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1.
S. A. Saseendran K. K. Singh L. S. Rathore S. V. Singh S. K. Sinha 《Climatic change》2000,44(4):495-514
The CERES-Rice v3. crop simulation model, calibrated and validated for its suitability to simulate rice production in the tropical humid climate Kerala State of India, is used for analysing the effect of climate change on rice productivity in the state. The plausible climate change scenario for the Indian subcontinent as expected by the middle of the next century, taking into account the projected emissions of greenhouse gases and sulphate aerosols, in a coupled atmosphere-ocean model experiment performed at Deutsches Klimarechenzentrum, Germany, is adopted for the study. The adopted scenario represented an increase in monsoon seasonal mean surface temperature of the order of about 1.5°C, and an increase in rainfall of the order of 2 mm per day, over the state of Kerala in the decade 2040–2049 with respect to the 1980s. The IPCC Business-as-usual scenario projection of plant usable concentration of CO2 about 460 PPM by the middle of the next century are also used in the crop model simulation. On an average over the state with the climate change scenario studied, the rice maturity period is projected to shorten by 8% and yield increase by 12%. When temperature elevations only are taken into consideration, the crop simulations show a decrease of 8% in crop maturity period and 6% in yield. This shows that the increase in yield due to fertilisation effect of elevated CO2 and increased rainfall over the state as projected in the climate change scenario nearly makes up for the negative impact on rice yield due to temperature rise. The sensitivity experiments of the rice model to CO2 concentration changes indicated that over the state, an increase in CO2 concentration leads to yield increase due to its fertilisation effect and also enhance the water use efficiency of the paddy. The temperature sensitivity experiments have shown that for a positive change in temperature up to 5°C, there is a continuous decline in the yield. For every one degree increment the decline in yield is about 6%. Also, in another experiment it is observed that the physiological effect of ambient CO2 at 425 ppm concentration compensated for the yield losses due to increase in temperature up to 2°C. Rainfall sensitivity experiments have shown that increase in rice yield due to increase in rainfall above the observed values is near exponential. But decrease in rainfall results in yield loss at a constant rate of about 8% per 2 mm/day, up to about 16 mm/day. 相似文献
2.
Assessing the impacts of climate change on rice yields in the main rice areas of China 总被引：8，自引：1，他引：8
Fengmei Yao Yinglong Xu Erda Lin Masayuki Yokozawa Jiahua Zhang 《Climatic change》2007,80(3-4):395-409
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. 相似文献
3.
WANG Chunyi BAI Yueming GUO Jianping WEN Min HUO Zhiguo LIU Jiangge LI Lei 《Acta Meteorologica Sinica》2003,17(4):503-508
The impacts of O3 concentration change on rice yields for different lengths of exposure time are studied by means of the OTC-1 open-top chamber.The resuhs indicate that when O3 concentration increased from 50 ppb to 200 ppb during the time period of 20 to 80 days in the experiment,the rice yield was reduced by 6.78% to 33.72%.Two main influencing factors for rice yields are the increased O3 concentration and the extended exposure time.Using a logarithm function to simulate the impacts of O3 concentration on rice yields is better than using a the Weibull function. 相似文献
4.
陕西汉中盆地水稻冷害初探 总被引：2，自引：1，他引：2
本文采用“多重比较”检验、方差分析和回归积分方法,求算了水稻冷害的温度指标,确立了产量预报的积分经验公式和温度影响产量的时间函数a_j(t),从而揭示了水稻产量和温度分布状况的定量关系,为稳产高产提供依据。 相似文献
5.
Access to food, water, and good air quality is indispensable for human life, as reflected in various United Nations Sustainable Development Goals (SDGs); however, pursuing food security may pose threats to water security and/or air quality. An important case is northwest India including the Punjab and Haryana states, which is the ‘breadbasket’ of India with a significantly increasing paddy rice area. The rapid expansion of rice farming has stressed groundwater resources and impacted air quality. Satellite observations have the potential to provide data for better decisions on food security, water storage, and air pollution, which would be vital for regional sustainable development. Based on observations from multiple satellites from 2001 to 2018, we found that paddy rice expansion (+22%) increased groundwater depletion (−1.50 cm/yr), residue burning (+500%), and air pollution (+29%, PM2.5) in the breadbasket of India. Moreover, satellite observations showed changes in these interactions after the enactment of a groundwater protection policy in 2009, which decelerated groundwater depletion (−1.20 cm/yr) due to delayed rice planting and harvest dates (∼15d); the latter elevated air pollution in November (+29%, PM2.5). Our finding stresses the need to reconcile the trade-offs and consider the interactions among SDGs 2 (food), 3 (good health), 6 (clean water), and 11 (air quality in cities), in policy-making for sustainable development. An efficient crop residue ultilization and management system, bottom-up groundwater use regulations, and cropping system shift towards less water-consuming crops are critically required to resolve the trade-offs of the food-water–air quality nexus in the northern India. Our study also showcases remote sensing approaches and methods to support and aid the achievement of the SDGs and track their progreses to support regional sustainable development. 相似文献
6.
