倩等[34]和黄健熙等[35]分别采用DSI指数和各省产量统计数据,研究了不同干旱强度、不同历时以及不同干旱发生时间对华北平原冬小麦产量的影响,表明不同生长阶段发生不同等级干旱对产量影响具有显著差异;Guo等[36]和刘维等[37]分别评估了中国东北地区干旱时空特征及其对玉米产量的影响;朱冉等[38]则采用作物缺水指数研究了柯西河流域干旱对作物产量的影响及其空间差异。
此外,国内外****亦探讨了全球主要粮食作物对干旱和高温复合事件的响应[39,40,41,42,43],如Lobell等发现热浪对非洲玉米产量对热浪响应的非线性特征[44],且同样会抵消很大一部分由技术、CO2施肥和其他因素带来的产量增加,并指出气温和降水的长期趋势造成欧洲小麦和大麦分别减产2.5%和3.8%[45];Gammans等采用历史产量数据和气象数据研究了法国小麦和大麦对气温和降水的响应特征[46];Zandalinas等研究了干旱和热浪共同发生对作物产量的影响,认为任何单一灾害或灾害组合对作物生物过程的影响机制都是有差异的[47];Vogel等则指出极端气温和降水可以解释18%~43%产量的变化,且不同作物类型对极端气温和降水的响应存在差异[48]。可见,当前学界已将研究视角从单一关注干旱向关注干旱和热浪等复合极端事件视角转变。需要说明的是,干旱不仅是雨养农业区作物产量的最主要的限制因子[29, 49],同时也对灌溉农业区可获取水资源量构成威胁。基于统计模型的作物产量影响评估具有可操作性强,研究周期长等优点,是了解历史气候背景下干旱对作物产量影响研究最有效的研究方法,且当前统计方法也从线性向非线性转变,如随机森林、贝叶斯网络分析等,显著提高了作物产量模拟精度。然而该方法仅从数据本身规律上得出结论,对作物产量影响内部机理过程描述不足,且统计模型外推效果较差,尤其是在未来情景作物产量预测方面存在很大的局限性。
2.1.3 基于作物模型的作物产量影响评估 作物生长过程模型综合考虑了作物系统、土壤系统、气候系统和田间管理系统等与作物生长密切相关的系统,用数学公式描述生理生态过程、物理和化学过程,从而实现对作物生长全过程的精细化模拟实验。自1969年de Wit提出第一个农业计算机模型后,国内外****已开发百余种作物生长模型,当前作物生长模型主要分为单点作物生长模型和空间作物生长模型,并通过调节模型中水分供给量实现干旱对作物生长和产量影响的定量刻画。国内外****从站点尺度到全球尺度已应用作物生长模型模拟气候变化对不同作物长势和作物产量的影响[50,51],由于不同作物模型在模拟中存在较大的不确定性,国际上已开展多项作物模型比较计划,旨在统一框架和输入数据下开展气候变化对作物产量影响模拟,以减小单个模型模拟的不确定性,比较有代表性的模型比较计划有ISI-MIP（The Inter-Sectoral Impact Model Intercomparison Project）[13]和AgMIP（The Agricultural Model Intercomparison and Improvement Project）[12],前者作为部门间影响模型比较计划,旨在对气候变化对不同行业和部门的影响以及不确定性开展定量和综合分析;后者主要针对气候变化对全球农业生产的影响研究,旨在提高气候变化对全球粮食安全的模拟能力,以提高气候变化的适应能力。值得一提的是,AgMIP中的Global Gridded Crop Model Intercomparison实现了空间格点尺度上的气候变化影响模拟,为研究空间格局提供了重要支撑,其中Zhao等[41]和Liu等[43]分别采用AgMIP模型比较计划输出结果,结合统计模型和田间观测实验,全面分析了气候变暖对全球主要粮食作物产量的影响;Charles等利用作物模型综述了气候变化对非洲玉米产量的影响[52];Peng等提出了用于评估气候变化适应性的多尺度作物模型分析框架,该框架综合考虑了基因型和农业管理等因素来提高作物适应能力,促进农业系统可持续发展[53]。
在国内,Tao等系统研究了不同作物模型结构、模型参数和气候情景输入数据对气候变化对农业生产影响研究的不确定性[50];而孙扬越等则系统梳理了当前作物模型研究现状,并指出作物模型能够有效评估不同气候变化情景对农业生产带来的影响[54]。区域尺度上,Wang等采用日尺度SPEI和作物生长模型定量评估了干旱对作物产量的影响[55];王亚凯等利用APSIM模型模拟了冬小麦和夏玉米的产量变化,并用模拟产量与SPEI得到了显著的相关性[56];徐建文等[57]和张建平等[58]分别利用DSSAT作物模型和WOFOST作物生长模型模拟了黄淮海平原冬小麦关键生育期干旱对产量的影响。需要说明的是,作物模型实现了作物生长全过程的模拟,能够实现不同气候因子作用的定量模拟,且能够对未来作物产量进行预测。然而当前作物模型仍存在一定的不确定性,如模型仅简单刻画了最主要的生理生态过程、模型参数获取的不确定性、作物模型输入数据在区域尺度上的代表性不足以及模型参数本地化等问题。作物模型评估水资源短缺对灌溉农业作物产量的影响仍存在加大的挑战,主要原因是水资源管理系统的复杂性[59]。当前作物模型主要开展了无灌溉和全灌溉两种模式下作物长势和产量模拟,而对灌溉农田水资源的可用性并没有刻画,从而导致研究结果存在一定的不确定性[60]。此外,当前作物机理模型对复合极端气候事件的模拟能力不足,亟待加强相关研究工作。
