Topographic zonation of infiltration in the hilly loess region,north china

Field infiltration tests using portable rainfall infiltrometers were conducted in the Wangjiagou experimental basin in the hilly loess region of north China. Based on data collected at 27 sites, a topographic zonation of infiltration characteristics was observed. The average steady infiltration rate and the average ponding time decreased from the hilltop to the hillslope and further decreased to the gully wall. Such a zonation is closely related to the variations of topography, soil and land use conditions in the study area. A general infiltration model is proposed. Collected field data are used to establish the applicability of the proposed model in the study area.     

Mapping and Assessing Landfills Surface Temperature Using Landsat 8 Satellite Data. A Case Study in Vietnam

Izvestiya, Atmospheric and Oceanic Physics - In recent years, rapid urbanization and population growth have led to an overload of waste in big cities of Vietnam. Waste decomposition is always...     

Multi-objective optimal design for flood risk management with resilience objectives

In flood risk management, the divergent concept of resilience of a flood defense system cannot be fully defined quantitatively by one indicator and multiple indicators need to be considered simultaneously. In this paper, a multi-objective optimization (MOO) design framework is developed to determine the optimal protection level of a levee system based on different resilience indicators that depend on the probabilistic features of the flood damage cost arising under the uncertain nature of rainfalls. An evolutionary-based MOO algorithm is used to find a set of non-dominated solutions, known as Pareto optimal solutions for the optimal protection level. The objective functions, specifically resilience indicators of severity, variability and graduality, that account for the uncertainty of rainfall can be evaluated by stochastic sampling of rainfall amount together with the model simulations of incurred flood damage estimation for the levee system. However, these model simulations which usually require detailed flood inundation simulation are computationally demanding. This hinders the wide application of MOO in flood risk management and is circumvented here via a surrogate flood damage modeling technique that is integrated into the MOO algorithm. The proposed optimal design framework is applied to a levee system in a central basin of flood-prone Jakarta, Indonesia. The results suggest that the proposed framework enables the application of MOO with resilience objectives for flood defense system design under uncertainty and solves the decision making problems efficiently by drastically reducing the required computational time.     

Satellite-based monitoring of contrasting characteristics of suspended sediment discharged from the Red and the Ma river systems along the northern coast of Vietnam

The northern coast of Vietnam has accumulated a significant amount of sediment discharged from the multiple distributaries of rivers such as the Red River and Ma River.While recent decreases of the sediment supply appears to have a significant impact on coastal erosion,the complex network of these distributaries makes it difficult to determine the overall spatiotemporal characteristics of sediment discharges and related topographic changes.The goal of the current study is to develop a satellite-based monitoring system for observation of turbidity discharged from the multiple rivers and to investigate the applicability of the developed monitoring system through a case study on the northern coast of Vietnam.Based on the in-situ observed data,a formulawas determined for estimation of the surface water turbidity as a function of the red band reflectance of Moderate Resolution Imaging Spectro-radiometer(MODIS)images.The formula was then combined with a newly determined threshold for cloud-masking to obtain maps of the nearshore turbidity patterns.These maps capture the spatiotemporal water surface turbidity along the entire coast of the Red River Delta and the coast around theMa River mouth over the past sixteen years with frequency of twice a day.Finally,long-term trends of the turbidity patterns from multiple rivers were compared with the in-situ observation data and it was found that the Red River and the Ma River showed clearly contrasting characteristics,which reasonably explain the recent coastal shoreline changes and characteristics of sediment sampled along the coast.     

Multi‐dimensional analyses of the SEAM controlled source electromagnetic data—the story of a blind test of interpretation workflows

Using a subset of the SEG Advanced Modeling Program Phase I controlled‐source electromagnetic data, we apply our standard controlled‐source electromagnetic interpretation workflows to delineate a simulated hydrocarbon reservoir. Experience learned from characterizing such a complicated model offers us an opportunity to refine our workflows to achieve better interpretation quality. The exercise proceeded in a blind test style, where the interpreting geophysicists did not know the true resistivity model until the end of the project. Rather, the interpreters were provided a traditional controlled‐source electromagnetic data package, including electric field measurements, interpreted seismic horizons, and well log data. Based on petrophysical analysis, a background resistivity model was established first. Then, the interpreters started with feasibility studies to establish the recoverability of the prospect and carefully stepped through 1D, 2.5D, and 3D inversions with seismic and well log data integrated at each stage. A high‐resistivity zone is identified with 1D analysis and further characterized with 2.5D inversions. Its lateral distribution is confirmed with a 3D anisotropic inversion. The importance of integrating all available geophysical and petrophysical data to derive more accurate interpretation is demonstrated.     

Married couples’ decision-making about household natural hazard preparedness: a case study of hurricane hazards in Sarasota County,Florida

Natural Hazards - Survey-based studies of household natural hazard preparedness have often relied on individual-level data to predict household-level preparedness behaviors, in doing so neglecting...     

Analysis of ground vibrations due to underground trains by 2.5D finite/infinite element approach

The 2.5D finite/infinite element approach is adopted to study wave propagation problems caused by underground moving trains. The irregularities of the near field, including the tunnel structure and parts of the soil, are modeled by the finite elements, and the wave propagation properties of the far field extending to infinity are modeled by the infinite elements. One particular feature of the 2.5D approach is that it enables the computation of the three-dimensional response of the half-space, taking into account the load-moving effect, using only a two-dimensional profile. Although the 2.5D finite/infinite element approach shows a great advantage in studying the wave propagation caused by moving trains, attention should be given to the calculation aspects, such as the rules for mesh establishment, in order to avoid producing inaccurate or erroneous results. In this paper, some essential points for consideration in analysis are highlighted, along with techniques to enhance the speed of the calculations. All these observations should prove useful in making the 2.5D finite/infinite element approach an effective one.     

三维电磁阵列剖面法的基本原理及应用

本文论述了三维电磁阵列剖面法的基本原理，并从理论上论述了大地电磁测深中的静态效应是由电磁响应中与频率无关的静态项引起的，基于这一原理，本文提出了三维ＥＭＡＰ野外采集方式和数据处理方程。三维ＥＭＡＰ法不仅能消除ＭＴ中的静态效应，而且由于采集信息量大大增加，较常规ＭＴ有更好的地质效果，文中给出的实例证明了这一点。     

Structural damage detection using the optimal weights of the approximating artificial neural networks

This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd.