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。     

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。     

参数投影寻踪模型在农村公路交通发展综合评价的应用

农村公路建设是农业和农村经济赖以发展的重要基础设施．是推进社会主义新农村建设的重要内容。通过对各个省份农村公路建设的综合评价，可以找出各地区农村公路发展规模的差距，并指出优先发展的指标。以往的评价多采用模糊综合评判技术，不可避免地存在人为赋予权重的干扰，导致评价结果的出入。为此，采用新兴的降维技术一投影寻踪评价模型，通过改进遗传算法来优化投影寻踪模型多维参数．建立了4省农村公路交通发展的基于改进遗传算法的参数投影寻踪综合评价模型。有效地克服了主观赋予权重的干扰．取得了满意效果；同时，指出了各个省份发展农村公路建设优先考虑的指标顺序，为该方面研究提供了新的思路与研究方法。     

辽河流域防洪系统综合评价指标体系研究

随着我国许多流域防洪体系建设的逐渐完善和水利部门防洪思路的逐渐改变，对流域防洪系统进行综合评价显得很有必要，而要进行防洪系统综合评价首先要建立评价指标体系。阐述了社会系统、经济系统和防洪系统之间的既相互制约又相互促进的关系，说明三者处于一种动态的协调平衡中；结合三者之间的关系，从辽河流域实际情况出发，考虑资料收集的可行性，以全面而精练为准则，分别建立了社会系统、经济系统和防洪系统指标体系，以期对辽河流域防洪系统进行全面、客观的科学评价。该指标体系结合实际作适当修改可以应用于其他流域的防洪系统评价中。