Failure process and hydrologic response of a two layer physical model: Implications for rainfall-induced landslides

Field observations and theoretical analysis have been used in the literature to assess slope instability caused by permeability variations. This investigation aims to study the influence of permeability variations on slope behaviour by experimental means. It focuses particularly on the pore water pressure generation in the vicinity of soils with different permeabilities, and the corresponding failure mode. A series of generated failures in a model with 2 soil layers was performed by means of a flume device. The soil layers were made of a medium-sized sand and a fine sand, placed in horizontal layers. A combination of photography and pore water pressure measurements was used to examine the relationship between the pore water pressure generation and failure modes. Experiments were conducted for different arrangements of soil layers (by changing the soil layer position), and infiltration direction (downward infiltration by sprinkling water on the soil, and upward infiltration from the bottom of the lower soil layer).The results revealed no clear link between the failure mode and recorded pore water pressure. Instead, the failure mode was seen to depend mostly on the relative layer position, and the recorded pore water pressures on the imposed infiltration direction. Failure was not confined to a single failure mode, but ranged instead from retrogressive slides and lateral spreads to seepage erosion. Regarding the hydrologic response, interesting results were recorded for experiments performed by downward infiltration, where perched water tables were formed. The granular nature of both soils and the absence of an impermeable barrier at the downslope end of the model seem to have favoured water seepage as the controlling failure mechanism, enhancing seepage erosion and sliding, and restricting other failure modes that require a high soil saturation such as flow failure.As the drainage conditions were not controlled, these experiments provided a unique opportunity to study the effect of water seepage as a trigger. In some experiments, failure evolution was seen to be dominated by sand washout, which started after the pore water pressure reached its maximum, suggesting that the dragging effect of seepage forces have a minor impact on triggering failure. An extra set of experiments conducted in a triaxial apparatus supported the efficacy of pore water pressure as a trigger rather than the dragging effect of seepage forces. The results obtained here provide an insight into the pre-failure mechanisms and processes of heterogeneous natural slopes.     

Simulation of event-based landslides and debris flows at watershed level

A coupled model has been developed to simulate, at watershed level, landslides and debris flows induced by a severe typhoon (tropical cyclone) in Taiwan. The model comprises a landslide susceptibility model to predict landslide occurrence, an empirical model to select debris-flow initiation points, and a debris flow model to simulate the transport and deposit of failed materials from the identified source areas. In raster format with a 10 m spatial resolution, the model output includes unstable cells, debris-flow initiation cells, debris-flow velocities, runout paths, and deposition zones. The model was first tested and calibrated in a small area, where the damage by landslides had been investigated and recorded. It was then applied to a watershed, and the simulation results were validated by comparing them with a landslide/debris-flow inventory map prepared from satellite images using a multiple change detection technique. Model test and validation results confirm the usefulness of the model in predicting the number and size of affected areas (landslides and runouts combined), runout path, and volume of runout deposits. It is a common practice in Taiwan to separate landslide and debris-flow inventories and to study debris flows only in select drainage basins. This study suggests that landslide and debris flow should be modeled as a sequential process for efficient watershed management.     

Representative rainfall thresholds for landslides in the Nepal Himalaya

Measuring some 2400 km in length, the Himalaya accommodate millions of people in northern India and Pakistan, Nepal, Bhutan, and parts of other Asian nations. Every year, especially during monsoon rains, landslides and related natural events in these mountains cause tremendous damage to lives, property, infrastructure, and environment. In the context of the Himalaya, however, the rainfall thresholds for landslide initiation are not well understood. This paper describes regional aspects of rainfall thresholds for landslides in the Himalaya. Some 677 landslides occurring from 1951 to 2006 were studied to analyze rainfall thresholds. Out of the 677 landslides, however, only 193 associated with rainfall data were analyzed to yield a threshold relationship between rainfall intensity, rainfall duration, and landslide initiation. The threshold relationship fitted to the lower boundary of the field defined by landslide-triggering rainfall events is I = 73.90D^− 0.79 (I = rainfall intensity in mm h^− 1 and D = duration in hours), revealing that when the daily precipitation exceeds 144 mm, the risk of landslides on Himalayan mountain slopes is high. Normalized rainfall intensity–duration relationships and landslide initiation thresholds were established from the data after normalizing rainfall-intensity data with respect to mean annual precipitation (MAP) as an index in which N_I = 1.10D^− 0.59 (N_I = normalized intensity in h^− 1). Finally, the role of antecedent rainfall in causing landslides was also investigated by considering daily rainfall during failure and the cumulative rainfall to discover at what point antecedent rainfall plays an important role in Himalayan landslide processes. Rainfall thresholds presented in this paper are generalized so they can be used in landslide warning systems in the Nepal Himalaya.     

