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Featured researches published by K.C. Yeh.


Stochastic Environmental Research and Risk Assessment | 1997

Regionalization of unit hydrograph parameters .1. Comparison of regression analysis techniques

Yeou-Koung Tung; K.C. Yeh; Jinn-Chuang Yang

Hydrologic regionalization is a useful tool that allows for the transfer of hydrological information from gaged sites to ungaged sites. This study developed regional regression equations that relate the two parameters in Nashs IUH model to the basin characteristics for 42 major watersheds in Taiwan. In the process of developing the regional equations, different regression procedures including the conventional univariate regression, multivariate regression, and seemingly unrelated regression were used. Multivariate regression and seeming unrelated regression were applied because there exists a rather strong correlation between the Nashs IUH parameters. Furthermore, a validation study was conducted to examine the predictability of regional equations derived by different regression procedures. The study indicates that hydrologic regionalization involving several dependent variables should consider their correlations in the process of establishing the regional equations. The consideration of such correlation will enhance the predictability of resulting regional equations as compared with the ones from the conventional univariate regression procedure.


Stochastic Environmental Research and Risk Assessment | 1997

Regionalization of unit hydrograph Parameters: 2. Uncertainty analysis

K.C. Yeh; Jinn-Chuang Yang; Yeou-Koung Tung

Hydrologic model parameters obtained from regional regression equations are subject to uncertainty. Consequently, hydrologic model outputs based on the stochastic parameters are random. This paper presents a systematic analysis of uncertainty associated with the two parameters, N and K, in Nashs IUH model from different regional regression equations. The uncertainty features associated with N and K are further incorporated to assess the uncertainty of the resulting IUH. Numerical results indicate that uncertainty of N and K from the regional regression equations are too significant to be ignored.


Stochastic Environmental Research and Risk Assessment | 1997

Reliability analysis of hydraulic structures considering unit hydrograph uncertainty

Bing Zhao; Yeou-Koung Tung; K.C. Yeh; Jinn-Chuang Yang

Unit hydrographs (UHs), along with design rainfalls, are frequently used to determine the discharge hydrograph for design and evaluation of hydraulic structures. Due to the presence of various uncertainties in its derivation, the resulting UH is inevitably subject to uncertainty. Consequently, the performance of hydraulic structures under the design storm condition is uncertain. This paper integrates the linearly constrained Monte-Carlo simulation with the UH theory and routing techniques to evaluate the reliability of hydraulic structures. The linear constraint is considered because the water volume of each generated design direct runoff hydrograph should be equal to that of the design effective rainfall hyetograph or the water volume of each generated UH must be equal to one inch (or cm) over the watershed. For illustration, the proposed methodology is applied to evaluate the overtopping risk of a hypothetical flood detention reservoir downstream of Tong-Tou watershed in Taiwan.


International Journal for Numerical Methods in Fluids | 2000

Depth-averaged two-dimensional curvilinear explicit finite analytic model for open-channel flows

Chih-Tsung Hsu; K.C. Yeh; Jinn-Chuang Yang

SUMMARY A depth-averaged two-dimensional model has been developed in the curvilinear co-ordinate system for free-surface flow problems. The non-linear convective terms of the momentum equations are discretized based on the explicit‐finite‐analytic method with second-order accuracy in space and first-order accuracy in time. The other terms of the momentum equations, as well as the mass conservation equation, are discretized by the finite difference method. The discretized governing equations are solved in turn, and iteration in each time step is adopted to guarantee the numerical convergence. The new model has been applied to various flow situations, even for the cases with the presence of sub-critical and supercritical flows simultaneously or sequentially. Comparisons between the numerical results and the experimental data show that the proposed model is robust with satisfactory accuracy. Copyright


Stochastic Environmental Research and Risk Assessment | 1993

Evaluation of safety of hydraulic structures affected by migrating pits

Y-K. Tung; K.C. Yeh

Because it can be carried by flowing water, a sand/gravel pit on the river bed could migrate downstream. Consequently, the presence of pits on river beds could pose a safety threat to in-stream hydraulic structures such as bridge piers. A pit migration model can be used to predict progressive changes of pit geometry as it migrates downstream. However, due to the existence of many uncertainties, the maximum pit depth cannot be predicted with certainty. This paper adopted a simple pit migration model and evaluated the uncertainty associated with the calculated maximum pit depth. Such information is essential for evaluating the probability that a migrating pit could pose a safety threat to a downstream hydraulic structure. Three reliability analysis techniques were applied and their performances were compared.


Journal of Hydraulic Engineering | 1999

BEND FLOW SIMULATION USING 2D DEPTH-AVERAGED MODEL

Ho-Cheng Lien; Te-Yung Hsieh; Jinn-Chuang Yang; K.C. Yeh


International Journal for Numerical Methods in Fluids | 2002

Iterative explicit simulation of 1D surges and dam‐break flows

Chih-Tsung Hsu; K.C. Yeh


J. of Hydraulic Engr. | 1993

Uncertainty and sensitivity of a pit migration model

K.C. Yeh; Yeou-Koung Tung


Hydraulic Engineering | 1993

Analyzing uncertainty of IUH of Nash

Jinn-Chuang Yang; S.Y. Tarng; Yeou-Koung Tung; K.C. Yeh


Hydraulic Engineering | 1993

Nonuniform Transient Sediment Transport Modeling

K.C. Yeh; Chian-Min Wu; Jinn-Chuang Yang; Shian-Jang Li

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Jinn-Chuang Yang

National Chiao Tung University

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Yeou-Koung Tung

Hong Kong University of Science and Technology

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Chih-Tsung Hsu

National Chiao Tung University

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Ho-Cheng Lien

National Chiao Tung University

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Te-Yung Hsieh

Industrial Technology Research Institute

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Bing Zhao

Arizona State University

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Y-K. Tung

University of Wyoming

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