基于鸡西市第一中学新校区规划建设的思考

在鸡西市第一中学建设新校区的规划设计中,通过对总体布局、交通组织、场区竖向、运动场地及校园绿化等方面做详细的设计思考后再进行规划设计,使其设计效果和使用功能都达到了国家级示范高中的标准,推动了教育改革向更深层次发展。     

农业水利工程专业社会实践教学体系研究

结合四川农业大学农业水利工程专业多年实践教学中积累的研究经验,深刻分析大学生学习心理、社会需求以及专业教育中存在的问题,针对社会实践教育的主要问题,构建新形势下我国农业水利工程专业实践教育体系的新模式,成效显著。     

胆汁引流对黑熊健康状况影响的研究

通过三个实验来研究取胆汁对熊的健康状况的影响。首先,比较了取胆汁熊和没有取胆汁熊的健康状态;其次,比较了引流3年以上的熊和没有进行引流熊的健康状况;最后,比较了不同取胆汁方式熊的健康状况。实验证明,引流取胆汁影响了熊的身体健康,其中,引流取胆汁对熊的危害明显,穿刺取胆汁对熊的危害较小。引流取胆汁对熊的健康影响主要体现在易患胆囊炎症、胆结石,还容易发生脂溶性维生素缺乏症状。     

天山北坡水资源开发对地下水资源的影响及其合理利用

本文论述了包括乌鲁木齐市在内的天山北坡山前平原范围内的地下水资源数量、补给关系及开采利用条件,以及地下水开发后对该地区地下水位、数量、质量及泉水渗出等方面的影响,并对如何合理利用本地区地下水资源提出了意见。     

甘肃秦王川灌区土壤盐分特征及次生盐渍化预测

在秦王川灌区水文地质条件和土壤盐分含量特征调查研究的基础上,采用有限差分法建立了预测模型,对灌溉实施后1～5年间地下水位及其埋深变化进行了预测。结果表明,地下水位呈普遍抬升趋势,可导致约2000ha土地产生次生盐渍化。如果不及时采取防治措施,土壤次生盐渍化面积还会进一步扩大。     

地下室排水系统的设计研究

随着城市建设的发展,地下空间得到了更多的开发和利用。由于各种设计手册和教科书中对关于“地下室排水系统设计”的篇幅较少。为此根据多年的设计经验,总结了不同情况下地下室排水系统设计方法,并对设计中易出现的问题提出了注意事项。     

新疆平原灌区综合排水措施与模式

在总结已有研究成果及实践经验的基础上,结合近期开展的水盐监测与试验研究,综合地下水开发利用、节水节肥、土地资源合理配置以及农业结构调整等成果资料.应用土壤水盐运移理论与系统分析原理,为实现干旱内陆河流域水土资源可持续利用,系统地提出适应于不同地貌单元,不同土壤盐碱化治理阶段的竖井排灌、竖井与水平联合排灌、水平排水等工程措施,以及利用自然与人造微地形情况下的农田干排盐、生物排盐措施.     

双重排水条件下控制措施对银南灌区水稻田水盐关系的影响分析

针对宁夏银南灌区目前存在的排水过量问题,研究者提出了利用控制排水措施,在适当时段减少排水量的建议。然而,灌区在农沟以及更深层的支、干沟及黄河(低地)的影响下,受着深层排水和浅层排水的双重作用。其中深层排水一般不会受到田间措施的影响,它的存在“淡化或中和”了由于浅层排水的减少引起的田间含盐量的增加。本文在对双重排水情况下的水盐运动进行概化的基础上,建立了基于特定地区排水特性的“浅层排水与深层排水比-浅层排水控制率-排水含盐量增加率”的关系。最后结合根据地下水洗淋的临界情况,确定了达到这一目标控制指标以及浅层地下水控制率。结果显示,对于研究的典型情况,当地下水的盐分含量达到临界的1.62 g/l时,可以将1m深的农沟控制至30cm深;这时的浅层地下水仅为现状的14%,即从731mm减少到了102mm。     

Quantifying the nitrogen retention capacity of natural wetlands in the large-scale drainage basin of the Baltic Sea

We estimate the nitrogen retention capacity of natural wetlands in the 1.7 million km² Baltic Sea drainage basin, using a wetland GIS data base. There are approximately 138,000 km² of wetlands (bogs and fens) in the Baltic Sea drainage basin, corresponding to 8% of the area. The input of nitrogen to natural wetlands from atmospheric deposition was estimated to 55,000–161,000 ton y¹. A map of the deposition of both wet and dry nitrogen is presented. The input from the human population was estimated to 255,000 ton y¹ in terms of excretory release in processed sewage water. There may also be leakage from forests and agricultural land into the wetlands. Due to lack of data on hydrology and topography, such potential nitrogen sources are not accounted for here. The capacity of the wetlands to retain the atmospheric deposition of nitrogen was estimated to 34,000–99,000 ton y¹. The potential retention by wetlands was estimated to 57,000–145,000 ton y¹ when the nitrogen input from the human population was added. If drained wetlands were to be restored and their area added to the present wetland area, the nitrogen retention capacity was estimated to increase to 196,000–261,000 ton y¹. Our results indicate that existing natural wetlands in the Baltic Sea drainage basin annually can retain an amount of nitrogen which corresponds to about 5–13% of annual total (natural and anthropogenic) nitrogen emissions entering the Baltic Sea. The ecosystem retention service performed by wetlands accounts for a substantial nitrogen removal, thereby reducing the eutrophication of the Baltic Sea.     

A model of arctic tundra vegetation derived from topographic gradients

We present a topographically-derived vegetation model (TVM) that predicts the landscape patterns of arctic vegetation types in the foothills of the Brooks Range in northern Alaska. In the Arctic there is a strong relationship between water and plant structure and function and TVM is based on the relationships between vegetation types and slope (tan ) and discharge (), two independent variables that can be easily derived from digital terrain data. Both slope and discharge relate to hydrological similarity within a landscape: slope determines the gravitational hydrological gradient and hence influences flow velocity, whereas discharge patterns are computed based on upslope area and quantify lateral flow amount. TVM was developed and parameterized based on vegetation data from a small 2.2 km² watershed and its application was tested in a larger 22km² region. For the watershed, TVM performed quite well, having a high spatial resolution and a goodness-of-fit ranging from 71–78%, depending on the functions used. For the larger region, the strength of the vegetation types predictions drops somewhat to between 56–59%. We discuss the various sources of error and limitations of the model for purposes of extrapolation.