IM‐based and EDP‐based decision models for the verification of the seismic collapse safety of buildings

Decision models for the verification of seismic collapse safety of buildings are introduced. The derivations are based on the concept of the acceptable (target) annual probability of collapse, whereas the decision making involves comparisons between seismic demand and capacity, which is familiar to engineering practitioners. Seismic demand, which corresponds to the design seismic action associated with a selected return period, can be expressed either in terms of an intensity measure (IM) or an engineering demand parameter (EDP). Seismic capacity, on the other hand, is defined by dividing the near‐collapse limit‐state IM or EDP by an appropriate risk‐targeted safety factor (γ _im or γ _edp ), which is the only safety factor used in the proposed decision model. Consequently, the seismic performance assessment of a building should be based on the best possible estimate. For a case study, it is shown that if the target collapse risk is set to 10^?4 (0.5% over a period of 50 years), and if the seismic demand corresponds to a return period of 475 years (10% over a period of 50 years), then it can be demonstrated that γ _im is approximately equal to 2.5 for very stiff buildings, whereas for buildings with long periods the value of γ _im can increase up to a value of approximately 5. The model using γ _edp is equal to that using γ _im only if it can be assumed that displacements, with consideration of nonlinear behavior, are equal to displacements from linear elastic analysis.     

Application of Structure‐from‐Motion photogrammetry to river restoration

Structure‐from‐Motion (SfM) photogrammetry is now used widely to study a range of earth surface processes and landforms, and is fast becoming a core tool in fluvial geomorphology. SfM photogrammetry allows extraction of topographic information and orthophotos from aerial imagery. However, one field where it is not yet widely used is that of river restoration. The characterisation of physical habitat conditions pre‐ and post‐restoration is critical for assessing project success, and SfM can be used easily and effectively for this purpose. In this paper we outline a workflow model for the application of SfM photogrammetry to collect topographic data, develop surface models and assess geomorphic change resulting from river restoration actions. We illustrate the application of the model to a river restoration project in the NW of England, to show how SfM techniques have been used to assess whether the project is achieving its geomorphic objectives. We outline the details of each stage of the workflow, which extend from preliminary decision‐making related to the establishment of a ground control network, through fish‐eye lens camera testing and calibration, to final image analysis for the creation of facies maps, the extraction of point clouds, and the development of digital elevation models (DEMs) and channel roughness maps. The workflow enabled us to confidently identify geomorphic changes occurring in the river channel over time, as well as assess spatial variation in erosion and aggradation. Critical to the assessment of change was the high number of ground control points and the application of a minimum level of detection threshold used to assess uncertainties in the topographic models. We suggest that these two things are especially important for river restoration applications. Copyright © 2016 John Wiley & Sons, Ltd.     

An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models

To assess the performances of state-of-the-art global climate models on simulating the Arctic clouds and surface radiation balance, the 2001–2014 Arctic Basin surface radiation budget, clouds, and the cloud radiative effects(CREs) in 22 coupled model intercomparison project 6(CMIP6) models are evaluated against satellite observations. For the results from CMIP6 multi-model mean, cloud fraction(CF) peaks in autumn and is lowest in winter and spring, consistent with that from three satellite observation products(Cloud Sat-CALIPSO, CERESMODIS, and APP-x). Simulated CF also shows consistent spatial patterns with those in observations. However,almost all models overestimate the CF amount throughout the year when compared to CERES-MODIS and APP-x.On average, clouds warm the surface of the Arctic Basin mainly via the longwave(LW) radiation cloud warming effect in winter. Simulated surface energy loss of LW is less than that in CERES-EBAF observation, while the net surface shortwave(SW) flux is underestimated. The biases may result from the stronger cloud LW warming effect and SW cooling effect from the overestimated CF by the models. These two biases compensate each other,yielding similar net surface radiation flux between model output(3.0 W/m~2) and CERES-EBAF observation(6.1 W/m~2). During 2001–2014, significant increasing trend of spring CF is found in the multi-model mean,consistent with previous studies based on surface and satellite observations. Although most of the 22 CMIP6 models show common seasonal cycles of CF and liquid water path/ice water path(LWP/IWP), large inter-model spreads exist in the amounts of CF and LWP/IWP throughout the year, indicating the influences of different cloud parameterization schemes used in different models. Cloud Feedback Model Intercomparison Project(CFMIP)observation simulator package(COSP) is a great tool to accurately assess the performance of climate models on simulating clouds. More intuitive and credible evaluation results can be obtained based on the COSP model output. In the future, with the release of more COSP output of CMIP6 models, it is expected that those inter-model spreads and the model-observation biases can be substantially reduced. Longer term active satellite observations are also necessary to evaluate models' cloud simulations and to further explore the role of clouds in the rapid Arctic climate changes.     

