气候变化对河南省灌溉小麦的影响及对策初探

灌溉是河南省冬小麦最重要的种植管理模式。在DSSAT-CERES小麦模型参数调试和区域适用性验证的基础上,利用区域气候模式PRECIS输出的未来气候情景资料,量化分析了2021—2050年河南省灌溉条件下冬小麦产量的可能变化,结果表明:若不采取其他措施,未来A2,B2两种温室气体排放情景下,河南省冬小麦产量平均减少5%左右,A2情景减产率略高于B2;随着产量降低,产量波动区间略有缩小,但25%~75%的稳产区间也相应缩小,且B2情景下更容易出现极端低产的年份;冬小麦水分利用效率相应降低。采取适当应对措施,如延迟播种期、减小种植密度等有利于提高产量或缓解减产趋势。     

A2和B2情景下冀鲁豫冬小麦气象产量估算

冬小麦是我国的主要粮食作物之一,河北、山东、河南三省是我国的冬小麦主产区。利用1978—2008年冀、鲁、豫三省的历史气象资料和冬小麦产量数据,分别建立了三省冬小麦趋势产量和气象产量模型,趋势产量模型的复相关系数超过0.90,气象产量模型均通过0.05的显著性检验。将区域气候模式PRECIS输出的基准气候条件下的格点资料回代到冬小麦气象产量模型,以验证区域气候模式的可用性。利用区域气候模式输出的A2和B2情景下三省的格点资料和三省冬小麦气象产量模型,估算得到了三省2012—2050年的冬小麦气象产量,结果表明:无论在A2还是B2情景下,河北和河南两省冬小麦气象产量均表现出以减产为主、山东省冬小麦气象产量以增产为主的趋势。     

气候变化对我国小麦发育及产量可能影响的模拟研究

利用随机天气模型, 将气候模式对大气中CO₂倍增时预测的气候情景与CERES-小麦模式相连接, 研究了气候变化对我国冬小麦和春小麦生产的可能影响.结果表明, 气候变化后小麦发育将加快, 生育期缩短, 冬小麦平均缩短7.3天, 春小麦平均缩短10.5天, 春小麦生育期缩短的绝对数和相对数均大于冬小麦.籽粒产量呈下降趋势, 冬小麦平均减产7%~8%, 雨养条件下比水分适宜时减产幅度略大.春小麦的减产幅度大于冬小麦, 水分适宜时平均减产17.7%, 雨养时平均减产31.4%.     

CMIP5和RegCM4.0模式对西南区域未来降水的预估

利用CMIP5全球模式数据集和RegCM4.0区域气候模式进行连续积分获得的模拟数据,对西南区域未来在RCP2.6,RCP4.5和RCP8.5几种温室气体排放情景下年平均降雨、四季降水,极端降雨事件的特征及其相对历史基准期的变化进行预估。结果表明,不同RCP情景下西南区域降水都将呈持续上升趋势,3种情景下西南区域降水在2020—2050年变化特征差别较小,2050年后差别较大,RCP2.6情景下降水变化幅度最小,CMIP5和RegCM4.0模式模拟的西南区域降水变化的地理分布特征基本一致,降水的高值区都位于青藏高原东南部,横断山脉和四川中部,差异在于RegCM4.0模拟的西藏西部的降雨量级更小,而青藏高原东南部、四川中部和贵州的降雨高值区量级更大。未来近期2020—2060年和远期2061—2099年RCP4.5情景下暴雨天数显著减少的区域主要在西藏东南部(0.5~1 d),未来远期2061—2099年RCP4.5情景云南南部和贵州东部区域暴雨天数显著性增加,而RCP8.5情景下上述区域暴雨天数显著性减少。     

２种降尺度方法在太湖流域的应用对比

同时应用统计降尺度模型SDSM(Statistical Downscaling Model)和区域气候模式PRECIS(Providing Regional Climate for Impacts Studies),对太湖流域的日降水量和日最高、最低气温进行降尺度处理,建立未来2021-2050年的气候变化情景,并对比分析两种方法的适用性.结果表明,两种方法模拟的未来时期日最高、最低气温季节和年的变化情景增幅总体上比较一致,高排放情景A2下模拟生成的情景增温幅度较B2情景大,未来时期最高气温增加幅度比最低气温明显.两种方法模拟的降水变化情景差异明显,PRECIS模拟的2021-2050年降水增加趋势明显,增幅较大;而SDSM模拟的未来时期降水存在一定的减少趋势,变化幅度相对较小.以上结果说明PRECIS和SDSM都能较好地模拟太湖流域未来气温变化情景,而对未来降水的模拟不确定性较大.     