Brown planthopper (BPH), Nilaparvata lugens (Stal.) development studied at six constant temperatures, 19, 22, 25, 28, 31 and 33 ±1 °C on rice plants revealed that developmental period from egg hatching to adult longevity decreased from 46.8 to 18.4 days as temperature increased from 19 to 31 °C. Through regression of development rate on temperature, thermal constant of small nymph (1st-2nd instar), large nymph (3rd–5th instar) and adult were determined to be 126.6, 140.8 and 161.3 degree days (DD), respectively with corresponding development threshold being 8.8, 9.5 and 9.6 °C. A thermal constant-based mechanistic-hemimetabolous-population model was adapted for BPH and linked with InfoCrop, a crop simulation model to simulate climate change impact on both the pest population and crop-pest interactions. The model was validated with field data at New Delhi and Aduthurai (Tamil Nadu, India), (R 2?=?0.96, RMSE?=?1.87 %). Climate-change-impact assessment through coupled BPH-InfoCrop model, in the light of the projected climate-change scenario for Indian subcontinent, showed a decline of 3.5 and 9.3–14 % in the BPH population by 2020 and 2050, respectively, during the rainy season at New Delhi, while the pest population exhibited only a small decline of 2.1–3.5 % during the winter at Aduthurai by 2050. BPH population decline is attributed to reduction in fecundity and survival by simulation model, which otherwise was not possible to account for with an empirical model. Concomitant to its population decline, BPH-induced yield loss also indicated a declining trend with temperature rise. However, the study considered the effect of only CO2 and temperature rise on the BPH population and crop yield, and not that of probable changes in feeding rate and adaptive capacity of the pest. 相似文献
7.
晚稻单产动态预测方法研究 总被引：11，自引：0，他引：11
晚稻单产与气象条件关系分析表明：气象要素是影响相邻两年晚稻单产变化的主要影响因素,尤其是气温和日照.根据业务服务的需要,提出利用晚稻主产省份的产量资料和代表站的旬平均气温、旬降水量和旬日照时数等气象资料,运用综合聚类原理,建立全国晚稻产量动态预报方法.此方法能够在晚稻播种一段时间后动态预测晚稻单产,具有简便、实用、准确率较高的特点,并且克服了常用回归方法在较短时间内筛选预测因子难的缺点,有一定的业务应用价值. 相似文献
8.
The purpose of this paper is to analyze the trends and variability in extreme temperature indices and its impact on rice–wheat productivity over two districts of Bihar, India, which is part of the middle Indo-Gangetic Basin. Mann–Kendall non-parametric test was employed for detection of trend and Sen slope was determined to quantify the magnitude of such trends. We have analyzed 10 extreme temperature indices for monthly and seasonally. The influence of extreme temperature indices on rice–wheat productivity was determined using correlation analysis. As far as Patna is concerned, if the number of cool days during September ≥10, the rice productivity will increase due to the availability of sufficient duration to fill up the grain. However, higher warm days during all the months except June will affect the productivity. A significant negative correlation was noticed between maximum value of minimum temperature during September and rice productivity. Highly significant positive correlation was noticed between number of cool days during September with rice productivity while it was highly significant negative correlation in the case of number of warm days during the same month. As far as Samastipur is concerned, a negative correlation was noticed between wheat productivity and maximum value of maximum temperature (TXx) during February, but not statistically significant. The higher temperature may affect the kernel weight and thereby yield. It is seen that a critical value of TXx ≥29.2 °C will be harmful to wheat crop during February. A significant positive correlation of number of cool nights with wheat productivity also supports the above relationship. The critical values of extreme temperature indices during rice and wheat growing months provide an indicator to assess the vulnerability of rice–wheat productivity to temperature for Patna and Samastipur districts and there is a need to prepare an adaptive strategy and also develop thermo-insensitive rice–wheat high yielding varieties suitable for this region to sustain rice–wheat productivity under projected climate change situation. 相似文献
9.