2.1.4 基于遥感观测的作物产量影响评估 基于遥感观测的作物产量影响评估一方面是将遥感观测数据与作物模型进行同化,提高作物产量模拟的空间信息模拟能力;另一方面是利用遥感反演模型估算作物产量,进而将作物产量与气候因子进行相关分析以解析极端气候对作物产量的影响。该方法的重点在于基于多源遥感数据的农作物长势和产量信息提取,而农作物长势监测作为农情遥感监测的重要基础,通常采用不同光谱波段建立的植被指数对农作物长势进行表征[61]。当前国内外已发展近百种植被指数,如归一化植被指数、比值植被指数、叶面积指数以及植被条件指数等均被广泛用于作物产量估产研究。就国家层面而言,美国农业部于1974年应用Landsat卫星开展了大面积作物估产试验（LACIE）,随后又开展了不同种类粮食作物产量预报的遥感调查计划项目,欧盟则在1987年提出了MARS计划,该计划旨在应用SPOT卫星影像对农作物种植面积和作物产量进行监测预报[62]。而中国作物遥感监测与估产研究由陈述彭院士于1979年提出,随后农业部牵头利用NOAA/AVHRR卫星数据对我国重点农业区开展了主要粮食作物产量的遥感估产研究,奠定了中国大规模遥感估产工作的基础。不同****也利用遥感数据开展了大量的研究工作,如Lobell等通过MODIS反演了印度西北地区作物在高温环境下生长期变短,导致作物减产,发现模型结果低估了产量下降程度[63],并进一步利用遥感数据估算了美国中西部玉米产量时空变化特征[64];Azzari等将遥感数据与作物模型相结合开发了基于遥感数据的多尺度作物产量高精度制图系统[65]。在国内,吴炳方等利用遥感手段建立了中国农情遥感监测速报系统,能够实现大尺度作物长势和粮食产量等农情信息的快速监测预报[66,67];而陈仲新等则对中国作物长势遥感监测与产量估算进行系统梳理和回顾[68];李强子等通过作物生长过程曲线分析了2010年西南干旱对作物产量的影响[69];黄健熙等综合利用植被指数和蒸散发同化数据进行冬小麦遥感估产,显著提升了估测精度[70]。
在数据源方面,遥感数据以其高空间覆盖、高重放周期等特点被广泛应用于农用地制图和作物估产研究,且随着高时空分辨率传感器的发展,与产量密切相关的地块尺度的农情信息（产量、播种日期、作物类型）提取得到快速发展,为作物产量影响评估提供了数据基础[71]。20世纪90年代兴起的叶绿素荧光遥感通过对光合作用过程释放叶绿素荧光的探测实现对生物量的反演,可实现从区域到全球尺度上的农作物长势监测和产量精确估算,进而结合气候信息可以得出气候变化对作物产量的影响[72],其中Peng等评估了荧光数据与传统植被指数产品在作物产量估算中的差异,指出高质量的荧光产品可有效提高作物估产精度[73]。在遥感作物信息提取方法方面,随着深度学习、随机森林、支持向量机、蜂群和蚁群算法等机器学习方法的不断丰富,大大提高了传统遥感信息分类方法的精度。将遥感信息提取算法与Google Earth Engine进行有机结合,克服了当前遥感信息提取计算能力不足的限制,实现了对海量遥感数据源的综合利用和快速提取。需要说明的是,新型遥感传感器的不断丰富,显著提升了对地观测的时空分辨率和光谱分辨率,实现了地块级、区域级或全球级作物信息的高精度提取和动态变化分析。因此,基于遥感观测的方法有效弥补了传统田间观测数据少且分布不均、统计数据缺乏空间信息以及作物模型模拟空间分辨率低等不足。然而基于遥感的作物产量估算研究仍面临着估产指标对产量指示能力不足、遥感反演精度不高、与模型同化方法尚不能满足估产需求,且无法表征作物品种更替对作物产量估算带来的不确定性和时间序列不均一性等不足。此外,中国耕地破碎化程度高和种植结构复杂等问题进一步加剧了作物长势监测和产量估算的难度,限制了干旱对作物产量影响的精确评估和预测,因而如何将遥感与作物模型进行同化成为未来遥感作物产量评估的重要研究内容（表1）。
Tab. 1
表1
表1干旱对作物产量影响研究方法比较
Tab. 1
| 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 |
新窗口打开|下载CSV
2.2 干旱对作物产量影响的文献计量分析
为了更好地揭示干旱对作物产量影响研究的发展历程,本文进一步从文献计量分析视角全面系统回顾了近30年干旱对作物产量影响的发展脉络。以“drought and crop yield”作为关键词在“Web of Science”核心合集数据库进行主题检索（检索时段为1990—2019年,检索时间为2020年7月24日）。文献统计结果表明,1990—2020年干旱对作物产量影响研究文献发文量和引文量均呈现指数增长态势,其中2005年之后增速尤为显著,说明干旱对作物产量影响研究日益受到国内外****的广泛关注（图3a）。笔者进一步利用文献关键词统计了研究主题的演变特征,可以发现干旱对作物产量影响研究主题经历了由传统的作物水分胁迫研究到作物受旱影响与适应综合研究的转变过程,体现了研究视角的不断深化和综合。从不同国家和不同研究机构的发文量来看,排在前五名的国家分别为美国、中国、印度、澳大利亚和德国,共占发文总量的62.18%;而排在前五名的研究机构分别为美国农业部、中国科学院、国际半干旱热带作物研究所、费萨拉巴德大学和昆士兰大学,且不同机构之间存在着紧密的合作关系。图3
