作物生长模型的应用研究进展

作物生长模型不仅能够进行单点尺度上作物生长发育的动态模拟,而且能够从系统角度评价作物生长状态与环境要素的关系。本文通过梳理当前作物生长模型应用的诸多研究成果,剖析模型在气候变化对农业生产影响研究、作物生长模型区域应用中的关键问题,总结了当前以作物生长模型为核心的农业决策支持系统开发的研究情况,意在促进作物生长模型在生态、农业、区域气候资源和气候变化等研究中更广泛地应用。结果表明,作物生长模型在国内外的研究与应用广泛而深入,在气候变化背景下,应用作物生长模型进行历史时期气候条件和农业气象灾害对作物生产状况和产量的影响研究已相当广泛且相对成熟。利用全球气候模式（GCM）或区域气候模式（RCM）构建未来气候变化情景,再与作物生长模型耦合已发展成为评估未来气候变化对农业生产影响的重要手段。通过集成与整合多作物生长模型、多气候模式集合模拟、优化气候模拟数据订正方法可有效降低气候变化对农业生产影响评估的不确定性。遥感数据同化技术能够将站点模型运用到区域尺度上评价不同环境因子对农业生产的影响,拓宽了作物生长模型的应用尺度范围并有效提高作物产量估算的精度。以作物生长模型为核心的农业决策支持系统的研究与应用越来越多元化,是辅助农业生产管理和决策的重要工具。然而,由于作物生态系统的复杂性,作物生长模型模拟结果仍存在很大的不确定性,今后对作物生长机理及过程间耦合机制的探索还需加强,以便进一步完善和改进模型,促进作物生长模型更广泛地应用。     

气候变化对非洲水资源和农业的影响

尽管非洲是世界上温室气体排放总量或人均排放量最少的地区,但在承受气候变化造成的恶劣影响方面首当其冲。气候变化已经给非洲的水资源、农业、生物多样性、人类健康和国家安全等带来诸多严重影响,粮食生产和水资源一直是非洲长期面临的两大难题,也是深受气候变化影响的两大领域还较欠缺,需要在未来的研究中进一步加强,以探寻减缓气候变化对非洲水资源和农业不利影响的有效途径。本文系统梳理了气候变化对非洲水资源系统和农业生产影响的研究成果和不足,以期为非洲气候变化影响评估工作提供一定参考和借鉴。已有的观测结果表明,气候变化导致非洲许多山脉冰川面积正在大范围缩减、大部分地区降水量有所减少,降雨的年际间分布也更为不稳定,通过水文模型的模拟预测,未来气候变化将进一步影响降水量和非洲部分地区河流的径流量,导致非洲水资源供给压力加大。同样,气候变化也给非洲农业生产带来了巨大的挑战,无论是观测结果分析,还是统计模型和作物模型等对不同气候情景和时间尺度下非洲农业的模拟研究,都显示气候变化对非洲农业以负面影响为主,导致非洲干旱加剧、生长季改变和粮食产量下降,并可能危及非洲的粮食安全。然而,现有研究结果还存在较多不确定性,其主要集中在未来气候情景数据、研究方法、数据的质量和数量等方面。与世界其它地区相比,非洲气候变化影响研究无论是研究的深度和广度都     

作物模型与气候模型的连接研究进展

针对目前气候变化对农业影响的大气模型与作物模型尺度差异问题,介绍了气候变化对农业生产影响中气候模型与作物模型相连接的方法,即大气模型的降尺度和作物模型的升尺度连接,指出目前这些方法中存在的问题,并对各方法中常用方式如天气发生器、作物模型区域校正等进行了介绍,最后指出未来的发展方向。     

