Extension analysis-based tropical cyclone landfall incidences prediction

Feng L.H.,1* Zhang Q.2 and Si D.2

Variation of tropical cyclone (TC) landfall results from the comprehensive effect of various physical factors including celestial activities, atmospheric circulation and influences from underlying surfaces. In this study, the previous predictors are used to conduct calculation, thus enabling the extension analysis to have prediction function. Through repeated adjustment of the grade limit value (classical domain and joint domain) of the factors, the historical fitting value of the calculation number of TC landfall incidences with the actual number can be made to reach the maximum value with good results. It has practical significance to typhoon prevention and disaster relief in coastal areas. Results indicate that using extension analysis to predict TC landfall incidences is an effective method.

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An Approach to Temperature analysis and forecasting using Empirical Mode Decomposition Method and Wavelet Neural Network

Guo Yongcai, Shao Yanhua* and Gao Chao

Temperature analysis and forecasting is a kind of classic meteorological problem and the temperature coefficient plays an important role in many fields. In order to analyze the temperature process more profound and predict the future temperature more exactly, the Empirical Mode Decomposition (EMD) and Wavelet Neural Network (WNN) method are used to obtain more valuable information based on the limited historical temperature data in Chongqing Municipality of China. The main steps are as follows: first, we carry out temperature signal de-noising by using wavelet transform. Secondly, decomposed signals under different scales are obtained by using EMD to reduce the non-stationarity in the signals. The temperature data of Chongqing from 1951 years to 2010 years are used as the training set. They are first normalized and then utilized as input data for the WNN. Finally, the component of decomposition is predicted by using WNN and then the predicted results are restructured. The method was tested by the temperature data of 2011 whole year. The predict results, which compared with Elman ANN and WNN, show that the predicted results are in good agreement with the actual data. So this method is reliable and useful for the temperature’s analysis and forecasting

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Earthquake Disaster Mitigation by using Magneto-rheo¬logical dampers

Guo Ying-Qing1* and Xu Zhao-Dong2

In the course of the vibration mitigation control of structures by using magneto-rheological (MR) dampers, the control currents of MR dampers have to be chosen accurately and quickly. The fuzzy control technology has strong robustness and intelligent characteristics, so it is used to choose the control currents of MR damper. How to design a fuzzy controller for MR damper is studied and a five-floor steel structure with five MR dampers (each floor with one damper) using the designed fuzzy controller is simulated. Simulation results of the fuzzy control structure are compared with those of the ON control structure, the OFF control structure and the uncontrolled structure. Analysis results demonstrate that the fuzzy control strategy can determine control currents of MR dampers accurately and quickly, furthermore, the fuzzy control strategy reduces seismic responses of structures more effectively than the ON control strategy and the OFF control strategy.

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Optimization in Structural Altitude for Seismic Base Isolation at Medium Risk Earthquake Disaster Region

Islam A.B.M.S.,* Jameel M., Jumaat M. Z. and Rahman M. M.

Seismic isolation through rubber bearing at structural base poses significant reduction in energy ensuring flexibility to the structure. The bearings act as earthquake induced load resisting system. This seismic load is predominant lateral load acting on building structures along with wind load. If wind load is much greater than the earthquake load, inserting isolator will bring no advantage in design. Furthermore, if the time period of a building without isolator is greater than the reasonable value, incorporation of isolator will not convey much difference to the building behavior with respect to seismic load. So the objective of the study is to examine the building structures in region of medium risk seismicity for dissimilar heights and plan area to predict critical height up to which energy dissipation bearing is competent. 108 numbers of models for different configurations of 4 to 30 stories structures have been built up. All the structures are analyzed in finite element approach subjected to proper lateral loading. The characteristics and functions of different kinds of isolators are introduced along with isolation suitability for building structures. The relationship among governing lateral load, building altitude and time period is evaluated as well. The study reveals that though seismic base shear governs up to larger building height, for higher tallness, the structure may experience larger time periods than the most suitably limiting value for incorporating isolator. Realistic structural analyses envisage that up to 30~40m height seismic base isolator can be efficiently incorporated in medium risk seismic vicinity for RCC building structures.