新窗口打开|下载原图ZIP|生成PPT图3干旱对作物产量影响的文献计量分析
Fig. 3Bibliometric analysis of drought impact on crop yield
干旱对作物产量影响研究涉及农学、大气科学、水资源、环境科学、土壤学以及植物生理学等多个学科。从不同学科发文量来看,干旱对作物产量影响研究所涉及的各个学科之间存在较大差异,其中农学发文量最大,占所有发文量的36.28%,紧随其后的分别为植物学、环境科学、水资源和大气科学,分别占总发文量的17.99%、7.81%、5.09%和3.80%,以上5个学科发文量占总发文量比例超过70%（图3b）。需要说明的是,干旱对作物产量影响研究是植物—土壤—大气连续体在水分亏缺条件下共同作用的结果,研究中应充分考虑不同系统间的耦合关系和互馈机制,加强不同学科间的交叉研究。虽然地理学的多要素和多尺度系统性研究范式对于系统认知植物—土壤—大气连续体下的干旱对作物产量影响机理和综合评估具有至关重要的作用[74],然而当前地理学在干旱对作物产量影响方面的相关研究稍显不足,建议未来应加强地理学在粮食安全和农业系统可持续发展研究中的作用,从时空视角综合分析区域和国家尺度的农业生产和粮食安全问题。
3 干旱对作物产量影响研究展望
粮食安全受气候变化等自然因素和人口增长等社会经济因素的共同控制[75],而气候变化及其引致的极端气候事件作为全球粮食安全状况恶化的主要诱因,是引发严重粮食危机的重要因素,且逐渐损害粮食安全的所有维度,即粮食的可供量、获取、利用和稳定性[8]。虽然当前国内外****针对干旱对作物产量影响研究开展了大量卓有成效的研究工作,然而干旱对作物产量影响研究仍存在较大的不确定性,一方面在于作物产量影响因素的复杂性,如作物生长过程和产量形成过程受多种因素共同控制（图1）,单一灾种无法刻画作物损失;另一方面则是产量估算的不确定性,如不同时间序列的产量结果受作物品种更替的影响、遥感监测作物长势与最终产量脱钩问题以及作物机理模型本身的不确定性。因此,无论在基础数据搜集、干旱对作物产量影响机理、作物生长过程模型以及粮食安全监测平台等方面都亟需开展系统性和综合性的集成研究,从供需平衡视角确保中国粮食安全,实现农业系统健康可持续发展（图4）。图4
新窗口打开|下载原图ZIP|生成PPT图4粮食安全未来重点研究方向
Fig. 4Future directions of food security
3.1 构建干旱对作物产量影响的多源信息数据库
当前国内外学界已利用统计数据和作物模型从全球尺度、国家尺度、省域尺度以及样地尺度系统开展了干旱对作物产量影响研究,然而干旱对作物产量影响的高精度空间分布信息却依然匮乏,究其原因主要在于多源信息数据库的缺失[76],如不同区域、不同作物类型以及不同作物品种的多尺度产量数据,农田管理中的灌溉、施肥以及人工管理等数据,尤其是地块级作物和田间管理统计数据更为缺乏,严重阻碍了干旱对作物产量影响的高精度模拟,而建立统一的数据采集系统,标准化的数据搜集流程以及统一数据框架的多源信息数据库被认为是解决上述困境的关键环节。具体而言,应建立田间观测实验信息平台,实现不同区域田间观测数据的共享和分发,完善不同行政级别作物统计数据的统计内容和上报规范,以及提高作物模型模拟空间分辨率等。此外,作物品质作为作物生长和人类营养的重要内容,未来应加强作物品质数据的收集,提高学界对作物品质及人类营养的关注与研究。需要说明的是,由于站点数据、统计数据、遥感数据以及模型模拟数据等不同数据的格式不同,为了更好地整合多源信息数据库,必要的技术与方法支持需要不断完善,如数据空间化、数据同化以及数据衍生技术等,将不同来源的数据在统一框架下生成高时空分辨率农情基础信息数据集。而遥感数据与作物模型模拟数据进行同化被认为是作物生长机理与空间分布信息的有力结合,因而遥感反演技术及其与作物模型数据的同化技术亟需不断完善。另外,可靠的作物产量影响评估方法是明晰干旱对作物产量影响的重要支撑,当前学界主要采用统计方法和定量实验方法开展作物产量影响评价,然而不同****采用的方法的差异导致结论间的可比性不强,难以真实反映干旱对作物产量影响的客观性和真实性。因此,建议未来应建立普适性的评估方法,以消除因数据和方法差异而导致研究结论的差异。
3.2 阐明干旱对作物产量影响的关键过程及机理
系统认知干旱对作物生长影响机理是提高作物模拟能力的重要基础与关键环节。作物水力胁迫是作物受旱的最主要特征,虽然当前研究中充分考虑了不同生育期内水分胁迫对最终作物产量的影响,然而对于作物生长、碳吸收、水分利用、营养元素变化以及产量形成过程的认识相对欠缺,且对于作物产量受损的水分胁迫阈值尚不明晰。因此,未来应加强干旱对作物产量影响的关键过程和作用机理的认识,重点关注作物水分胁迫条件下的长势响应规律及其对产量作用的机理。从产量形成过程视角综合分析干旱导致作物减产原因,并从作物的光合生理、根系生长、作物形态、产量形成等方面分析作物生长对干旱响应的生理机制,明晰不同等级干旱对作物生长的促进与抑制作用过程[77,78]。另外,还应关注作物水分胁迫条件下的碳吸收和水分胁迫对作物产量影响的相对贡献率,探索碳吸收与水胁迫间的互馈关系,明晰作物产量变化的机理等。高温胁迫会对粮食产量造成显著影响,并且和干旱形成复合灾害放大效应[39]。然而当前研究中多将不同灾害分开研究,对于复合灾害特征及其对作物影响机制的认识知之甚少。未来应加强对复合灾害对作物产量影响的叠加放大效应的关注,研发复合灾害检测方法及其对作物产量影响的耦合机制分析,并将复合灾害特征纳入作物生长模型,提高模型刻画复合灾害的能力。此外,未来还应注重干旱对作物产量影响的级联效应研究,例如干旱等极端事件对全球粮食价格和人类营养状况等级联效应的评估。虽然当前国内已有****初步尝试利用投入产出模型开展干旱对玉米供应链级联效应影响的案例研究[79],然而对级联过程的机理尚缺乏定量化理解,建议未来应加强对级联效应的关注与研究。应说明的是,粮食作为流通性的资源,兼具自然属性和社会属性,未来应在数据搜集基础上,加强干旱及其影响的综合评估方法的探索,为机理研究和模型构建提供方法支撑。
3.3 发展耦合宏观与微观过程作物生长机理模型
作物生长模型是开展作物长势监测、产量预估以及作物产量对气候变化响应研究的理想工具,能够定量分离和刻画不同环境驱动因子对作物长势和产量的贡献[54]。虽然作物模型已由最初的单系统和单过程模型逐步发展成为耦合多系统和多过程的综合模型,然而当前作物模型仍主要用于单点尺度作物生长过程的模拟研究,缺乏高空间分辨率作物产量及对气候变化响应的模拟能力,难以反映区域尺度上的作物生长和产量状况。加之目前对作物生态系统过程、作物生长各过程间耦合机制以及模型参数初始化问题等仍不明确,极大限制了作物模型对作物生长过程和产量形成的高精度模拟。因此,未来应大力发展兼具空间模拟能力和微观机理模拟能力的综合作物模型。具体而言,在宏观层面上,构建作物生长模型与遥感数据同化系统,借助遥感观测数据优化作物模型参数,提高作物模型空间模拟能力;在微观层面上,研发作物品种对作物产量影响以及生理生化过程模拟模块[80]。同时,构建作物生长模型标准框架,以减少模型结构、参数以及输入数据带来的模拟误差[50]。目前农业灾害呈现出由单一灾种向多灾种并发的特征转变,主要表现为干旱和高温事件同时发生并相互加强,从而形成灾害耦合放大效应,然而目前作物模型对复合极端气候事件的模拟能力尚显不足,难以准确刻画复合灾害情景下作物长势及其产量的变化特征。加之当前作物模型中对灌溉模式的描述仍过于简单,难以准确刻画灌溉活动对作物长势及产量的影响,因此,未来应加强对复合灾害（如高温和干旱）和灌溉活动的模拟能力,提高作物模型对作物生长的模拟精度。此外,农业系统作为自然系统和人类系统高度交织的领域[81],作物生长模型的功能还应充分考虑自然和社会生态系统相互作用的特征,建议未来作物模型的发展一方面要与气候模型相结合,以开展未来气候情景预测研究;另一方面作物模型要与社会经济模型、决策支持系统以及专家系统进行耦合,形成对作物产量、粮食供给、粮食价格和社会经济等级联影响的一体化评估模型,为宏观决策提供参考依据。
3.4 搭建作物产量与粮食安全综合监测平台系统
灾害监测预警作为减轻农业灾害损失最有效的手段受到了国内外政府和学界的高度关注与研究。当前国内外已建立多个农情监测系统,用于农业气象条件、作物长势、产量预测以及全球粮食贸易监测,其中,中国Crop Watch作为全球农情监测的重要组成部分,为中国粮食安全和农业可持续发展提供了重要的保障[66]。应指出的是,粮食安全由供给和需求共同决定,供给侧的粮食产量、种植面积、灌溉措施以及品种改良等和需求侧的人口数量、饮食结构、粮食价格和食物应用等均会对粮食安全造成影响（图5）。因此,未来在粮食监测系统中应充分考虑粮食安全的各个维度信息,搭建多尺度联动的作物产量与粮食安全综合监测平台,实现由粮食育种到粮食生产再到粮食消费的全过程监测预警与科学管理,以减少一系列灾害风险对全球作物产量和粮食安全的影响。具体而言,监测系统在时间维度上应具有定期或实时监测的能力,在空间维度上应具有县市、省域、国家尺度的监测预警能力。图5
新窗口打开|下载原图ZIP|生成PPT图5粮食安全供需系统框架
Fig. 5Framework of supply and demand of food security
2015年联合国提出17项可持续发展目标,其中消除饥饿,实现粮食安全,改善营养和促进可持续农业是实现各项可持续发展目标的重要支撑。中国作为人口大国,在保障粮食安全问题上仍存在诸多极具挑战的现实问题,其中水资源与粮食生产的空间错位问题是阻碍中国农业实现可持续发展的关键因素,如中国目前依然面临“北粮南运”和“南水北调”的双重挑战,而如何增强中国南方地区粮食生产能力和北方地区作物抵御干旱等气候风险能力将成为未来粮食安全领域研究的重要议题。因此,中国粮食安全监测平台系统应充分考虑上述问题与挑战,综合利用空—天—地一体化手段监测水资源和能源资源等与农业生产密切相关的基础性资源,并从系统协同发展的视角开展基础性资源的全面监测评估,建立定期发布农情产品并支持决策和灾害快速响应与预警的粮食安全监测平台,旨在通过系统认知粮食安全框架和科学管控,实现粮食安全和农业生态系统可持续发展。
4 结语
干旱作为农业系统面临的最主要灾害之一,严重威胁着全球粮食安全和农业系统可持续发展。本文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,指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,体现了研究视角的不断深化和综合。然而由于作物产量估产的不确定性以及影响因素的复杂性,导致当前干旱对作物产量影响研究仍存在较大挑战。建议未来应从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等方面开展综合性和系统性的研究,以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。致谢
感谢中国科学院空天信息创新研究院李强子研究员、西北农林科技大学何建强教授和福州大学王前锋副教授对本文成文过程中提出的宝贵建议。参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
[本文引用: 1]
[本文引用: 1]
DOI:10.1360/SSTe-2019-0041URL [本文引用: 1]
[本文引用: 1]
DOI:10.11821/dlxb201511012 [本文引用: 3]
In this paper, we compared the concept of agricultural drought and its relationship with other types of drought, and discussed research progress in agricultural drought monitoring from the site-based and remote sensing aspects, respectively. The applicability and limitations of different drought monitoring indexes were also compared. Results showed that the site-based drought index has experienced a long development history and become the main way of monitoring drought. Meanwhile, the remote sensing based drought index was mainly established from two aspects, soil water and crop water, and has achieved good results in agricultural drought monitoring. In addition, through mathematical statistics and document comparison, the development and latest progress of agricultural drought monitoring has been revealed, suggesting a transformation of agricultural drought monitoring from traditional single meteorological monitoring indicators to integrated meteorology and remote sensing monitoring indicators, mainly reflected in the introduction of multisource data and the innovation of research methods. The applicability and limitations of comprehensive drought monitoring indexes established in recent years were also discussed. Finally, through the analysis of current challenges in agricultural drought monitoring, future research prospects in agricultural drought monitoring are proposed, including further investigating the mechanism of agricultural drought, identifying the influences of agricultural drought, developing a multi spatiotemporal scale agricultural drought monitoring model, coupling the qualitative and quantitative agricultural drought evaluation models, and improving the application level of remote sensing data in agricultural drought monitoring.