未来气候情景下农牧交错带不同灌溉水平马铃薯产量和水分利用效率

未来气候变化对农牧交错带不同灌溉水平马铃薯产量和水分利用的影响鲜有研究。该研究基于农牧交错带张北和武川站不同灌溉条件下大田试验数据评估了APSIM-Potato模型的适应性;基于33个全球气候模式(global climate model,GCM)通过统计降尺度方法获得的未来2个气候情景(RCP4.5和RCP8.5)逐日气候数据驱动APSIM-Potato模型,模拟未来气候变化对不同灌溉水平(灌1水、灌2水、灌3水和灌4水)马铃薯产量和水分利用的影响。结果表明:APSIM-Potato模型能够较好地模拟2个站点马铃薯产量和土壤水分动态。2个站点实测产量和模拟产量的相对误差均小于22.6%,实测土壤水分和模拟土壤水分相对均方根误差均小于18.1%。基于33个GCM模拟结果,2030 s、2060 s和2090 s马铃薯生育期温度、CO2浓度、总降水量和总辐射量相比于基准期(1981-2010)均呈增加趋势。相比于基准期灌1水、灌2水、灌3水和灌4水马铃薯产量,张北站和武川站在RCP4.5情景下均有提升,张北站为4.1%~36.2%,武川站为2.5%~13.6%。RCP8.5情景下,2个站点分别提升3.1%~36.8%和3.1%~38.5%。且2个气候情景下均是灌1水情景下马铃薯产量提升最高。2个气候情景下,马铃薯水分利用效率在2030 s-2090 s均呈增加趋势。研究结果表明未来气候变化对农牧交错带地区马铃薯产量和水分利用效率具有积极影响,未来气候情景下该地区更适宜灌溉马铃薯的生产。     

水稻格点作物模型在中国区域的不确定性评估

作物模型是评估气候变化对农业生产影响的主要手段之一,但中国对格点作物模型间的比较研究尚处于初始阶段。为全面评估不同作物模型在中国不同区域对水稻产量模拟的有效性,利用联合国粮农组织（FAO）和中国农业农村部种植业管理司（SYB）水稻年平均产量统计资料,对由2种气候资料（AgMERRA和WFDEI-GPCC）和 3种不同种植管理情景（Default、Fullharm和Harmnon情景）驱动的7种全球格点作物模型（CGMS-WOFOST、CLM-CROP、EPIC-BOKU、GEPIC、LPJML、PDSSAT和PEPIC模型）模拟的中国水稻产量进行了对比分析。结果表明：不同格点作物模型之间的模拟结果差异较大,在不同区域不同格点作物模型的模拟效果差异显著,不同格点作物模型对气候变化和种植管理情景的响应和敏感性不同,大部分模拟结果低估了水稻产量。使用不同水稻统计产量数据会对评估结果产生一定的影响。格点作物模型能够一定程度上模拟出水稻产量的年际变化和气候变化对产量的影响,但对于统计水稻产量上升的趋势较难模拟。通过综合分析产量在时间和空间上的波动情况,并利用2种评分方法对模拟表现打分,发现LPJML和PDSSAT在7种格点作物模型中模拟效果最好,同时也对不同气候数据和种植管理情景的变化最敏感,CLM-CROP的模拟效果最差。对不同种植管理情景,Default情景下的模拟效果显著高于Fullharm和Harmnon情景。多种格点作物模型集合平均（MME）可以降低单个格点作物模型模拟的误差,但需对MME中的集合模型进行挑选。     

作物模型应用与遥感信息集成技术研究进展

作物模型和遥感技术以各自独有的优势在作物生产监测、评估及未来预测等方面发挥着关键作用。作物模型与遥感信息集成技术在大尺度、高精准的农业生产监测、评估与预测上具有明显的应用优势和广阔的发展前景。为了促进这些技术在区域尺度上的作物产量预测、农业气象灾害影响评估及农业应对气候变化决策等方面更加广泛地应用,本文采用文献综述的方法,系统归纳了欧洲、美国、澳大利亚及中国作物模型的发展与应用,总结了当前主流的数据集成方法的原理、特点和不足,概述了作物模型与遥感信息集成技术的实际应用,探讨了提升数据集成精度存在的问题,并对未来研究方向进行展望。结果表明,国内外对于作物模型及其与遥感数据集成的研究与应用广泛而深入,利用同化方法能够有效提高作物模型模拟精度,为作物模型实现区域尺度作物生长及产量评估、气候变化对产量影响、农田管理决策等提供技术支撑。作物模型模拟结果及遥感反演数据的不确定性、数据同化策略的多样性以及尺度效应是进一步提高集成系统精度与效率的限制因素。因此,遥感数据多源融合、同化过程多变量协同、作物模型多类型耦合以及数据高性能并行计算是未来作物模型与遥感数据集成研究的发展趋势。     

