Center for Disaster Reduction

Science and, Taiwan

Center for Disaster Reduction

Science and, Taiwan
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Chen W.-B.,Center for Disaster Reduction | Lin L.-Y.,Center for Disaster Reduction | Jang J.-H.,National Cheng Kung University | Chang C.-H.,Center for Disaster Reduction
Water (Switzerland) | Year: 2017

The storm tide is a combination of the astronomical tide and storm surge, which is the actual sea water level leading to flooding in low-lying coastal areas. A full coupled modeling system (Semi-implicit Eulerian-Lagrangian Finite-Element model coupled with Wind Wave Model II, SELFE-WWM-II) for simulating the interaction of tide, surge and waves based on an unstructured grid is applied to simulate the storm tide and wind waves for the northeastern coast of Taiwan. The coupled model was driven by the astronomical tide and consisted of main eight tidal constituents and the meteorological forcings (air pressure and wind stress) of typhoons. SELFE computes the depth-averaged current and water surface elevation passed to WWM-II, while WWM-II passes the radiation stress to SELFE by solving the wave action equation. Hindcasts of wind waves and storm tides for five typhoon events were developed to validate the coupled model. The detailed comparisons generally show good agreement between the simulations and measurements. The contributions of surge induced by wave and meteorological forcings to the storm tide were investigated for Typhoon Soudelor (2015) at three tide gauge stations. The results reveal that the surge contributed by wave radiation stress was 0.55 m at Suao Port due to the giant offshore wind wave (exceeding 16.0 m) caused by Typhoon Soudelor (2015) and the steep sea-bottom slope. The air pressure resulted in a 0.6 m surge at Hualien Port because of an inverted barometer effect. The wind stress effect was only slightly significant at Keelung Port, contributing 0.22 m to the storm tide. We conclude that wind waves should not be neglected when modeling typhoon-induced storm tides, especially in regions with steep sea-bottom slopes. In addition, accurate tidal and meteorological forces are also required for storm tide modeling. © 2017 by the authors.

Chen W.-B.,Center for Disaster Reduction | Liu W.-C.,National United University | Liu W.-C.,Taiwan Typhoon and Flood Research Institute
Water (Switzerland) | Year: 2014

Low-lying coastal regions and their populations are at risk during storm surge events and high freshwater discharges from upriver. An integrated storm surge and flood inundation modeling system was used to simulate storm surge and inundation in the Tsengwen River basin and the adjacent coastal area in southern Taiwan. A three-dimensional hydrodynamic model with an unstructured grid was used, which was driven by the tidal elevation at the open boundaries and freshwater discharge at the upriver boundary. The model was validated against the observed water levels for three typhoon events. The simulation results for the model were in reasonable agreement with the observational data. The model was then applied to investigate the effects of a storm surge, freshwater discharge, and a storm surge combined with freshwater discharge during an extreme typhoon event. The super Typhoon Haiyan (2013) was artificially shifted to hit Taiwan: the modeling results showed that the inundation area and depth would cause severe overbank flow and coastal flooding for a 200 year return period flow. A high-resolution grid model is essential for the accurate simulation of storm surges and inundation. © 2014 by the authors.

Hsu P.-H.,National Taiwan University | Su W.-R.,Center for Disaster Reduction
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2012

Due to the particular geographical location and geological condition, Taiwan suffers from many natural hazards which often cause series property damages and life losses. To reduce the damages and casualty, an effective real-time system for hazard prediction and mitigation is necessary. In this study, a case study for landslide hotspots and hazard factors investigation are analyzed in accordance with spatial data mining technology from massive spatial database. Many different kinds of geospatial data, such as the terrain elevation, land cover types, the distance to roads and rivers, geology maps, and monitoring rainfall data etc., are collected into the database for spatial autocorrelation and spatial regression analysis. In order to guarantee the data quality, the spatial data cleaning is essential to remove the noises, errors, outliers, and inconsistency hiding in the input spatial data sets. The experiment results show that the hot spot analysis exactly has the ability to indicate the hazards locations. In addition, the spatial relationship can be built using the geographically weight regression (GWR) model. © 2012 IEEE.

Lee C.-S.,Center for Disaster Reduction | Chou -C.,National Taiwan University | Teng H.-H.,National Taiwan University
Proceedings of the American Society for Composites - 29th Technical Conference, ASC 2014; 16th US-Japan Conference on Composite Materials; ASTM-D30 Meeting | Year: 2014

The purpose of this paper is to introduce an analytical procedure and experimental validation on the lateral load-displacement behavior of FRP Jacketed RC columns. To successfully apply FRP materials to building columns, bridge piers and pile foundation, the key is to understand the mechanical behavior of FRP-confined concrete and accurately predict the load-displacement response of the column. To aim this purpose, Lee and Hegemier (2009) developed a dilatancy-based concrete model to predict strain softening/hardening vs. level of lateral confinement on FRP-confined concrete. Incorporated with this novel concrete model, a moment-curvature program and a residual shear model were developed to predict the actual sectional capacity and shear strength of FRP-jacketed RC columns. Further, a load-displacement model and an associated computational algorithm for FRP jacketed RC columns subjected to lateral loads were developed. The proposed load-displacement model was validated by the experimental response and failure conditions of RC columns subject to combined axial and seismic-type (lateral) loads. It was also validated via the results of the UCSD quasi-static tests on "blast columns", and satisfactory correlation with the experimental load-displacement curves was observed. This paper will also introduce a uniaxial compressive test series on the concrete cylinders jacketed by a new FRP composite system developed by authors. A set of cylinder specimens with various FRP jacket designs are designed. Through these tests, the authors expect to verify the efficiency of the advanced FRP composite jacket and establish the axial stress-strain and axial-lateral responses on the whole material system, and use the stress-strain relation to predict the lateral load-displacement responses of the RC columns jacketed by the new FRP composite system via the proposed model.

Jang J.-H.,Center for Disaster Reduction | Yu P.-S.,National Cheng Kung University | Yeh S.-H.,Center for Disaster Reduction | Fu J.-C.,Center for Disaster Reduction | Huang C.-J.,Center for Disaster Reduction
Hydrological Processes | Year: 2012

Deterministic flood inundation mapping is valuable for the investigation of detailed flood depth and extent. However, when these data are used for real-time flood warning, uncertainty arises while encountering the difficulties of timely response, message interpretation and performance evaluation that makes statistical analysis necessary. By incorporating deterministic flood inundation map outputs statistically by means of logistic regression, this paper presents a probabilistic real-time flood warning model determining region-based flood probability directly from rainfall, being efficient in computation, clear in message, and valid in physical meaning. The calibration and validation of the probabilistic model show a satisfactory overall correctness rate, with the hit rate far surpassing the false alarm rate in issuing flood warning for historical events. Further analyses show that the probabilistic model is effective in evaluating the level of uncertainty lying within flood warning which can be reduced by several techniques proposed in order to improve warning performance. © 2011 John Wiley & Sons, Ltd.

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