ASSESSING THE SUITABILITY OF THE EPIC CROP MODEL FOR USE IN THE STUDY OF IMPACTS OF CLIMATE VARIABILITY AND CLIMATE CHANGE IN WEST AFRICA

The EPIC (Erosion Productivity Impact Calculator) crop model, developed by scientists of the United States Department of Agriculture (USDA), has been successfully applied to the study of erosion, water pollution, crop growth and production in the US but is yet to be introduced for serious research purposes in other countries or regions. This paper reports on the applicability of the EPIC 8120 crop model for the assessment of the potential impacts of climate variability and climate change on crop productivity in sub‐Saharan West Africa, using Nigeria as the case study. Among the crops whose productivity has been successfully simulated with this model are five of West Africa's staple food crops: maize, millet, sorghum (guinea corn), rice and cassava. Thus, using the model, the sensitivities of maize, sorghum and millet to seasonal rainfall were demonstrated with coefficients of correlation significant at over 98 per cent confidence limits. The validation tests were based on a comparison of the observed and the model‐generated yields of rice and maize. The main problems of validation relate to the multiplicity of crop varieties with contrasting performances under similar field conditions. There are also the difficulties in representing micro‐environments in the model. Thus, some gaps appear between the observed and the simulated yields, arising from data or model deficiencies, or both. Based on the results of the sensitivity and validation tests, the EPIC crop model could be satisfactorily employed in assessing the impacts of and adaptations to climate variability and climate change. Its use for the estimation of production and the assessment of vulnerabilities need to be pursued with further field surveys and field experimentation.     

Growth response of the saltbush Atriplex nummularia L. to inoculation with the arbuscular mycorrhizal fungus Glomus intraradices

Plantlets of Atriplex nummularia were inoculated with the arbuscular mycorrhizal fungi Glomus intraradices in a pot experiment. Plants were grown in a low P soil. Highly significant growth response of a Chenopodiaceae was recorded for the first time. Mycorrhizal colonization of roots was well developed, internal hyphae and vesicles were observed, but not arbuscules. These observations suggest that arbuscules are not necessary to obtain significant growth stimulation from mycorrhizal inoculation. Atriplex nummularia is already used as forage crops, its high mycorrhizal dependency offers possibilities to develop this production and revegetation strategies.     

内蒙古河套灌区春玉米作物系数试验研究

作物系数曲线是估算作物生长季耗水量变化的重要参数。基于2013年4—9月内蒙古巴彦淖尔市临河区田间水分试验和1994—2013年气象站观测资料,利用水量平衡法反求春玉米作物系数,分析生长季内的变化规律, 建立动态模拟方程,并与联合国粮农组织 (FAO) 分段直线法结果进行比较, 提出胁迫条件下作物系数的叶面积修正方法。结果表明:玉米作物系数随发育进程可用三项式曲线描述,变化趋势与产量水平无关, 但随产量增高而变幅增大;以出苗后相对积温为时间变量建立模拟方程效果较好,决定系数 (R2) 均在0.92以上;模拟计算出各站点最大 (1.30~1.48) 和平均 (0.831~0.919) 作物系数,与FAO分段直线法计算的典型值和区间值基本一致,生长中期平均相对误差为3.4%~7.2%;提出利用相对叶面积指数修正作物系数的计算方法;通过2014年实例检验,土壤水分模拟值与实测值的平均相对误差为6.3%,相对误差小于15%的占95.8%。     

Monitoring of water stress in wheat using multispectral indices derived from Landsat-TM

Detection of crop water stress is crucial for efficient irrigation water management. Potential of Satellite data to provide spatial and temporal dynamics of crop growth conditions makes it possible to monitor crop water stress at regional level. This study was conducted in parts of western Uttar Pradesh and Haryana. Multi-temporal Landsat data were used for detecting wheat crop water stress using vegetation indices (VIs), viz. vegetation water stress index (VWSI) and land surface wetness index water stress factor (Ws_LSWI). The estimated water stress from satellite data-based VIs was validated by water stress factor (Ws) derived from flux-tower data. The study observed Ws_LSWI to be better index for water stress detection. The results indicated that Ws_LSWI was superior over other index showing RMSE = 0.12, R² = 0.65, whereas VWSI showed overestimated values with mean RD 4%.     

