Version 1
: Received: 11 March 2018 / Approved: 12 March 2018 / Online: 12 March 2018 (07:56:58 CET)
How to cite:
Liu, W.; Liu, H. Integrating Monte Carlo and the Hydrodynamic Model for Predicting Extreme Water Levels in River Systems. Preprints2018, 2018030088. https://doi.org/10.20944/preprints201803.0088.v1
Liu, W.; Liu, H. Integrating Monte Carlo and the Hydrodynamic Model for Predicting Extreme Water Levels in River Systems. Preprints 2018, 2018030088. https://doi.org/10.20944/preprints201803.0088.v1
Liu, W.; Liu, H. Integrating Monte Carlo and the Hydrodynamic Model for Predicting Extreme Water Levels in River Systems. Preprints2018, 2018030088. https://doi.org/10.20944/preprints201803.0088.v1
APA Style
Liu, W., & Liu, H. (2018). Integrating Monte Carlo and the Hydrodynamic Model for Predicting Extreme Water Levels in River Systems. Preprints. https://doi.org/10.20944/preprints201803.0088.v1
Chicago/Turabian Style
Liu, W. and Hong-Ming Liu. 2018 "Integrating Monte Carlo and the Hydrodynamic Model for Predicting Extreme Water Levels in River Systems" Preprints. https://doi.org/10.20944/preprints201803.0088.v1
Abstract
Estimates of extreme water level return periods in river systems are crucial for hydraulic engineering design and planning. Recorded historical water level data of Taiwan’s rivers are not long enough for traditional frequency analyses when predicting extreme water levels for different return periods. In this study, the integration of a one-dimensional flash flood routing hydrodynamic model with the Monte Carlo simulation was developed to predict extreme water levels in the Danshuei River system of northern Taiwan. The numerical model was calibrated and verified with observed water levels using four typhoon events. The results indicated a reasonable agreement between the model simulation and observation data. Seven parameters, including the astronomical tide and surge height at the mouth of the Danshuei River and the river discharge at five gauge stations, were adopted to calculate the joint probability and generate stochastic scenarios via the Monte Carlo simulation. The validated hydrodynamic model driven by the stochastic scenarios was then used to simulate extreme water levels for further frequency analysis. The design water level was estimated using different probability distributions in the frequency analysis at five stations. The design high-water levels for a 200-year return period at Guandu Bridge, Taipei Bridge, Hsin-Hai Bridge, Da-Zhi Bridge, and Chung-Cheng Bridge were 2.90 m, 5.13 m, 6.38 m, 6.05 m, and 9.94 m, respectively. The estimated design water levels plus the freeboard are proposed and recommended for further engineering design and planning.
Keywords
extreme water level; hydrodynamic model; Monte Carlo; joint probability; model calibration and verification; Danshuei River system
Subject
Engineering, Civil Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
