我国北方地区节水农业技术水平及评价

在系统分析我国节水农业技术水平现状的基础上 ,对各类节水技术的差距和存在问题进行了探讨 ,提出了各类技术亟待研究解决的若干重点问题。并指出建立以渠道防渗技术、管道输水技术及地面灌水技术为核心 ,符合国情的节水农业技术体系已迫在眉睫。     

罗湾水电站引水系统过渡过程研究

为了对罗湾水电站增容前后的引水系统过渡过程和机组增容改造对引水系统建筑物的影响进行研究，应用水击计算方法中的电算法进行计算，得出了调压室最低、最高涌浪水位，蜗壳处最大压力水头和机组转速最大升高。结果表明，电站增容后引水系统完全能满足有关规范和设计的要求。     

基于框架理论的变电站操作票自动生成系统

介绍了一种基于框架理论的变电站操作票自动生成系统。该系统用框架知识表示法来描述电力系统的设备参数，建构了一个直观的、层次分明的数据结构。通过融合框架理论于面向对象的语言VC 中，开发出了一个集通用、实用、智能于一体的操作票专家系统。     

Managing secondary dryland salinity: Options and challenges

Salt occurs naturally at high levels in the subsoils of most Australian agricultural land. As a result of clearing native vegetation, groundwater tables have risen, mobilising the stored salt and causing adverse impacts on farmland, infrastructure, water resources, and biodiversity. The main action required to prevent groundwater tables from rising is establishment of perennial plants, either herbaceous (pastures or crops) or woody (trees and shrubs). Recent technical and economic research has emphasised how difficult it will be to establish sufficient perennials to get control of groundwater tables. Where watertables are already shallow, the options for farmers are salt-tolerant plants (e.g. saltbush for grazing) or engineering (e.g. deep open drains). The existing options for farm-level salinity management are reviewed, with mixed but somewhat disappointing findings regarding their suitability for addressing salinity. However, there are also a number of good prospects for development of new and better options for plant-based management of salinity, and these are described.     

灌溉渠系水利用系数的分析与计算

灌溉渠系的布置形式一般可分为串联渠系、等效并联渠系和非等效并联渠系 ,对这 3种灌溉渠系水利用系数进行了理论研究。用实例验证了上述的理论分析。研究成果可应用于实际灌溉工程     

固定式喷灌系统喷头经济压力的研究

在能源危机的冲击下，节能已成为广大喷灌工作者共同关心的问题。降低喷灌系统工作压力是节能的主要方法之一，而喷头的工作压力与喷灌系统工作压力紧密相关。本文提出了固定式喷灌系统喷头经济压力的概念及其确定方法，并将此法运用到实例中。在选择经济、合理的喷头及其经济工作压力方面做了有意义的探讨。     

Performance of CERES-Rice and CERES-Wheat models in rice–wheat systems: A review

Rice–wheat (RW) systems are critical to food security and livelihoods of rural and urban poor in south Asia and China, and to regional economies in southeast Australia. The sustainability of RW systems in south Asia is, however, threatened by yield stagnation or decline, and declining partial factor productivity, soil organic C and water availability. Crop models potentially offer a means to readily explore management options to increase yield, and to determine trade-off between yield, resource-use efficiency and environmental outcomes. This paper reviews the performance of CERES-Rice and CERES-Wheat in Asia and Australia in relation to their potential application towards increasing resource use efficiency and yield of RW systems.

The performance of the models was evaluated using simulated and observed data on anthesis and maturity dates, in-season LAI and growth, final grain yield and its components, and soil water and N balances from published studies across Asia and Australia, and then by computing the statistical parameters for the major characters. Over the four data sets examined for anthesis and six for maturity dates, CERES-Rice predicted those dates fairly well (normalised RMSE = 4–5%; D-index = 0.94–0.95), but over the 11 sets for grain and 4 for biomass yield, the predictions were more variable (normalised RMSE = 23% for both; D-index 0.90 and 0.76, for grain and biomass, respectively). Model performance was poorer under conditions of low N, water deficit, and low temperatures during the reproductive stages. Over the three data sets examined, CERES-Wheat predicted the anthesis and maturity dates quite well (normalised RMSE = 4–5%; D-index = 0.94–0.99), and over eight sets for grain and two sets for biomass yield the model predicted them also reasonably well (RMSE = 13–16%; D-index = 0.86–0.97). Only one study evaluated the DSSAT RW sequence model with fairly satisfactory predictions of rice and wheat yields over 20 years with adequate N, but not the long-term change in soil organic C and N. Predictions of in-season LAI and crop growth, and soil and water processes were quite limited to investigate the robustness of model processes.

Application of models to evaluate options to increase water and N use efficiency requires the ability to perform well at the margin where deficit stress begins. While both models generally perform satisfactorily under water and N non-limiting conditions, the little evidence available suggests that they do not perform well under resource-limiting situations. We recommend that the models’ key processes under the water and N limiting conditions be further evaluated urgently. The DSSAT sequence model also needs to be further evaluated against observations for a range of locations and management using data from long-term experiments in RW systems.     

支持向量机在水质评价中的应用

介绍了支持向量机算法的原理，建立了基于支持向量机的水质评价多层次分类检测模型，通过提取水质评价标准中的物质成分为特征参数，利用几个SVM分类器的串联组合，实现对水质的分类和识别，同时，引入类权重因子，解决训练样本类别数量不平衡而导致的错分问题，实验结果显示该方法提高了水质评价的准确性和效率。     

EMC单片机技术在粮仓库门控制系统中的应用

介绍了一种基于EMC单片机的粮仓库门自动控制系统.该系统分为红外遥控和接收两部分,其中红外遥控部分通过EM78P153控制红外无线遥控器发射指令信号,而红外接收部分通过接收模块接收到信号后由EM78P447来控制粮仓库门的开、关、停、限位和夜间自动点灯.系统结构简单,功能齐全,具有低成本、低功耗和可靠性高等特点.     

Inverse Modeling to Quantify Irrigation System Characteristics and Operational Management

Remotely sensed (RS) data is a major source to obtain spatialdata required for hydrological models. The challenge for thefuture is to obtain besides the more direct observable data(landcover, leaf area index, digital elevation model andevapotranspiration), non-visible data such as soilcharacteristics, groundwater depth and irrigation practices.In this study we have explore the option of using inversemodeling to obtain these non-RS-visible data. For a commandarea in Haryana, India, we applied for the 2000–2001 rabiseason a RS-GIS-combined inverse modeling approach to derivenon-RS-visible data required in the regional application ofhydrological models. A Genetic Algorithm loaded stochasticphysically based soil-water-atmosphere-plant model (SWAP) wasdeveloped for the inverse problem and used in the study. Theresults showed good agreement with the inventoried data suchas soil hydraulic properties, sowing dates, groundwaterdepths, irrigation practices and water quality. The deriveddata could be used to predict the state of the system at anytime in the cropping season, which can be used to evaluateoperational management strategies.