Impacts of a Ghg-Induced Climate Change on Crop Yields: Effects of Acceleration in Maturation, Moisture Stress and Optimal Temperature

The present study involves using the Canadian Climate Centre (CCC) climate change scenario to evaluate the impacts of a CO₂-induced climate change on agriculture in Québec and vicinity. Climate change using the CCC General Circulation Model (GCM) data are fed into a crop model (FAO) so as to gauge the changes in agroclimatic factors such as growing season length and growing degree days, and subsequently potential yield changes for a variety of cereal (C₃ and C₄), leguminous, oleaginous, vegetable and special crops, for twelve major agricultural regions in southern Québec. Our results show that depending upon the agricultural zone and crop type, yields may increase (ex. corn and sorghum by 20%) or decrease (ex. wheat and soybean by 20 to 30%). Also, these crop yield changes appear to be related to acceleration in maturation rates, mainly to change in moisture stress and to shifts in optimal thermal growth conditions. These possible shifts in agricultural production potentials would solicit the formulation of appropriate adaptation strategies.     

基于冬小麦农业气候分区的WOFOST模型参数标定

以1981—2010年河南省113个气象观测站影响冬小麦生长及产量形成的主要气象因素为区划指标,利用K均值聚类算法,将河南省划分为5个农业气候生态区。根据2013—2017年地面农业气象观测数据,利用Sobol全局敏感性分析方法,各分区选择总敏感指数大于0.01的作物参数,得到9种敏感参数。以产量与叶面积指数为代价函数,采用差分进化马尔科夫链蒙特卡洛方法对敏感参数进行分区标定,并使用2018—2019年观测数据进行验证。结果表明:分区进行参数标定时,叶面积指数动态模拟精度和产量模拟精度均显著优于使用默认参数或整个研究区使用同一套优化参数时的精度,其中,使用分区调参后验平均值模拟关键生育期叶面积指数的总均方根误差为0.655,其模拟产量的均方根误差为672.016 kg·hm-2。该方法将农业气候学知识与差分进化马尔科夫链蒙特卡洛优化算法相结合,通过合理、高效地分区域标定作物模型参数,可为作物模型区域应用和模型参数调整优化提供科学依据。     

Assessing Winter Wheat Responses to Climate Change Scenarios: A Simulation Study in the U.S. Great Plains

Hard red winter wheat (Triticum aestivum L.) is a major crop in the Great Plains region of the U.S. The goal of this assessment effort was to investigate the influence of two contrasting global climate change projections (U.K. Hadley Center for Climate Prediction and Research and Canadian Centre for Climate Modelling and Analysis) on the yield and percent kernel nitrogen content of winter wheat at three locations in Nebraska. These three locations represent sub-humid and semi arid areas and the transition between these areas and are also representative of major portions of the winter wheat growing areas of the central Great Plains. Climate scenarios based on each of the projections for each location were developed using the LARS-WG weather generator along with data from automated weather stations. CERES-Wheat was used to simulate the responses for two contrasting cultivars of wheat using two sowing dates. The first sowing date represented current sowing dates appropriate for each location. The second sowing date was later and represents the approximate date when the mean air temperature from the climate scenarios is the same as the mean air temperature from the actual climate data at the current sowing dates. The yield and percent kernel nitrogen content using the two climate scenarios generally decrease going from the sub-humid eastern to the semi arid western parts of Nebraska. Results from these simulations indicate that yield and percent kernel nitrogen content using the two climate scenarios could not both be maintained at levels currently simulated. Protein content (directly related to kernel nitrogen content) and end-use quality are the primary determinants for the use of hard red winter wheat in baked goods. Nitrogen management and new cultivars, which can enhance the uptake and translocation of nitrogen, will be proactive steps to meet the challenges of global climate change as represented by these climate scenarios.     

