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1.
国外作物模型区域应用研究进展   总被引：30，自引：2，他引：30  
文章针对目前作物模拟模型从单点和田间尺度应用于更大区域尺度的问题，介绍了诸如模型数据标准化，模块化建模，作物模型和天气发生器结合，作物模拟和地理信息系统结合，作物模型与遥感技术结合，区域升尺度连接，基于Web的建模等作物模型区域化应用中技术问题及当前作物模型区域应用的研究进展。  相似文献   

2.
采用EFAST方法和SCE-UA算法优化WheatSM模型参数,采用区域模拟和单站插值的方法对2013—2017年鹤壁市冬小麦各发育期日数和产量进行模拟修订,为WheatSM作物模型在豫北地区的业务应用提供参考。研究发现:区域模拟方法对鹤壁地区冬小麦生育期开始日期的模拟效果除出苗期、越冬期的外,其他均好于单点插值方法的。单点插值方法对越冬期的模拟效果明显好于区域模拟方法的。冬小麦产量的模拟效果区域模拟方法也比单点插值方法好,但两种结果的相对误差均较大。通过对WheatSM模型得到的冬小麦气象产量模拟结果进行修订,可以明显提高模型产量模拟结果。2013—2017年鹤壁地区模拟产量的误差为-17. 92%～-2. 98%,RMSE为1114. 9 kg/hm~2,NMSE为12. 59,模拟效果较好。利用区域模拟方法可以对区域内单个站点的冬小麦生长发育和产量进行模拟,但对越冬期开始时间的模拟需要参考单点插值方法的相应结果。  相似文献   

3.
基于遥感信息的华北冬小麦区域生长模型及模拟研究   总被引：21，自引：1，他引：21  
卫星遥感估产和作物生长模拟在作物监测和产量预测方面有各自不可替代的优势。但是,遥感估产难以揭示作物生长发育和产量形成的内在机理,作物模拟在区域应用时初始值的获取和参数的区域化遇到很多困难。如何利用二者的互补性使其相互结合受到人们关注。该文在Wofost模型本地化和区域化的基础上,首次利用同化法的思路探讨了MODIS遥感信息与华北冬小麦生长模拟模型结合的可行性和方法,初步建立了潜在生产水平(水分适宜条件)下区域遥感-作物模拟框架模型(WSPFRS模型)。模拟结果显示:WSPFRS模型对区域尺度的出苗期重新初始化后,模拟的开花期、成熟期空间分布的准确性比Wofost模拟结果有所改进;利用遥感信息对区域尺度上返青期生物量重新初始化后,模拟贮存器官干重的空间分布更接近实际单产的分布,贮存器官干重的高值区与实际高产区基本相符。该研究将为下一步实际水分供应条件下基于遥感信息的冬小麦区域生长模拟研究奠定了基础。  相似文献   

4.
不同物候模型对作物发育期模拟的对比分析   总被引：1，自引：0，他引：1       下载免费PDF全文
作物发育期预报在农业气象业务中具有重要意义。通过比较4种作物发育期模型的模拟效果,为中国东北地区作物发育期预报提供参考。基于东北地区玉米、水稻和大豆的发育期观测数据及其对应的气象资料,利用模拟退火算法估算了4个发育期模型的参数值,并对模型进行内外部验证。结果表明：在参数本地化过程中,高亮之模型和沈国权模型的效果较好,均方根误差平均分别为3.31d和3.72d。在模型验证过程中,沈国权模型的模拟效果较好,均方根误差平均为5.22d,因此,相对而言,沈国权模型对作物发育期模拟效果较好。  相似文献   

5.
利用作物模型提取小麦干热风灾损方法探讨   总被引：2，自引：0，他引：2  
如何将干热风灾害对小麦造成的产量损失从全部产量损失中提取出来,是目前小麦干热风研究的一个难点.根据小麦生物学特性以及产量结构与干热风发生规律的关系,构建了小麦作物模型,并利用河南省1981-2004年气象资料与小麦产量资料对模型进行了分析与验证.结果表明:利用作物模型方法得到的小麦产量损失与传统方法得到的产量损失相近,两者的标准均方根误差(NRMSE)为0.36,平均准确率为68.69％,决定系数(R2)为0.81.这表明利用小麦作物模型来提取干热风灾损是可行的,可以用于干热风非典型年份的灾害产量损失计算.  相似文献   