[本文引用: 3]
DOI:10.1038/nature16467URL [本文引用: 3]
DOI:10.1360/N072016-00098URL [本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 4]
DOI:10.11821/dlxb201407013 [本文引用: 1]
Using the daily minimum temperature data of 121 meteorological stations in Inner Mongolia and its surrounding areas, this paper analyzed the spatiotemporal variation of cold surge and its possible influencing factors in Inner Mongolia during 1960-2012, based on piecewise regression model, Sen+Mann-Kendall model, and correlation analysis. The results show that, (1) The occurrence frequency of single-station cold surge presented a decreasing trend in Inner Mongolia during recent 53 years, with a linear tendency of -0.5 times/10a (-2.4-1.2 times/10a), of which a significant decreasing trend was detected before 1991, being -1.1 times/10a (-3.3-2.5 times/10a), while an increasing trend of 0.45 times/10a (-4.4-4.2 times/10a) was found after 1991. On the seasonal scale, the trend of spring cold surge was consistent with that of the annual value, and the most obvious change of cold surge also occurred in spring. The frequency of monthly cold surge showed a bimodal structure, and November witnessed the highest incidence of cold surge. (2) Spatially, the high incidence of cold surge is mainly observed in the northern and central parts of Inner Mongolia, and higher in the northern than the central part. The inter-decadal characteristic also detected that high frequency and low frequency regions presented a decreasing trend and an increasing trend, respectively, during 1960-1990, while high frequency regions expanded after the 1990s, regions with high frequency of cold surge were mainly distributed in Tol Gol, Xiao’ergou, and Xi Ujimqin Banner. (3) On annual scale, the cold surge was dominated by AO, NAO, CA, APVII, and CQ, while the difference in driving forces among seasons was detected. Winter cold surge was significantly correlated with AO, NAO, SHI, CA, TPI, APVII, CW, and IZ, indicating that cold surge in winter was caused multifactor. Autumn cold surge was mainly affected by CA and IM, while spring cold surge was significantly correlated with CA and APVII.
[本文引用: 1]
DOI:10.1016/j.scitotenv.2018.10.434URL [本文引用: 4]
DOI:10.1111/gcb.2019.25.issue-7URL [本文引用: 1]
DOI:10.1016/j.agrformet.2012.09.011URL [本文引用: 2]
DOI:10.1073/pnas.1312330110PMID:24344316 [本文引用: 2]
The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up.
DOI:10.1007/s11430-018-9363-5URL [本文引用: 1]
[本文引用: 2]
DOI:10.1016/j.fcr.2004.01.005URL [本文引用: 1]
PMID:30846745 [本文引用: 1]
Maize is a sensitive crop to drought and heat stresses, particularly at the reproductive stages of development. The present study investigated the individual and interactive effects of drought (50% field capacity) and heat (38?°C/30?°C) stresses on morpho-physiological growth, yield, nutrient uptake and oxidative metabolism in two maize hybrids i.e., 'Xida 889' and 'Xida 319'. The stress treatments were applied at tasseling stage for 15 days. Drought, heat and drought?+?heat stress caused oxidative stress by the over-production of ROS (O, HO, OH) and enhanced malondialdehyde contents, which led to reduced photosynthetic components, nutrients uptake and yield attributes. The concurrent occurrence of drought and heat was more severe for maize growth than the single stress. However, both stresses induced the metabolites accumulation and enzymatic and non-enzymatic antioxidants to prevent the oxidative damage. The performance of Xida 899 was more prominent than the Xida 319. The greater tolerance of Xida 889 to heat and drought stresses was attributed to strong antioxidant defense system, higher osmolyte accumulation, and maintenance of photosynthetic pigments and nutrient balance compared with Xida 319.
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
URL [本文引用: 1]
DOI:10.1016/j.agrformet.2020.107928URL [本文引用: 1]
DOI:10.1016/j.agwat.2017.03.023URL [本文引用: 1]
[本文引用: 1]
[本文引用: 1]
DOI:10.1016/j.jag.2005.06.002URL [本文引用: 1]
DOI:10.1126/science.1204531PMID:21551030 [本文引用: 1]
Efforts to anticipate how climate change will affect future food availability can benefit from understanding the impacts of changes to date. We found that in the cropping regions and growing seasons of most countries, with the important exception of the United States, temperature trends from 1980 to 2008 exceeded one standard deviation of historic year-to-year variability. Models that link yields of the four largest commodity crops to weather indicate that global maize and wheat production declined by 3.8 and 5.5%, respectively, relative to a counterfactual without climate trends. For soybeans and rice, winners and losers largely balanced out. Climate trends were large enough in some countries to offset a significant portion of the increases in average yields that arose from technology, carbon dioxide fertilization, and other factors.
