Field and numerical modeling study of turbidity current in shimen reservoir during typhoon events
Journal
Journal of Hydraulic Engineering
Journal Volume
145
Journal Issue
5
Date Issued
2019
Author(s)
Abstract
A two-dimensional (2D) layer-averaged model was previously developed to simulate turbidity current characteristics and its sluicing in reservoirs. It was calibrated and validated using the data from a down-scale physical model of the Shimen Reservoir with great success. This study aims to calibrate and validate the numerical model to predict turbidity currents in the Shimen Reservoir in the field-scale scenarios with the goal of using the model for real-time forecasts for reservoir operation. Field studies are also carried out to assist the model calibration and validation. Three field events surveyed include typhoons Soudelor and Dujuan in 2015 and Megi in 2016. The study serves three key points. First, it verifies that the previously developed 2D turbidity current model is also valid and practical for field applications, which has not been done before based on the authors’ knowledge. The model is capable of predicting turbidity current movement toward a reservoir dam face, as well as the sluicing out of outlets at different levels. The model results are compared with the available field data. Second, this study establishes guidelines on how to perform a practical turbidity current modeling in the field based on the model sensitivity study. It is found that the drag coefficient and mesh size are the primary parameters, and the proper ranges of these parameters are recommended. Third, the model is used to understand the turbidity current characteristics in the reservoir; they include the arrival time of the turbidity current, the concentration distribution in the reservoir, and sediment sluicing through the sluice gates. The results show that the developed 2D turbidity current model is mature enough that it can be combined with the real-time observation data to conduct the current rolling prediction and sluicing volume estimate. The modeling results provide the data necessary for the prediction of sediment turbidity current characteristics, as well as for the reservoir management.
SDGs
Type
journal article