This paper presents numerical simulations of dam-break flow over a movable bed. Two different mathematical models were compared: a fully coupled formulation of shallow water equations with erosion and deposition terms...This paper presents numerical simulations of dam-break flow over a movable bed. Two different mathematical models were compared: a fully coupled formulation of shallow water equations with erosion and deposition terms(a depth-averaged concentration flux model), and shallow water equations with a fully coupled Exner equation(a bed load flux model). Both models were discretized using the cell-centered finite volume method, and a second-order Godunov-type scheme was used to solve the equations. The numerical flux was calculated using a Harten, Lax, and van Leer approximate Riemann solver with the contact wave restored(HLLC). A novel slope source term treatment that considers the density change was introduced to the depth-averaged concentration flux model to obtain higher-order accuracy. A source term that accounts for the sediment flux was added to the bed load flux model to reflect the influence of sediment movement on the momentum of the water. In a onedimensional test case, a sensitivity study on different model parameters was carried out. For the depth-averaged concentration flux model,Manning's coefficient and sediment porosity values showed an almost linear relationship with the bottom change, and for the bed load flux model, the sediment porosity was identified as the most sensitive parameter. The capabilities and limitations of both model concepts are demonstrated in a benchmark experimental test case dealing with dam-break flow over variable bed topography.展开更多
Quantitative application on remote sensing of suspended sediment is an important aspect of the engineering application of remote sensing study. In this paper, the Xiamen Bay is chosen as the study area. Eleven differe...Quantitative application on remote sensing of suspended sediment is an important aspect of the engineering application of remote sensing study. In this paper, the Xiamen Bay is chosen as the study area. Eleven different phases of the remote sensing data are selected to establish a quantitative remote sensing model to map suspended sediment by using remote sensing images and the quasi-synchronous measured sediment data. Based on empirical statistics developed are the conversion models between instantaneous suspended sediment concentration and tidally-averaged suspended sediment concentration as well as the conversion models between surface layer suspended sediment concentration and＂ the depth-averaged suspended sediment concentration. On this basis, the quantitative application integrated model on remote sensing of suspended sediment is developed. By using this model as well as multi-temporal remote sensing images, multi-year averaged suspended sediment concentration of the Xiamen Bay are predicted. The comparison between model prediction and observed data shows that the multi-year averaged suspended sediment concentration of studied sites as well as the concentration difference of neighboring sites can be well predicted by the remote sensing model with an error rate of 21.61% or less, which can satisfy the engineering requirements of channel deposition calculation.展开更多
文摘This paper presents numerical simulations of dam-break flow over a movable bed. Two different mathematical models were compared: a fully coupled formulation of shallow water equations with erosion and deposition terms(a depth-averaged concentration flux model), and shallow water equations with a fully coupled Exner equation(a bed load flux model). Both models were discretized using the cell-centered finite volume method, and a second-order Godunov-type scheme was used to solve the equations. The numerical flux was calculated using a Harten, Lax, and van Leer approximate Riemann solver with the contact wave restored(HLLC). A novel slope source term treatment that considers the density change was introduced to the depth-averaged concentration flux model to obtain higher-order accuracy. A source term that accounts for the sediment flux was added to the bed load flux model to reflect the influence of sediment movement on the momentum of the water. In a onedimensional test case, a sensitivity study on different model parameters was carried out. For the depth-averaged concentration flux model,Manning's coefficient and sediment porosity values showed an almost linear relationship with the bottom change, and for the bed load flux model, the sediment porosity was identified as the most sensitive parameter. The capabilities and limitations of both model concepts are demonstrated in a benchmark experimental test case dealing with dam-break flow over variable bed topography.
基金supported by the Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (Grant No. 2009491711)
文摘Quantitative application on remote sensing of suspended sediment is an important aspect of the engineering application of remote sensing study. In this paper, the Xiamen Bay is chosen as the study area. Eleven different phases of the remote sensing data are selected to establish a quantitative remote sensing model to map suspended sediment by using remote sensing images and the quasi-synchronous measured sediment data. Based on empirical statistics developed are the conversion models between instantaneous suspended sediment concentration and tidally-averaged suspended sediment concentration as well as the conversion models between surface layer suspended sediment concentration and＂ the depth-averaged suspended sediment concentration. On this basis, the quantitative application integrated model on remote sensing of suspended sediment is developed. By using this model as well as multi-temporal remote sensing images, multi-year averaged suspended sediment concentration of the Xiamen Bay are predicted. The comparison between model prediction and observed data shows that the multi-year averaged suspended sediment concentration of studied sites as well as the concentration difference of neighboring sites can be well predicted by the remote sensing model with an error rate of 21.61% or less, which can satisfy the engineering requirements of channel deposition calculation.
