喷灌工程规划设计多方案选优的语言化与定量化相结合模糊综合评判数学模型

本文提出了喷灌工程规划设计多方案选优的语言化与定量化相结合的模糊综合评判数学模型,从而可得到比传统喷灌工程规划设计方案选优方法更为合理、满意的结果。     

地理信息系统在环境影响评价中的应用

为了研究地理信息系统（GIS）在环境影响评价中的应用，在介绍地理信息系统的组成、类型、功能和应用领域的基础上，分析了GIS技术在环境影响评价中的优势，并结合实例，探讨了地理信息系统在水环境影响评价中的具体应用过程。     

区域水资源可持续利用的未确知测

针对水资源系统是一个具有未确知性特征的复杂大系统。在未确知测度空间基础上，构建了区域水资源可持续利用评价的未确知测度模型，并将该模型应用于西安市水资源开发利用程度的评价。通过单指标未确知测度、多指标综合测度计算以及指标定权等过程，实现对各分区水资源开发利用程度的综合评价与排序。实例研究表明，运用未确知测度模型进行区域水资源可持续利用问题研究，理论上是可行的，评价结果是可信的，这为信息不确定条件下的区域水资源可持续利用评价提供了一种新方法。     

基于灰色关联度变权法的浅层地下水环境质量综合评价

引入指数型白化权函数对灰色关联度变权法中的白化权函数进行修正,使得能够对地下水更合理、客观、准确地评价。将晋江市浅层地下水看作一个灰色系统,在灰色关联度变权法模型基础上,对各水质监测点不同类别的隶属度和灰色关联度作对比分析判断其评价等级以及质量优劣次序,说明灰色关联度变权法对地下水环境质量综合评价方法适当。研究区内绝大多数地区水质状况良好,影响区域地下水质量的指标主要为TDS、锰、硝酸盐、亚硝酸盐、氨氮、氯化物,水质较差区主要分布于沿海工业分布较密集区及引污水灌溉农田地区,说明工农业发展、人类活动加剧及海水入侵是造成本区水质变化的主要原因之一。     

黑龙江省江川灌区灌溉水资源的综合评价

在介绍江川灌区流域概况的基础上，提出了该灌区所面临的地下水灌溉水稻米质差、产量低、大米销路不好等问题的解决办法，即发展地表水灌溉水稻，通过引松花江水来解决灌溉水源；分别对地下水、地表水(松花江水)的水量和水质进行评价。结果表明，该灌区的地下水严重超采、水质中总铁量超标(超6mg/L)，pH值偏碱，不适合用于农业灌溉；地表水(松花江水)除铁离子略高外，其余各项指标均满足灌溉要求，为该灌区引松花江水灌溉水稻提供了较为科学的依据。     

城市生活用水考核指标体系

提出了城市生活用水考核的指标体系。该考核体系分城市生活用水单元和城市总体生活用水两个类型，从生活用水、重复利用、排水、用水管理等4个方面对生活用水进行考核，从而全面的反映城市生活用水情况，对城市生活用水的规范化、科学化管理，促进节约用水将起到积极的作用。     

驾驶员坐姿模型及坐姿舒适性模糊综合评价

依据驾驶员驾驶姿势的特殊性，建立了第5、第50、第95百分位的男女驾驶员杆状、平面、三维坐姿人体模型。综合考虑不同百分位人体模型的坐姿舒适性，建立了驾驶员坐姿舒适性二级模糊综合评价模型，并用实例进行了验证。     

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。     

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。