Modeling climate change and biophysical impacts of crop production in the Austrian Marchfeld Region

Climate change affects major biophysical processes in agricultural crop production (e.g. evaporation of plants and soils, nutrient cycles, and growth of plants). This analysis aims to assess some of these effects by simulating regional climate projections that are integrated in the biophysical process model EPIC (Environmental Policy Integrated Climate). Statistical climate models have been developed for six weather parameters based on daily weather records of a weather station in the Austrian Marchfeld region from 1975 to 2006. These models have been used to estimate daily weather parameters for the period 2007–2038. The resulting projections have been compared to climate scenarios provided from the TYNDALL Centre for Climate Change Research, which are based on General Circulation Models (GCMs). The comparison indicates some differences, namely a smaller temperature increase and a higher precipitation amount in the TYNDALL data. Both climate datasets have been used to simulate impacts of climate change on crop yields, topsoil organic carbon content, and nitrate leaching with EPIC and thus to perform a sensitivity analysis of EPIC. Yield impacts have been assessed for four simulated crops, i.e. 6.2?t/ha for winter wheat for statistical climate projections compared to 5.7?t/ha for TYNDALL scenarios, 10.6?t/ha for corn compared to 10.5?t/ha, 3.9?t/ha for sunflower compared to 3.7?t/ha, and 4.5?t/ha for spring barley compared to 4.3?t/ha—all values as an average over the period 2007–2038. Smaller differences have been simulated for topsoil organic carbon content i.e. 55.1?t/ha for the statistical climate projections compared to 55.3?t/ha for the TYNDALL scenarios and nitrate leaching i.e. 7.1?kg/ha compared to 11.1?kg/ha. All crop yields as well as topsoil organic carbon content and nitrate leaching show highest sensitivity to temperature and solar radiation.     

Precipitation extremes in a karst region: a case study in the Guizhou province, southwest China

The topography of hilly landscapes modifies crop environment changing the fluxes of water and energy, increasing risk in these vulnerable agriculture systems, which could become more accentuated under climate change (drought, increased variability of rainfall). In order to quantify how wheat production in hilly terrain will be affected by future climate, a newly developed and calibrated micro-meteorological model for hilly terrain was linked to a crop growth simulation model to analyse impact scenarios for different European regions. Distributions of yield and growing length of rainfed winter wheat and durum wheat were generated as probabilistic indices from baseline and low (B2) and high (A2) emission climate scenarios provided from the Hadley Centre Regional Climate Model (HadRM3). We used site-specific terrain parameters for two sample catchments in Europe, ranging from humid temperate (southeast UK) to semi-arid Mediterranean (southern Italy). Results for baseline scenario show that UK winter wheat is mainly affected by annual differences in precipitation and yield distributions do not change with terrain, whilst in the southern Mediterranean climate yield variability is significantly related to a slope × elevation index. For future climate, our simulations confirm earlier predictions of yield increase in the UK, even under the high emission scenario. In the southern Mediterranean, yield reduction is significantly related to slope × elevation index increasing crop failure in drier elevated spots but not in wet years under baseline weather. In scenarios for the future, the likelihood of crop failure rises sharply to more than 60%, and even in wet years, yields are likely to decrease in elevated spots.     

Assessment of future olive crop yield by a comparative evaluation of drought indices: a case study in western Turkey

A comparative performance analysis was studied on well-known drought indices (Standardized Precipitation Index, Palmer Drought Severity Index (PDSI) and its moisture anomaly index (Orig-Z), and self-calibrated Palmer Drought Severity Index (SC-PDSI) and its moisture anomaly index (SC-Z)) to determine the most appropriate index for assessing olive (O. europaea L.) yield for oil in seven crop regions (Mu?la, Ayd?n, ?zmir, Manisa, Bal?kesir, ?anakkale, and Bursa) in western Turkey and to evaluate the vulnerability of olive yield for oil to climate change with future projections provided by the Hadley Centre for Climate Prediction and Research ENSEMBLES project (HadCM3Q0). A series of curvilinear regression-based crop yield models were developed for each of the olive-growing regions based on the drought indices. The crop yield model that performed the best was the SC-PDSI model in Mu?la, Ayd?n, ?zmir, and Manisa regions and the PDSI model in ?anakkale, Bal?kesir, and Bursa regions. The SC-PDSI index-based model described 65%, 62%, 61%, and 62% of the measured variability of olive yield in Mu?la, Ayd?n, ?zmir, and Manisa regions, respectively. The PDSI index-based model explained 59%, 58%, and 64% of the measured variability of olive yield in Bal?kesir, ?anakkale, and Bursa regions, respectively. The vulnerability of the olive yield for oil to HadCM3Q0 future climate projections was evaluated for Ayd?n and ?anakkale regions due to the resolution of the regional climate model. In terms of the future scenarios, the expected decrease in olive yield residuals was 2.5?ton (10³ trees)^?1 and 1.78?ton (10³ trees)^?1 in Ayd?n and ?anakkale regions, respectively.     