气候变化背景下蚌埠市暴雨与淮河上游洪水遭遇概率分析

利用6个全球/区域气候模式和VIC模型,预估了IPCC RCPs情景下2021—2050年淮河干流蚌埠水文站(吴家渡断面)的日流量过程。在此基础上,运用Copula函数构建了蚌埠市暴雨与淮河上游洪水遭遇概率模型,分析了RCP2.6、RCP4.5和RCP8.5情景下不同重现期暴雨和洪水组合遭遇概率的变化趋势。结果表明,2021—2050年多模式预估上游洪水与城市暴雨遭遇的概率较基准期(1971—2000年)有所增大,具有较高的一致性,平均增幅46%~79%。暴雨与洪水遭遇概率的增大,将会增加未来蚌埠市防洪工作的难度。     

基于高分辨率区域气候模式的三峡库区降水变化模拟与预估

基于三峡库区1961—2005年逐日降水格点数据,评估由BCC_CSM1.1模式驱动的RegCM4区域气候模式、MPI—ESM—LR模式驱动的CCLM区域气候模式对三峡库区年平均降水量、极端降水的模拟能力,筛选出与观测更为接近的区域气候模式模拟数据,预估在RCP4.5温室气体排放情景下未来2016—2050年三峡库区降水变化特征。结果表明:RegCM4和CCLM模式能够模拟出三峡库区降水量和暴雨日数的季节、年际变化特征和空间分布形态,但在库区东南部模拟的数值均偏少,而对暴雨强度不具备模拟能力。总体而言,CCLM模式对三峡库区降水的模拟效果好于RegCM4。在RCP4.5情景下,2016—2050年三峡库区年降水量未表现出明显变化趋势,而年暴雨日数将显著增加,平均较当代(1986—2005年)增加1.2 d。     

未来气候情景下冬小麦潜在北移区农业气候资源变化特征

基于区域气候模式系统PRECIS输出的RCP4.5气候情景数据分析表明,相较于1981-2010年,至2071-2097年冬小麦种植北界将平均向北移动147.8 km,北移面积约1.86×105 km²。选取代表光、温、水资源的9项农业气候资源指标,探究未来情景下,2021-2097年冬小麦潜在北移区内农业气候资源变化特征,结果表明：(1)相较于基准时段(1961-1990年),未来潜在北移区内光照资源变化呈减少趋势;热量资源呈明显增加趋势,在21世纪末的30年,波动性加大;降水资源整体增加趋势不明显,但波动性亦呈现增大趋势。(2)未来潜在北移区内,2030T (2021-2050年)、2050T (2041-2070年)和2070T (2061-2090年)时段光照资源在研究区域的东北部减少幅度较大,而在西南部较小;热量资源在研究区域的北部增加比南部明显;降水资源则主要在研究区域的东北部增加明显。     

气候变化对中国南方稻区水稻产量影响的模拟和分析

采用了DSSAT作物模式和区域气候模式相连接,模拟分析了A2和B2气候变化情景对中国主要地区灌溉水稻产量的影响。气候变化情景采用了IPCC发布的SRES(Special Report on Emissions Scenarios)系列的最新温室气体排放情景,气候情景值采用区域气候模式PRECIS(Provide Regional Climates for Impact Studies)的模拟值。通过研究站点水稻对A2和B2增温梯度敏感性的分析表明:温度增加,水稻产量呈下降趋势,随着温度增加,产量下降幅度增大。且在同一增温水平下,在南方热带地区的昆明和海口,产量下降幅度大于其他站点。A2和B2的产量相对于基准年(1961~1990年)的变化分别为:气候变化对不同站点的年代际水稻平均产量表现了正面或负面的影响(A2情景下为2.3%~-10.2%,B2情景下为4.0%~-13.6%),在某一些站点,水稻高产年和低产年的概率明显增加,产量分布趋于两极化。     

未来气候变化对云南柠檬气候适宜性的影响

气候变化影响柠檬生长、产量和品质,本文利用云南省125个国家气象站1981-2018年,月平均气温、月平均降水量、月日照时数,进行基准年代下云南柠檬气候适宜性分区;采用RCP2.6、RCP4.5、RCP8.5气候情景模式,研究2021-2030年、2031-2040年、2041-2050年云南柠檬气候适宜区的变化,探讨...     

