Effect of 2D spatial variability on slope reliability: A simplified FORM analysis

To meet the high demand for reliability based design of slopes, we present in this paper a simplified HLRF(Hasofere Linde Rackwitze Fiessler) iterative algorithm for first-order reliability method(FORM). It is simply formulated in x-space and requires neither transformation of correlated random variables nor optimization tools. The solution can be easily improved by iteratively adjusting the step length. The algorithm is particularly useful to practicing engineers for geotechnical reliability analysis where standalone(deterministic) numerical packages are used. Based on the proposed algorithm and through direct perturbation analysis of random variables, we conducted a case study of earth slope reliability with complete consideration of soil uncertainty and spatial variability.     

Landfill site selection based on reliability concepts using the DRASTIC method and AHP integrated with GIS – a case study of Bengaluru city,India

The selection of landfill sites for municipal solid waste (MSW) disposal involves consideration of geological, hydrological and environmental parameters which exhibit large spatial variability. Therefore, it is necessary to define, to what extent the chosen sites are reliable such that the probability of environmental pollution and health risks to population is minimal. In the present study, groundwater vulnerability to contamination has been assessed using the standard DRASTIC method. The results showed that the study region has 9.45% of very less, 32.94% of less, 25.47% of moderate, 22.79% of high and 9.35% of very high vulnerable zones. The study also revealed that none of the landfills are located in safe zones. This suggests that it requires proper remedial measures to avoid environmental pollution. A landfill site selection process has been carried out using the Analytical Hierarchy Process integrated with Geographical Information System tools. The obtained results showed that only 3.59?km² (0.08%) of the total area is suitable for landfills. The reliability analysis of the site suitability revealed that landfills are located at unreliable locations where the probability of risk to environmental pollution is high. The presented approach assists decision-makers in selecting reliable locations for the safe disposal of MSW.     

基于高分二号卫星数据的煤矿区地质灾害信息提取研究

随着遥感数据获取技术和能力的全面提高,遥感数据呈现出明显的大数据特征。发展适应于遥感大数据的智能分析和信息挖掘技术,成为当前遥感技术研究的前沿。高分二号（GF-2）卫星数据是我国首颗自主研发的亚米级高分辨率卫星数据,具有观测幅宽、重访周期短、高辐射精度、高定位精度等优势,为未来我国地质灾害的长期、动态地监测和研究提供了高精度、稳定可靠的数据源。本文选取安徽谢桥煤矿2015年1月8日的GF-2卫星影像为研究数据,在对煤矿区主要地质灾害遥感地学分析的基础上,采用面向对象的影像分析方法对研究区由采煤活动所诱发的地质灾害信息进行自动提取。结果表明：利用GF-2卫星数据能够有效地识别地质灾害体的位置、范围、形态等空间分布特征;面向对象的自动提取方法对于煤矿区大面积的积水塌陷盆地、小规模的塌陷坑和线性的地裂缝都有很高的提取精度,识别精度达90% 以上;基于逐层剔除的思路构建的提取规则,为GF-2数据在地质灾害调查和大数据分析中的应用提供了很好的技术支持,也为其它地物目标的提取提供了参考,但在特征的选择和阈值的设定上需要具体分析。     

面向矿产资源信息的空间关联性分析

关联性分析是综合多源、多类数据,发现和挖掘数据中潜在的相关关系,提取和挖掘数据之间的关联性。该方法对于充分利用地质大数据、发现地质要素之间的共生组合规律具有重要的意义。本文首先基于数据的空间位置,将不同类型的地质空间数据建立联系,形成空间属性数据库;其次应用统计方法,对不同来源数据中的属性特征进行分析,发现热液型金矿的形成与火山作用存在明显相关性;最后基于Apriori算法提取热液型金矿的伴生矿与侵入岩的频繁项集,发现伴生矿与侵入岩酸碱性二者密切相关。因此,在今后的工作中,有望应用空间关联性的方法对地球物理、地球化学、遥感等多源地质数据开展深入的研究分析。     

A CRPS-Based Spatial Technique for the Verification of Ensemble Precipitation Forecasts

Traditional precipitation skill scores are affected by the well-known“double penalty”problem caused by the slight spatial or temporal mismatches between forecasts and observations. The fuzzy (neighborhood) method has been proposed for deterministic simulations and shown some ability to solve this problem. The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts. We developed an ensemble precipitation verification skill score, i.e., the Spatial Continuous Ranked Probability Score (SCRPS), and used it to extend spatial verification from deterministic into ensemble forecasts. The SCRPS is a spatial technique based on the Continuous Ranked Probability Score (CRPS) and the fuzzy method. A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency, which were then used in the reference score to calculate the skill score of the SCRPS. The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained. The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used.     

A model for integrated spatial land use characteristics linking to surface nutrient concentration

Quantifying land use heterogeneity helps better understand how it influences biophysical systems. Land use area proportions have been used conventionally to predict water quality variables. Lacking an insight into the combined effect of various spatial characteristics could lead to the statistical bias and confused understanding in previous studies. In this study, using spatial techniques and mathematical models, a diagnostic model was developed and applied for quantifying and incorporating three spatial components, namely, slope, distance to sampling spots, and arrangement. The upper catchment of Miyun Reservoir was studied as the test area. Total nitrogen, total phosphorus, and chemical oxygen demand of water samples from field measurements were used to characterize the surface water quality in 52 sub-watersheds. Using parameter calibrations and determinations, combined spatial characteristics were explored and detected. Adjusted land use proportions were calculated by spatial weights of discriminating the relative contribution of each location to water quality and used to build the integrated models. Compared with traditional methods only using area proportions, our model increased the explanatory power of land use and quantified the effects of spatial information on water quality. This can guide the optimization of land use configuration to control water eutrophication.     