预测银川市大气主要污染物浓度的一种动力统计模型

本文以箱模式为原理,从大气污染物平流扩散方程出发,经过简化推导,得出预测大气主要污染物浓度的动力统计模型。在模型中既考虑了气象条件的作用,又考虑了起报日的污染物浓度,与纯数学统计模型相比,有着更可信的物理基础;与数值模式相比,本模型不需要污染源排放清单,具有简便易行的优点。利用银川市2001-2004年大气主要污染物SO_2、NO_2、PM_(10)逐日平均浓度监测值和同期地面气象要素资料,通过回归分析确定了主要污染物浓度24 h变率预报方程,经2005年6～9月的预报检验,本模型对银川市大气主要污染物浓度的变化有一定的预报能力。     

An extended Huff-model for robustly benchmarking and predicting retail network performance

This study proposes a modified Huff model that takes directly into account spatial competition between stores of the same brand, brand attraction based on actual brand performance and spatially variable substitution. The model uses only publicly available or easily acquirable data as input, whereas model output is extensively validated on various levels. These levels include comparison of modeled and real market shares on block, store and brand level for the Belgian food market. Results show that multi-objective optimization of model parameters yields comparable results on block level to other models in the literature but improved results on store and brand levels, thereby ensuring model robustness. This robustness also enables the application of the model for various business purposes as store location determination, leaflet distribution optimization, store and store concept benchmarking, without loss of spatial generality.     

An initial formal model for spatial data infrastructures

The Commission on Spatial Data Standards of the International Cartographic Association is working to define formal models and technical characteristics of Spatial Data Infrastructures (SDI). To date, this work has been restricted to the Enterprise and Information Viewpoints from the ISO Reference Model for Open Distributed Processing standard. The Commission has developed models for these two viewpoints. These models describe how the different parts of an SDI fit together in the viewpoints in question. These models should be seen as a contribution towards the overall model of the SDI and its technical characteristics. During the model development process, the roles of the different Actors in an SDI in the Enterprise and Information Viewpoints have also been identified in Use Case diagrams of an SDI. All the models have been developed using the Unified Modeling Language.     

An integrated data-directed numerical method for estimating the undiscovered mineral endowment in a region

An integrated data-directed numerical method has been developed to estimate the undiscovered mineral endowment within a given area. The method has been used to estimate the undiscovered uranium endowment in the San Juan Basin, New Mexico, U.S.A. The favorability of uranium concentration was evaluated in each of 2,068 cells defined within the Basin. Favorability was based on the correlated similarity of the geologic characteristics of each cell to the geologic characteristics of five area-related deposit models. Estimates of the undiscovered endowment for each cell were categorized according to deposit type, depth, and cutoff grade. The method can be applied to any mineral or energy commodity provided that the data collected reflect discovered endowment.     

An integrated model of clastic injectites and basin floor lobe complexes: implications for stratigraphic trap plays

Injectites sourced from base‐of‐slope and basin‐floor parent sandbodies are rarely reported in comparison to submarine slope channel systems. This study utilizes the well‐constrained palaeogeographic and stratigraphic context of three outcrop examples exposed in the Karoo Basin, South Africa, to examine the relationship between abrupt stratigraphic pinchouts in basin‐floor lobe complexes, and the presence, controls, and character of injectite architecture. Injectites in this palaeogeographic setting occur where there is: (i) sealing mudstone both above and below the parent sand to create initial overpressure; (ii) an abrupt pinchout of a basin‐floor lobe complex through steep confinement to promote compaction drive; (iii) clean, proximal sand beds aiding fluidization; and (iv) a sharp contact between parent sand and host lithology generating a source point for hydraulic fracture and resultant injection of sand. In all outcrop cases, dykes are orientated perpendicular to palaeoslope, and the injected sand propagated laterally beneath the parent sand, paralleling the base to extend beyond its pinchout. Understanding the mechanisms that determine and drive injection is important in improving the prediction of the location and character of clastic injectites in the subsurface. Here, we highlight the close association of basin‐floor stratigraphic traps and sub‐seismic clastic injectites, and present a model to explain the presence and morphology of injectites in these locations.     

An aeolian transport model for flat shifting sand fields under dynamic-limiting conditions

Estimating aeolian transport rates in the field is a difficult task even though various transport equations have been proposed. In this study, we used 5 years of field data on aeolian transport from an experimental plot for aeolian research located in the southeastern Tengger Desert to develop a practical aeolian transport equation capable of estimating transport rates in flat shifting sand fields. The resulting equation relates transport to the average wind velocity during a given period through a modified power function. The transport rate increases linearly with the cube of the average wind velocity. The equation can be generalized rate to a form that contains a proportionality coefficient and a threshold average wind velocity. The proposed model has an advantage over previous models in that it is based on a much larger sample size and corrected to account for variability in wind direction, sampling efficiency, and the height of the wind measurements.     

Estimating rainfall erosivity by incorporating seasonal variations in parameters into the Richardson model

Rainfall erosivity is an important climatic factor for predicting soil loss. Through the application of high-resolution pluviograph data at 5 stations in Huangshan City, Anhui Province, China, we analyzed the performance of a modified Richardson model that incorporated the seasonal variations in parameters α and β. The results showed that (1) moderate to high seasonality was presented in the distribution of erosive rainfall, and the seasonality of rainfall erosivity was even stronger; (2) seasonal variations were demonstrated in both parameters α and β of the Richardson model; and (3) incorporating and coordinating the seasonality of parameters α and β greatly improved the predictions at the monthly scale. This newly modified model is therefore highly recommended when monthly rainfall erosivity is required, such as, in planning soil and water conservation practices and calculating the cover-management factor in the Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE).     

Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China

The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission (TRMM) data with rain gauge data and further to use this TRMM data to drive a Distributed Time-Variant Gain Model (DTVGM) to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year (2001-2010) daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R² varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years (2001-2007) of data on daily hydrological processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamflow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.     

基于XGBoost的多源降水数据融合方法研究

气象站点观测降水难以精确反映降水时空分布与变化,而雷达降水存在复杂地形区域精度不高等问题。为了最大限度发挥两者的优势,文章以广东省北部山区为研究区域,选择2018-08-26—30一次暴雨过程为研究对象,结合地形、与海岸线距离、植被指数、经纬度等地表辅助参量,分析地面站点降水与地表辅助参量、雷达降水的相关关系,利用XGBoost算法与克里金插值方法,构建地面-雷达日降水数据融合模型,得到了空间分辨率为1 km的日降水融合数据集。此外,采用多元线性回归（LM）与克里金插值方法,实现了地面-雷达日降水数据的融合,并利用地面降水数据分别对XGBoost与LM日降水融合性能进行精度验证。结果表明：1）地面降水与雷达降水存在显著的正相关,地面降水与地表辅助参量之间的相关性随时间变化;2）XGBoost预测精度整体上高于LM预测结果;经模型残差校正后,XGBoost融合模型的精度整体上优于LM融合模型,这是因为XGBoost方法在捕捉地面降水与地表辅助参量、雷达降水之间关系性能上优于LM方法。     

跨国公司功能区位实证研究

随着交通通讯技术的发展,跨国公司在东道国内部实现功能空间分离.伴随中国渐进式的改革开放进程,全球500 强跨国公司逐步在中国实现地理扩张和功能扩张.本文基于1979-2008 年电子信息和医药化工产业的全球500 强跨国公司在华投资数据研究跨国公司功能区位.研究表明,跨国公司倾向于在已有投资的城市追加投资,不同功能呈现一定差异性地理分布,但功能之间共聚趋势明显.区域性总部和商务功能聚集在一线城市,生产功能布局于省会和一线城市周边地区,研发功能追随生产功能.条件逻辑模型分析表明,跨国公司功能区位存在显著的公司内集聚、跨公司集聚、来源国集聚以及跨功能共聚现象.市场潜力及城市行政地位也是吸引跨国公司投资的重要因素.随着全方位开放格局形成,集聚效应较制度优势更为重要.跨国公司分支机构地理集聚提升一线城市的功能,强化顶级城市的领导力和聚集力.跨国公司的功能片段化布局既依托我国的城市等级体系,又在一定程度上重塑我国城市空间结构,促进城市体系按价值链等级进行专业化分工并推动区域协作.     

预测陕西关中地区需水量的改进GM(1,1)模型

需水量评价与预测是水资源规划与管理一项重要的研究内容。本文采用定额法计算需水量。通过对陕西关中地区需水量要素组成的分析,认为需水量要素属平稳时间序列,且一阶累加生成数据系列满足指数规律,符合灰色预测条件。为了提高GM(1,1)模型的精度,采用一种改变背景值的新方法,即:中心逼近方法。通过精度检验,中心逼近式GM(1,1)模型平均误差百分比、误差平方和分别比传统的GM(1,1)模型提高了0.147和1.579。用中心逼近式GM(1,1)模型预测需水量各要素近期和中长期值,经检验,其中非农业人口、农业人口、耕地面积、工业总产值预测模型满足一级模型,等级为良好。牲畜头数预测模型为不合格模型,分析其原因,主要是因为时间序列数据不完全符合指数规律。通过定额法计算,预计75%保证率时2005年和2010年关中地区工农业需水量分别占总需水量的92.21%和89.75%,生活需水量分别占7%和9.04%。     

新加坡产业竞争力的钻石模型分析

本文以波特钻石模型为基础，吸取其它钻石模型分析方法的长处，分析模型的内生及外生因素的相互作用，及其对新加坡产业竞争力的影响，认为外生因素的变动至关重要，提出在经济全球化背景下，钻石模型各要素自我强化的途径。     

An integrated approach for addressing geographic uncertainty in spatial optimization

There exist many facets of error and uncertainty in digital spatial information. As error or uncertainty will not likely ever be completely eliminated, a better understanding of its impacts is necessary. Spatial analytical approaches, in particular, must somehow address data-quality issues. This can range from evaluating impacts of potential data uncertainty in planning processes that make use of methods to devising methods that explicitly account for error/uncertainty. To date, little has been done to structure methods accounting for error. This article develops an integrated approach to address data uncertainty in spatial optimization. We demonstrate that it is possible to characterize uncertainty impacts by constructing and solving a new multi-objective model that explicitly incorporates facets of data uncertainty. Empirical findings indicate that the proposed approaches can be applied to evaluate the impacts of data uncertainty with statistical confidence, which moves beyond popular practices of simulating errors in data.