Climate change impacts on sugarcane attainable yield in southern Brazil

This study evaluated the effects of climate change on sugarcane yield, water use efficiency, and irrigation needs in southern Brazil, based on downscaled outputs of two general circulation models (PRECIS and CSIRO) and a sugarcane growth model. For three harvest cycles every year, the DSSAT/CANEGRO model was used to simulate the baseline and four future climate scenarios for stalk yield for the 2050s. The model was calibrated for the main cultivar currently grown in Brazil based on five field experiments under several soil and climate conditions. The sensitivity of simulated stalk fresh mass (SFM) to air temperature, CO₂ concentration [CO₂] and rainfall was also analyzed. Simulated SFM responses to [CO₂], air temperature and rainfall variations were consistent with the literature. There were increases in simulated SFM and water usage efficiency (WUE) for all scenarios. On average, for the current sugarcane area in the State of São Paulo, SFM would increase 24 % and WUE 34 % for rainfed sugarcane. The WUE rise is relevant because of the current concern about water supply in southern Brazil. Considering the current technological improvement rate, projected yields for 2050 ranged from 96 to 129 t?ha^?1, which are respectively 15 and 59 % higher than the current state average yield.     

RCP情景下内蒙古黄河流域径流预估及其对水资源的影响

根据内蒙古黄河流域内72个国家气象站观测的1961—2005年和区域气候模式CCLM模拟的1961—2100年的气温和降水数据,采用BP人工神经网络模型,预估分析3种RCP情景下头道拐水文站2011—2100年流量变化,评估未来气候变化对流域水资源的可能影响。结果表明:①2011—2100年内蒙古黄河流域气温升高,降水变化不明显,年平均流量呈减少趋势,RCP2.6、RCP4.5和RCP8.5情景分别减少3.6%、2.7%和23.4%。②未来春季流量以增加为主;夏季在不同情景的变化趋势不一致;秋季在21世纪50年代前以增加为主,之后以减少为主;冬季则以减少为主。③未来流域可利用水资源呈减少趋势,尤其夏季水资源的供需矛盾加剧,以及径流季节分配发生变化,可能产生更大的春季径流。     

Future Climate Impact on the Productivity of Sugar Beet (Beta vulgaris L.) in Europe

The impact of future climate change on sugar beet yields is assessed over western Europe using future (2021–2050) climate scenario data from a General Circulation Model (GCM) and the Broom's Barn simulation model of rain-fed crop growth and yield. GCM output for the 1961–1990 period is first compared with observed climate data and shown to be reliable for regions west of 24° E. Comparisons east of this meridian were less reliable with this GCM (HadCM2) and so were omitted from simulations of crop yield. Climate change is expected to bring yield increases of around 1 t/ha of sugar in northern Europe with decreases of a similar magnitude in northern France, Belgium and west/central Poland, for the period 2021–2050. Averaged for the study area (weighted by current regional production), yields show no overall change due to changed climate. However, this figure masks significant increases in yield potential (due to accelerated growth in warmer springs) and in losses due to drought stress. Drought losses are predicted to approximately double in areas with an existing problem and to become a serious new problem in NE France and Belgium. Overall west and central Europe simulated average drought losses rise from 7% (1961–1990) to 18% (2021–2050). The annual variability of yield (as measured by the coefficient of variation) will increase by half, from 10% to 15% compared to 1961–1990, again with potentially serious consequences for the sugar industry. The importance of crop breeding for drought tolerance is further emphasised. These changes are independent of the 9% yield increase which we estimate, on the basis of work by Demmers-Derks et al. (1998), is the likely direct effect of the increase in atmospheric CO₂ concentration by 2021–2050.     

气候变化背景下中国小麦需水量的敏感性研究

利用CROPWAT作物模型模拟分析了过去50年（1961-2010年）及IPCC RCPs情景下未来2020年代（2020-2029年）中国小麦需水量的变化情况。在此基础上,以小麦需水量的变化率作为敏感性因子,对RCP4.5和RCP8.5排放情景下中国小麦需水量的敏感性进行了探讨。结果表明：中国小麦多年平均需水量约为1056.4亿m³,最高值位于黄淮海地区。小麦需水量对气候变化的敏感性存在空间差异,华北和西北地区是小麦需水量的重度和极度敏感区,东北地区以及云贵高原地带是小麦需水量的轻度敏感区,而中国中部及南方部分地区的小麦需水量对气候变化不敏感。不同RCP排放情景下小麦需水量的敏感性分布不同,RCP8.5高排放情景下的小麦需水量敏感性区域比RCP4.5中排放情景下明显扩大,轻度和中度敏感区域扩大尤为明显。     