DOI:10.1007/s10584-006-9141-3URL [本文引用: 1]
DOI:10.1126/science.1251423PMID:24786079 [本文引用: 2]
A key question for climate change adaptation is whether existing cropping systems can become less sensitive to climate variations. We use a field-level data set on maize and soybean yields in the central United States for 1995 through 2012 to examine changes in drought sensitivity. Although yields have increased in absolute value under all levels of stress for both crops, the sensitivity of maize yields to drought stress associated with high vapor pressure deficits has increased. The greater sensitivity has occurred despite cultivar improvements and increased carbon dioxide and reflects the agronomic trend toward higher sowing densities. The results suggest that agronomic changes tend to translate improved drought tolerance of plants to higher average yields but not to decreasing drought sensitivity of yields at the field scale.
DOI:10.1002/2017GL073606URL [本文引用: 1]
DOI:10.1016/j.agrformet.2018.09.019URL [本文引用: 1]
DOI:10.1111/gcb.12381PMID:24038882 [本文引用: 1]
Global climate change is predicted to increase temperatures, alter geographical patterns of rainfall and increase the frequency of extreme climatic events. Such changes are likely to alter the timing and magnitude of drought stresses experienced by crops. This study used new developments in the classification of crop water stress to first characterize the typology and frequency of drought-stress patterns experienced by European maize crops and their associated distributions of grain yield, and second determine the influence of the breeding traits anthesis-silking synchrony, maturity and kernel number on yield in different drought-stress scenarios, under current and future climates. Under historical conditions, a low-stress scenario occurred most frequently (ca. 40%), and three other stress types exposing crops to late-season stresses each occurred in ca. 20% of cases. A key revelation shown was that the four patterns will also be the most dominant stress patterns under 2050 conditions. Future frequencies of low drought stress were reduced by ca. 15%, and those of severe water deficit during grain filling increased from 18% to 25%. Despite this, effects of elevated CO2 on crop growth moderated detrimental effects of climate change on yield. Increasing anthesis-silking synchrony had the greatest effect on yield in low drought-stress seasonal patterns, whereas earlier maturity had the greatest effect in crops exposed to severe early-terminal drought stress. Segregating drought-stress patterns into key groups allowed greater insight into the effects of trait perturbation on crop yield under different weather conditions. We demonstrate that for crops exposed to the same drought-stress pattern, trait perturbation under current climates will have a similar impact on yield as that expected in future, even though the frequencies of severe drought stress will increase in future. These results have important ramifications for breeding of maize and have implications for studies examining genetic and physiological crop responses to environmental stresses. © 2013 John Wiley & Sons Ltd.
[本文引用: 1]
DOI:10.11821/dlxb201901007 [本文引用: 1]
Based on the MOD09A1 and MOD16A2 datasets with a temporal resolution of 8 days during a period from 2001 to 2016, Drought Severity Index (DSI) was quantified to characterize spatiotemporal distribution of droughts of different drought intensities. The correlation coefficients were quantified between drought-affected cropland area and the climatic winter wheat yield. In addition, relevant impacts of droughts with different drought intensities were investigated on the winter wheat yield during different growing periods. The results show that: (1) drought regimes during 2001-2016 showed a declining trend in terms of drought intensity at annual and inter-annual scales. The most severe drought occurred during 2001-2002 while regional and intermittent droughts could be observed during 2003-2010, and were alleviated during 2011-2016 with persistent wetting tendency thereafter. In terms of annual drought distribution, droughts occurred mainly in spring and autumn, some occurred in summer and few droughts in winter; (2) Generally, in terms of the spatial distribution of droughts, central and northern Hebei, southern Henan, Anhui and Jiangsu, and eastern Shandong provinces were dominated by frequent droughts though droughts were in decreasing trends; (3) analysis results concerning effects of droughts on winter wheat yield show that the incipient drought during the winter period can promote the winter wheat yield, while in the milking stage of the winter wheat, occurrence of droughts may decrease crop yield. The mild drought potential has significant effects on winter wheat yield during the ripening interval, while the moderate drought occurs during flowering, milking and ripening periods can have a significant impact on the winter wheat yield. Meanwhile, droughts with higher degree of intensity will have more significant impacts on winter wheat at its earlier growing season. In addition, water shortage due to drought effects during planting periods will reduce the yield of winter wheat, and severe and extreme droughts in particular. Therefore, it is of great merits in quantification of impacts of droughts with different intensities on winter wheat yield in different growing seasons, and it has important theoretical and practical significance for the planning of irrigation and the increase of soil moisture in the study region.