Influence d'un changement climatique dû à une hausse de gaz à effet de serre sur l'agriculture au quebec

Abstract

This study, using a climate change scenario generated by the Canadian Climate Centre (CCC) general circulation model (GCM) examines the impacts of such a climate change on agriculture in southern Quebec. Using a crop model from the Food and Agriculture Organization (FAO), yield responses of a variety of cereals, legumes, oleaginous and special crops to climate change are analysed and discussed.

Results show that under the 2 × CO₂ climate scenario the growing season would be longer and accumulation of corn heat units and growing degree days would be more important than under actual climate (1961–1990). One of the more important results of this study is that, on the one hand yield of C₃ cereals would be lower and that of C₄ cereals higher in most agricultural regions. On the other hand, the direct fertilisation effect of increased CO₂ is not considered. It must be cautioned however that we can not generalise results obtained for one legume crop to all legumes.     

近30年我国气候变化的不稳定性及其与农业生产的关系

引入信息论中熵值分析方法，利用全国七大区１９６１－１９９０年的气象和产量资料，讨论了近年平均气温，最高气温，最低气温和降水量的熵值时空变化类型。详细分析了我国气候变化的不稳定性，在此基础上，定性讨论了气候波动与农业气象灾害的关系及其对农业产量的影响，并分区建立了产量与气象要素熵的回归模型。     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

As carbon dioxide and other greenhouse gasses accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how a changing climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the General Circulation Model (GCM)-derived climate change projections, described in Part 1, to drive the crop production and water resource models EPIC (Erosion Productivity Impact Calculator) and HUMUS (Hydrologic Unit Model of the United States). These models are described and validated in this paper using historical crop yields and streamflow data in the conterminous United States in order to establish their ability to accurately simulate historical crop and water conditions and their capability to simulate crop and water response to the extreme climate conditions predicted by GCMs. EPIC simulated grain and forage crop yields are compared with historical crop yields from the US Department of Agriculture (USDA) and with yields from agricultural experiments. EPIC crop yields correspond more closely with USDA historical county yields than with the higher yields from intensively managed agricultural experiments. The HUMUS model was validated by comparing the simulated water yield from each hydrologic basin with estimates of natural streamflow made by the US Geological Survey. This comparison shows that the model is able to reproduce significant observed relationships and capture major trends in water resources timing and distribution across the country.     

Effects of changes in temperature and CO2 concentration on simulated spring wheat yields in The Netherlands

A crop growth simulation model based on SUCROS87 was constructed to study the effects of temperature rise and increase of the atmospheric CO₂ concentration on spring wheat yields in The Netherlands. The model simulated potential production (limited by crop characteristics, temperature and radiation but without any stress from water or nutrient shortages or pests, diseases and weeds) and water-limited production in which growth is also limited by water shortage. The model was validated for the present climatic conditions. When daily weather data from a nearby station were used, the model was well able to simulate yields obtained in field experiments.Effects of several combinations of temperature rise and atmospheric CO₂ concentration on simulated yields were studied. A temperature rise resulted in a reduction in simulated yield due to shortening of the growing period. Large variations existed in the magnitude of this reduction. Increases in atmospheric CO₂ concentration led to yield increases due to higher assimilation rates and to increase of the water use efficiency. Combination of temperature rise and higher CO₂ concentration resulted in small yield increases in years in which water was not limiting growth and large yield increases in dry years.Change of variety or of sowing date could not reduce the negative effects of temperature rise on simulated yields.     

Assessment of climate variability and trend on wheat productivity in West Bengal,India: crop growth simulation approach

Wheat is the second important cereal crop after rice in West Bengal. During last three decades, due to climate fluctuations and variability, the productivity of this crop remains almost constant, bringing the threat of food security of this State. The objectives of the present study were to assess the trend of climatic variables (rainfall, rainy days, and temperature) over six locations covering five major agro-climatic sub-zones of West Bengal and to estimate the variability of potential, simulated yield using crop simulation model (DSAATv4.5) and the yield gap with actual yield. There were no significant change of rainfall and rainy days in annual, seasonal and monthly scale at all the study sites. In general, the maximum temperature is decreasing throughout West Bengal. Except for Birbhum, the minimum temperature increased significantly in different study sites. District average yield of wheat varied from 1757 kg ha^?1 at Jalpaiguri to 2421 kg ha^?1at Birbhum. The actual yield trend ranged from ??4.7 kg ha^?1 year^?1 at Nadia to 32.8 kg ha^?1 year^?1 at Birbhum. Decreasing trend of potential yield was observed in Terai (Jalpaiguri), New Alluvial Zone (Nadia) and Coastal saline zone (South 24 Parganas), which is alarming for food security in West Bengal.     