灌水量和气温对玉米生物耗水及产量的影响

为了掌握玉米适宜灌水量,以石羊河流域武威荒漠生态和农业气象试验站为试验地点,按照常规灌水方式设计玉米全生育期灌水量3 750 m3·hm-2、4 500 m3·hm-2、5 250 m3·hm-2、6 000 m3·hm-24种处理,并按1∶1.5∶1∶1比例分4次灌溉,采用水量平衡法计算玉米不同生育阶段的耗水量,分析研究不同灌水处理对玉米产量的影响。结果表明:在相同气候年景下,不同灌水条件对玉米发育期影响不明显;在玉米生物耗水过程中,气温升高耗水量增加,气温升高1℃,耗水量增加124mm;玉米全生育期耗水量呈抛物线变化,峰值出现在拔节至抽雄期间,此期间也正是耗水量影响玉米产量最敏感的时期,期间耗水量每增加1 mm,玉米产量增加0.33 kg·hm-2;不同灌水处理情景下,水分利用率以灌水量为5 250 m3·hm-2最高,可达34.7 kg·hm-2·mm-1,故该灌水量可视为当地适宜灌水量。     

The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios

This paper presents a preliminary assessment of the relative effects of rate of climate change (four Representative Concentration Pathways - RCPs), assumed future population (five Shared Socio-economic Pathways - SSPs), and pattern of climate change (19 CMIP5 climate models) on regional and global exposure to water resources stress and river flooding. Uncertainty in projected future impacts of climate change on exposure to water stress and river flooding is dominated by uncertainty in the projected spatial and seasonal pattern of change in climate. There is little clear difference in impact between RCP2.6, RCP4.5 and RCP6.0 in 2050, and between RCP4.5 and RCP6.0 in 2080. Impacts under RCP8.5 are greater than under the other RCPs in 2050 and 2080. For a given RCP, there is a difference in the absolute numbers of people exposed to increased water resources stress or increased river flood frequency between the five SSPs. With the ‘middle-of-the-road’ SSP2, climate change by 2050 would increase exposure to water resources stress for between approximately 920 and 3,400 million people under the highest RCP, and increase exposure to river flood risk for between 100 and 580 million people. Under RCP2.6, exposure to increased water scarcity would be reduced in 2050 by 22-24 %, compared to impacts under the RCP8.5, and exposure to increased flood frequency would be reduced by around 16 %. The implications of climate change for actual future losses and adaptation depend not only on the numbers of people exposed to changes in risk, but also on the qualitative characteristics of future worlds as described in the different SSPs. The difference in ‘actual’ impact between SSPs will therefore be greater than the differences in numbers of people exposed to impact.     

2021—2050年河南省夏玉米净灌溉需水量对气候变化的响应

基于河南省17个气象站点观测资料和25个CMIP5模式预估数据,采用BCC/RCG-WG 3.0天气发生器构建区域气候变化情景,集合评估了RCP4.5情景下2021—2050年夏玉米净灌溉需水量较1961—2000年的变化及其空间分布。结果表明：全生育期内气温升高1.8℃,降水增加3.6%,引起作物需水量和有效降水量分别增加5.1%和1.5%,净灌溉需水量增加5.6%。受气温升高和降水减少的双重影响,播种－拔节期净灌溉需水量增幅较大,达到21.3%;拔节－乳熟期尽管有效降水量增加3.0%,但这并不足以抵消气温升高引起的作物需水量增加5.1%的影响,净灌溉需水量仍然增加3.4%;乳熟－成熟期,由于有效降水量增加8.2%,超过了作物需水量增加7.4%的影响,净灌溉需水量减少1.4%。豫西三门峡、孟津和豫西南栾川、西峡等4站在各生育期内净灌溉需水量均有不同程度的增加。     

Temperature variations and rice yields in China: historical contributions and future trends

Temperature is the principal factor that determines rice growth, development and ultimately grain yield. In this study, normal growing-degree-days (NGDD) and killing growing-degree-days (KGDD) were used to capture the different effects of normal and extreme temperatures on rice yields, respectively. Based on these indexes, we assessed the contributions of temperature variations to county-level rice yields across China during the historical period (1980–2008), and estimated the potential exposure of rice to extreme temperature stress in the near future (2021–2050). The results showed that historical temperature variations had measurable impacts on rice yields with a distinct spatial pattern: for different regions, such variations had contributed much to the increased rice yields in Northeast China (Region I) (0.59 % yield year^?1) and some portions of the Yunnan-Guizhou Plateau (Region II) (0.34 % yield year^?1), but seriously hindered the improvements of rice yields in the Sichuan Basin (SB) (?0.29 % yield year^?1) and the southern cultivation areas (Region IV) (?0.17 % yield year^?1); for the entire country, half of the contributions were positive and the other half were negative, resulting in a balance pattern with an average of 0.01 % yield year^?1. Under the RCP8.5 scenario, climate warming during 2021–2050 would substantially reduce cold stress but increase heat stress in the rice planting areas across China. For the future period, Region I, II and eastern China would be continually exposed to more severe cold stress than the other regions; Region III (including SB and the mid-lower reaches of Yangtze River (MLRYR)) would be the hot spot of heat stress.