鲁中山区地形对山东省一次暴雨影响的敏感性数值模拟试验

利用PSU/NCAR MM5V3中尺度数值模式进行了鲁中山区地形对一次台风暴雨的数值模拟敏感性试验,结果分析表明:鲁中山区地形作用对山东省暴雨有重要影响,迎风坡可引起低层气流和水汽的辐合上升运动增强,降水量增加,但偏北气流在迎风坡的水汽辐合不明显,降水量影响不大;山顶引起低层辐合上升运动减弱,辐散下沉运动增强,降水量减小;背风坡引起低层气流和水汽的辐合上升运动增强,降水量增加。     

Non‐local damage modelling of concrete: a procedure for the determination of model parameters

This paper presents a procedure for the determination of parameters of non‐local damage models. This is to assure a consistent response of a non‐local damage model, as choice of the internal length and other parameters of the model are varied. Correlations between the internal length and other parameters governing the local constitutive behaviour of the model are addressed and exploited. Focus is put on the relationship between the internal length of the non‐local model and the width of the fracture process zone. Numerical examples are used to demonstrate the rigour of the proposed method. Copyright © 2006 John Wiley & Sons, Ltd.     

Experimental study of extreme shear stress for shallow flow under simulated rainfall

The raindrop impact and overland flow are two major factors causing soil detachment and particle transportation. In this study, the turbulent characteristics of the shallow rain‐impacted water flow were investigated using a 2‐D fibre‐optic laser Doppler velocimetry (FLDV) and an artificial rainfall simulator. The fluctuating turbulent shear stress was computed using digital data processing techniques. The experimental data showed that the Reynolds shear stress follows a probability distribution with heavy tails. The tail probability increases with an increase of rainfall intensity or raindrop diameter, and it decreases with an increase of Reynolds number. A modified empirical equation was derived using both the raindrop diameter and rainfall intensity as independent variables to provide a better prediction of the Darcy‐Weisbach friction coefficient f under rainfall conditions. Copyright © 2009 John Wiley & Sons, Ltd.     

临沂中尺度数值预报系统及应用

介绍了临沂中尺度数值预报系统及预报产品的释用和模式系统应用雷达资料情况,并对2005年6~10月的业务运行结果进行了检验,对小雨和中雨预报效果较好,TS评分较高,对夜间温度预报平均值绝对误差在1.52~2.52℃之间,平均均方根误差在2.01~2.93℃之间。该系统降水预报质量较高,气温预报误差小,准确率高,对定时、定点、定量的精细化预报具有较高的参考价值。应用自主开发的SDAF软件包,对系统的预报产品进行释用,研制了暴雨、空气质量、极端气温、干热风等预报方法。将多普勒雷达回波强度加入模式,改变模式水汽场,明显改进了预报。对径向速度反演降水系统内部风场进入中尺度模式进行了初步试验,得出了一些有益结论。     

A multi-gene genetic programming model for estimating stress-dependent soil water retention curves

Soil water retention curve (SWRC) is an important parameter required for seepage modelling in unsaturated soil and is used for analysing rainfall-induced slope failures, design of waste contaminant liners and cover, etc. The influence of stress, which is one of constitutive variables that governs unsaturated soil behaviour on the SWRC, has been well recognised by researchers. Stress is essential for study as it drastically alters the soil fabric which includes macropores, minipores and micropores and thus affects the ability of soil to retain water. Various computational modelling techniques that formulate models based on existing databases such as UNSODA, ISRIC and HYPRES for the estimation of SWRC do not take into account the stress influence on soil behaviour. In the present work, three artificial intelligence (AI) methods of support vector regression, artificial neural network and multi-gene genetic programming (MGGP) have been applied to formulate the mathematical relationship between the water content and input variables such as stress and suction (i.e. stress-dependent soil water characteristic curves (SDSWRCs)). The results indicate that the MGGP model outperforms the other two models and is able to extrapolate the water content values satisfactorily along the stress value of 800 kPa. This MGGP model can then be deployed by experts for the estimation of SDSWRCs, thus eliminating the need for conducting costly and time-consuming experiments.     

Discharge prediction using hydraulic characteristics of mean velocity equation

Discharge is an important factor in river design for water utilization, water control and hydraulic structures; therefore, an accurate estimation of the discharge is required. At present, a rating curve depicting the relationship between a stage and discharge is used to calculate the discharge from river systems. Although the rating curve has an advantage in that it can predict and use the discharge during the flood season in which the measurement is difficult, there is room for improvement as it does not reflect the hydraulic characteristics of rivers. Therefore, in this study, discharge was predicted using the convenient calculation method with empirical mediating variables of the Manning and Chezy equations which were proposed by the author’s previous research as a new methodology for estimating discharge in an open channel. This was proven, based on the data measured in a meandering open channel system in a lab at the Mississippi River in the US and at the Columbia Del Dique Canal, and an accuracy level at a coefficient of 0.8 was demonstrated. Thus, this method, which reflects the hydraulic characteristics and predicts the discharge in a simple manner, is expected to be convenient in practice.     

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.