Potential impact of climate change on durum wheat cropping in Tunisia

The potential effect of climate change on durum wheat in Tunisia is assessed using a simple crop simulation model and a climate projection for the 2071–2100 period, obtained from the Météo-France ARPEGE-Climate atmospheric model run under the IPCC (International Panel on Climate Change) scenario A1B. In the process-oriented crop model, phenology is estimated through thermal time. Water balance is calculated on a daily basis by means of a simple modelling of actual evapotranspiration involving reference evapotranspiration, crop coefficients and some basic soil characteristics. The impact of crop water deficit on yield is accounted for through the linear crop-water production function developed by the FAO (Food and Agriculture Organization of the United Nations). Two stations are chosen to study the climate change effect. They are representative of the main areas where cereals are grown in Tunisia: Jendouba in the northern region and Kairouan in the central region. In the future scenario, temperature systematically increases, whereas precipitation increases or decreases depending on the location and the period of the year. Mean annual precipitation declines in Jendouba and raises in Kairouan. Under climate change, the water conditions needed for sowing occur earlier and cycle lengths are reduced in both locations. Crop water deficit and the corresponding deficit in crop yield happen to be slightly lower in Kairouan; conversely, they become higher in Jendouba.     

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.     

Climate Change and People-Caused Forest Fire Occurrence in Ontario

Climate change that results from increasing levels of greenhouse gases in the atmosphere has the potential to increase temperature and alter rainfall patterns across the boreal forest region of Canada. Daily output from the Canadian Climate Centre coupled general circulation model (GCM) and the Hadley Centre's HadCM3 GCM provided simulated historic climate data and future climate scenarios for the forested area of the province of Ontario, Canada. These models project that in climates of increased greenhouse gases and aerosols, surface air temperatures will increase while seasonal precipitation amounts will remain relatively constant or increase slightly during the forest fire season. These projected changes in weather conditions are used to predict changes in the moisture content of forest fuel, which influences the incidence of people-caused forest fires. Poisson regression analysis methods are used to develop predictive models for the daily number of fires occurring in each of the ecoregions across the forest fire management region of Ontario. This people-caused fire prediction model, combined with GCM data, predicts the total number of people-caused fires in Ontario could increase by approximately 18% by 2020–2040 and50% by the end of the 21st century.     

Assessing the impacts of climate change on rice yields in the main rice areas of China

This paper assesses the impact of climate change on irrigated rice yield using B2 climate change scenario from the Regional Climate Model (RCM) and CERES-rice model during 2071--2090. Eight typical rice stations ranging in latitude, longitude, and elevation that are located in the main rice ecological zones of China are selected for impact assessment. First, Crop Estimation through Resource and Environment Synthesis (CERES)-rice model is validated using farm experiment data in selected stations. The simulated results represent satisfactorily the trend of flowering duration and yields. The deviation of simulation within ± 10% of observed flowering duration and ± 15% of observed yield. Second, the errors of the outputs of RCM due to the difference of topography between station point and grid point is corrected. The corrected output of the RCM used for simulating rice flowering duration and yield is more reliable than the not corrected. Without CO₂ direct effect on crop, the results from the assessment explore that B2 climate change scenario would have a negative impact on rice yield at most rice stations and have little impacts at Fuzhou and Kunming. To find the change of inter-annual rice yield, a preliminary assessment is made based on comparative cumulative probability at low and high yield and the coefficient variable of yield between the B2 scenario and baseline. Without the CO₂ direct effect on rice yield, the result indicates that frequency for low yield would increase and it reverses for high yield, and the variance for rice yield would increase. It is concluded that high frequency at low yield and high variances of rice yield could pose a threat to rice yield at most selected stations in the main rice areas of China. With the CO₂ direct effect on rice yield, rice yield increase in all selected stations.     

