三峡库区武隆县地质灾害研究

武隆县是三峡库区地质灾害较为严重的城镇之一,滑坡、危岩、崩塌、泥石流等地质灾害分布广,危害程度大,严重地制约着地方经济和社会的可持续发展。在大量野外调查的基础上,分析了该地区地质灾害的主要类型及其分布特征,从地形地貌、岩土体性质、地下水、降雨、人类工程活动等方面总结了地质灾害成灾机理。在此基础上,进一步提出了该地区地质灾害的防治对策和措施,力求有效地预防和减少地质灾害的发生。     

Good deposits are not enough: Mining labor productivity analysis in the copper industry in Chile and Peru 1992–2009

Chile and Peru produce almost 45% of world’s mine copper output. This situation reflects their natural endowment and mining tradition, but is also the result of development processes undertaken over the last decades. As a result, both countries multiplied its mine copper production in more than 3 times in the last 20 years. Mining labor productivity played a central role achieving these amazing growth rates. Although there is a consensus about the relevance of this variable for the mining industry, the specific factors behind labor productivity changes are not completely understood.     

非营养缺陷型原生质体融合选育角蛋白酶生产菌

以两性霉素B抗性作为标记,通过单株灭活,进行栖土曲霉种内非营养缺陷型原生质体融合.在40%的PEG(Mr＝6000)促融下,融合频率为1.62×10-5.连续传接10代后,获得稳定的融合子.对孢子体积、核DNA含量、生长速度进行了测定,并利用RAPD技术分析比较了亲本及融合子的基因组DNA指纹多态性,证明融合子为杂合二倍体,产角蛋白酶活力较亲本显著提高.图3表4参17     

安徽地区近45年蒸发皿蒸发量变化特征及影响因素初探

利用线性倾向性估计和Mann Kendal检验方法,研究了过去的45年（1963~2007年）安徽地区32个代表站 20 cm 口径蒸发皿蒸发量的变化特征。结果表明：（1）安徽地区蒸发皿蒸发量呈现明显下降趋势（-65.3 mm/10 a，信度001），年蒸发总量在1976年发生突变，1982年显著减少，夏季突变最为明显；（2）32个代表台站中24个台站蒸发皿蒸发量表现为显著下降趋势，仅1个表现为上升趋势（信度005），在空间上减少趋势基本呈现“北多南少”的态势。结合其它气候要素研究发现：气温显著升高，蒸发量明显减少，即安徽地区存在“蒸发悖论”规律，但气温与蒸发量之间相关性不明显；日照，日较差和风速存在显著减少趋势，相关性〖JP+1〗分析表明它们是影响蒸发皿蒸发量减少的最重要因子；低云量，降水量和相对湿度等要素本身没有明显变化趋势但对蒸发皿蒸发量的减少作用也不可忽视。     

非电力驱动多用途系列喷射式吸风器研制与应用

给出喷射式吸风器的结构及其工作原理;介绍了喷射器的性能与特点;笔者运用喷射器在大型化肥塔类设备内外施焊、等离子切割、球罐喷砂、箱式电炉模壳焙烧及马达线圈高温浸漆等10个不同施工场所进行了实际应用和验证,结果表明,该系列吸风器通风换气或排烟、排尘、排毒等性能安全可靠,且使用效果良好;同时,进一步研讨了改进和完善喷射式吸风器的有关技术问题。     

A Comparison of Statistical Approaches for Predicting Stream Temperatures Across Heterogeneous Landscapes1

Abstract: Estimating stream temperatures across broad spatial extents is important for regional conservation of running waters. Although statistical models can be useful in this endeavor, little information exists to aid in the selection of a particular statistical approach. Our objective was to compare the accuracy of ordinary least‐squares multiple linear regression, generalized additive modeling, ordinary kriging, and linear mixed modeling (LMM) using July mean stream temperatures in Michigan and Wisconsin. Although LMM using low‐rank thin‐plate smoothing splines to measure the spatial autocorrelation in stream temperatures was the most accurate modeling approach; overall, there were only slight differences in prediction accuracy among the evaluated approaches. This suggests that managers and researchers can select a stream temperature modeling approach that meets their level of expertise without sacrificing substantial amounts of prediction accuracy. The most accurate models for Michigan and Wisconsin had root mean square errors of 2.0‐2.3°C, suggesting that only relatively coarse predictions can be produced from landscape‐based statistical models at regional scales. Explaining substantially more variability in stream temperatures likely will require the collection of finer‐scale hydrologic and physiographic data, which may be cost prohibitive for monitoring and assessing stream temperatures at regional scales.     

