Browsing by Author "Wu, Shiang-Jen"

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A probabilistic model for evaluating the reliability of rainfall thresholds for shallow landslides based on uncertainties in rainfall characteristics and soil properties
(2017-05-01)
Wu, Shiang-Jen
;
Hsiao, Yi-Hua
;
Yeh, Keh-Chia
;
Yang, Sheng-Hsueh
;
土木工程學系
This study aims to develop a probabilistic rainfall threshold estimation model for shallow landslides (PRTE_LS) in order to quantify its reliability while being affected by uncertainties in the rainfall characteristics and soil properties. The rainfall characteristics include the rainfall duration, depth and storm patterns in which their uncertainties result from temporal variation. The effective cohesion of soil, the unit weight of soil, the angle of internal friction, hydraulic conductivity and hydraulic diffusivity are the soil properties represented as the soil parameters in the TRIGRS model in which uncertainties are attributed to spatial variation. After analyzing the sensitivity of rainfall characteristics and TRIGRS parameters to the estimation of rainfall thresholds, the maximum rainfall intensity, storm pattern and soil parameters (soil cohesion, soil friction angle and total unit weight of soil) are retreated as uncertainty factors used in the model development. The proposed PRTE_LS model is used for the reliability assessment of the issued rainfall thresholds in the Jhoukou River watershed, southern Taiwan, to demonstrate its applicability. The results indicate that the corresponding exceedance probability (i.e., underestimated risk) approximates 0.1 on average. In other words, its reliability reaches 0.9. However, issued rainfall thresholds with high reliability might hardly achieve the goal of early warning because shallow landslides can possibly happen before the actual rainfall amount exceeds the threshold. Consequently, the proposed PRTE_LS model can modify issued rainfall thresholds with the specific occurrence probability under the critical safety factors and warning durations being considered. As a result, the proposed PRTE_LS can not only quantify the reliability of the issued rainfall thresholds, but its results can also be referred to in modifying the issued thresholds in order to enhance the early-warning performance.
Application of modified nonlinear storage function on runoff estimation
(2011-03-01)
Wu, Shiang-Jen
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Ho, Lin-Fang
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Yang, Jinn-Chuang
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土木工程學系
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Department of Civil Engineering
This study proposed a modified nonlinear storage function runoff model to take into account the storage hysteresis effect, in which there exists difference of the storage-discharge relationship between the rising and recession limb. Since the modified storage function runoff has seven parameter, a parameter-calibration method, which combines the genetic algorithm with the least square criterion. For model calibration and validation, twenty rainfall-runoff events (1968-2005) recorded at Wudu gage in Keelung River in northern Taiwan were used in the study. The results of model validation reveal that the modified storage function runoff model not only produces the realistic storage-discharge relationship, but also provides a good estimation of the runoff. (C) 2011 International Association of Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.
Incorporating Daily Rainfall to Derive At-Site Hourly Depth-Duration-Frequency Relationships
(2009-09-01)
Wu, Shiang-Jen
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Tung, Yeou-Koung
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Yang, Jinn-Chuang
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土木工程學系
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Department of Civil Engineering
Two models are herein presented to derive at-site hourly based rainfall depth-duration-frequency (DDF) relationships by incorporating daily rainfall information. The model development is motivated by the desire to utilize daily rainfall data that are in existence prior to the conversion from a manned gauge to an automatic one for improving the establishment of hourly based rainfall DDF relation at the site. The performance of the proposed models is assessed by comparing the rainfall DDF relationships derived from the conventional method using solely annual maximum rainfalls of various durations. Hourly rainfall data at Hong Kong Observatory over the period of 1884-1990 are used to demonstrate the application of the two proposed models and to examine their performance. Results from the numerical experiments show that the two proposed models, which incorporate daily rainfall data, are capable of producing more accurate and reliable rainfall DDF relationships than the conventional method solely on the basis of annual maximum hourly rainfalls.
Modeling probabilistic lag time equation in a watershed based on uncertainties in rainfall, hydraulic and geographical factors
(2016-12)
Wu, Shiang-Jen
;
Yeh, Keh-Chia
;
Ho, Chih-Hung
;
Yang, Sheng-Hsueh
;
土木工程學系
This study proposes a framework for developing a probabilistic lag time (PLT) equation by taking into account uncertainty factors, including the rainfall factor (i.e., the maximum rainfall intensity), the hydraulic factor (i.e., the roughness coefficient in the river), and the geometrical factors (the catchment area, the length, and the basin slope). The proposed PLT equation is established based on the lag time equation by means of the uncertainty and risk analysis, i.e., the advanced first-order and second-moment approach. Hourly rainfall data in the Bazhang River watershed are used in the model development and application. The results indicate that compared with observed lag times extracted from historical events, the observed ones are mostly located within the 95% confidence interval of the simulated lag times. In addition, the resulting underestimated risk from the PLT equation can reasonably represent the degree of the difference between the estimated lag time and observed lag time. Consequently, the proposed PLT equation not only estimates the lag time at specific locations along the river, but also provides a corresponding reliability.
Risk analysis for flood-control structure under consideration of uncertainties in design flood
(2011-07-01)
Wu, Shiang-Jen
;
Yang, Jinn-Chuang
;
Tung, Yeou-Koung
;
土木工程學系
;
Department of Civil Engineering
This study presents a risk analysis model to evaluate the failure risk for the flood-control structures in the Keelung River due to the uncertainties in the hydrological and hydraulic analysis, including hydrologic, hydraulic, and geomorphologic uncertainty factors. This study defines failure risk as the overtopping probability of the maximum water level exceeding the levee crown, and the proposed risk analysis model integrates with the advanced first-order and second-moment (AFOSM) method to calculate the overtopping probability of levee system. The proposed model is used to evaluate the effects of the freeboard and flood-diversion channel on the flood-control ability of the levees in the Keelung River, which were designed based on the 3-day, 200-year design rainfall event. The numerical experiments indicate that the hydrologic uncertainty factors have more effect on the estimated maximum water level than hydraulic and geomorphologic uncertainty factors. In addition, the freeboard and the flood-diversion channel can effectively reduce the overtopping probability so as to significantly enhance the flood-control capacity of the levee system in the Keelung River. Eventually, the proposed risk analysis successfully quantifies the overtopping risk of the levee system under a scenario, the increase in the average 200-year rainfall amount due to climate change, and the results could be useful when planning to upgrade the existing levee system.
Stochastic generation of hourly rainstorm events
(2006-12-01)
Wu, Shiang-Jen
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Tung, Yeou-Koung
;
Yang, Jinn-Chuang
;
土木工程學系
;
Department of Civil Engineering
Occurrence of rainstorm events can be characterized by the number of events, storm duration, rainfall depth, inter-event time and temporal variation of rainfall within a rainstorm event. This paper presents a Monte-Carlo based stochastic hourly rainfall generation model considering correlated non-normal random rainstorm characteristics, as well as dependence of various rainstorm patterns on rainfall depth, duration, and season. The proposed model was verified by comparing the derived rainfall depth-duration-frequency relations from the simulated rainfall sequences with those from observed annual maximum rainfalls based on the hourly rainfall data at the Hong Kong Observatory over the period of 1884-1990. Through numerical experiments, the proposed model was found to be capable of capturing the essential statistical features of rainstorm characteristics and those of annual extreme rainstorm events according to the available data.