WOFOST模型对河南省冬小麦模拟的适用性分析

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。     

京津冀周边秸秆燃烧对PM2.5无机组分影响

华北平原是我国主要农作物产区,田间秸秆焚烧现象普遍存在,选取秋收季节（2014年10月）分析了秸秆燃烧的排放特征,利用区域化学传输模型WRF-Chem模拟研究了燃烧排放对气态前体物及其氧化产物的影响,以及最终导致的PM_2.5中硫酸盐、硝酸盐和铵盐的变化。研究表明:2014年秋收季节,河南和山东等省份的秸秆燃烧排放会在东南风的输送作用下影响京津冀地区;秸秆燃烧排放大量挥发性有机物（VOCs）,导致火点源及周边地区大气中主要氧化剂浓度上升,提升了区域大气氧化能力;当携带大量VOCs的秸秆燃烧烟羽与以化石燃料排放为主的城市气团相混合时,大气氧化性增强会加速城市地区人为源排放的NO_x和SO₂等气态前体物的氧化过程,提高硫酸盐和硝酸盐的形成速率、促进二次无机气溶胶的生成。     

Influence of multipurpose trees on agricultural crops in arid regions of Haryana, India

The effects of multipurpose trees on the productivity of agricultural crops were studied in the arid regions of Haryana. In one of the experiments, wheat was grown on irrigated farms having scattered trees ofDalbergia sissoo, Azadirachta indica, Prosopis cinerariaandAcacia nilotica. Data of wheat yield for each tree species at different distances (1, 3, 5, and 7 m) and four directions (East, West, North and South) from the tree bases and control (no trees) were collected. Results indicate thatAzadirachta indicaandProsopis cinerariadid not produce any significant difference in the wheat yield while the other two species (Dalbergia sissooandAcacia nilotica) gave a reduction in yield.A. niloticahad a more significant and prominent effect and a reduction of 40 to 60 % wheat yield was observed.Dalbergia sissooreduced yield by 4 to 30 % but the reduction was only up to a distance of 3 m. In general, the impact of trees on productivity was observed up to 3 m distance and there was little, if any, impact up to 5 m and almost no impact at 7 m.In another experiment,D. sissoo(18-years-old) was raised as windbreak and productivity of cotton was assessed. The tree belt reduced the wind speed by 15 to 45 %, depending on season and wind speed. The influence of trees on cotton yield was observed to be negative up to 2H (36 m), where H is tree height, i.e. 18 m. Cotton productivity was observed to be maximum between 2H and 5H. Depending upon orientation of tree belt, the increase in cotton yield was found to be 4 to 10 %.     

对建立遥感估产模式的几点初步认识

本文从分析遥感光谱参数的生物学意义着手，论证了正确建立遥感估产模型的可能途径。对几种有代表性的遥感估产模型作了分析，作者认为把可见光、近红外波段的遥感信息与热红外信息有机结合是解决遥感估产模型的最佳方案。对ＮＯＡＡ－ＡＶＨＲＲ的第１通道与第２通道光谱数值进行非朗伯体特性的纠正是必要的。遥感估产模型不仅可以使估产的空间尺度大大缩小而且参数数目亦可大大减小，更有利于实际运行。     

利用GVG线采样技术提取农作物种植面积及其精度分析

GVG(GIS&Video&GPS)线采样系统提出以线状样区代替以往成数抽样中的点样区与面积样区概念,通过统计线状样区内作物种植面积成数来反映区域总体农作物种植面积成数。通过 GVG实地采样,将其结果与解译遥感影像提取的作物种植面积成数结果进行了对比分析,结果显示采用GVG线采样方式精确度较高,其采样系统具有实用性和推广价值。