基于贝叶斯网络的地下水环境系统决策管理研究

应用贝叶斯网络解决地下水环境管理中具有不确定性的多目标决策问题,通过对决策变量氮肥施用量以及灌溉模式的调控,减少水中的硝酸盐含量,达到既能有效改善水环境又不至使农民经济利益受到损害的目标。通过分析具体的地下水环境管理系统中变量间的相互关系,构建描述变量间不确定性关系的贝叶斯网络模型,其中包括表示其依赖关系的有向无环图和表示其具体概率依赖程度的条件概率表。并在多个水环境管理目标均达到最优的前提下进行概率推理,得到决策变量氮肥施用量以及灌溉模式取不同值时目标变量的概率分布情况。最终确定出能使所有目标均达到最优的合理的水环境管理决策:(1)使用喷灌,将氮肥施用量控制在0.01~0.03 kg/m2;(2)使用漫灌,将氮肥施用量控制在0.01~0.02 kg/m2。     

地图综合中线要素综合的不确定性分析

地图综合是GIS领域研究的热点问题之一,也是GIS中最需要智能化的课题之一。为了保证地图综合的数据质量,地图综合的不确定性和地图综合的数据质量问题应该在地图综合领域中受到重视。通过研究对比分析4种线要素综合算法各自的优缺点,评价曲线综合算法和对数据不确定性进行分析。使用Autodesk公司的AutoCAD平台的Object-ARX二次开发包在VC＋＋语言平台下实现Douglas-Peucker综合算法和Li-Openshaw综合算法对地图线要素的综合;分析了目前主要的线要素综合方法的各自的特点与适用范围;通过对几种常用综合算法不确定性的分析,总结了线要素综合的不确定性的各种表现,包括原始数据保持的不确定性、阈值的不确定性与综合后数据评定指标和评定方法的不确定性等。     

暴雨山洪灾害预警方法研究进展

暴雨山洪灾害预警是中小流域山洪灾害防控体系的薄弱环节,也是决定山洪灾害防控成败的关键。论文围绕山洪灾害预警的核心问题,从中国山洪灾害区域差异特征、山洪灾害预警技术方法、山洪灾害概率预警现状3个方面进行了综述。中国山洪灾害分布存在明显的时空差异,因此有必要根据山洪灾害的区域差异发展有针对性的预警方法。以临界雨量为指标的雨量预警是目前中国中小流域暴雨山洪灾害预警的主要技术手段,但常规方法仅给出一个(组)确定的临界雨量阈值,导致预警结果存在突出的不确定性问题。概率预警可以定量评估诸多不确定性,给出山洪灾害概率预警结果,因此具备很好的理论优势与潜在应用价值。论文展望了山洪灾害概率预警未来的研究重点与方向：(1)充分挖掘暴雨洪水样本信息,开展山洪灾害概率预警基础方法与技术集成研究;(2)加强非平稳性条件下的临界雨量阈值估算与山洪灾害概率预警研究;(3)综合考虑预警阈值发生概率及其致灾概率,优化“多级预警、多级响应”技术方法,推进山洪灾害综合预警业务系统建设与应用。     

The Role of the Aerosol Indirect Effect in the Northern Indian Ocean Warming Simulated by CMIP5 Models

The northern Indian Ocean （NIO） experienced a decadal-scale persistent warming from 1950 to 2000, which has influenced both regional and global climate. Because the NIO is a region susceptible to aerosols emis- sion changes, and there are still large uncertainties in the representation of the aerosol indirect effect （ALE） in CMIP5 （Coupled Model Intercomparison Project Phase 5） models, it is necessary to investigate the role of the AIE in the NIO warming simulated by these models. In this study, the authors select seven CMIP5 models with both the aerosol direct and indirect effects to investigate their performance in simulating the basin-wide decadal-scale NIO warming. The results show that the decreasing trend of the downwelling shortwave flux （FSDS） at the surface has the major damping effect on the SST increasing trend, which counteracts the warming effect of greenhouse gases （GHGs）. The FSDS decreasing trend is mostly contrib- uted by the decreasing trend of cloudy-sky surface downwelling shortwave flux （FSDSCL）, a metric used to measure the strength of the AIE, and partly by the clear-sky surface downwelling shortwave flux （FSDSC）. Models with a relatively weaker AIE can simulate well the SST increasing trend, as compared to observation. In contrast, models with a relatively stronger AIE produce a much smaller magnitude of the increasing trend, indicat- ing that the strength of the AIE in these models may be overestimated in the NIO.     

The Combined Effect of Initial Error and Model Error on ENSO Prediction Uncertainty Generated by the Zebiak-Cane Model

Initial errors and model errors are the source of prediction errors. In this study, the authors compute the conditional nonlinear optimal perturbation （CNOP）-type initial errors and nonlinear forcing singular vector （NFSV）- type tendency errors of the Zebiak-Cane model with respect to El Nifio events and analyze their combined effect on the prediction errors for E1 Nino events. The CNOP- type initial error （NFSV-type tendency error） represents the initial errors （model errors） that have the largest effect on prediction uncertainties for E1 Nifio events under the perfect model （perfect initial conditions） scenario. How- ever, when the CNOP-type initial errors and the NFSV- type tendency errors are simultaneously considered in the model, the prediction errors caused by them are not am- plified as the authors expected. Specifically, the predic- tion errors caused by the combined mode of CNOP-type initial errors and NFSV-type tendency errors are a little larger than those caused by the NFSV-type tendency er- rors. This fact emphasizes a need to investigate the opti- mal combined mode of initial errors and tendency errors that cause the largest prediction error for E1 Nifio events.     