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An attempt to predict earthquake with satellite date

Yang Jie * and Guo Guangmeng

Satellite thermal anomaly and earthquake cloud were two kinds of possible earthquake precursors reported widely. Most of the reports were post-earthquake analysis. In the paper, we used these two methods to make an attempt to predict earthquake. First, cloud anomaly according to the FY2C and FY-2D satellite data was analyzed to get a suspicious area roughly and then thermal anomaly of outgoing IR radiation according to the National Oceanic and Atmospheric Administration(NOAA) satellite data was analyzed to verify this anomaly. The result of two prediction examples indicates that the earthquake prediction success percent with these two kinds of precursors is better than that done with only one precursor. In the future, if the geophysical data such as ground water, Rn gas, gravity, geology structure data and so on were used together, the successful percent will surely increase in futur

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Application of Geospatial Technology and Information Value Technique in Landslide Hazard Zonation Mapping: A Case Study of Giri Valley, Himachal Pradesh

Balasubramani K.* and Kumaraswamy K.

Landslide is the movement of a mass of rock, debris or earth down a slope. It is considered as one of the most devastating natural hazards which cause severe damage to properties and human lives in a region. Landslides are mostly unpredictable in nature and the susceptibility of occurrence can be assessed either qualitatively or quantitatively using geospatial techniques. This paper evaluates application potential of such technology and information value technique (quantitative) in landslide hazard zonation. To evaluate the application potential and result, a part of Giri valley of Himachal Pradesh, India has been chosen as the study area. This area exhibits a variety of landslide movements and can be easily located through remote sensing images. The major parameters considered in the landslide zonation include lithology, lineament, slope, streams, vegetation, land use/land cover and road. The layers are generated from satellite images coupled with collateral data. Landsat ETM+ and ASTER GDEM data are used for creating Digital Elevation Model (DEM) and related layers trough ArcGIS. All these layers are processed through information value technique to find out different landslide hazard zones. The area has been classified into five zones viz. very low, low, moderate, high and very high landslide hazard prone on the basis of subjectivity. Further, the final hazard zonation map is compared with the actual landslide map for validation.

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DPSIR and Disaster Risk Analysis

Lee Hsiang-Chieh

This study develops a model that uses the DPSIR (Drivers, Pressures, States, Impacts and Responses) model to elucidate the relations between hazard, risk and society. The DPSIR model is used because it places emphasis on current state as well as time and change. In addition, it talks about chains of causation which helps us understand the different types of causes of disasters. This study compares its proposed model to similar models by UNEP etc. Three major advantages of the model proposed in this study are: (1) Theoretically, this study adds to the literature of disaster risk by combining the idea of DPSIR and disaster risk; (2) Practically, this study provides suggestions regarding how to implement the DPSIR model. It suggests starting from Impacts when analyzing historical cases and beginning from Drivers, Pressures and States when studying potential impacted zones without disaster experience; (3) Practically, the model helps researchers explore the causes of disaster and inspect risk management strategies from different angles (Drivers, Pressures, or States).

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Prediction of Shallow Landslide prone regions in Undulating Terrains

Ramachandra T. V. 1,2,3,* Bharath H. Aithal,1,2 Uttam Kumar1 and Joshi N. V.1

Genetic Algorithm for Rule-set Prediction (GARP) and Support Vector Machine (SVM) with free and open source software (FOSS) – Open Modeller were used to model the probable landslide occurrence points. Environmental layers such as aspect, digital elevation, flow accumulation, flow direction, slope, land cover, compound topographic index and precipitation have been used in modeling. Simulated output of these techniques is validated with the actual landslide occurrence points, which showed 92% (GARP) and 96% (SVM) accuracy considering precipitation in the wettest month and 91% and 94% accuracy considering precipitation in the wettest quarter of the year.

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Improving Communication and Collaboration for Drought Vulnerability Analysis in China

Wang Jinsong1,2* and Hayes Michael J. 2

Drought is an inevitable recurrent climatic event and a natural disaster affecting the greatest spatial extent around the world. It also has wide-reaching impacts on society and environment. Because of its dual characteristics in both the natural and social domains, drought has drawn widespread attention in the geosciences research community, the government and the society. The characteristics of drought also make it a challenge to detect and monitor drought accurately and especially to determine the onset and the end time of drought. Because of this challenge, it is essential to reduce the drought vulnerability and the subsequent drought impacts. This paper discusses the historical and recent drought conditions in China, the lessons and experiences of drought vulnerability analysis learnt from several locations and how these lessons and experiences can be applied in China.

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