《气候变化2014:影响、适应和脆弱性》对农业气象学科发展的启示

通过对政府间气候变化专门委员会第二工作组(IPCC AR5 WGII)的报告《气候变化2014:影响、适应和脆弱性》有关涉农章节的解读,分析有助于国内外农业气象学科发展的科学问题,并提出进一步研究的优先领域。IPCC认为,如果不考虑适应,局地温度比20世纪晚期升高2℃或更多,对热带和温带地区主要作物产量(小麦、水稻和玉米)都将产生负面影响。预计的影响随作物、区域和适应情景而不同。约10%的研究结果预测2030-2049年比20世纪晚期可能增产10%,也有10%的研究结果则预测减产25%以上。对比国内有关气候变化对农业影响评估的研究,反映的差距主要集中在:(1)农业系统对气候变化敏感程度和脆弱性的定量评估能力较弱;(2)难以识别气候对农业的直接和间接影响程度;(3)综合研究不够,还不能定量分析各种非气候因素的贡献;(4)适应对策实例和经验总结不够,有关的成本效益分析不够。建议本学科优先在以下领域进一步深入研究:(1)更新并完善粮食生产影响模型,建立区域和全球尺度的、可靠的、综合的粮食系统模型;(2)进一步认识CO2与臭氧对作物生长的综合影响程度,高温和低温对作物的影响,以及干旱和洪涝的生理阈值;(3)开展与各种变暖情景有关的粮食生产实验和模拟,包括作物、家畜、渔业、水果和蔬菜等生产要素以及加工、分配及零售和消费模式等非生产要素的气候影响和适应。     

气候变化对开都河流域径流的影响研究

利用SWAT模型模拟开都河流域的径流变化,并采用1990—2009年的水文站点径流数据进行精度验证,然后设定气候变化情景,模拟不同气候条件下径流的响应特征。结果表明:模拟结果与实测径流较吻合,剔除异常年份（1994年、1995年）后,校准期（1990—2000年）效率系数为0.58,平均相对误差为-5.7%,线性拟合度为0.8;验证期（2000—2009年）的结果与校准期接近,均达到了模型的评价标准,说明SWAT模型在开都河流域的适用性较好。基于此,采用任意情景设置方法,设置了25种气候变化（气温和降水）组合情景,研究了该流域对气候变化的响应,结果表明,气候变化对径流量的影响较为显著,降水增加或气温降低均会导致径流量增加,流域未来年均径流变化的主要影响因素是降水,温度的影响相对较弱。     

气候变化情景下东北地区玉米产量变化模拟

WOFOST作物模型在东北地区玉米适应性验证的基础上,结合气候模型BCC-T63输出的未来60年(2011～2070年)气候情景资料,模拟分析了未来气候变化情景下我国东北地区玉米生育期和产量变化情况。模拟结果显示:未来气候变化情景下,玉米生育期将缩短,其中,中熟玉米平均缩短3.4 d,晚熟玉米平均缩短1.1 d;玉米产量将相应下降,中熟玉米平均减产3.5%,晚熟玉米平均减产2.1%。     

滦河流域气候变化的水文响应研究

以滦河流域为研究区,基于未来气候变化研究成果建立了16种气候变化情景,结合SWAT分布式水文模型模拟了不同气候变化情景下的水文过程,对滦河流域气候变化的水文响应进行了分析。结果表明:SWAT模型可以较好地模拟滦河流域的月流量过程,在研究区具有较好的适用性;流域气温升高将会导致蒸发量增加、径流减少。在以升温为主、降水变化存在很大不确定性的情况下,滦河流域径流量可能进一步衰减。在未来降水增加的情况下,流域年均地表径流增加趋势的空间差异显著,尤其是流域下游的迁西县等地增加幅度超过12mm,研究结果将为变化环境下滦河流域的水资源管理提供参考。     

