New Methodology to Characterize Shear Behavior of Joints by Combination of Direct Shear Box Testing and Numerical Simulations

A new procedure is presented, which combines big shear box tests on rocks and corresponding numerical simulations with explicit consideration of joint roughness to get deeper insight into the shear behavior of rock joints. The procedure consists of three parts: (1) constant normal load- or CNS-shear box tests with registration of shear- and normal-components of stress and displacements and deduction of basis rock mechanical parameters; (2) high resolution 3D-scanning of joint surface to deduce joint topography; and (3) set-up, run and evaluation of 3-dimensional numerical model with explicit duplication of joint roughness as back-analysis of shear box tests. The numerical back-analysis provides deeper insight into the joint behavior at the micro-scale. Several parameters can be deduced, like micro-slope angle distribution, aperture size distribution, local normal stress distribution and detailed analysis of dilation in relation to shear direction. The potential of the new procedure is illustrated exemplary by shear box tests on slate.     

Statistical data fusion of multi-sensor AOD over the Continental United States

This article illustrates two techniques for merging daily aerosol optical depth (AOD) measurements from satellite and ground-based data sources to achieve optimal data quality and spatial coverage. The first technique is a traditional Universal Kriging (UK) approach employed to predict AOD from multi-sensor aerosol products that are aggregated on a reference grid with AERONET as ground truth. The second technique is spatial statistical data fusion (SSDF); a method designed for massive satellite data interpolation. Traditional kriging has computational complexity O(N³), making it impractical for large datasets. Our version of UK accommodates massive data inputs by performing kriging locally, while SSDF accommodates massive data inputs by modelling their covariance structure with a low-rank linear model. In this study, we use aerosol data products from two satellite instruments: the moderate resolution imaging spectrometer and the geostationary operational environmental satellite, covering the Continental United States.     

Floodplain hydrology of the Mekong Delta,Vietnam

The Mekong Delta is one of the largest and most intensively used estuaries in the world. Each year it witnesses widespread flooding which is both the basis of the livelihood for more than 17 million people but also the major hazard. Therefore, a thorough understanding of the hydrologic and hydraulic features is urgently required for various planning purposes. While the general causes and characteristics of the annual floods are understood, the inundation dynamics in the floodplains in Vietnam which are highly controlled by dikes and other control structures have not been investigated in depth. Especially, quantitative analyses are lacking, mainly due to scarce data about the inundation processes in the floodplains. Therefore, a comprehensive monitoring scheme for channel and floodplain inundation was established in a study area in the Plain of Reeds in the northeastern part of the Vietnamese Delta. This in situ data collection was complemented by a series of high‐resolution inundation maps derived from the TerraSAR‐X satellite for the flood seasons 2008 and 2009. Hence, the inundation dynamics in the channels and floodplains, and the interaction between channels and floodplains, could be quantified for the first time. The study identifies the strong human interference which is governed by flood protection levels, cropping patterns and communal water management. In addition, we examine the tidal influence on the inundation in various parts of the Delta, since it is expected that climate change‐induced sea level rise will increase the tidal contribution to floodplain inundation. Copyright © 2011 John Wiley & Sons, Ltd.     

Ensemble rainfall forecasting with numerical weather prediction and radar‐based nowcasting models

The overall objective of this study is to improve the forecasting accuracy of the precipitation in the Singapore region by means of both rainfall forecasting and nowcasting. Numerical Weather Predication (NWP) and radar‐based rainfall nowcasting are two important sources for quantitative precipitation forecast. In this paper, an attempt to combine rainfall prediction from a high‐resolution mesoscale weather model and a radar‐based rainfall model was performed. Two rainfall forecasting methods were selected and examined: (i) the weather research and forecasting model (WRF); and (ii) a translation model (TM). The WRF model, at a high spatial resolution, was run over the domain of interest using the Global Forecast System data as initializing fields. Some heavy rainfall events were selected from data record and used to test the forecast capability of WRF and TM. Results obtained from TM and WRF were then combined together to form an ensemble rainfall forecasting model, by assigning weights of 0.7 and 0.3 weights to TM and WRF, respectively. This paper presented results from WRF and TM, and the resulting ensemble rainfall forecasting; comparisons with station data were conducted as well. It was shown that results from WRF are very useful as advisory of anticipated heavy rainfall events, whereas those from TM, which used information of rain cells already appearing on the radar screen, were more accurate for rainfall nowcasting as expected. The ensemble rainfall forecasting compares reasonably well with the station observation data. Copyright © 2012 John Wiley & Sons, Ltd.     

