小麦栽培模拟优化决策系统(WCSODS)介绍及应用

作物生长过程的计算机模拟是国际上近 30年来迅速崛起的一项新技术 ,它的应用与发展已引起农学家、作物生理学家、作物生态学家和农业气象学家与日俱增的重视[1] 。在此背景下 ,江苏省农科院高亮之、金之庆先生从 1 992～ 1 997年主持完成了国家自然科学基金项目小麦栽培模拟优化决策系统ＷＣＳＯＤＳ (ＷＨＥＡＴＣＵＬＴＩＶＡＴＩＯＮＡＬＳＩＭＵＬＡＴＩＯＮＯＰＴＩＭＩＺＡＴＩＯＮＤＥＣＩ ＳＩＯＮ -ＭＡＫＩＮＧＳＹＳＴＥＭ )的研制工作。ＷＣＳＯＤＳ是继水稻栽培模拟优化决策系统之后 ,我国自行研制的又一个大型综合性的农作物…     

TIBETAN PLATEAU FIELD EXPERIMENT（TIPEX）AND STUDY ON THE IMPACT OF PHYSICAL PROCESSES OVER TIBETAN PL

ＴＩＢＥＴＡＮＰＬＡＴＥＡＵＦＩＥＬＤＥＸＰＥＲＩＭＥＮＴ（ＴＩＰＥＸ）ＡＮＤＳＴＵＤＹＯＮＴＨＥＩＭＰＡＣＴＯＦＰＨＹＳＩＣＡＬＰＲＯＣＥＳＳＥＳＯＶＥＲＴＩＢＥＴＡＮＰＬＡＴＥＡＵＯＮＧＬＯＢＡＬＣＬＩＭＡＴＥＡＮＤＤＩＳＡＳＴＲＯＵＳＷＥＡＴＨ...     

CHINA GLOBAL ATMOSPHERE WATCH BASELINE OBSERVATORY AND ITS MEASUREMENT PROGRAM

ＣＨＩＮＡＧＬＯＢＡＬＡＴＭＯＳＰＨＥＲＥＷＡＴＣＨＢＡＳＥＬＩＮＥＯＢＳＥＲＶＡＴＯＲＹＡＮＤＩＴＳＭＥＡＳＵＲＥＭＥＮＴＰＲＯＧＲＡＭＴａｎｇＪｉｅ（汤洁），ＷｅｎＹｕｐｕ（温玉璞），ＸｕＸｉａｏｂｉｎ（徐晓斌），ＺｈｅｎｇＸｉａｎｇｄｏｎｇ（郑...     

ADVANCES IN STUDY OF INTERACTIONS ASSOCIATED WITH RAINSTORM

ＡＤＶＡＮＣＥＳＩＮＳＴＵＤＹＯＦＩＮＴＥＲＡＣＴＩＯＮＳＡＳＳＯＣＩＡＴＥＤＷＩＴＨＲＡＩＮＳＴＯＲＭ￥ＭａＳｎｕｆｅｎ（马淑芬）（ＩｎｓｔｉｔｕｔｅｏｆＳｙｎｏｐｔｉｃａｎｄＤｙｎａｍｉｃＭｅｔｅｏｒｏｌｏｇｙ）Ｂｅｉｊｉｎｇ１０００８１ａｎｄＤ...     

使用AHDM Ver3.0软件几个问题的解决方法

１　将ＡＨＤＭＶｅｒ３０软件拷进微机后,需将ＵＣＤＯＳ中的打印字库读取程序即ＵＰＢＡＴ中的Ｃ：ｗＵＣＤＯＳｗＰＲＩＮＴ改名为Ｃ：ｗＵＣＤＯＳｗＢＡＴ如ＱＢＢＡＴ等,可避免打印报表时只打印一行“”的现象。２　有关台站参数虽然在选择主菜单〔９〕功能中已经建立,但选择主菜单〔４〕采集报表数据时,仍需重新输入基本参数,否则报表封面打印时基本参数部分空白。３　０２时相对湿度加（　）时,先按正常记录输入,通过计算方式存入Ｅ、Ｕ、ＴＤ后,再在该记录上加（　）,但因打印报表时此（　）打印不出,故需人…     