6.
王石立  马玉平 《气象》2008,34(6):3-10
近年来我国农业气象科研和业务部门紧密结合,开展了作物生长模拟模型应用于农业气象业务的研究和应用试验工作.基于国外作物生长模拟模型的应用进展以及我国农业气象业务的现状,简要分析了农业气象业务中应用作物生长模拟模型的必要性和紧迫性.针对单点理论模型能否在业务中应用的疑惑,详细讨论了国外引进作物生长模型的本地化和单点理论模型在区域尺度上模拟应用等两个关键问题的重要性和技术方法.重点介绍了近年来我国气象系统农业气象科研和业务部门在推进作物生长模拟模型在农业气象业务应用方面所做的工作,即基于东北玉米、华北小麦和江南双季稻生长模型的气象条件影响评价和产量动态预测方法等.最后从改进完善作物生长模拟模型、探讨区域模拟应用技术及稳健推进业务应用和实施等方面分析了目前存在和出现的问题,以及可能的解决途径.  相似文献   

7.
利用黑龙江省1961～2003年逐日气象资料,采用世界粮食研究模型(WOFOST)和气候变化趋势分析的数学方法,分析了气候变化趋势对小麦产量变化趋势的影响.在黑龙江省中部、东部和北部相对湿润的小麦种植区域,辐射量降低趋势是小麦模拟产量降低趋势的主要气候原因;在松嫩平原西南部的齐齐哈尔市、大庆市和哈尔滨市,降水量增加的趋势是小麦模拟产量增加趋势的主要气候原因;在西北部的北安、五大连池、克山和克东4县,辐射量增加趋势是小麦模拟产量增加趋势的主要气候原因;黑龙江省小麦模拟产量变化趋势百分率的平均值为-1.57%/10a.  相似文献   

8.
大气季节内振荡的数值模拟比较研究   总被引：13，自引：0，他引：13  
李崇银  贾小龙  董敏 《气象学报》2006,64(4):412-419
用国内外两个较好的大气环流模式、在观测海表温度的强迫下进行了长时间(1978—1989年)的数值积分,然后对数值模拟结果与NCAR/NCEP再分析资料进行比较分析,其结果清楚表明,模式模拟结果的均方根误差中有30%—40%是来自于模拟的大气季节内振荡的均方根误差。尤其是,大气季节内振荡模拟的均方根误差的分布形势与总的均方根误差的分布形势几乎完全一致。对热带地区大气季节内振荡动能的模拟结果与NCAR/NCEP再分析资料的比较分析表明,其差异也十分明显,说明模式对热带大气季节内振荡的模拟能力也还比较差。因此可以认为,大气季节内振荡在天气气候模拟中极为重要,而如何在数值模式中模拟好大气季节内振荡还需要进行很好地研究。  相似文献   

9.
为进一步研究WOFOST模型在河南省冬麦区的适用性,以河南省30个农业气象观测站1991—2014年冬小麦观测资料、历史气象资料和土壤资料为依据,对WOFOST模型进行逐站调参和验证,分别建立了30个站的冬小麦模型参数。其中1991—2010年为模型调参年份,2011—2014年为模型验证年份。各站开花期和成熟期调参模拟的归一化均方根误差NRMSE分别小于5%和3%,验证误差分别为3.7%和2.9%。除潢川和固始外,模型对其余各站产量模拟的归一化均方根误差NRMSE全省各站均小于20.0%,验证误差全省平均为15.2%,大部分站点观测值和模拟值相关系数r通过了显著检验。利用调参后的模型模拟2011—2014年冬小麦生长动态变化可知,模拟地上部总干物重与实测单株干物重、模拟LAI与单株叶面积有较一致的变化趋势,拟合度较高。因此,WOFOST模型对河南省冬小麦主要发育阶段、产量及干物质积累模拟能力较强,具有良好的应用前景。  相似文献   