Soil erosion in the Anthropocene: Research needs

Soil erosion is a geomorphological and, at the same time, a land degradation process that may cause environmental and property damage, loss of livelihoods and services as well as social and economic disruption. Erosion not only lowers soil quality on‐site, but causes also significant sediment‐related problems off‐site. Given the large number of research papers on this topic, one might therefore conclude that we know now almost everything about soil erosion and its control so that little new knowledge can be added. This conclusion can be refuted by pointing to some major research gaps. There is a need for more research attention to (1) improved understanding of both natural and anthropogenic soil erosion processes and their interactions, (2) scaling up soil erosion processes and rates in space and time, and (3) innovative techniques and strategies to prevent soil erosion or reduce erosion rates. This is illustrated with various case studies from around the world. If future research addresses these research gaps, we will (1) better understand processes and their interactions operating at a range of spatial and temporal scales, predict their rates as well as their on‐site and off‐site impacts, which is academically spoken rewarding but also crucial for better targeting erosion control measures, and (2) we will be in a better position to select the most appropriate and effective soil erosion control techniques and strategies which are highly necessary for a sustainable use of soils in the Anthropocene. Copyright © 2017 John Wiley & Sons, Ltd.     

On the importance of soil moisture in calibration of rainfall–runoff models: two case studies

Streamflow modelling results from the GR4H and PDM hydrological models were evaluated in two Australian sub-catchments, using (1) calibration to streamflow and (2) joint-calibration to streamflow and soil moisture. Soil moisture storage in the models was evaluated against soil moisture observations from field measurements. The PDM had the best performance in terms of both streamflow and soil moisture estimations during the calibration period, but was outperformed by GR4H during validation. It was also shown that the soil moisture estimation was improved significantly by joint-calibration for the case where streamflow and soil moisture estimations were poor. In other cases, addition of the soil moisture constraint did not degrade the results. Consequently, it is recommended that GR4H be used, in preference to the PDM, in the foothills of the Murrumbidgee catchment or other Australian catchments with semi-arid to sub-humid climate, and that soil moisture data be used in the calibration process.     

北京平原地区VS30估算模型适用性研究

本文使用基于钻孔测井数据的3类模型,即常速度外推模型、速度梯度模型、双深度参数外推模型,通过对北京地区460个深度超过30m的钻孔剪切波速资料进行分析,详细探究了V_S30估算模型在本研究区的适用性。研究结果表明双深度参数外推模型在估算V_S30上准确度很高,其不需要大量的数据进行回归分析,且不具有区域独立性,可以为全球包括北京地区场地类别划分提供依据,进而在震害快速评估中用于确定场地影响,是一种值得推广的估算模型。     

半参数模型稳健估计及其应用

在半参数模型估计中,均假设观测误差服从正态分布。当观测量含有粗差时,粗差对参数和非参数估计的影响是不可忽略。基于此,首先在总结线性参数模型稳健估计基本理论的基础上,论述了M估计权因子的确定方法。然后提出了半参数模型稳健估计方法,并导出半参数模型(广义)补偿最小二乘稳健估计的基本公式。最后通过两个模拟算例验证了其估计方法的有效性。     

Spatial distribution of block falls using volumetric GIS–decision-tree models

Block falls are considered a significant aspect of surficial instability contributing to losses in land and socio-economic aspects through their damaging effects to natural and human environments. This paper predicts and maps the geographic distribution and volumes of block falls in central Lebanon using remote sensing, geographic information systems (GIS) and decision-tree modeling (un-pruned and pruned trees). Eleven terrain parameters (lithology, proximity to fault line, karst type, soil type, distance to drainage line, elevation, slope gradient, slope aspect, slope curvature, land cover/use, and proximity to roads) were generated to statistically explain the occurrence of block falls. The latter were discriminated using SPOT4 satellite imageries, and their dimensions were determined during field surveys. The un-pruned tree model based on all considered parameters explained 86% of the variability in field block fall measurements. Once pruned, it classifies 50% in block falls’ volumes by selecting just four parameters (lithology, slope gradient, soil type, and land cover/use). Both tree models (un-pruned and pruned) were converted to quantitative 1:50,000 block falls’ maps with different classes; starting from Nil (no block falls) to more than 4000 m³. These maps are fairly matching with coincidence value equal to 45%; however, both can be used to prioritize the choice of specific zones for further measurement and modeling, as well as for land-use management. The proposed tree models are relatively simple, and may also be applied to other areas (i.e. the choice of un-pruned or pruned model is related to the availability of terrain parameters in a given area).     

不规则三角网的几种数据结构及其存储机制研究

在比较分析了TIN的几种常见数据结构的基础上,针对TIN拓扑查询与搜索问题,提出了另外几种强调边拓扑信息的TIN数据结构,根据拓扑关系的表达方式可以将它们分为内存索引式结构、数组索引式结构及二者的混合结构,并给出了这些数据结构的多种序列化存储方式:数组索引直接存储、对象ID存储法、PythoncPickle存储、对象内存地址的存储法。研究比较发现数组索引直接存储的数据占用空间最少,对象ID存储法和对象内存地址存储法的二进制方式占用空间相同,Python cPickle只适合于极小规模的TIN数据的存储。对基于不同数据结构的TIN模型构网效率测试表明,不包含边信息的结构的构网效率最高,含有边信息的结构中采用数组索引表示拓扑关系的构网效率最高。研究结果将对TIN模型的软件实现具有理论及应用价值。