Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration,crops coefficients,leaf area index and remotely-sensed vegetation indices

The monitoring of crop production and irrigation at a regional scale can be based on the use of ecosystem process models and remote sensing data. The former simulate the time courses of the main biophysical variables which affect crop photosynthesis and water consumption at a fine time step (hourly or daily); the latter allows to provide the spatial distribution of these variables over a region of interest at a time span from 10 days to a month. In this context, this study investigates the feasibility of using the normalised difference vegetation index (NDVI) derived from remote sensing data to provide indirect estimates of: (1) the leaf area index (LAI), which is a key-variable of many crop process models; and (2) crop coefficients, which represent the ratio of actual (AET) to reference (ET₀) evapotranspiration.A first analysis is performed based on a dataset collected at field in an irrigated area of the Haouz plain (region of Marrakesh, Central Morocco) during the 2002–2003 agricultural season. The seasonal courses of NDVI, LAI, AET and ET₀ have been compared, then crop coefficients have been calculated using a method that allows roughly to separate soil evaporation from plant transpiration. This allows to compute the crop basal coefficient (K_cb) restricted to the plant transpiration process. Finally, three relationships have been established. The relationships between LAI and NDVI as well as between LAI and K_cb were found both exponential, with associated errors of 30% and 15%, respectively. Because the NDVI saturates at high LAI values (>4), the use of remotely-sensed data results in poor accuracy of LAI estimates for well-developed canopies. However, this inaccuracy was not found critical for transpiration estimates since AET appears limited to ET₀ for well-developed canopies. As a consequence, the relationship between NDVI and K_cb was found linear and of good accuracy (15%).Based on these relationships, maps of LAI and transpiration requirements have been derived from two Landsat7-ETM+ images acquired at the beginning and the middle of the agricultural season. These maps show the space and time variability in crop development and water requirements over a 3 km × 3 km irrigated area that surrounds the fields of study. They may give an indication on how the water should be distributed over the area of interest in order to improve the efficiency of irrigation. The availability, in the near future, of Earth Observation Systems designed to provide both high spatial resolution (10 m) and frequent revisit (day) would make it feasible to set up such approaches for the operational monitoring of crop phenology and irrigation at a regional scale.     

A Comparison of Satellite-Derived Vegetation Indices for Approximating Gross Primary Productivity of Grasslands

Gross primary productivity (GPP) is a key component of ecosystem carbon fluxes and the carbon balance between the biosphere and the atmosphere. Accurate estimation of GPP is essential for quantifying plant production and carbon balance for grasslands. Satellite-derived vegetation indices (VIs) are often used to approximate GPP. The widely used VIs include atmospherically resistant vegetation index, enhanced vegetation index (EVI), normalized difference greenness index, normalized difference vegetation index, reduced simple ratio, ratio vegetation index, and soil-adjusted vegetation index (SAVI). The evaluation of the performance of these VIs for approximating GPP, however, has been limited to one or two VIs and/or using GPP observations from one or two sites. In this study, we examined the relationships between the nine VIs derived from the moderate resolution imaging spectroradiometer (MODIS) and tower-based GPP at five eddy covariance flux sites over the grasslands of northern China. Our results showed that the nine VIs were generally good predictors of GPP for grasslands of northern China. Overall, EVI was the best predictor. The correlation between EVI and GPP also declined from the south to the north, indicating that EVI and GPP exhibited closer relationships in more southerly sites with higher vegetation cover. We also examined the seasonal influence on the correlation between VIs and GPP. SAVI exhibited the best correlation with GPP in spring when the grassland canopy was sparse, while EVI exhibited the best correlation with GPP in summer when the grassland cover was dense. Our results also showed that VIs could capture variations in observed GPP better in drought period than in nondrought period for an alpine meadow site because of the suppression of vegetation growth by drought.     

基于HJ-CCD数据的水稻洪涝灾情诊断分析及长势监测

It has great significance to study quick monitoring of rice flood disaster and applying timely remedial measures in the disaster area.LAI is a very important physiological parameter in crop growth characterization index, which can reflect the crop growing information objectively.The existing methods of flood monitoring using remote sensing technology rarely consider the damage and the post disaster growth of rice.The HJ-CCD data take advantage of high temporal resolution and high spatial resolution remote sensing image, which can be used for gathering rice growing information during the critical period.The growth situation after rice flood disaster in Anhui Province was monitored using 3 screens HJ-CCD data as the data source on 16th July, 19th August, 26th August, 2009, respectively.The semi-empirical function model based on Beer-Lambert laws was constructed for this inversion LAI.And LAI were acquired in each stage after flood disaster, the trend of growth diagnosis dynamic change was analyzed and assessed by rice flood disaster evaluation indicator.At the same time, the 40 field investigate data were used to verify the model and the R2=0.4251, RMSE=2.053.The results show that LAI can be well evaluated the degree of rice flood disaster growth based on HJ-CCD data, and it is effective for monitoring and diagnosing rice flood disaster.The results provide a theoretical basis for rice flood disaster research, post disaster rehabilitation and recovery, and provide a theoretical basis for the implementation of targeted remedial measures at the same time.     