SVD方法在气象场诊断分析中的普适性

本文首次从理论上推导证明两个气象场的奇异值分解（ＳＶＤ）在气象场时空分布耦合信号的诊断分析中具有普适性。结果表明，两个场的ＳＶＤ求解准则不同于典型相关分析（ＣＣＡ），且ＣＣＡ模型可视为ＳＶＤ之特例，尤其当各个场经ＰＣＡ滤波后，其ＣＣＡ完全与ＳＶＤ等价。ＳＶＤ分析的结果不但可完全代替ＣＣＡ，且计算更简便，所得耦合信号的物理解释更清晰，特别适合于大尺度气象场的遥相关型研究。     

THE VARIATION FEATURES OF AGROCLIMATIC RESOURCES AND CROP YIELD OF CHINA IN RECENT 40 YEARS

ＴＨＥＶＡＲＩＡＴＩＯＮＦＥＡＴＵＲＥＳＯＦＡＧＲＯＣＬＩＭＡＴＩＣＲＥＳＯＵＲＣＥＳＡＮＤＣＲＯＰＹＩＥＬＤＯＦＣＨＩＮＡＩＮＲＥＣＥＮＴ４０ＹＥＡＲＳＧａｏＳｕｈｕａ（高素华）ａｎｄＺｈａｎｇＹｕ（张宇）ＲｅｓｅａｒｃｈＣｅｎｔｅｒｆｏｒＡｇｒｉ...     

VSAT小站安装使用中应注意的一个问题

ＶＳＡＴ小站安装使用中应注意的一个问题＠刘杰￥贵州省六盘水市气象局ＶＳＡＴ小站安装使用中应注意的一个问题在ＶＳＡＴ小站的安装过程中一个非常重要的指标是零一地交流干扰电压≤２Ｖ。一般情况下，达不到这个技术指标。我局ＶＳＡＴ小站的零一地交流干扰电压在１５－２５...     

THE CHANGES AND CLIMATIC JUMPS INFERRED FROM THE AGRICULTURAL DRYNESS AND WETNESS IN THE CHANGJIANG－HUAIHE VALLEY FOR THE LAST 500 YEARS

ＴＨＥＣＨＡＮＧＥＳＡＮＤＣＬＩＭＡＴＩＣＪＵＭＰＳＩＮＦＥＲＲＥＤＦＲＯＭＴＨＥＡＧＲＩＣＵＬＴＵＲＡＬＤＲＹＮＥＳＳＡＮＤＷＥＴＮＥＳＳＩＮＴＨＥＣＨＡＮＧＪＩＡＮＧ－ＨＵＡＩＨＥＶＡＬＬＥＹＦＯＲＴＨＥＬＡＳＴ５００ＹＥＡＲＳＸｕｅＨｅｎｇ（薛...     

EFFECTS OF COLD OR WARM CLIMATIC CHANGEON AGRICULTURAL ENVIRONMENT OVER THE LOWER AND MIDDLE REACHES OF CHANGJIANG RIVER IN THE LAST CENTURY

ＥＦＦＥＣＴＳＯＦＣＯＬＤＯＲＷＡＲＭＣＬＩＭＡＴＩＣＣＨＡＮＧＥＯＮＡＧＲＩＣＵＬＴＵＲＡＬＥＮＶＩＲＯＮＭＥＮＴＯＶＥＲＴＨＥＬＯＷＥＲＡＮＤＭＩＤＤＬＥＲＥＡＣＨＥＳＯＦＣＨＡＮＧＪＩＡＮＧＲＩＶＥＲＩＮＴＨＥＬＡＳＴＣＥＮＴＵＲＹＺｈａｎｓＹ...     

Yield estimation and sowing date optimization based on seasonal climate information in the three CLARIS sites

The present article is a contribution to the CLARIS WorkPackage “Climate and Agriculture”, and aims at testing whether it is possible to predict yields and optimal sowing dates using seasonal climate information at three sites (Pergamino, Marcos Juarez and Anguil) which are representative of different climate and soil conditions in Argentina. Considering that we focus on the use of climate information only, and that official long time yield series are not always reliable and often influenced by both climate and technology changes, we decided to build a dataset with yields simulated by the DSSAT (Decision Support System for Agrotechnology Transfer) crop model, already calibrated in the selected three sites and for the two crops of interest (maize and soybean). We simulated yields for three different sowing dates for each crop in each of the three sites. Also considering that seasonal forecasts have a higher skill when using the 3-month average precipitation and temperature forecasts, and that regional climate change scenarios present less uncertainty at similar temporal scales, we decided to focus our analysis on the use of quarterly precipitation and temperature averages, measured at the three sites during the crop cycle. This type of information is used as input (predictand) for non-linear statistical methods (Multivariate Adaptive Regression Splines, MARS; and classification trees) in order to predict yields and their dependency to the chosen sowing date. MARS models show that the most valuable information to predict yield amplitude is the 3-month average precipitation around flowering. Classification trees are used to estimate whether climate information can be used to infer an optimal sowing date in order to optimize yields. In order to simplify the problem, we set a default sowing date (the most representative for the crop and the site) and compare the yield amplitudes between such a default date and possible alternative dates sometimes used by farmers. Above normal average temperatures at the beginning and the end of the crop cycle lead to respectively later and earlier optimal sowing. Using this classification, yields can be potentially improved by changing sowing date for maize but it is more limited for soybean. More generally, the sites and crops which have more variable yields are also the ones for which the proposed methodology is the most efficient. However, a full evaluation of the accuracy of seasonal forecasts should be the next step before confirming the reliability of this methodology under real conditions.     