10.
在内蒙古东南部地区引入成熟的作物模型并进行适应性验证,可为模型区域化应用提供研究依据。文章基于内蒙古东南部地区田间试验数据、农业气象观测数据结合同期气象数据和土壤数据,利用"试错法"对WOFOST模型参数进行了调试,对WOFOST模型发育期、叶面积指数及各器官生物量、产量等的模拟能力进行了验证。结果表明,模型对玉米发育期模拟较好,抽雄期和成熟期的模拟误差在6d以内,其中对抽雄期的模拟效果更好,在3d左右;模型对生育期内叶面积指数和各器官模拟良好,实测值和模型值的决定系数R2较高,均通过显著性检验,模拟各器官生物量和产量的均方根误差(RMSE)在641～1414kg·hm-2,其中模拟LAI的均方根误差(RMSE)为1.22。通过校准模型参数值,WOFOST模型能够较好地模拟内蒙古东南部地区春玉米生长发育及其生物量的动态积累过程,能够应用于内蒙古东南部地区春玉米生产。  相似文献   

11.
We use the CERES family of crop models to assess the effect of different spatial scales of climate change scenarios on the simulated yield changes of maize (Zea mays L.), winter wheat (Triticum aestivum L.),and rice (Oryza sativa L.) in the Southeastern United States. The climate change scenarios were produced with the control and doubled CO2 runs of a high resolution regional climate model anda coarse resolution general circulation model, which provided the initial and lateral boundary conditions for the regional model. Three different cases were considered for each scenario: climate change alone, climate change plus elevated CO2, and the latter with adaptations. On the state level,for most cases, significant differences in the climate changed yields for corn were found, the coarse scale scenario usually producing larger modeled yield decreases or smaller increases. For wheat, however, which suffered large decreases in yields for all cases, very little contrast in yield based on scale of scenario was found. Scenario scale resulted in significantly different rice yields, but mainly because of low variability in yields. For maize the primary climate variable that explained the contrast in the yields calculated from the two scenarios is the precipitation during grain fill leading to different water stress levels. Temperature during vernalization explains some contrasts in winter wheat yields. With adaptation, the contrasts in the yields of all crops produced by the scenarios were reduced but not entirely removed. Our results indicate that spatial resolution of climate change scenarios can be an important uncertainty in climate change impact assessments, depending on the crop and management conditions.  相似文献   

12.
India is predicted to be one of the most vulnerable agricultural regions to future climate changes. Here, we examined the sensitivity of winter cropping systems to inter-annual climate variability in a local market and subsistence-based agricultural system in central India, a data-rich validation site, in order to identify the climate parameters to which winter crops – mainly wheat and pulses in this region – might be sensitive in the future. We used satellite time-series data to quantify inter-annual variability in multiple climate parameters and in winter crop cover, agricultural census data to quantify irrigation, and field observations to identify locations for specific crop types. We developed three mixed-effect models (250 m to 1 km scale) to identify correlations between crop cover (wheat and pulses) and twenty-two climate and environmental parameters for 2001-2013. We find that winter daytime mean temperature (November–January) is the most significant factor affecting winter crops, irrespective of crop type, and is negatively associated with winter crop cover. With pronounced winter warming projected in the coming decades, effective adaptation by smallholder farmers in similar landscapes would require additional strategies, such as access to fine-scale temperature forecasts and heat-tolerant winter crop varieties.  相似文献   

13.
The first-order or initial agricultural impacts of climate change in the Iberian Peninsula were evaluated by linking crop simulation models to several high-resolution climate models (RCMs). The RCMs provided the daily weather data for control, and the A2 and B2 IPCC scenarios. All RCMs used boundary conditions from the atmospheric general circulation model (AGCM) HadAM3 while two were also bounded to two other AGCMs. The analyses were standardised to control the sources of variation and uncertainties that were added in the process. Climatic impacts on wheat and maize of climate were derived from the A2 scenario generated by RCMs bounded to HadAM3. Some results derived from B2 scenarios are included for comparisons together with impacts derived from RCMs using different boundary conditions. Crop models were used as impact models and yield was used as an indicator that summarised the effects of climate to quantify initial impacts and differentiate among regions. Comparison among RCMs was made through the choice of different crop management options. All RCM-crop model combinations detected crop failures for winter wheat in the South under control and future scenarios, and projected yield increases for spring wheat in northern and high altitude areas. Although projected impacts differed among RCMs, similar trends emerged for relative yields for some regions. RCM-crop model outputs compared favourably to others using European Re-Analysis data (ERA-15), establishing the feasibility of using direct daily outputs from RCM for impact analysis. Uncertainties were quantified as the standard deviation of the mean obtained for all RCMs in each location and differed greatly between winter (wheat) and summer (maize) seasons, being smaller in the latter.  相似文献   