基于遗传优化BP神经网络的水稻气象产量预报模型 总被引：9，自引：4，他引：5
利用1951—2010年江苏省水稻产量及同期14个气象站点的逐日平均气温、降水资料,采用因子膨化及相关分析,研究了水稻气象产量的影响因子及影响时段。在此基础上建立了逐步回归、PCA-BP神经网络以及PCA-GA-BP神经网络3种产量预报模型。结果表明:(1)7—9月份是水稻产量形成的关键时期,对气温、降水的变化最为敏感,气温对气象产量的影响大于降水;(2)两种神经网络模型预报效果好于回归模型;(3)遗传优化的神经网络模型比未优化模型的训练速度提高了70%左右,预报精度也提高了4.3%。 相似文献
10.
This paper reports results of a comparison of two popular rice growth models- Ceres-Rice and ORYZA1N for the same input conditions. Both models use different approaches for simulating growth and yield, are sensitive to climate change parameters, and represent two major schools of crop modelling. A dataset of 32 experiments consisting of 98 treatments was assembled from an extensive literature search. These experiments were conducted over the period of 1980–1993 in diverse Indian locations from 11° N–33° N. The treatments varied in N management, sowing dates, varieties and seasons. The flowering duration in the dataset varied between 37 and 86 days and grain yields between 2587 kg ha–1 and 8877 kg ha–1. Seven treatments from this dataset, one for each variety, were selected for calibration. The genetic coefficients of different varieties used in the analysis for both models were estimated from this short-listed dataset by repeated iterations until a close match between simulated and observed phenology and yield was obtained in these treatments. Similarly 11 treatments with zero or low N applications were used for calibration of initial soil N for different locations. The remaining 80 treatments were used for validation of the models. Both models predicted satisfactorily the trends of leaf area and dry matter growth, grain number, days to flowering and grain yields. Simulated yields were within +15% of the measurements. Considering that the field measurements also generally have 10–15% error and that the treatments widely varied in weather conditions, particularly in temperature, it was concluded that both models are adequate to simulate the effects of climate change on rice yields in diverse agro-environments of India that are free from all pests. 相似文献
11.
A physical model was developed for describing the thermal environment of ponded shallow water as a model for rice fields in relation to climatic conditions. The model was used to assess probable effects of CO2-induced warming on the thermal conditions of ponded shallow water. It was assumed that an altered equilibrium climate was produced by atmospheric CO2 which was twice that of present levels. The 1951–80 climatic means of Japan were used as baseline data. Water temperature and energy balance characteristics predicted from the model were compared between both climates. The most notable results were that water temperature under CO2 doubling rose 2 to 4 °C. These increases in temperature would induce a remarkable northward shift of the 15 °C isotherm which characterizes the isochrone of safe transplanting dates for rice seedlings. CO2-warming would have a considerable influence on the energy balance characteristics, intensifying the evaporation rate from the water surface. Changes in thermal conditions of rice fields due to CO2-induced climatic warming are, therefore, expected to bring about significant effects on aquatic environments and the life forms they support. 相似文献
12.
A. Datta S. K. Sharma R. C. Harit V. Kumar T. K. Mandal H. Pathak 《Asia-Pacific Journal of Atmospheric Sciences》2012,48(3):275-281
Ammonia (NH3) emission from wheat (November to April) and rice (July to October) crops was measured using the chemiluminescence method at a subtropical agricultural area of India during 2009?C2010. Samples were collected from the canopy height during different growth stages of wheat crop to study the variations of NH3 emission during different growth stages of the crop. Background atmospheric concentration of NH3 was measured at 5 m height at the study site. Background NH3 concentration was subtracted from the NH3 concentration at crop canopy height to estimate the emission of NH3 from crop canopy. The NH3 emission from the wheat crop were recorded as 33.3 to 57.0; 15.3 to 29.2; 10.3 to 28.0; 8.7 to 23.9 and 13.9 to 28.9 ??g m?2 d?1 during sowing, crown root initiation (CRI), panicle initiation, grain filling and maturity stages of the crop respectively. The NH3 emission followed a diurnal pattern with significant correlation with ambient temperature at different crop growth stages. Cumulative seasonal NH3 emission to the atmosphere was accounted for the loss of ??10% of applied N-fertilizer during the wheat crop growing period. Immediate increase in NH3 emission was recorded from rice crop, grown under temperature gradient tunnel (TGT). However, the NH3 emission inside the TGT decreases within 3?C4 h after the N-fertilizer application. Continuous estimation of NH3 concentration at the crop canopy inside the TGT, suggests that the NH3 emission to the atmosphere reaches its peak within ??20 h of N-fertilizer application and continues up to 5 d following a diurnal pattern. 相似文献
13.