VULNERABILITY OF AGRONOMIC SYSTEMS IN BULGARIA

In recent years the problem of climate and its variations under the influence of natural processes and factors of anthropogenetic origin has come to the forefront of scientific and practical problems on a world-wide scale. Climate change vulnerability assessments of agronomic systems in Bulgaria have been initiated. In this paper preliminary results of this study are presented. Different climate change scenarios were defined. Global circulation model (GCM) scenarios and incremental scenarios for Bulgaria were created and applied. The influence of climate change on potential crop growing season above a base of 5° and 10 °C in Bulgaria was investigated. Increases in temperature can be expected to lengthen the potential growing season, resulting in a shift of thermal limits of agriculture in Bulgaria. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 2.1 was used to assess the influence of climate change on grain yield of maize and winter wheat. Maize and winter wheat yields decreased with increasing temperatures and decreasing precipitation.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

PNNLs Agriculture and Land Use is used to demonstrate the impact of potential changes in climate on agricultural production and land use in the United States. AgLU simulates production of four crop types in several world regions, in 15-yr time steps from 1990 to 2095. Changes in yield of major field crops in the United States, for 12 climate scenarios, are obtained from simulations of the EPIC crop growth model. Results from the HUMUS model are used to constrain crop irrigation, and BIOME3 model is used to simulate productivity of unmanaged ecosystems. Assumptions about changes in agricultural productivity outside the United States are treated on a scenario basis, either responding in the same way as in the United States, or not responding to climate.     

Spatial and temporal changes in vapor pressure deficit and their impacts on crop yields in China during 1980–2008

Vapor pressure deficit (VPD) is a widely used measure of atmospheric water demand. It is closely related to crop evapotranspiration and consequently has major impacts on crop growth and yields. Most previous studies have focused on the impacts of temperature, precipitation, and solar radiation on crop yields, but the impact of VPD is poorly understood. Here, we investigated the spatial and temporal changes in VPD and their impacts on yields of major crops in China from 1980 to 2008. The results showed that VPD during the growing period of rice, maize, and soybean increased by more than 0.10 kPa (10 yr)^–1 in northeastern and southeastern China, although it increased the least during the wheat growing period. Increases in VPD had different impacts on yields for different crops and in different regions. Crop yields generally decreased due to increased VPD, except for wheat in southeastern China. Maize yield was sensitive to VPD in more counties than other crops. Soybean was the most sensitive and rice was the least sensitive to VPD among the major crops. In the past three decades, due to the rising trend in VPD, wheat, maize, and soybean yields declined by more than 10.0% in parts of northeastern China and the North China Plain, while rice yields were little affected. For China as a whole, the trend in VPD during 1980–2008 increased rice yields by 1.32%, but reduced wheat, maize, and soybean yields by 6.02%, 3.19%, and 7.07%, respectively. Maize and soybean in the arid and semi-arid regions in northern China were more sensitive to the increase in VPD. These findings highlight that climate change can affect crop growth and yield through increasing VPD, and water-saving technologies and agronomic management need to be strongly encouraged to adapt to ongoing climate change.     