论中国国家公园地质考察与评价——以浙江丽水百山祖国家公园为例

鉴于保护地调查评价历史与目标,国家公园地质考察评价基准是地质学关于地球的“时间、空间、演化”知识的发现路径,既识别国家公园候选地的国家符合性地质事件,又识别国家公园自然性、独特性、优美性、多样性、整体性的地质机制,提供国家公园最重要的自然生态系统与自然景观保育管理的地质学支撑。浙江丽水百山祖国家公园符合性的地质事件是公园发现的4.0~4.2 Ga冥古宙陆核物质的锆石晶体、中生代岛弧陆盆火山酸性火山岩系列和从流纹岩山岭到花岗岩—变质岩谷底的“峰—岭—丘—谷（盆）”的亚热带滨海山地地貌结构,地貌结构发育演化是百山祖公园最重要的自然生态系统、区域性流域水源地、独特山水景观的形成基础。保护百祖山公园地貌结构和过程的完整性与真实性是确保其重要自然生态系统自然演化和生态服务产品持续供给的基础。     

A novel index to evaluate discretization methods:A case study of flood susceptibility assessment based on random forest

The selection of a suitable discretization method(DM)to discretize spatially continuous variables(SCVs)is critical in ML-based natural hazard susceptibility assessment.However,few studies start to consider the influence due to the selected DMs and how to efficiently select a suitable DM for each SCV.These issues were well addressed in this study.The information loss rate(ILR),an index based on the informa-tion entropy,seems can be used to select optimal DM for each SCV.However,the ILR fails to show the actual influence of discretization because such index only considers the total amount of information of the discretized variables departing from the original SCV.Facing this issue,we propose an index,infor-mation change rate(ICR),that focuses on the changed amount of information due to the discretization based on each cell,enabling the identification of the optimal DM.We develop a case study with Random Forest(training/testing ratio of 7:3)to assess flood susceptibility in Wanan County,China.The area under the curve-based and susceptibility maps-based approaches were presented to compare the ILR and ICR.The results show the ICR-based optimal DMs are more rational than the ILR-based ones in both cases.Moreover,we observed the ILR values are unnaturally small(＜1％),whereas the ICR values are obviously more in line with general recognition(usually 10％-30％).The above results all demonstrate the superiority of the ICR.We consider this study fills up the existing research gaps,improving the ML-based natural hazard susceptibility assessments.     

中尺度降水集合预报随机参数扰动方法敏感性试验

中尺度降水模式预报具有很大的不确定性,为更好地描述与模式降水预报密切相关的物理过程关键参数的不确定性,基于中国气象局GRAPES（Global/Regional Assimilation and Prediction System）中尺度区域集合预报模式,从对模式降水预报不确定性有较大影响的积云对流、云微物理、边界层及近地面层等4个参数化方案中选取了18个关键参数,设计了一种随机参数扰动方案（Stochastically Perturbed Parameterization,SPP）,并通过2015年6—7月总计10 d的随机扰动集合预报试验,对比分析了SPP方案对不同物理过程参数扰动敏感性、随机场时、空尺度敏感性、能量变化特征及其集合预报效果。结果显示,对所选择的任一物理过程参数化方案增加SPP扰动后,降水及等压面要素的概率预报技巧优于无SPP扰动的预报,而扰动积云对流和边界层过程中的参数较扰动云微物理过程中的参数影响更显著,且同时扰动积云对流、云微物理、边界层及近地面层参数化方案中的18个参数的集合预报效果优于扰动任何单一物理过程中的部分参数,表明SPP方案能够有效地提高中尺度降水概率预报技巧;从能量变化特征可知,不同物理过程的参数扰动对动能、内能和总能量的影响层次和特征有所不同,但总体而言,扰动前后各项能量基本相同;随机场时、空尺度敏感性试验发现,SPP扰动随机场时间、空间相关尺度对集合预报效果有明显影响,当扰动随机场选用12 h抗相关时间及截断波数20时,集合预报结果最优。上述结果表明,SPP随机参数扰动方案不仅能够有效提高集合概率预报效果,还能够提高集合降水概率预报技巧,具有良好的业务应用与发展前景。      

福建省晋江市城市热岛强度时空变化特征分析

利用传统的气象站法, 结合空间统计学方法(普通克里金插值法), 对福建省晋江市2010—2014年40个自动气象站逐小时温度资料加以计算处理, 分析了晋江市年、季、昼夜热岛强度时空变化规律。(1)晋江市年、季、昼夜热岛强度都呈带状分布, 等值线呈西南-东北走向, 年、季、昼夜变化趋势显著, 北部热岛强度高于南部。五年间热岛强度持续增强, 但增幅不大, 增速放缓。(2)城市化水平的提高, 会导致热岛强度高值出现季节提前, 故旅游区秋冬季热岛强度高于春夏季, 中心城区和产业经济区夏秋季热岛强度高于冬春季。(3)晋江市热岛效应昼夜空间分布格局差异性大, 夜间热岛强度显著高于白天, 最低值出现在14—16时, 中心城区和产业经济区最低值出现时间较旅游区略推迟, 三个功能区的最高值均出现在凌晨。