A FORM-based approach for probabilistic analysis in geotechnics: Application to a reinforced concrete drainage culvert

As numerical models are increasingly used as a design tool in geotechnical engineering, it is highly desirable if geotechnical reliability analysis can be conducted based on numeral models. Currently, the practical use of geotechnical reliability analysis-based numerical models is still quite limited. In this study, an easy to access method is derived to conduct geotechnical reliability analysis based on numerical models. To facilitate its application, a procedure is outlined to implement the suggested method such that geotechnical reliability analysis can be automated using existing geotechnical numerical packages. The procedure is illustrated in detail with an example, and the source codes provided can be easily adapted to analyze other similar problems. The method described in this paper is used to study the reliability of a deteriorating reinforced concrete drainage culvert in Shanghai, China. The suggested method provides a convenient means for reliability analysis of complex geotechnical problems.     

Application of the patient rule induction method to detect hydrologic model behavioural parameters and quantify uncertainty

Finding an operational parameter vector is always challenging in the application of hydrologic models, with over‐parameterization and limited information from observations leading to uncertainty about the best parameter vectors. Thus, it is beneficial to find every possible behavioural parameter vector. This paper presents a new methodology, called the patient rule induction method for parameter estimation (PRIM‐PE), to define where the behavioural parameter vectors are located in the parameter space. The PRIM‐PE was used to discover all regions of the parameter space containing an acceptable model behaviour. This algorithm consists of an initial sampling procedure to generate a parameter sample that sufficiently represents the response surface with a uniform distribution within the “good‐enough” region (i.e., performance better than a predefined threshold) and a rule induction component (PRIM), which is then used to define regions in the parameter space in which the acceptable parameter vectors are located. To investigate its ability in different situations, the methodology is evaluated using four test problems. The PRIM‐PE sampling procedure was also compared against a Markov chain Monte Carlo sampler known as the differential evolution adaptive Metropolis (DREAM_ZS) algorithm. Finally, a spatially distributed hydrological model calibration problem with two settings (a three‐parameter calibration problem and a 23‐parameter calibration problem) was solved using the PRIM‐PE algorithm. The results show that the PRIM‐PE method captured the good‐enough region in the parameter space successfully using 8 and 107 boxes for the three‐parameter and 23‐parameter problems, respectively. This good‐enough region can be used in a global sensitivity analysis to provide a broad range of parameter vectors that produce acceptable model performance. Moreover, for a specific objective function and model structure, the size of the boxes can be used as a measure of equifinality.     

Amplification of hydrological model uncertainties in projected climate simulations of the Upper Indus Basin: Does it matter where the water is coming from?

There is a growing appreciation of the uncertainties in the estimation of snow-melt and glacier-melt as a result of climate change in high elevation catchments. Through a detailed examination of three hydrological models in two catchments, and interpretation of results from previous studies, we observed that many variations in estimated streamflow could be explained by the selection of a best parameter set from the possible good model parameters. The importance of understanding changing glacial dynamics is critically important for our study areas in the Upper Indus Basin where Pakistan's policymakers are planning infrastructure to meet the future energy and water needs of hundreds of millions of people downstream. Yet, the effect of climate on glacial runoff and climate on snowmelt runoff is poorly understood. With the HBV model, for example, we estimated glacial melt as between 56% and 89% for the Hunza catchment. When rainfall was a scaled parameter, the models estimated glacial melt as between 20% and 100% of streamflow. These parameter sets produced wildly different projections of future climate for RCP8.5 scenarios in 2046–2075 compared to 1976–2005. Assuming no glacial shrinkage, for one climate projection, we found that the choice among good parameter sets resulted in projected values of future streamflow across a range from +54% to +125%. Parameter selection was the most significant source of uncertainty in the glaciated catchment and amplified climate model uncertainty, whereas climate model choice was more important in the rainfall dominated catchment. Although the study focuses on Pakistan, the overall conclusions are instructive for other similar regions in the world. We suggest that modellers of glaciated catchments should present results from at least the book-ends: models with low sensitivity to ice-melt and models with high sensitivity to ice-melt. This would reduce confusion among decision makers when they are faced with similar contrasting results.     

