Economic feasibility of adapting crop enterprises to future climate change: a case study of flexible scheduling and irrigation for representative farms in Flathead Valley,Montana, USA

Future climate change directly impacts crop agriculture by altering temperature and precipitation regimes, crop yields, crop enterprise net returns, and net farm income. Most previous studies assess the potential impacts of agricultural adaptation to climate change on crop yields. This study attempts to evaluate the potential impacts of crop producers’ adaptation to future climate change on crop yield, crop enterprise net returns, and net farm income in Flathead Valley, Montana, USA. Crop enterprises refer to the combinations of inputs (e.g., land, labor, and capital) and field operations used to produce a crop. Two crop enterprise adaptations are evaluated: flexible scheduling of field operations; and crop irrigation. All crop yields are simulated using the Environmental Policy Integrated Climate (EPIC) model. Net farm income is assessed for small and large representative farms and two soils in the study area. Results show that average crop yields in the future period (2006–2050) without adaptation are between 7% and 48% lower than in the historical period (1960–2005). Flexible scheduling of the operations used in crop enterprises does not appear to be an economically efficient form of crop enterprise adaptation because it does not improve crop yields and crop enterprise net returns in the future period. With irrigation, crop yields are generally higher for all crop enterprises and crop enterprise net returns increase for the canola and alfalfa enterprises but decrease for all other assessed crop enterprises relative to no adaptation. Overall, average crop enterprise net return in the future period is 45% lower with than without irrigation. Net farm income decreases for both the large and small representative farms with both flexible scheduling and irrigation. Results indicate that flexible scheduling and irrigation adaptation are unlikely to reduce the potential adverse economic impacts of climate change on crop producers in Montana’s Flathead Valley.     

Refining spatial resolution and spillovers of a micro-econometric analysis of adapting portfolios to climate change using the global positioning system

This paper refines the spatial resolution and spillover effects of a micro-econometric analysis of adaptation of agricultural portfolios to climate change using the Global Positioning System (GPS). From the household surveys collected across South America by the World Bank, the GPS recordings of exact farm locations such as latitude, longitude, and altitude are matched with high resolution grid cell climate data from the Climate Research Unit as well as geographically referenced soils and geography data from the Food and Agriculture Organization. The choice of agricultural systems at the farm level is estimated using spatial Logit model and the conditional land value is estimated for each system of agriculture after correcting for selection bias and spatial spillovers. Future choices and land values are simulated using the fine resolution climate scenarios by the UKMO (United Kingdom Meteorological Office) and GISS (Goddard Institute for Space Studies). This paper finds that, under the UKMO HadGEM1 (Hadley Center Global Environmental Model 1) scenario by around 2060, the choices of the specialized systems are expected to fall, but the mixed system would increase. The land value of the crops-only falls by 29 %, but the mixed system land value falls only by 12 %. Under a milder GISS ER (ModelE-R) scenario, the land value of the mixed system increases by 6 %. With full adaptations of agricultural systems, the expected land value falls by 17 %. Without adaptations, the damage increases. This paper demonstrates that adaptation behaviors can be best studied by a fine resolution micro-econometric analysis of agricultural portfolios using the GPS reference.     

Impact of climate change: an empirical investigation of Malaysian rice production

This paper examines the possible impact of climate change on Malaysian rice production. Using the Ricardian Method and farm household data, we have examined the effects on rice producers focusing on sharecropper adaptations and ecological causes. The principle goal of this research paper is to investigate the impact of climate variables such as temperature, rainfall and precipitation on rice production during main and off seasons, in Kedah, Malaysia. The main purpose of this paper is to examine how climate change affects the net income of paddy farmers in the study area. The statistically significant results show that temperature, rainfall, farm size, educational knowledge, land area and value of labour input have an impact on rice production per hectare revealing potential impacts of climate vulnerability on Malaysian agriculture. The results showed that net revenue increased by Ringgit Malaysia (RM 1= $0.3277) 4.78 per hectare throughout the main seasons as a result of minimal increase in the temperature while there is a decrease of RM 3.02 in the net revenue per hectare during off seasons. During the off season, rainfall increased revenue per hectare by RM 1.32 and during the main season it reduced revenue per hectare by RM 1.01. The evidence from this study may be useful for Malaysian policymakers to facilitate greater preventive measures during the main and off-seasons to counteract climate uncertainty and vulnerability.     

