Remote sensing of biotic and abiotic stress for irrigation management of cotton

The applicability of commercially available remote sensing instrumentation was evaluated for site-specific management of abiotic and biotic stress on cotton (Gossypium hirsutum L.) grown under a center pivot low energy precision application (LEPA) irrigation system. This study was conducted in a field where three irrigation regimes (100%, 75%, and 50% ET_c) were imposed on areas of Phymatotrichum (root rot) with the specific objectives to (1) examine commercial remote sensing instrumentation for locating areas showing biotic and abiotic stress symptomology in a cotton field, (2) compare data obtained from commercial aerial infrared photography to that collected by infrared transducers (IRTs) mounted on a center pivot, (3) evaluate canopy temperature changes between irrigation regimes and their relationship to lint yield with IRTs and/or IR photography, and (4) explore the use of deficit irrigation and the use of crop coefficients for irrigation scheduling. Pivot-mounted IRTs and an IR camera were able to differentiate water stress among irrigation regimes. The IR camera distinguished between biotic (root rot) and abiotic (drought) stress with the assistance of groundtruthing. The 50% ET_c regime had significantly higher canopy temperatures than the other two regimes, which was reflected in significantly lower lint yields when compared to the 75% and 100% ET_c regimes. Deficit irrigation down to 75% ET_c had no impact on lint yield, indicating that water savings were possible without reducing yield.     

Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches

Different methods have been developed to estimate evapotranspiration from remote sensing data, from empirical approaches such as the simplified relationship to complex methods based on remote sensing data assimilation along with SVAT models. The simplified relationship has been applied from small spatial scale using airborne TIR images to continental scale with NOAA data. Assimilation procedures often require remote sensing data over different spectral domains to retrieve input parameters which characterize surface properties such as albedo, emissivity or Leaf Area Index. A brief review of these different approaches is presented, with a discussion about the main physical bases and assumptions of various models. The paper reports also some examples and results obtained over the experimental area of the Alpilles Reseda project, where various types of models have been applied to estimate surface fluxes from remote sensing data.     

Diagnosis of regional evaporation by remote sensing to support irrigation performance assessment

The success of water management in large irrigation schemes with composites of soil, crop, wetness and micro-meteorological conditions is difficult to quantify. Performance assessment indicators, being among others a function of evaporation, are useful tools to evaluate the actual functioning of an irrigation system. The inevitable spatial variability of evaporation in large irrigation schemes makes its determination with conventional point measurements almost impossible. A new remote sensing evaporation parameterization algorithm has been tested with high resolution Landsat Thematic Mapper data for the Eastern Nile Delta, Egypt. Although the implementation of such an algorithm requires assumptions to be made, the current case study shows that these assumptions do not hamper the estimation of actual and potential evaporation at regional scale. The actual evaporation has been used to express the uniformity of crop water use which is related to the equity of irrigation water distribution. The coefficient of variance in actual evaporation between 53 differenent irrigation districts is 10% on average. The relative evaporation was considered to determine whether the crop was adequately irrigated. The relative evaporation was more than 75% for 48 out of 53 irrigation districts. It is concluded, that improved information on actual crop growth conditions through remote sensing provides an essential insight into the planning of real-time and seasonal irrigation water deliveries.     

An entropy approach to spatial disaggregation of agricultural production

While agricultural production statistics are reported on a geopolitical – often national – basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agroecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach, tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels’ – typically 25–100 square kilometers in size. The information utilized includes crop production statistics, farming system characteristics, satellite-derived land cover data, biophysical crop suitability assessments, and population density. An application is presented in which Brazilian state level production statistics are used to generate pixel level crop production data for eight crops. To validate the spatial allocation we aggregated the pixel estimates to obtain synthetic estimates of municipality level production in Brazil, and compared those estimates with actual municipality statistics. The approach produced extremely promising results. We then examined the robustness of these results compared to short-cut approaches to allocating crop production statistics and showed that, while computationally intensive, the cross-entropy method does provide more reliable estimates of crop production patterns.     