应对气候变化对未来中国农业生产影响的问题和挑战

通过整合农业科学界从不同行业产业角度和不同的影响方面对气候变化可能带来农业生产影响的分析资料,梳理和辨析了气候变化对农业生产影响的途径和机理,提出了气候变化对中国国家尺度农业影响的“发酵”效应假设：气候变化因子间相互作用与交错叠加,产业的传递和反馈,可能带来不利效应的严重放大;未来气候变化下中国农业面临的基本问题将是：农业技术进步的迟滞性和农业生产能力的波动性,稳定农业生产水平和粮食供应能力将愈来愈困难。讨论和建议了应对气候变化的若干国家战略,这些战略应基于气候变化对中国农业生产的影响的敏感性行业和地区,气候变化的突出性趋势的认识。防患和应对极端性气象灾害事件将成为应对气候变化对农业影响的首要任务,需要加强研究和技术储备,同时迫切需要新的组织和运行机制全面开展气候变化对中国农业生产影响的试验和技术开发研究。     

气候变化对中国农业生产的影响

未来气候变化下中国农业的稳定事关中国的长远持续发展,国内外气候变化研究界和农业气象研究界对气候变化对中国农业生产的影响的评估未有一致的认识。本文从农业科学角度讨论了气候变化对中国农业生产涉及的气象资源、土地资源、农业生物环境和生态系统的影响,并从作物生长和经济产量形成的角度讨论和分析了气候变化对中国种植业、养殖业不同产业行业的影响,气候变化中一些趋势性变化因不同作物和不同区域而异,例如温度和CO2浓度变化对农业生产的影响因不同作物和不同时相而异,反之,极端性气候／天气事件对农业不同行业的生产都显得危害很大,而气候变化中区域性干旱将成为我国未来农业生产愈来愈严重的挑战。气候变化对中国农业生产的影响甚为复杂,一些气候变化因子的实际影响还存在很大不确定性。当前,定量评价气候变化对中国农业生产的影响还存在困难。     

The impacts of potential climate change and climate variability on simulated maize production in China

This study assessed the impacts of potential climate change on maize yields in China, using the CERES-Maize model under rainfed and irrigated conditions, based on 35 maize modeling sites in eastern China that characterize the main maize regions. The Chinese Weather Generator was developed to generate a long time series of daily climate data as baseline climate for 51 sites in China. Climate change scenarios were created from three equilibrium general circulation models: the Geophysical Fluid Dynamics Laboratory model, the high-resolution United Kingdom Meteorological Office model, and the Max Planck Institute model. At most sites, simulated yields of both rainfed and irrigated maize decreased under climate change scenarios, primarily because of increases in temperature, which shorten maize growth duration, particularly the grain-filling period. Decreases of simulated yields varied across the general circulation model scenarios. Simulated yields increased at only a few northern sites, probably because maize growth is currently temperature-limited at these relatively high latitudes. To analyze the possible impacts of climate variability on maize yield, we specified incremental changes to variabilities of temperature and precipitation and applied these changes to the general circulation model scenarios to create sensitivity scenarios. Arbitrary climate variability sensitivity tests were conducted at three sites in the North China Plain to test maize model responses to a range of changes (0%, +10%, and +20%) inthe monthly standard deviations of temperature and monthly variation coefficients of precipitation. The results from the three sites showed that incremental climate variability caused simulated yield decreases, and the decreases in rainfed yield were greater than those of irrigated yield.     

A new paradigm for assessing the role of agriculture in the climate system and in climate change

This paper discusses the diverse climate forcings that impact agricultural systems, and contrasts the current paradigm of using global models downscaled to agricultural areas (a top-down approach) with a new paradigm that first assesses the vulnerability of agricultural activities to the spectrum of environmental risk including climate (a bottom-up approach). To illustrate the wide spectrum of climate forcings, regional climate forcings are presented including land-use/land-cover change and the influence of aerosols on radiative and biogeochemical fluxes and cloud/precipitation processes, as well as how these effects can be teleconnected globally. Examples are presented of the vulnerability perspective, along with a small survey of the perceived drought impacts in a local area, in which a wide range of impacts for the same precipitation deficits are found. This example illustrates why agricultural assessments of risk to climate change and variability and of other environmental risks should start with a bottom-up perspective.     