Analysis of climate variability in the Manas River Valley,North-Western China (1956–2006)

This paper examines the short-run climate variability (change in the levels of temperature and precipitation) with a focus on the Manas River Valley, North-Western China, over the past 50 years (1956 to 2006) using data collected from four meteorological stations. The results show that the annual mean temperature had a positive trend, with temperature increasing at 0.4 °C per decade. Application of the Mann-Kendall test revealed that the overall positive trend became statistically significant at the p?=?0.95 level only after 1988. The increase in temperature was most marked in winter and spring (0.8 and 0.7 °C per decade, respectively), absent in summer and very small in autumn (0.1 °C per decade). Concerning precipitation, our results indicate a negative but not significant trend for the period between 1956 and 1982, while annual total precipitation tended to increase thereafter and the increase was mainly during the crop growing-season. Concerning variability in temperature and precipitation, the characteristic time scales were identified by application of wavelet analysis. For temperature the quasi-decadal variations were found on time scales between approximately 5 and 15 years, with a peak in wavelet variance on a time scale of 9 years. For precipitation, the most striking features were a precipitation increase (6.7 mm per decade) during the crop growing season. Irregularities and abrupt changes in both temperature and precipitation were more common at scales less than 10 years, indicating the complexity and uncertainty in the short-period climate variability. Possible causes of climate variability in the Manas River Valley may include anthropogenic factors such as intensive human activity and the expansion of both farmland and irrigation. Global climate variability might also have some impacts on the local climate variability; analyses of local and regional climate trends can better inform local adaptation actions for global impacts.     

The macro implications of a complete transformation of U.S. agricultural production to organic farming practices

A national interregional linear programming model of U.S. agriculture is used to evaluate and compare two conventional and three organic production alternatives. The objective is to estimate the effects on production, supply prices, land use, farm income, and export potential, of a complete transformation of U.S. agriculture to organic practices. Crop yields and production costs are estimated for 150 producing regions for seven crops under both conventional and organic methods. Results indicate that compared with conventional methods, widespread organic farming leads to a decrease in total production, lower export potential, higher supply prices, higher value of production, lower costs of production, and higher net farm income. The United States domestic crop demand can be met with organic methods, but would be more expensive. Some interregional shifts in crop production would also occur.     

Pasture diversification to combat climate change impacts on grazing dairy production

Among livestock systems, grazing is likely to be most impacted by climate change because of its dependency to feed quality and availability. In order to reduce the impact of climate change on grazing livestock systems, adaptation measures should be implemented. The goal of this study is to identify the best pasture composition for a representative grazing dairy farm in Michigan in order to reduce the impacts of climate change on production. In order to achieve the goal of this study, three objectives were sought: (1) identify the best pasture composition, (2) assess economic and resource use impacts of pasture compositions under future climate scenarios, and (3) evaluate the resiliency of pasture compositions. A representative farm was developed based on a livestock practices survey and incorporated into the Integrated Farm System Model (IFSM). For the pasture compositions, four cool-season grass species and two legumes were evaluated under both current and future climate scenarios. The effectiveness of adaptation measures based on economic and resource use criteria was evaluated. Overall, the pasture composition with 50% perennial ryegrass (Lolium multiflorum) and 50% red clover (Trifolium pratense) was identified as the best. In addition, the increase in precipitation and temperature of the most intensive climate scenario could significantly improve farm net return per cow (Bos taurus) and whole farm profit while no significant impact was observed on resource use criteria. Finally, the overall sensitivity assessment showed that the most resilient pasture composition under future climate scenarios was ryegrass with red clover and the least resilient was orchardgrass (Dactylis glomerata) with white clover (Trifolium repens).     

玛曲县土地利用/覆盖变化对区域生态系统服务价值的影响

运用GIS和遥感技术分析了玛曲县1975、1990和2005年的土地利用/覆盖特征,在此基础上使用生态价值系数(C)计算出该县生态系统服务价值.结果表明,该区域1975~2005年间生态系统服务价值从129.713亿元减少到123.961亿元,共损失5.75亿元,且损失量和损失幅度呈持续增加趋势;该区域生态系统服务价值中,废物处理价值最高,气候调节价值次之,原材料价值最低,且30年间各服务类型的价值均呈减小趋势;玛曲县1975、1990和2005年人均生态系统服务价值分别为58.96,42.80,29.51万元,表明玛曲县由于人口的增长,环境压力呈持续增大趋势.草地和湿地退化是导致该区域生态系统服务价值减少的主要原因.CS检验说明本研究所选C值较为合理.     