Sustainable groundwater development in the coastal Tra Vinh province in Vietnam under saltwater intrusion and climate change

Three-dimensional transient groundwater flow and saltwater transport models were constructed to assess the impacts of groundwater abstraction and climate change on the coastal aquifer of Tra Vinh province (Vietnam). The groundwater flow model was calibrated with groundwater levels (2007–2016) measured in 13 observation wells. The saltwater transport model was compared with the spatial distribution of total dissolved solids. Model performance was evaluated by comparing observed and simulated groundwater levels. The projected rainfalls from two climate models (MIROC5 and CRISO Mk3.6) were subsequently used to simulate possible effects of climate changes. The simulation revealed that groundwater is currently depleted due to overabstraction. Towards the future, groundwater storage will continue to be depleted with the current abstraction regime, further worsening in the north due to saltwater intrusion from inland trapped saltwater and on the coast due to seawater intrusion. Notwithstanding, the impact from climate change may be limited, with the computed groundwater recharge from the two climate models revealing no significant change from 2017 to 2066. Three feasible mitigation scenarios were analyzed: (1) reduced groundwater abstraction by 25, 35 and 50%, (2) increased groundwater recharge by 1.5 and 2 times in the sand dunes through managed aquifer recharge (reduced abstraction will stop groundwater-level decline, while increased recharge will restore depleted storage), and (3) combining 50% abstraction reduction and 1.5 times recharge increase in sand dune areas. The results show that combined interventions of reducing abstraction and increasing recharge are necessary for sustainable groundwater resources development in Tra Vinh province.

     

WV-3遥感数据在滇西矿产资源开发与地质灾害调查中的应用

选择云南三江中南段高黎贡山之南作为研究对象,利用WorldView-3卫星数据高空间分辨率的特点,基于Skyline软件构建三维模拟场景,从不同视域范围、远近尺度、方位视角对解译目标进行全方位展示,获取了不同矿山开发及地质灾害的典型识别标志,进行矿产资源开发状况精细识别及地质灾害详细信息提取,解译出区内建筑石料用灰岩等5种非金属矿以及滑坡等3种类型地质灾害,为矿山管理及地质灾害调查提供快速精准的目标,提升工作效率和质量。     

乌兰布和沙漠东南缘白沙蒿(Artemisia sphaerocphala)灌丛沙堆形态特征与固沙能力

白沙蒿(Artemisia sphaerocphala)灌丛沙堆是乌兰布和沙漠最为广泛分布的典型荒漠灌丛沙堆之一。本研究对白沙蒿灌丛的灌丛形态参数、沙堆形态参数进行了野外测定,探讨沙堆形态发育及固沙能力与白沙蒿灌丛形态的关系。结果表明:白沙蒿灌丛高度随着灌丛半径的增加而呈对数曲线增加,在灌丛较小时灌丛高度增长较快,随后渐趋于稳定,其水平方向发育速度大于垂直方向;白沙蒿灌丛沙堆半径及高度随灌丛半径和高度增加而增加,二者呈显著线性关系,沙堆水平方向发育受到灌丛冠幅的影响,沙堆垂直方向的发育水平取决于灌丛高度;随白沙蒿地上部分鲜重的增加,灌丛沙堆底面积、高度、沙堆体积和固沙效率均呈极显著线性增加(p0.01);白沙蒿灌丛越大其固积沙堆也越大,固沙率越高,不同大小灌丛白沙蒿间的固沙效率差异显著(p0.05);白沙蒿灌丛背风侧的积沙宽度(y)与积沙距离(x)显著相关(R2=0.9917),其线性回归方程为y=-19.654x+122.41,在距离灌丛背风面6~7倍高度的地方,积沙接近消失。     

Detection of mines in acoustic images using higher order spectral features

A new pattern-recognition algorithm detects approximately 90% of the mines hidden in the Coastal Systems Station Sonar0, 1, and 3 databases of cluttered acoustic images, with about 10% false alarms. Similar to other approaches, the algorithm presented here includes processing the images with an adaptive Wiener filter (the degree of smoothing depends on the signal strength in a local neighborhood) to remove noise without destroying the structural information in the mine shapes, followed by a two-dimensional FIR filter designed to suppress noise and clutter, while enhancing the target signature. A double peak pattern is produced as the FIR filter passes over mine highlight and shadow regions. Although the location, size, and orientation of this pattern within a region of the image can vary, features derived from higher order spectra (HOS) are invariant to translation, rotation, and scaling, while capturing the spatial correlations of mine-like objects. Classification accuracy is improved by combining features based on geometrical properties of the filter output with features based on HOS. The highest accuracy is obtained by fusing classification based on bispectral features with classification based on trispectral features.