非气候因素对草原植物生产力影响的最大熵研究

基于最大熵原理在生态位模拟中的应用及据此开发出来的软件MAXENT-V3.3.3k,以野外调查获得的植物种地理分布信息和相应的气候变量作为适生性评估输入,在优化变量的最佳配置下,评估该物种的适生性;借助类似于气孔导度理论的环境变量函数乘合模型(即可分离变量假设),能够区分物种对气候变量、非气候变量和人为影响的响应。对小针茅1984—1995年连续12年的模拟结果显示,评估很好地再现了小针茅产量的年际变化趋势,成功地创建了样本的单位面积产量正比于该局地适生性的简单关系;支持过度利用草原是小针茅植物退化的主要原因。     

夏玉米产量时空变化及气候年型分析

定量分析夏玉米同一品种产量及产量构成要素时空变化,探讨造成产量时空差异的气候年型组合变化特征。基于2004～2013年夏玉米种植区郑单958多点田间试验数据分析表明,夏玉米区域平均产量为9 055 kg/hm~2,年际差为1 635 kg/hm~2,变幅为18.1%;地点差4 258 kg/hm~2,变幅为47.1%。夏玉米区域平均千粒重为313 g,年际变幅为13.1%;地点变幅为27.8%。夏玉米区域平均穗粒数为479,年际变幅为18.0%,地点变幅为38.7%。千粒重的增加导致夏玉米产量显著增加。穗粒数显著降低和时空差异大是造成产量波动和时空差异变幅大的主要原因。夏玉米产量和产量构成要素,低产点受各气候要素变化的影响显著;平产点受温度和日最高温度大于33℃的天数影响显著;高产点受降水影响显著。     

Density and relative frequency effects on competitive interactions and resource use in pea–barley intercrops

Intercropping advantages may be influenced by both plant density and relative frequency of the intercrop components. In a field study barley (Hordeum vulgare L.) and pea (Pisum sativum L.) were sole cropped and intercropped at three densities and with two relative frequencies when intercropped.Earlier seedling emergence gave barley an initial growth advantage, assessed using the relative efficiency index (REIc), whereas pea was in general more growth efficient once the initial growth phase had been passed. This reversal in relative growth efficiency along with the observation that early barley dominance did not appear to suppress pea growth indicates that differences in phenology played a role in shaping the prevailing dynamics. Whereas increases in plant density had a positive effect on the growth of pea, the growth of intercropped barley was severely limited by increases in density at the end of the growing period and more so in the pea dominated intercrop. At the final harvest land equivalent ratios (LER) of 0.9–1.2 express resource complementarity in almost all studied intercrops, complementarity that was not directly affected by changes in plant density or relative frequency.Intercropped pea did not increase its reliance on atmospheric nitrogen fixation compared to the pea sole crop. With respect to soil nitrogen uptake there were no effect of plant density but a strong effect of the relative frequency of pea in the intercrop, the greater the proportion the lower the uptake.Changes in the competitive strength of the pea and barley crop over the growing season had a marked effect on the proportion of pea in the final grain yields of the intercrops. At low and recommended density the proportions of pea and barley in the final grain yield was not markedly different from the expected proportions sown; however, at high density the suppression of barley strongly increased the proportion of pea in the final grain yield.Weed infestation levels decreased as density was raised and the suppressing effect of density was clearly stronger the greater the frequency of pea in the crop. Earlier germination and tillering ability of barley are seen as likely explanations of lower weed load in the barley dominated crop treatments.This study points at the potential of employing density and relative crop frequency as “regulators” when specific intercrop objectives such as increased competitiveness towards weeds or specific grain yield composition are wanted.     

自动观测与人工观测土壤温度差异及分析

利用我国基本(准)站在人工观测与自动观测双轨运行期间的平行观测资料,分析了不同观测方式下各层土壤温度的差异.结果表明,全国平均自动与人工观测各层土壤温度的日对比差值均在0.11℃以下,且日对比差值随着深度的增加而减小.从5 cm到320 cm,无论冬季还是夏季,全国绝大部分地区平均对比差值在±0.2℃之间.由浅至深各层土壤温度日对比差值的标准差从0.78℃减小至0.47℃,其不确定度在5～ 20 cm时均超过了1.0℃,但在深层(40 cm及以下),不确定度已经低于1.0℃.除极个别站外,各层自动与人工观测日平均值无显著性差异.自动与人工观测土壤温度的差异主要是由于土壤中水平温度场分布非均匀和土壤垂直温度梯度很大及对比观测时间不同步造成的.     

玉米生长后期的根系分布研究

为了研究玉米生长后期根系的生长发育规律,利用中国气象局固城农业气象试验站大型根剖面系统,采用微根管观测系统及方形整段标本法和地下根系室玻璃窗,对‘屯玉46号’玉米根系的生长状况进行了试验研究。结果表明:垂直方向上,方形整段标本法和微根管法测得的根长密度占整层总根长密度比例的变化趋势一致,相关系数分别为0.987和0.717,且两种方法在0~20 cm土层的根长密度比例均为最大。0~60 cm土层为玉米根系生长活跃区,方形整段标本法测得根长密度生长量为其余层的4倍。两种方法测得的根长密度无显著差异,相关系数为0.830,均匀性水平较好。玉米成熟期根系的水平幅度较乳熟期窄,下层根系仍处于生长中,垂直深度增加。玻璃窗与方形整段标本法观测的根深测定结果存在差异,这可能与观测环境条件不一致有关。