Global evaluation of the effects of agriculture and water management adaptations on the water-stressed population

Fresh water is one of the most important resources required for human existence, and ensuring its stable supply is a critical issue for sustainable development. The effects of a general set of agriculture and water management adaptations on the size of the world’s water-stressed population were assessed for a specific but consistent scenario on socio-economic development and climate change during the 21st century. To maintain consistency with agricultural land use change, we developed a grid-based water supply–demand model integrated with an agro-land use model and evaluated the water-stressed population using a water withdrawals-to-availability ratio for river basins. Our evaluation shows that, if no adaptation options are implemented, the world’s water-stressed population will increase from 1.8 billion in 2000 to about 3.3 billion in 2050, and then remain fairly constant. The population and economic growth rather than climate change will be dominant factors of this increase. Significant increase in the water-stressed population will occur in regions such as North Africa and the Middle East, India, Other South Asia, China and Southeast Asia. The key adaptation options differ by region, depending on dominant crops, increase in crop demand and so on. For instance, ‘improvement of irrigation efficiency’ and ‘enhancement of reclamation water’ seem to be one of important options to reduce the water stress in Southeast Asia, and North Africa and the Middle East, respectively. The worldwide implementation of adaptation options could decrease the water-stressed population by about 5 % and 7–17 %, relative to the scenario without adaptations, in 2050 and 2100, respectively.     

Impacts of climate change on savannah woodland biomass carbon density and water-use: a modelling study of the Sudanese gum belt region

This paper analyzes potential impacts of climate change on biomass carbon (C) density and water-use (actual evapotranspiration, AET) of savannah woodlands in Sudan. Climate change scenarios were developed from five General Circulation Models (GCMs; CGCM2, CSIRO2, ECHam4, HadCM3 and PCM) under two IPCC (Intergovernmental Panel on Climate Change) emission scenarios (A1FI and B1). Baseline (1961-90) climate and climate change scenarios for 2080s for eight map sheet grids (1° latitude x 1.5° longitude) were constructed. Compared to baseline values, mean annual precipitation (MAP) showed both increases (+112 to +221 mm) and decreases (?13 to ?188 mm) but mean annual temperature (MAT) only showed increases (+1.2 to +8.3 °C). Baseline biomass C densities showed an exponential relationship with MAP (y?=?6.798 e ^0.0054x, R²?=?0.70). Depending on climate change MAP, biomass C densities increased (+14 to +241 g C m^?2) or decreased (?1 to ?148 g?C m^?2). However, because of uncertainty in biomass C density estimates, the changes were only significant (P <0.05) for some of the climate change scenarios and for grids with MAP >260 mm. Under A1FI emission scenarios, only HadCM3 did not have a significant effect while under B1 emission scenarios, only CGCM2 and ECHam4 had a significant effect on biomass C density. AET also showed both increases (+100 to +145 mm for vertisols and +82 to +197 mm for arenosols) and decreases (?12 to ?178 mm for vertisols and ?12 to ?132 mm for arenosols). The largest relative changes in AET (up to 31 %) were associated with grids receiving the lowest rainfall. Thus, even if MAP increases across the study region, the increase will have little impact on biomass levels in the driest areas of the region, emphasizing the need for improved management and use of savannah woodlands.     

锡林郭勒草原荒漠化气候因素分析

利用1961-2006年锡林郭勒草原年、季、月降水量、平均气温、沙尘暴日数等气象资料,针对锡林郭勒草原荒漠化的现状进行分析。在气候变暖背景下,研究锡林郭勒草原干旱发生的规律及其成因,分析其带给锡林郭勒草原荒漠化的影响,得到以下结论：1．锡林郭勒草原沙化、荒漠化严重,沙化面积位居内蒙古自治区第一,荒漠化面积位居内蒙古自治区第二。2．锡林郭勒草原春夏季降水趋势存在准25a气候振动,年代际变化特征比较突出。干旱发生的频率较高。3．气候变暖给锡林郭勒草原干旱带来较大的影响。4．沙尘暴频发与干旱相互影响,同时对锡林郭勒草原草场生态资源产生一定的影响。5．生态环境恶化,导致大面积土地资源和生物资源丧失。恶化的生态环境已经影响到了锡林郭勒草原社会经济的发展。     