融雪剂对大叶黄杨生长和生理特性的影响

为了研究融雪剂对道路绿化植物的影响,以大叶黄杨（Euonymus japonicus Thunb）为研究材料,研究了其在3种融雪剂（JLR-01、LBR-4、芦笛一号）不同施用量影响下的生长量和生理特性。结果表明：随着融雪剂LBR-4和芦笛一号的施用量的增大,大叶黄杨叶片的相对生长量和株高相对生长量、光合速率（Pn）、水分利用效率（WUE）、蒸腾速率（Tr）和气孔导度（Gs）随之减小,而低施用量的融雪剂JLR-01对大叶黄杨生长量、Pn、WUE和Tr有促进作用。随着融雪剂作用时间的延长,3种融雪剂的Pn和WUE也随之减小,Tr则是先减小后有所增大。当融雪剂施用量较小和胁迫时间较短时,Pn下降是因为气孔关闭;而当施用量较大和胁迫时间较长时,Pn下降是因为叶肉同化能力下降;3种融雪剂对大叶黄杨的胁迫程度由大到小的次序为：芦笛一号〉LBR-4〉JLR-01;大叶黄杨对3种融雪剂施用量的忍耐阈值在80 g.m-2左右,大叶黄杨对施用LBR-4和芦笛一号的耐受时间阈值大约为3周,对施用JLR-01的耐受时间阈值为3周以上。     

Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.     

Achieving sustainability goals for urban coasts in the US Northeast: research needs and challenges

In the wake of Hurricane Sandy and other recent extreme events, urban coastal communities in the northeast region of the United States are beginning or stepping up efforts to integrate climate adaptation and resilience into long-term coastal planning. Natural and nature-based shoreline strategies have emerged as essential components of coastal resilience and are frequently cited by practitioners, scientists, and the public for the wide range of ecosystem services they can provide. However, there is limited quantitative information associating particular urban shoreline design strategies with specific levels of ecosystem service provision, and research on this issue is not always aligned with decision context and decision-maker needs. Engagement between the research community, local government officials and sustainability practitioners, and the non-profit and private sectors can help bridge these gaps. A workshop to bring together these groups discussed research gaps and challenges in integrating ecosystem services into urban sustainability planning in the urban northeast corridor. Many themes surfaced repeatedly throughout workshop deliberations, including the challenges associated with ecosystem service valuation, the transferability of research and case studies within and outside the region, and the opportunity for urban coastal areas to be a focal point for education and outreach efforts related to ecosystem services.     

基于多源遥感影像融合的武汉市土地利用分类方法研究

准确高效的获取土地利用信息,对于合理利用和开发土地资源具有十分重要的意义。在快速城镇化地区,土地利用活动频繁且密集,土地利用格局演变十分剧烈,增加了城市土地利用精准分类的不确定性;且受环境气候和云雨天气影响增加了有效光学影像获取的难度。为提高城市土地分类精度,该文选取武汉市中心城区为研究案例,以Sentinel-1A和Landsat8 OLI影像为数据源,采用Gram-Schmidt变换方法进行影像融合,选取最大似然、支持向量机、CART决策树、BP神经网络等4种分类方法对融合的影像进行分类,提取了研究区土地利用信息,并对其进行分析。进一步,通过与光学影像的分类结果对比,探究了Sentinel-1A和Landsat8 OLI融合影像在土地利用信息提取方面是否具有优势。研究结果表明:(1)对比其他3种方法,CART决策树分类方法对于融合后的影像分类精度最高,总体分类精度和Kappa系数分别达到88.55%和0.841 4;(2)与光学影像相比,Sentinel-1A和Landsat8 OLI融合影像可以更有效地获取高精度城市土地利用信息;(3)基于多源遥感影像融合的CART决策树分类方法是获取研究区高精度土地利用信息的一种行之有效的技术手段。研究成果可为快速城镇化区域的土地利用分类提供参考。