拖拉机液压提升能力试验加载方案的对比研究

综述了国内外拖拉机液压提升能力试验的几种加载方案，并就其优缺点进行了探讨，给出了一种适于基层单位进行液压提升器检测维修的经济型方案。     

基于多源数据融合的盐分遥感反演与季节差异性研究

为提高多光谱盐分遥感反演的精度,利用实测高光谱与多光谱进行数据融合,并分析了不同季节盐分遥感的差异性。以河套灌区永济灌域为研究区域,以实测光谱仪测定的土壤高光谱数据和Landsat-8 OLI多光谱数据为基础,通过光谱变换和多元逐步回归方法筛选特征波段和特征光谱指数,构建了春、秋两季土壤盐分多光谱、高光谱反演模型,并利用特征光谱指数的线性回归构建了高-多光谱数据融合反演模型。结果表明:高光谱的反射率总体比多光谱高36. 83%,春季反射率比秋季平均高23. 78%。利用模型中最优变量-特征光谱指数对多光谱模型与高光谱模型进行融合,高-多光谱融合反演模型训练集和验证集R2平均值分别为0. 651和0. 635,RMSE平均值分别为2. 44 g/kg和2. 49 g/kg,精度明显高于对应的多光谱反演模型,其中训练集、验证集的R2平均值分别提高了36. 19%和35. 64%,RMSE平均值分别降低了34. 28%和41. 72%。春季多光谱、高光谱和融合反演模型的精度均高于秋季,其中训练集R2平均值比秋季模型分别提高了6. 03%、6. 05%和4. 40%,验证集R2平均值分别提高了19. 07%、12. 21%和1. 75%。构建的高-多光谱融合模型反演灌域春秋两季平均盐分含量分别为6. 05、5. 97 g/kg,平均相对误差分别为9. 65%和10. 68%,总体上该区域春季土壤主要为重盐化土,秋季土壤主要为中盐化土。     

农网电力负荷中期预测方法探讨

电力负荷中期预测是指未来3～5年的负荷预测,是制定电力系统发展规划的基础,也是规划工作的重要组成部分,其目的是为合理地安排电源和电网建设进度提供宏观决策的依据,使电力建设满足国民经济增长和人民生活水平提高的需要。为此,通过对各种预测方法及特点的分析比较,得出用灰色模型预测方法作为农网电力负荷中期预测的方法,且该方法所需原始数据少、误差小、精度高。     

作物茎秆膨胀收缩监测柔性可穿戴传感器研制与试验

作物茎秆膨胀和收缩变化与其水分状态密切相关,实时监测茎秆的膨胀和收缩变化能够及时掌握作物水分状态,对指导灌溉、提高农业水资源利用率具有重要意义。目前,对于作物茎秆膨胀和收缩变化的监测主要采用基于线性微位移测量原理的传感器,通过测量茎秆的膨胀和收缩引起的位移变化来反映水分状态,存在体积大、价格高、安装不便等问题。为此,该研究提出了一种基于压阻效应的柔性可穿戴传感器,采用柔性压力电极作为传感元件,贴附在作物茎秆表面,通过监测茎秆膨胀和收缩引起的压力变化来反映作物的水分状态,压力检测电路和数据采集电路将作物茎秆的压力信号转换成电信号进行输出和存储。首先在实验室环境下对传感器性能进行测试和标定,然后在温室环境下将传感器安装在番茄茎秆上观测番茄茎秆的压力变化,并与线性微位移传感器观测结果进行比较,最后在充分灌溉和水分亏缺2种条件下观测番茄茎秆的膨胀和收缩变化。结果表明,柔性压力传感器稳定性测试的平均相对变化率为0.109%;弯折前后引起的输出变化非常小,可以忽略不计;标定结果的决定系数大于0.99,最合适的工作压力范围为2～100 kPa;实验室环境下,柔性压力传感器与线性微位移传感器输出值之间的决定系数为0.9551;温室环境下,充分灌溉组中柔性压力传感器与线性微位移传感器输出值变化趋势一致,两者之间的决定系数为0.7672,亏缺灌溉组中两类传感器输出值均因水分亏缺而呈现下降趋势,输出值之间的决定系数为0.8519。本文所设计的柔性可穿戴压力传感器不仅能够实时监测番茄茎秆的膨胀和收缩变化,还可以对番茄亏水胁迫进行诊断,为实现高效节水灌溉提供重要的技术支撑。     

Spectral indices measured with proximal sensing using canopy reflectance sensor, chlorophyll meter and leaf color chart for in-season grain yield prediction of basmati rice

A number of optical sensing tools are now available and can potentially be used for refining need-based fertilizer nitrogen (N) topdressing decisions.Algorithms for estimating field-specific fertilizer N needs are based on predictions of yield made while the crops are still growing in the field.The present study was conducted to establish and validate yield prediction models using spectral indices measured with proximal sensing using GreenSeeker canopy reflectance sensor,soil and plant analyzer ...     

灯泡贯流式水轮机增减负荷动态特性分析

水轮机频繁经历变负荷工况转换过程,使得机组在较短时间内工作参数急剧变化,严重影响电站稳定运行。该研究以某贯流式水轮机为研究对象,在考虑自由液面和水体重力的情况下,采用动网格技术对贯流式水轮机相同出力范围下的减、增负荷过渡过程的动态特性进行分析。研究结果表明：由于增负荷和减负荷过渡过程的起始工况导致起始流动状态不同,因此在相同出力时,机组内的流动分布不同,减负荷过程尾水管内的涡流面积及强度明显小于增负荷工况,且尾水管涡带尺度也明显小于增负荷过程;相比于增负荷过程,减负荷过程中转轮叶片大范围的低压区极易引发空化;机组内的水压力脉动主要以尾水管涡带引起的0.1fn(fn为转频)低频压力脉动和转轮的旋转引起3fn的高频压力脉动为主,增负荷过程的压力脉动幅值明显大于减负荷过程,两种压力脉动共同作用,使得贯流式水轮机主要振动区域集中于转轮。研究结果对贯流式水轮机的设计与运行具有一定的指导意义。