14.
河南省稻麦类作物对气候变化的响应   总被引：4，自引：1，他引：3  
小麦和水稻是世界最重要的粮食作物。利用河南省小麦和水稻的历史观测资料,结合DSSAT-CERES小麦和ORYZA2000水稻模拟模型,分析和模拟河南省稻麦类作物在历史气候变化条件下生育期和产量的变化。结果表明:冬小麦全生育期长度呈缩短趋势,但播种-越冬天数平均每10 a增加1.7 d,开花到乳熟天数平均每10 a增加2-4 d,返青后各生育期均表现出不同程度的提前;水稻各生育期均有不同程度的提前,尤其是拔节期以前,分蘖前的生育期间隔天数以缩短为主,拔节后以延长为主。雨养小麦模拟产量和水氮增产潜力均呈减少趋势;随着播种期的提前,水稻减产趋势逐渐减弱。  相似文献   

15.
Agricultural systems models are essential tools to assess potential climate change (CC) impacts on crop production and help guide policy decisions. In this study, impacts of projected CC on dryland crop rotations of wheat-fallow (WF), wheat-corn-fallow (WCF), and wheat-corn-millet (WCM) in the U.S. Central Great Plains (Akron, Colorado) were simulated using the CERES V4.0 crop modules in RZWQM2. The CC scenarios for CO2, temperature and precipitation were based on a synthesis of Intergovernmental Panel on Climate Change (IPCC 2007) projections for Colorado. The CC for years 2025, 2050, 2075, and 2100 (CC projection years) were super-imposed on measured baseline climate data for 15–17 years collected during the long-term WF and WCF (1992–2008), and WCM (1994–2008) experiments at the location to provide inter-annual variability. For all the CC projection years, a decline in simulated wheat yield and an increase in actual transpiration were observed, but compared to the baseline these changes were not significant (p > 0.05) in all cases but one. However, corn and proso millet yields in all rotations and projection years declined significantly (p < 0.05), which resulted in decreased transpiration. Overall, the projected negative effects of rising temperatures on crop production dominated over any positive impacts of atmospheric CO2 increases in these dryland cropping systems. Simulated adaptation via changes in planting dates did not mitigate the yield losses of the crops significantly. However, the no-tillage maintained higher wheat yields than the conventional tillage in the WF rotation to year 2075. Possible effects of historical CO2 increases during the past century (from 300 to 380 ppm) on crop yields were also simulated using 96 years of measured climate data (1912–2008) at the location. On average the CO2 increase enhanced wheat yields by about 30%, and millet yields by about 17%, with no significant changes in corn yields.  相似文献   

16.
With the continuing warming due to greenhouse gases concentration, it is important to examine the potential impacts on regional crop production spatially and temporally. We assessed China’s potential maize production at 50 × 50 km grid scale under climate change scenarios using modelling approach. Two climate changes scenarios (A2 and B2) and three time slices (2011–2040, 2041–2070, 2071–2100) produced by the PRECIS Regional Climate Model were used. Rain-fed and irrigated maize yields were simulated with the CERES-Maize model, with present optimum management practices. The model was run for 30 years of baseline climate and three time slices for the two climate change scenarios, without and with simulation of direct CO2 fertilization effects. Crop simulation results under climate change scenarios varied considerably between regions and years. Without the CO2 fertilization effect, China’s maize production was predicted to suffer a negative effect under both A2 and B2 scenarios for all time slices, with greatest production decreases in today’s major maize planting areas. When the CO2 fertilization effect is taken into account, production was predicted to increase for rain-fed maize but decrease for irrigated maize, under both A2 and B2 scenarios for most time periods.  相似文献   