甘肃省农田水分平衡及其时空分布规律

采用农田水量平衡模型,以县域为基本单元,对甘肃省1961～2001年10种作物逐月天然状态下农田水分平衡时空分布规律进行了研究。结果表明:天然状态下,甘肃省多年平均农田需水量为121.06×10⁸m3;亏水量为43.28×10⁸m3;盈水量为0.62×10⁸m3,降水不能满足作物生长需求。在25%、50%、75%三种降水保证率下,作物的亏水总量分为35.99×10⁸m3、42.93×10⁸m3、49.85×10⁸m3,盈水量分别为0.61×10⁸m3、0.11×10⁸m3、0.00×10⁸m3。农田水分亏缺是甘肃省农田水分平衡的主要特征。对大多数作物而言,亏水量集中于夏季,10种作物夏季亏水总量占全年亏水总量的60.2%。全生育期棉花水分盈亏的稳定性最强,水量盈亏变异系数为6.9%,麻类最差,变异系数高达43.6%。全省天然状态下,农田亏水量由东南向西北、高山向河谷递增,农田盈水量由东南向西北递减,农田水分满足率与农田水分盈亏波动性具有从东南向西北递减的趋势。     

Adaptation to climate change in Ethiopia and South Africa: options and constraints

Climate change is expected to adversely affect agricultural production in Africa. Because agricultural production remains the main source of income for most rural communities in the region, adaptation of the agricultural sector is imperative to protect the livelihoods of the poor and to ensure food security. A better understanding of farmers’ perceptions of climate change, ongoing adaptation measures, and the decision-making process is important to inform policies aimed at promoting successful adaptation strategies for the agricultural sector. Using data from a survey of 1800 farm households in South Africa and Ethiopia, this study presents the adaptation strategies used by farmers in both countries and analyzes the factors influencing the decision to adapt. We find that the most common adaptation strategies include: use of different crops or crop varieties, planting trees, soil conservation, changing planting dates, and irrigation. However, despite having perceived changes in temperature and rainfall, a large percentage of farmers did not make any adjustments to their farming practices. The main barriers to adaptation cited by farmers were lack of access to credit in South Africa and lack of access to land, information, and credit in Ethiopia. A probit model is used to examine the factors influencing farmers’ decision to adapt to perceived climate changes. Factors influencing farmers’ decision to adapt include wealth, and access to extension, credit, and climate information in Ethiopia; and wealth, government farm support, and access to fertile land and credit in South Africa. Using a pooled dataset, an analysis of the factors affecting the decision to adapt to perceived climate change across both countries reveals that farmers were more likely to adapt if they had access to extension, credit, and land. Food aid, extension services, and information on climate change were found to facilitate adaptation among the poorest farmers. We conclude that policy-makers must create an enabling environment to support adaptation by increasing access to information, credit and markets, and make a particular effort to reach small-scale subsistence farmers, with limited resources to confront climate change.     

Projected change in climate thresholds in the Northeastern U.S.: implications for crops, pests, livestock, and farmers

Most prior climate change assessments for U.S. agriculture have focused on major world food crops such as wheat and maize. While useful from a national and global perspective, these results are not particularly relevant to the Northeastern U.S. agriculture economy, which is dominated by dairy milk production, and high-value horticultural crops such as apples (Malus domestica), grapes (Vitis vinifera), sweet corn (Zea mays var. rugosa), cabbage (Brassica oleracea var. capitata), and maple syrup (sugar maple, Acer saccharum). We used statistically downscaled climate projections generated by the HadCM3 atmosphere–ocean general circulation model, run with Intergovernmental Panel on Climate Change future emissions scenarios A1fi (higher) and B1 (lower), to evaluate several climate thresholds of direct relevance to agriculture in the region. A longer (frost-free) growing season could create new opportunities for farmers with enough capital to take risks on new crops (assuming a market for new crops can be developed). However, our results indicate that many crops will have yield losses associated with increased frequency of high temperature stress, inadequate winter chill period for optimum fruiting in spring, increased pressure from marginally over-wintering and/or invasive weeds, insects, or disease, or other factors. Weeds are likely to benefit more than cash crops from increasing atmospheric carbon dioxide. Projections of thermal heat index values for dairy cows indicate a substantial potential negative impact on milk production. At the higher compared to lower emissions scenario, negative climate change effects will occur sooner, and impact a larger geographic area within the region. Farmer adaptations to climate change will not be cost- or risk-free, and the impact on individual farm families and rural communities will depend on commodity produced, available capital, and timely, accurate climate projections.     