Landscape‐scale modelling of erosion processes and soil carbon dynamics under land‐use and climate change in agroecosystems

Soil organic carbon (SOC) sequestration and soil redistribution are linked to soil properties, land use, farming system and climate. In a global‐change context, landscape and climate changes are expected and will most probably have impacts on changes in the soil. Soil change was simulated from 2010 to 2100 in an 86‐ha hedgerow landscape under different scenarios of landscape and climate changes. These scenarios combined contrasting land uses, hedgerow networks and climates. Two models were combined to evaluate the impact of these scenarios on soils: LandSoil, a soil redistribution model, and a SOC model based on RothC‐26.3. A soil thickness of 105 cm was considered. The results indicate that the main factor influencing soil degradation was land‐use change: when compared with the baseline business‐as‐usual landscape, the landscape with the most intensive agricultural systems had the greatest soil erosion (+0.26 t ha^?1 year^?1) and reduced mean SOC stocks (?17 t ha^?1 after 90 years). The second significant factor was climate change, followed by hedgerow network density. Sensitivity to climate change differed between landscapes, and the most sensitive were those with continuous winter wheat. The results indicate that a hedgerow landscape is well adapted to protect soil (regarding carbon storage and soil erosion) in a context of climate change. However, this type of landscape is highly sensitive to cropping intensification and should be protected.     

Soil erosion from sugar beet in Central Europe in response to climate change induced seasonal precipitation variations

This study estimates the implications of projected seasonal variations in rainfall quantities caused by climate change for water erosion rates by means of a modeling case study on sugar beet cultivation in the Central European region of Upper-Austria. A modified version of the revised Morgan–Morgan–Finney erosion model was used to assess soil losses in one conventional and three conservation tillage systems. The model was employed to a climatic reference scenario (1960–89) and a climate change scenario (2070–99). Data on precipitation changes for the 2070–99 scenario were based on the IPCC SRES A2 emission scenario as simulated by the regional climate model HadRM3H. Weather data in daily time-steps, for both scenarios, were generated by the stochastic weather generator LARS WG 3.0. The HadRM3H climate change simulation did not show any significant differences in annual precipitation totals, but strong seasonal shifts of rainfall amounts between 10 and 14% were apparent. This intra-annual precipitation change resulted in a net-decrease of rainfall amounts in erosion sensitive months and an overall increase of rainfall in a period, in which the considered agricultural area proved to be less prone to erosion. The predicted annual average soil losses under climate change declined in all tillage systems by 11 to 24%, which is inside the margins of uncertainty typically attached to climate change impact studies. Annual soil erosion rates in the conventional tillage system exceeded 10 t ha^− 1 a^− 1 in both climate scenarios. Compared to these unsustainably high soil losses the conservation tillage systems show reduced soil erosion rates by between 49 and 87%. The study highlights the importance of seasonal changes in climatic parameters for the discussion about the impacts of global climate change on future soil erosion rates in Central Europe. The results also indicate the high potential of adaptive land-use management for climate change response strategies in the agricultural sector.     

Distinct and combined impacts of climate and land use scenarios on water availability and sediment loads for a water supply reservoir in northern Morocco

The objective of this study was to examine the impacts of climate and land use changes on water availability and sediment loads for a water supply reservoir in northern Morocco using data-intensive simulation models in a data-scarce region. Impacts were assessed by comparing the simulated water and sediment entering the reservoir between the future period 2031–2050 and the 1983–2010 reference period. Three scenarios of land use change and two scenarios of climate change were developed in the Tleta watershed. Simulations under current and future conditions were performed using the Soil and Water Assessment Tool (SWAT) model. The simulations showed that climate change will lead to a significant decrease in the annual water supply to the reservoir (−16.9% and −27.5%) and in the annual volume of sediment entering the reservoir (−7.4% and −12.6%), depending on the climate change scenarios tested. The three scenarios of land use change will lead to a moderate change in annual water inflow into the reservoir (between −6.7% and +6.2%), while causing a significant decrease in sediment entering the reservoir (−37% to −24%). The combined impacts of climate and land use changes will cause a reduction in annual water availability (−9.9% to −33.3%) and sediment supplies (−28.7% to −45.8%). As a result, the lifetime of the reservoir will be extended, but at the same time, the risk of water shortages will increase, especially from July to March. Therefore, alternative water resources must be considered.     