17.
Estimates of impact of climate change on crop production could be biased depending upon the uncertainties in climate change scenarios, region of study, crop models used for impact assessment and the level of management. This study reports the results of a study where the impact of various climate change scenarios has been assessed on grain yields of irrigated rice with two popular crop simulation models- Ceres-Rice and ORYZA1N at different levels of N management. The results showed that the direct effect of climate change on rice crops in different agroclimatic regions in India would always be positive irrespective of the various uncertainties. Rice yields increased between 1.0 and 16.8% in pessimistic scenarios of climate change depending upon the level of management and model used. These increases were between 3.5 and 33.8% in optimistic scenarios. At current as well as improved level of management, southern and western parts of India which currently have relatively lower temperatures compared to northern and eastern regions, are likely to show greater sensitivity in rice yields under climate change. The response to climate change is small at low N management compared to optimal management. The magnitude of this impact can be biased upto 32% depending on the uncertainty in climate change scenario, level of management and crop model used. These conclusions are highly dependent on the specific thresholds of phenology and photosynthesis to change in temperature used in the models. Caution is needed in using the impact assessment results made with the average simulated grain yields and mean changes in climatic parameters.  相似文献   

18.
We investigated the effect of two different spatial scales of climate change scenarios on crop yields simulated by the EPIC crop model for corn, soybean, and wheat, in the central Great Plains of the United States. The effect of climate change alone was investigated in Part I. In Part II (Easterling et al., 2001) we considered the effects ofCO2 fertilization effects and adaptation in addition to climate change. The scenarios were formed from five years of control and 2 ×CO2 runs of a high resolution regional climate model (RegCM) and the same from an Australian coarse resolution general circulation model (GCM), which provided the initial and lateral boundary conditions for the regional model runs. We also investigated the effect of two different spatial resolutions of soil input parameters to the crop models. We found that for corn and soybean in the eastern part of the study area, significantly different mean yield changes were calculated depending on the scenario used. Changes in simulated dryland wheat yields in the western areas were very similar, regardless of the scale of the scenario. The spatial scale of soils had a strong effect on the spatial variance and pattern of yields across the study area, but less effect on the mean aggregated yields. We investigated what aspects of the differences in the scenarios were most important for explaining the different simulated yield responses. For instance, precipitation changes in June were most important for corn and soybean in the eastern CSIRO grid boxes. We establish the spatial scale of climate changescenarios as an important uncertainty for climate change impacts analysis.  相似文献   

19.
小麦和水稻是世界最重要的粮食作物。利用河南省小麦和水稻的历史观测资料,结合DSSAT-CERES 小麦和ORYZA2000水稻模拟模型,分析和模拟河南省稻麦类作物在历史气候变化条件下发育期和产量的变化。结果表明：冬小麦全育期长度呈缩短趋势,但播种-越冬天数平均每10年增加1.7天,开花到乳熟天数平均每10年增加2-4天,返青后各发育期均表现出不同程度的提前;水稻各发育期均有不同程度的提前,尤其是拔节期以前,分蘖前的发育期间隔天数以缩短为主,拔节后以延长为主。雨养小麦模拟产量和水氮增产潜力均呈减少趋势;随着播种期的提前,水稻减产趋势逐渐减弱。  相似文献   

20.
We analyze a set of nine regional climate model simulations for the period 1961–2000 performed at 25 and 50 km horizontal grid spacing over a European domain in order to determine the effects of horizontal resolution on the simulation of precipitation. All of the models represent the seasonal mean spatial patterns and amount of precipitation fairly well. Most models exhibit a tendency to over-predict precipitation, resulting in a domain-average total bias for the ensemble mean of about 20% in winter (DJF) and less than 10% in summer (JJA) at both resolutions, although this bias could be artificially enhanced by the lack of a gauge correction in the observations. A majority of the models show increased precipitation at 25 km relative to 50 km over the oceans and inland seas in DJF, JJA, and ANN (annual average), although the response is strongest during JJA. The ratio of convective precipitation to total precipitation decreases over land for most models at 25 km. In addition, there is an increase in interannual variability in many of the models at 25 km grid spacing. Comparison with gridded observations indicates that a majority of models show improved skill in simulating both the spatial pattern and temporal evolution of precipitation at 25 km compared to 50 km during the summer months, but not in winter or on an annual mean basis. Model skill at higher resolution in simulating the spatial and temporal character of seasonal precipitation is found especially for Great Britain. This geographic dependence of the increased skill suggests that observed data of sufficient density are necessary to capture fine-scale climate signals. As climate models increase their horizontal resolution, it is thus a key priority to produce high quality fine scale observations for model evaluation.  相似文献   

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