Assessing potential future urban heat island patterns following climate scenarios,socio-economic developments and spatial planning strategies

Climate change and urban development will exacerbate current urban heat island effects. While most studies acknowledge the importance of projected temperature increases for raising urban temperatures, little attention is paid to the impacts of future changes in urbanisation patterns. Yet, steering urban development may be an effective strategy to further limit increases in the intensity and spreading of the urban heat island effect. We describe a method that allows exploring the impact of urban development scenarios on the urban heat island effect. This paper starts with a basic analysis of the strength of this effect in a temperate climate under relatively favourable conditions based on data from amateur weather stations and own observations. It explains local variation in observed temperatures and quantifies how the urban heat island effect may develop in the coming 30 years. Using the obtained relations, we assess potential future changes building on existing scenarios of climatic and socio-economic changes and a land use simulation model. Our measurements for the Amsterdam region in the Netherlands indicate that the urban heat island effect induces maximum temperature differences with the surrounding countryside of over 3 °C on moderately warm summer days. The simulations of potential future changes indicate that strong local temperature increases are likely due to urban development. Climate change will, on average, have a limited impact on these changes. Large impacts can, however, be expected from the combination of urban development and potentially more frequent occurrences of extreme climatic events such as heat waves. Spatial planning strategies that reduce the lateral spread of urban development will thus greatly help to limit a further increase in urban heat island values.     

Potential benefits of drought and heat tolerance in groundnut for adaptation to climate change in India and West Africa

Climate change is projected to intensify drought and heat stress in groundnut (Arachis hypogaea L.) crop in rainfed regions. This will require developing high yielding groundnut cultivars that are both drought and heat tolerant. The crop growth simulation model for groundnut (CROPGRO-Groundnut model) was used to quantify the potential benefits of incorporating drought and heat tolerance and yield-enhancing traits into the commonly grown cultivar types at two sites each in India (Anantapur and Junagadh) and West Africa (Samanko, Mali and Sadore, Niger). Increasing crop maturity by 10 % increased yields up to 14 % at Anantapur, 19 % at Samanko and sustained the yields at Sadore. However at Junagadh, the current maturity of the cultivar holds well under future climate. Increasing yield potential of the crop by increasing leaf photosynthesis rate, partitioning to pods and seed-filling duration each by 10 % increased pod yield by 9 to 14 % over the baseline yields across the four sites. Under current climates of Anantapur, Junagadh and Sadore, the yield gains were larger by incorporating drought tolerance than heat tolerance. Under climate change the yield gains from incorporating both drought and heat tolerance increased to 13 % at Anantapur, 12 % at Junagadh and 31 % at Sadore. At the Samanko site, the yield gains from drought or heat tolerance were negligible. It is concluded that different combination of traits will be needed to increase and sustain the productivity of groundnut under climate change at the target sites and the CROPGRO-Groundnut model can be used for evaluating such traits.     

Impact of Climate Change on Maize Yield in Central and Northern Greece: A Simulation Study with Ceres-Maize

The potential impacts of climate change on the phenology and yield of two maize varieties in Greece were studied. Three sites representing the central and northern agricultural regions were selected: Karditsa, Naoussa and Xanthi. The CERES-Maize model, embedded in the Decision Support System for Agrotechnology Transfer (DSSAT 3.0), was used for the crop simulations, with current and possible future management practices. Equilibrium doubled CO₂ climate change scenarios were derived from the GISS, GFDL, and UKMO general circulation models (GCMs); a transient scenario was developed from the GISS GCM transient run A. These scenarios predict consistent increases in air temperature, small increases in solar radiation and precipitation changes that vary considerably over the study regions in Greece. Physiological effects of CO₂ on crop growth and yield were simulated. Under present management practices, the climate change scenarios generally resulted in decreases in maize yield due to reduced duration of the growing period at all sites. Adaptation analyses showed that mitigation of climate change effects may be achieved through earlier sowing dates and the use of new maize varieties. Varieties with higher kernel-filling rates, currently restricted to the central regions, could be extended to the northern regions of Greece. In the central regions, new maize varieties with longer grain-filling periods might be needed.     