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
DOI:10.1016/j.jhydrol.2017.07.060URL [本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
PMID:28102202 [本文引用: 2]
High temperatures are detrimental to crop yields and could lead to global warming-driven reductions in agricultural productivity. To assess future threats, the majority of studies used process-based crop models, but their ability to represent effects of high temperature has been questioned. Here we show that an ensemble of nine crop models reproduces the observed average temperature responses of US maize, soybean and wheat yields. Each day >30 degrees C diminishes maize and soybean yields by up to 6% under rainfed conditions. Declines observed in irrigated areas, or simulated assuming full irrigation, are weak. This supports the hypothesis that water stress induced by high temperatures causes the decline. For wheat a negative response to high temperature is neither observed nor simulated under historical conditions, since critical temperatures are rarely exceeded during the growing season. In the future, yields are modelled to decline for all three crops at temperatures >30 degrees C. Elevated CO2 can only weakly reduce these yield losses, in contrast to irrigation.
URL [本文引用: 1]
DOI:10.1073/pnas.1701762114URL [本文引用: 2]
DOI:10.1111/gcb.13530URL [本文引用: 1]
DOI:10.1038/nclimate3115URL [本文引用: 2]
[本文引用: 1]
DOI:10.1073/pnas.1409606112URL [本文引用: 1]
URL [本文引用: 1]
DOI:10.1111/ppl.2018.162.issue-1URL [本文引用: 1]
URL [本文引用: 1]
DOI:10.1016/j.jhydrol.2018.07.077URL [本文引用: 1]
DOI:10.1111/gcb.2018.24.issue-3URL [本文引用: 3]
DOI:10.5194/gmd-10-1403-2017URL [本文引用: 1]
DOI:10.5897/SREURL [本文引用: 1]
DOI:10.1038/s41477-020-0625-3PMID:32296143 [本文引用: 1]
Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales.
[本文引用: 2]
[本文引用: 2]
DOI:10.1007/s00484-016-1246-4URL [本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
DOI:10.5846/stxbURL [本文引用: 1]
[本文引用: 1]
[本文引用: 1]
DOI:10.1073/pnas.1222463110PMID:24344314 [本文引用: 1]
Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
DOI:10.1038/nclimate1356URL [本文引用: 1]
URL [本文引用: 1]
DOI:10.1016/j.rse.2017.04.014URL [本文引用: 1]
[本文引用: 2]
[本文引用: 2]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
DOI:10.1073/pnas.1616919114URL [本文引用: 1]
DOI:10.1111/gcb.2016.22.issue-2URL [本文引用: 1]
URL [本文引用: 1]
DOI:10.13249/j.cnki.sgs.2020.01.002 [本文引用: 1]
A discipline has typically the following four key features, namely independent research objects, independent research questions, unique characteristics, and unique social services. This paper first discusses the nature of Geography from three aspects, to reveal the characteristics of modern Geography. First, the research object of Geography is changing from simple to complex evolution. In performing geographic research, we should well recognize the complexity of geographic systems. Second, the framework of geographic research questions is structured by the fusion among geographic features, space, and time. This paper explains the essential distinction between different geographic research questions, which promotes the development of the methods and technologies for answering these questions. Third, the philosophy of combining reductionism and holism is growing continuously. A new pattern of research has been formed based on new disciplines and technologies, which is the parallel development of the research on geographic features and that on systems. This paper then identifies the essential characteristics of geographic research, summarizes the key research questions in Geography, and discusses the multiple effects of driving mechanisms on the laws of Geography. An understanding of the fundamental characteristics and the modern value of Geography illustrated in this paper will be contribute to the societal development of Geography.
[本文引用: 1]
[本文引用: 1]
DOI:10.1080/02626667.2018.1558367 [本文引用: 1]
For the development of sustainable, efficient risk management strategies for the hydrological extremes of droughts and floods, it is essential to understand the temporal changes of impacts, and their respective causes and interactions. In particular, little is known about changes in vulnerability and their influence on drought and flood impacts. We present a fictitious dialogue between two experts, one in droughts and the other in floods, showing that the main obstacles to scientific advancement in this area are both a lack of data and a lack of commonly accepted approaches. The drought and flood experts "discuss" available data and methods and we suggest a complementary approach. This approach consists of collecting a large number of single or multiple paired-event case studies from catchments around the world, undertaking detailed analyses of changes in impacts and drivers, and carrying out a comparative analysis. The advantages of this approach are that it allows detailed context- and location-specific assessments based on the paired-event analyses, and reveals general, transferable conclusions based on the comparative analysis of various case studies. Additionally, it is quite flexible in terms of data and can accommodate differences between floods and droughts.
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
[本文引用: 1]
DOI:10.1016/j.scib.2019.07.016URL [本文引用: 1]