近43年来黑龙江气候变化对农作物产量影响的模拟研究

从近43年来黑龙江省各地气候变化趋势的角度出发, 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) 和气候变化趋势的数学分析方法, 计算并分析了近43年来黑龙江省各地各主要作物模拟产量变化趋势的空间特征和各地气候要素变化趋势的空间特征, 讨论了气候变化趋势对主要粮食作物模拟产量变化趋势的影响。结果表明:气候变化趋势的空间差异对各主要作物模拟产量变化趋势的空间分布具有重要影响, 但不同作物影响不同。近43年来黑龙江省玉米模拟产量变化趋势增加, 平均增加幅度为4.81%/10a, 气温变化趋势的增高是其模拟产量变化趋势增加的主要气候因素。黑龙江省大豆模拟产量变化趋势总体上呈降低趋势, 平均降低幅度为1.52%/10a;气候变化趋势对北部和南部区域的大豆模拟产量变化趋势作用不同, 气温变化趋势的增高是北部大豆优势种植区域模拟产量变化趋势增加的主要气候因素, 气温和降水量的相应变化趋势是南部大豆种植区域模拟产量变化趋势降低的主要气候因素。     

基于东北玉米区域动力模型的低温冷害预报应用研究

在田间试验资料基础上，采用改进的发育模型和分区作物参数，结合前人有关研究成果建立了东北玉米区域动力模型，并利用模型模拟了12站40年 (1961~2000年) 玉米生长发育过程。确定抽雄期延迟天数为低温冷害指标，分析了历史低温冷害年及减产情况。模拟了典型冷害年和40年气候平均的0.25°×0.25°网格点玉米生长发育过程, 探讨了与区域气候模式结合进行低温冷害预报的方法。主要结论有:①玉米发育模型能够较好地模拟玉米发育期和发育期对低温冷害的响应，以抽雄期延迟天数为冷害指标评估的历史冷害发生状况基本符合历史实况。②模型有一定的模拟玉米生长量对低温冷害响应的能力，但还需要更多的试验数据校正品种参数，完善模型。③利用GIS技术，结合区域化的作物参数运行区域作物模型，是作物模型区域化应用的一种解决方案。④东北玉米区域动力模型解释性好，根据确定的害指标，以区域气候模式输出结果驱动玉米模型可以模拟和预测低温冷害，是农业气象灾害预测预报的一个有益的尝试。     

中国气象科学研究院农业气象研究50年进展

该文在简要回顾20世纪我国农业气象学科发展历程基础上, 重点阐述了50年来中国气象科学研究院在农业气象各主要研究领域, 包括农业气候资源与区划、农业产量气象预测与卫星遥感估产、农业气象灾害、气候变化影响评估、作物生长模拟与模式以及农业气象情报信息服务等所取得的若干重大进展, 并从当前面临的挑战与机遇出发, 探讨了中国气象科学研究院未来发展中在农业气象研究领域的可能热点趋势。     

Influence of Climate Change on Winter Wheat Growth in North China During 1950-2000

1. IntroductionChinese agriculture has undergone tremendousstructural changes over the last decades. The averagestaple crop productivity has doubled in 25 yr while thepopulation increased by 25 % [China Statistical Year-book (CSY), 2003]. Winter wheat is one of China'smost important staple food crops, with a total farm-ing area of nearly 24 million hectares and a produc-tion exceeding 92 million ton in 2002 (CSY, 2003).Although China has been the world's largest wheatproducer since 1983 (…     

East African food security as influenced by future climate change and land use change at local to regional scales

Climate change impacts food production systems, particularly in locations with large, vulnerable populations. Elevated greenhouse gases (GHG), as well as land cover/land use change (LCLUC), can influence regional climate dynamics. Biophysical factors such as topography, soil type, and seasonal rainfall can strongly affect crop yields. We used a regional climate model derived from the Regional Atmospheric Modeling System (RAMS) to compare the effects of projected future GHG and future LCLUC on spatial variability of crop yields in East Africa. Crop yields were estimated with a process-based simulation model. The results suggest that: (1) GHG-influenced and LCLUC-influenced yield changes are highly heterogeneous across this region; (2) LCLUC effects are significant drivers of yield change; and (3) high spatial variability in yield is indicated for several key agricultural sub-regions of East Africa. Food production risk when considered at the household scale is largely dependent on the occurrence of extremes, so mean yield in some cases may be an incomplete predictor of risk. The broad range of projected crop yields reflects enormous variability in key parameters that underlie regional food security; hence, donor institutions’ strategies and investments might benefit from considering the spatial distribution around mean impacts for a given region. Ultimately, global assessments of food security risk would benefit from including regional and local assessments of climate impacts on food production. This may be less of a consideration in other regions. This study supports the concept that LCLUC is a first-order factor in assessing food production risk.