非农就业对农户种植多样性的影响:以江苏省泰兴市和宿豫区为例

为分析非农就业对农户种植多样性的影响,通过农户问卷调查手段获得356份农户问卷,以在江苏省泰兴市和宿豫区的农户问卷调查数据为基础,采用Poisson回归方法,估计了农户种植多样性决策模型。依据模型估计结果,分析了非农就业对农户种植多样性的影响。分析表明,农户的种植多样性受到多种因素的影响。负责农业生产家庭成员受教育年限提高1 a,种植多样性提高1.5%左右;种植面积增加1 hm²,则农户种植多样性提高28%左右;就农户参与非农活动的影响而言,与负责农业生产家庭成员不参与非农活动的农户相比较,负责农业生产家庭成员参与非农活动家庭的种植多样性减少11%左右;负责农业生产家庭成员参与非农活动月数增加1个月,农户种植多样性大约降低1.4%。分析说明负责农业生产家庭成员参与非农就业会显著降低农户种植多样性。     

A Geographic Information System (GIS)-based approach to adaptation to regional climate change: a case study of Okutama-machi,Tokyo, Japan

Recently, local governments have an increasing need to take extensive and effective local measures to adapt to regional climate change, but have difficulty knowing how and when to adapt to such change. This study aims: 1) to characterize an efficient and cost-effective database management tool (DMT) for developing a Geographic Information System (GIS) based approach to using observed and projected data, for decision-making by non-expert government authorities, and 2) to document how DMT can be used to provide specialized yet understandable climate change information to assist local decision-makers in clarifying regional priorities within a wide array of adaptation options. The DMT combines climate change mapping, statistical GIS, and a vulnerability assessment. Okutama-machi, a 225.63 km² sparsely populated mountainous region (2012 population 5,856) northwest of Tokyo, Japan, was chosen for this pilot study. In this paper, the most recent regional climate projections (5 km resolution) are transcribed into an understandable form for use by non-expert citizens who use the GIS-based DMT. Results illustrate qualitative agreement in projection of summer daily mean temperatures; the mean temperature increase at Okutama-machi is the greatest of any area in Tokyo. In comparing near future and future conditions, August monthly mean temperature will increase more than 0.7–0.9 °C and 2.8–2.9 °C, and monthly precipitation by 50 % and 25–41 %, respectively. However, the root mean square (RMS) errors and bias of percentage change for monthly precipitation in summertime are 26.8 % and 4.3 %, respectively. These data provide an early warning and have implications for local climate policy response.     

2000～2020年西南地区植被NDVI时空变化及驱动机制探究

基于2000～2020年MOD13A3 NDVI时间序列、1999～2020年气象数据以及2000年和2020年两期土地利用类型数据,采用Theil-Sen Median趋势分析、 Mann-Kendall显著性检验、多重共线性检验、残差分析和相对作用分析等方法,分析了西南地区植被NDVI时空变化特征及气候变化和人类活动对植被NDVI变化的驱动机制.结果表明,研究时段内西南地区整体及各地貌单元植被NDVI均呈上升趋势,其中,广西丘陵和云贵高原植被NDVI上升趋势最为显著,青藏高原植被NDVI上升趋势最为微弱.气候变化和人类活动影响下西南地区植被NDVI上升斜率分别为0.001 0 a^-1和0.000 6 a^-1.气候变化和人类活动的共同驱动是引起西南地区植被改善的主要原因.西南地区植被改善主要受区域气候条件的控制,植被退化主要受人类活动的影响.总体上,植被NDVI与最低气温、降水、最高气温、可能蒸散率和相对湿度呈正相关,与平均气温、气压、日照时数、温暖指数和湿度指数呈负相关.最低气温、日照时数和降水是影响西南地区植被NDVI变化的主要气象因子...     

Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Great Plains

Crop simulation models are frequently used to estimate the impact of climate change on crop production. However, few studies have evaluated the model performance in ways that most researchers practiced in climate impact studies. In this article, we examined the reliability of the EPIC model in simulating grain sorghum (Sorghum bicolor (L.) Moench) yields in the U.S. Great Plains under different climate scenarios, namely in years with normal or extreme temperature and precipitation. We also investigated model uncertainties introduced by input data that are not site-specific but commonly used or available for climate change studies. Historical field trial data of sorghum at the Mead Experimental Center, NE, were used for model evaluations. The results showed that overall model reliability was about 56%. The mean absolute relative error (absRE) was about 29%. The degree of accuracy and reliability varied with climate-classes and nitrogen (N)-treatments. The largest bias occurred in drought years (RE = ?25%) and the most unreliable results were found in N-0 treatment (reliability = 32%). There was more than 69% probability that input-data-induced uncertainties were limited to less than 20% of absRE. Our results support the application of the EPIC model to climate change impact studies in the U.S. Great Plains. However, efforts are needed to improve the accuracy in simulating crop responses to extreme water- and nitrogen-stressed conditions.