GNSS参考站网络的电离层完备性监测研究

本文基于四川GPS综合服务网络(SIGN)的计算结果表明:IRIM指标可用于衡量参考站网络内的电离层完备性监测的总体情况,IRIU指标提供了完备性监测信息在参考站网络中更为详细的空间分布情况,上述指标应用于参考站网络数据处理中心进行实时电离层完备性监测,能有效保证参考站网络内流动端用户定位的时间空间可用性和可靠性。     

Investigation of Uncertainties of Establishment Schemes in Dynamic Global Vegetation Models简

In Dynamic Global Vegetation Models （DGVMs）, the establishment of woody vegetation refers to flowering, fertiliza- tion, seed production, germination, and the growth of tree seedlings. It determines not only the population densities but also other important ecosystem structural variables. In current DGVMs, establishments of woody plant functional types （PFTs） are assumed to be either the same in the same grid cell, or largely stochastic. We investigated the uncertainties in the competition of establishment among coexisting woody PFTs from three aspects： the dependence of PFT establishments on vegetation states; background establishment; and relative establishment potentials of different PFTs. Sensitivity experi- ments showed that the dependence of establishment rate on the fractional coverage of a PFT favored the dominant PFT by increasing its share in establishment. While a small background establishment rate had little impact on equilibrium states of the ecosystem, it did change the timescale required for the establishment of alien species in pre-existing forest due to their disadvantage in seed competition during the early stage of invasion. Meanwhile, establishment purely fiom background （the scheme commonly used in current DGVMs） led to inconsistent behavior in response to the change in PFT specification （e.g., number of PFTs and their specification）. Furthermore, the results also indicated that trade-off between irtdividual growth and reproduction/colonization has significant influences on the competition of establishment. Hence, further development of es- tablishment parameterization in DGVMs is essential in reducing the uncertainties in simulations of both ecosystem structures and successions.     

水文学确定性和不确定性方法的耦合初探

水文现象具有确定性和不确定性,常用确定性方法和不确定性方法分析。这两种方法在水文学中广泛应用并愈来愈密切耦合。对这种耦合的背景、实质和途径等进行了初步分析。给出了水文学确定性方法和不确定性方法耦合的内涵;分析了耦合的客观背景,指出确定性和不确定性辩证的统一、不确定性和确定性在一定条件下相互转化是耦合的哲学基础;总结了耦合的三大主要途径:(1)简单混合。对某一个水文问题的解决分成两个部份,一个部份用确定性方法,另一个部份用不确定性法;(2)一般嵌入。指在某种分析法的总体框架下,局部或某些部分嵌入另一种分析法以达到提高分析可靠性之目的;(3)复杂的渗入。指两种方法相互渗透,充分发挥各自特色促使耦合效应独突。     

东胜煤田北部地段3D煤层模型的动态构建及不确定性评估

以内蒙古东胜煤田北部艾来五库沟-台吉召地段勘查区为例,针对三维地质建模方法在多源多类地质数据应用、动态建模及建模结果不确定性评估等方面存在的不足进行研究,并实现了煤层三维建模.煤层三维建模要领是:先按照数据的内在逻辑关系和几何结构两个层次进行数据融合处理,将钻孔、剖面及断层等数据转化为形式简单、结构一致的离散化样品数据;再以这些数据和各类边界线为基础,通过距离幂次反比(inverse distance weighting,IDW)法插值得到煤层顶底板高程,并结合这些属性值和TIN(triangulated irregular network)剖分技术动态生成煤层结构模型;然后利用一个与煤层顶底板高程估值结果相对应的算子——插值方差,完成对煤层模型的局部不确定性评估.详细讨论了煤层三维建模的整体流程并基于三维地学信息系统平台QuantyView加以实现.实际应用结果表明,所提方法具有显著的实际应用价值.      

基于景观格局—过程的城市自然灾害生态风险研究:回顾与展望

随着当前中国城市化进程的不断加速,自然灾害对城市生态安全的潜在威胁日趋受到关注。城市景观结构和空间形态影响着城市生态环境问题的产生和解决途径,基于景观格局—过程的城市/区域自然灾害生态风险评价成为城市生态风险及可持续研究的重要方向。在明晰城市自然灾害生态风险基本概念内涵及单一、综合自然灾害作用下城市生态风险评价研究进展的基础上,系统梳理了城市地域自然灾害、生态风险与景观格局—过程之间的逻辑关联,综合探讨了城市景观格局—过程与自然灾害交互作用及其在城市生态风险评价、自然灾害生态风险防范等重点领域的研究进展,并提出城市景观格局—过程与自然灾害生态风险的相互影响机理探索、景观时空尺度分异与城市自然灾害生态风险的不确定性分析、基于景观格局—过程的城市自然灾害生态风险综合评估模型与情景模拟等三大重大研究趋向,以期实现基于景观优化的城市自然灾害和生态风险防范的研究目标。