Rice is the staple food in China, and the country’s enlarging population puts increasing pressure on its rice production as well as on that of the world. In this study, we estimate the impact of climate change, CO2 fertilization, crop adaptation and the interactions of these three factors on the rice yields of China using model simulation with four hypothetical scenarios. According to the results of the model simulation, the rice yields without CO2 fertilization are predicted to decrease by 3.3 % in the 2040s. Considering a constant rice-growing season (GS), the rice yields are predicted to increase by 3.2 %. When the effect of CO2 fertilization is integrated into the Agro-C model, the expected rice yields increase by 20.9 %. When constant GS and CO2 fertilization are both integrated into the model, the predicted rice yield increases by 28.6 %. In summary, the rice yields in China are predicted to decrease in the 2040s by 0.22 t/ha due to climate change, to increase by 0.44 t/ha due to a constant GS and to increase by 1.65 t/ha due to CO2 fertilization. The benefits of crop adaptation would completely offset the negative impact of climate change. In the future, the most of the positive effects of climate change are expected to occur in northeastern and northwestern China, and the expansion of rice cultivation in northeastern China should further enhance the stability of rice production in China. 相似文献
14.
We evaluated the potential impact of future climate change on spring maize and single-crop rice in northeastern China(NEC) by employing climate and crop models. Based on historical data, diurnal temperature change exhibited a distinct negative relationship with maize yield, whereas minimum temperature correlated positively to rice yield. Corresponding to the evaluated climate change derived from coupled climate models included in the Coupled Model Intercomparison Project Phase 5(CMIP5) under the Representative Concentration Pathway 4.5 scenario(RCP4.5), the projected maize yield changes for three future periods [2010–39(period 1), 2040–69(period 2), and 2070–99(period 3)] relative to the mean yield in the baseline period(1976–2005) were 2.92%, 3.11% and 2.63%, respectively. By contrast, the evaluated rice yields showed slightly larger increases of 7.19%, 12.39%, and 14.83%, respectively. The uncertainties in the crop response are discussed by considering the uncertainties obtained from both the climate and the crop models. The range of impact of the uncertainty became markedly wider when integrating these two sources of uncertainty. The probabilistic assessments of the evaluated change showed maize yield to be relatively stable from period 1 to period 3, while the rice yield showed an increasing trend over time. The results presented in this paper suggest a tendency of the yields of maize and rice in NEC to increase(but with great uncertainty) against the background of global warming, which may offer some valuable guidance to government policymakers. 相似文献
15.
水稻高温热害风险评估方法研究 总被引：3，自引：0，他引：3
以衡阳地区的水稻生长为研究对象,对ORYZA2000水稻模型的相应参数进行了本地化,模拟了该地区常年气候条件、设定高温条件及各年高温条件下的一季稻产量,并计算了各年实况及设定条件下的产量灾损率,在此基础上建立了两种水稻产量灾损率评估模型。研究发现：46 a来衡阳地区水稻开花灌浆期平均日最高气温为34.98℃,高于水稻生产的最适温度5℃以上;相对常年产量,由高温热害导致的产量灾损率最高为67.2%,历年灾损中2003年的灾损率接近最高值,达67.0%;高温造成的产量灾损率受高温程度及持续时间的共同影响,二者缺一不可;根据多元回归建立的灾损率评估模型,F计算值〉〉F查表值,方程有意义。其趋势预测完全一致,灾损率精确度〉72%;根据高温指标建立的灾损率评估模型通过了46 a的大样本检验,在高温热害风险评估方面具有一定的实际应用价值。 相似文献
16.