空间科学虚拟观测台体系结构研究

科学观测数据的海量增长,使得旨在实现资源互操作的虚拟观测台(VO)应运而生,并迅速受到相关学科的支持和重视。国际虚拟天文台联盟(IVOA)、行星科学数据系统(PDS)和空间物理归档检索抽取标准(SPASE)等数据组织,正加快制定数据管理模型,推动VO的发展和跨学科应用。结合空间科学应用研究的特点,在借鉴国内外天文和空间科学VO研究成果的基础上,提出了一种针对空间科学数据的Hybrid型VO体系结构,并基于此体系结构发展了一个支持同步收割、格式化管道和事件关联发现的空间科学VO原型。实践和应用结果表明,基于这种体系结构建立的VO在解决全局资源的实时同步、异构应用的高度集成和面向科学问题的数据发现等问题上,有一定的普适性。     

水文集合预报试验及其研究进展

水文集合预报是一种既可以给出确定性预报值,又能提供预报值的不确定性信息的概率预报方法。简述了水文集合预报试验(Hydrologic Ensemble Prediction Experiment,HEPEX)国际计划的主要研究内容,回顾了HEPEX研究进展,分析了对水文预报发展有重要意义的3个HEPEX前沿研究:降尺度研究、集合预报系统研究以及不确定性研究。研究表明,动力-统计降尺度法和高分辨率"单一"模式及低分辨率集合相结合是HEPEX未来研究的方向。     

A Proposal for the Publication of Geochemical Data in the Scientific Literature

A proposal is set out for the information and details that should accompany the publication of geochemical data in the research literature. This proposal is based on the principle that sufficient detail must be included both to allow independent replication of the results and for reviewers to confirm that data are fit‐for‐purpose in supporting the way in which they have been interpreted. In particular, it is recommended that all analytical measurements should be accompanied by an estimate of uncertainty that includes both field sampling and laboratory contributions together with a statement that summarises the way published data conform to the principles of traceability.     

对电感耦合等离子体质谱法测定的地下水中 B元素不确定度的评定

采用不确定度连续传递模型,以x、y的相对误差为权重进行双误差曲线回归,对电感耦合等离子体质谱法测定的地下水中B元素的不确定度进行评定。其不确定度分量主要包括标准储备溶液、配制标准系列溶液、重复性测量和曲线拟合产生的不确定度。研究表明,对于B浓度较高的样品,采用双误差拟合方式得到的不确定度结果比常规拟合方法(最小二乘法直线拟合)更为准确。     

海洋桩靴基础穿刺破坏实时预测研究

海上自升式钻井平台以其造价低廉、便于移动和安装的优势被广泛应用于海洋地质勘察、风电安装和油气开采等领域,其基础类型多为桩靴基础。为了保证平台能在恶劣的海洋环境中安全作业,桩靴基础需要贯入海床以下一定深度以获得足够的承载力。然而,当桩靴基础在上硬下软土层中贯入时可能发生穿刺破坏导致平台损坏甚至倾覆。已有的桩靴穿刺破坏分析方法基于预设的地层参数预测穿刺荷载,由于无法考虑海床中地层及土性的不确定性,其准确性有待提高。将桩靴基础贯入过程中的监测数据与穿刺破坏机理相结合,通过66组离心机模型试验结果表征土体不确定性的影响,发展贝叶斯预测模型,实现了峰值阻力和穿刺深度的实时预测。基于规范推荐的荷载扩展分析法和冲剪系数分析法,建立了适用于规范法的概率模型,采用该模型对上砂下黏土层中桩靴基础的穿刺行为进行了预测,结果表明所提方法的预测精度随着监测数据的增加而提高,预测得到的峰值阻力误差在10%以内。