气候变化对作物产量影响的动态统计评价模式

气候变化对作物产量影响的动态统计评价模式，主要是运用积分回归原理，探索作物生育期内以旬为时间单位的气候变化对作物产量形成的影响规律。由于该模式能及时连续地进行气候影响评价，使评价工作能直接的为农业生产进行跟踪服务。在建模过程中引用了三项式产量预报模型、特殊影响因子诊断分析和选取最佳积分因归方程等方法，并在试用中取得了较满意的结果。     

中国农业气象模式(CAMM1.0)构建与应用

为发展适宜中国区域农业种植特点的农业气象模式,基于国外作物生长模拟方法,通过模式机理过程改进或重构以及应用方式革新,建立了中国农业气象模式（Chinese AgroMeteorological Model version 1.0,CAMM1.0）。CAMM1.0利用平均温度和土壤水分改进了作物发育进程模式,利用土壤水分改进了作物叶片光合作用、干物质分配和叶面积扩展过程模式,通过蒸发比法扩展了作物蒸散过程模式;自主建立了基于发育进程的冬小麦株高、基于遥感信息的作物灌溉、遥感数据同化、作物长势与灾害评价等模式。基于互联网技术构造了实时运转平台,主要功能包括作物生长过程实时常规模拟与用户个性化定制模拟。CAMM1.0的部分子模式采用多种方法构造,便于多模式集成。CAMM1.0对作物发育进程、光合过程、株高的模拟效果较好,但对土壤水分变化过程的拟合略差,模拟产量略偏低。CAMM1.0评价淮河流域夏玉米年际干旱减弱而涝渍增加的趋势与实际基本相符。     

作物长势评估指数的设计与应用

合理有效地开展作物长势评估,可以及时反映作物生长状况及其对天气气候条件的响应。由于WOFOST模型、ORYZA2000模型在模拟冬小麦、玉米和水稻生长发育过程具备较强机理性,研究基于2001年以来全国冬小麦、玉米、水稻主产区逐日模拟的作物发育进程、叶面积指数和地上总生物量,通过隶属函数构建评估指数,开展高时空分辨率的作物长势评估。结果表明:长势综合评估指数在作物生长前期以发育进程、叶面积指数和地上总生物量三要素加权集合表征,中后期以发育进程和地上总生物量与穗重相关性的加权集合表征;长势评估指数与常规地面观测和遥感长势监测一致性较好,可以反映天气气候条件影响。在作物生长季内,以日为单位构建了作物长势评估指数数据库;根据长势评估指数将作物长势分为长势好、长势偏好、长势持平、长势偏差、长势差,实现空间上的长势监测、对比;以空间集成的方式,开展省级作物长势对比分析;利用长势评估指数变化反映典型天气气候条件对作物生长发育的影响。上述基于作物模型的作物长势评估指数符合现代化农业气象科研与业务服务发展的需求。     

Ammonia emission from subtropical crop land area in India

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.     

基于GRACE数据的天山阿克苏河流域水储量变化分析

水储量变化可视为气候变化对水文系统影响的指示器。基于GRACE数据,结合气候数据和冰川积雪数据,分析了近10 a年来阿克苏河流域的水储量变化。研究结果表明:(1)过去10 a间阿克苏河流域的水储量呈递减趋势,减少速率为-0.12±0.85 cm/a,且春季表现为正距平,而秋季表现为负距平;(2)山区冰川退缩和积雪消融是该流域山区水储量减少的主要原因,近半个世纪以来冰川物质平衡为负平衡,同时近十年来积雪面积递减速率为-24 km~2/a;(3)阿克苏河流域的耕地面积的迅速增加导致了地下水过度超采,是绿洲区水储量减少的主要驱动因子。     

阿克苏河灌区作物需水量对气候变化的敏感性分析

阿克苏河灌区是中纬度干旱区典型的绿洲灌溉系统,同时也是新疆第二大灌区,了解灌区作物需水量可为灌区种植结构调整、水资源优化配置提供科学依据。本研究基于联合国粮农组织(FAO)的Penman-Monteith蒸散发模型,结合作物系数法估算了阿克苏灌区作物需水量的时空变化及其对气候因子和作物种植结构的敏感性。结果表明,1960—2015年阿克苏灌区多年平均作物需水量为586 mm,且呈显著上升趋势,上升速率为38.43 mm/10 a。随着气候变化和作物种植结构的改变,1990—2015年间作物需水量急剧增加,增加速率高达99.37 mm/10 a。对于不同作物类型,果林的需水量最大,高达829.8 mm,其次是棉花、水稻和玉米,小麦需水量最低。阿克苏灌区的作物需水量对日最高气温和日照时数较为敏感,而对最低气温、风速和水汽压的敏感度较低。当日最高气温升高2℃时,作物需水量增加4%,当日照时数增加10%时,作物需水量将增加3.2%。另外,作物需水量对作物种植结构非常敏感,当果林的种植面积比例增加10%时,作物需水量增加了12.1%。