气候变化对畜牧业生产的影响

人类活动将导致气候变化，从而给畜牧业生产带来影响。文中从三个方面综述并分析了气候变化对畜牧业的影响：１）气候变化对草地生态系统和草地面积的影响；２）气候变化包括大气中ＣＯ２含量增加、温度和降水的变化对草地生产力和牲畜负载力的影响；３）气候变化对家畜健康、生长和繁殖的影响。     

未来气候变化对中国小麦产量影响的差异性研究——基于Meta回归分析的定量综述

对2017年以前预测未来气候变化对中国小麦产量影响的国内外相关研究进行了综述,并对其中26篇研究信息相对全面完整的文献进行Meta分析,总结了原始独立研究预测结果的差异,并讨论差异的可能来源,以期为本领域后续研究提供依据。结果表明：（1）未来气候变化对中国小麦产量的影响存在一定不确定性,但以负面影响为主;A2和B2主流气候情景下预测的小麦产量减产幅度较其它气候情景分别高18%和20%。（2）政策、技术、市场和投入等非气候性因素有助于适应气候变化,引入这些因素时小麦增产幅度预测结果增加10%;（3）研究数据和方法对预测结果有显著影响,预测时间间隔每延长一年,小麦产量增幅和减幅预测结果提高1%,进行产量分离、采用相应的气候模型和作物模型对预测增幅有显著的正向影响,增加水平分别为26%、22%和18%;（4）期刊文献比非期刊文献的产量增幅预测结果平均高5%。     

Future productivity of fallow systems in Sub-Saharan Africa: Is the effect of demographic pressure and fallow reduction more significant than climate change?

In this century climate change is assumed to be the major driver for changes in agricultural systems and crop productivity at the global scale. However, due to spatial differences in cropping systems and in the magnitude of climatic change regional variations of climate change impact are expected. Furthermore, the recent climate projections are highly uncertain for large parts of West Africa. In particular with respect to annual precipitation and variability the projections vary between trends with decreasing precipitation and trends with slightly increasing precipitation within the next decades. On the other hand, the extensive fallow systems in this region suffer from increasing population pressure, which compromises soil fertility restoration. In the Republic of Benin, the demographic projections for the first half of this century indicate a continuous growth of the population with a narrow interval of confidence. Thus, in the absence of an adequate soil fertility management with judicious use of mineral fertilizers, the soil degradation process with decreasing crop yields is expected to continue. The objective of this paper was, therefore, to quantify the regional effect of future population growth on crop yields in West Africa and to compare it with the potential effects of climate change scenarios. Three land use scenarios (L1, L2 and L3) for the Upper Ouémé catchment where derived from different demographic projections combined with assumptions regarding future road networks and legal frameworks for forest protection using the CLUE-S modeling approach. The fallow-cropland ratio decreased in the three scenarios from 0.87 in the year 2000 to 0.66, 0.48 and 0.68 for L1, L2 and L3, respectively in 2050. Based on the projected ratio of fallow and cropland, trends of maize yield for the three land use scenarios were calculated using the EPIC (Environmental Policy Integrated Climate) model coupled with a spatial database. Maize yields followed the decreasing trend of the fallow-cropland ratio and estimated yield reductions amounted to up to 24% in the period 2021-2050. This trend was compared with the impact of the SRES climate scenarios A1B and B1 based on the output of the GCM ECHAM5 downscaled with the REMO model and the A1B scenario output of the GCM HADC3Q0 downscaled with the RCMs SMHIRCA and HADRM3P. The yield reductions due to the projected climate change in the three models accounted for a yield decrease of up to 18% (REMO A1B scenario) in the same period. Taking into account the smaller uncertainties in the scenario assumptions and in the model output of the land use scenarios, it is concluded that, in low input fallow systems in West Africa, land use effects will be at least as important as climate effects within the next decades.