General circulation models (GCMs) project increases in the earth’s surface air temperatures and other climate changes by the mid or late 21st century, and therefore crops such as cotton (Gossypium spp L.) will be grown in a much different environment than today. To understand the implications of climate change on cotton production in India, cotton production to the different scenarios (A2, B2 and A1B) of future climate was simulated using the simulation model Infocrop-cotton. The GCM projections showed a nearly 3.95, 3.20 and 1.85 °C rise in mean temperature of cotton growing regions of India for the A2, B2 and A1B scenarios, respectively. Simulation results using the Infocrop-cotton model indicated that seed cotton yield declined by 477 kg?ha?1 for the A2 scenario and by 268 kg?ha?1 for the B2 scenario; while it was non-significant for the A1B scenario. However, it became non-significant under elevated [CO2] levels across all the scenarios. The yield decline was higher in the northern zone over the southern zone. The impact of climate change on rainfed cotton which covers more than 60 % of the country’s total cotton production area (mostly in the central zone) and is dependent on the monsoons is likely to be minimum, possibly on account of marginal increase in rainfall levels. Results of this assessment suggest that productivity in northern India may marginally decline; while in central and southern India, productivity may either remain the same or increase. At the national level, therefore, cotton production is unlikely to change with climate change. Adaptive measures such as changes in planting time and more responsive cultivars may further boost cotton production in India. 相似文献
17.
18.
Liu Weiguang Wang Guiling Yu Miao Chen Haishan Jiang Yelin Yang Meijian Shi Ying 《Climate Dynamics》2020,55(9-10):2725-2742
The future vegetation–climate system over East Asia, as well as its dependence on Representative Concentration Pathways (RCPs), is investigated using a regional climate–vegetation model driven with boundary conditions from Flexible Global Ocean–Atmosphere–Land System Model: Grid-point Version 2. Over most of the region, due to the rising CO2 concentration and climate changes, the model projects greater vegetation density (leaf area index) and gradual shifts of vegetation type from bare ground to grass or from grass to trees; the projected spatial extent of the vegetation shift increases from RCP2.6 to RCP8.5. Abrupt shifts are projected under RCP8.5 over northeast China (with grass replacing boreal needleleaf evergreen trees due to heat stress) and India (with tropical deciduous trees replacing grass due to increased water availability). The impact of vegetation feedback on future precipitation is relatively weak, while its impact on temperature is more evident, especially during DJF over northeast China and India with differing mechanisms. In northeast China, the projected forest loss induces a cooling through increased albedo, and daytime high temperature (Tmax) is influenced more than nighttime low temperature (Tmin); in India, increased vegetation cover induces an evaporative cooling that outweighs the warming effect of an albedo decrease in DJF, leading to a weaker impact on Tmax than on Tmin. Based on a single model, the qualitative aspects of these results may hold while quantitative assessment will benefit from a follow-up regional model ensemble study driven by multiple general circulation models.
相似文献19.
基于气候适宜指数的江西晚稻产量动态预报模型构建及应用 总被引：3，自引：1，他引：3
本文利用1981—2014年江西91个气象观测站的地面气象观测资料和同期的分县晚稻产量资料,结合江西地区气候特点及晚稻生理特性,构建适用于江西地区晚稻降水、温度、日照及综合适宜度模型,并根据适宜度与产量的相关关系,确定气候适宜指数,建立基于气候适宜指数的江西晚稻产量动态预报模型,并对模型进行了回代检验及预报检验,从而实现对江西地区晚稻气候适宜度诊断及晚稻产量动态预报的目的。结果表明:模型的回代检验、产量丰歉趋势、产量动态预报检验的准确率均较高,能够满足业务的需要。 相似文献
20.
K. Elampari S. B. Debaje S. Johnson Jeyakumar T. Chithambarathanu 《Journal of Atmospheric Chemistry》2013,70(4):357-371
Measurements of ground level ozone (O3), nitrogen dioxide (NO2) and meteorological parameters (air temperature, relative humidity and wind speed and direction) has been made for 3 years from March 2007 to February 2010 at Nagercoil (8.2°N, 77.5°E, 23 m above sea level), an equatorial rural coastal site of southern India. The monthly average of daytime maximum of O3 concentrations ranged from 28 to 50 parts per billion (ppb) with an annual average of 19.8 ppb. Similarly, monthly average of NO2 concentration ranged from 3.4 ppb to 7.7 ppb with an annual average of 5.3 ppb. The monthly variation of meteorological parameters shows the little changes being a coastal site. The estimated summer crops yield losses by 1.1–15.6 % from present O3 concentration level associated with AOT40 index 3.1–5 ppm h. 相似文献