Jianhua Tao

Numerical simulation of aquatic Eco-environment of Bohai bay

Abstract By using the numerical method, the hydro- dynamic characteristic and ecological system characteristic of Bohai bay have been investigated. The numerical models have been verified and calibrated by field monitoring data and laboratory experiments. Water exchange is presented by the relative matrix and indicated that the poor physical self-clean capacity of Bohai Bay. Wave induced long-shore current on the mild slope beach is studied by numerical method and experimental approach, and the pollutants transport law in the near shore area of Bohai bay has been found. Two ecologic system models are setup to simulate the eco-hydrodynamic process of the Bohai Bay.

Numerical simulation of shallow-water flooding using a two-dimensional finite volume model *

A 2-D Finite Volume Model (FVM) is developed for shallow water flows over a complex topography with wetting and drying processes. The numerical fluxes are computed using the Harten, Lax, and van Leer (HLL) approximate Riemann solver. Second-order accuracy is achieved by employing the MUSCL reconstruction method with a slope limiter in space and an explicit two-stage Runge-Kutta method for time integration. A simple and efficient method is introduced to deal with the wetting and drying processes without any correction of the numerical flux term or the source term. In this new method, a switch of alternative schemes is used to compute the water depths at the cell interface to obtain the numerical flux. The model is verified against benchmark tests with analytical solutions and laboratory experimental data. The numerical results show that the model can simulate different types of flood waves from the ideal flood wave to cases over complex terrains. The satisfactory performance indicates an extensive application prospect of the present model in view of its simplicity and effectiveness.

Eutrophication Prediction Model of Bohai Bay Based on Optimized Support Vector Machine

In this research, optimized SVM models were designed to describe eutrophication processes, based on the field measured data from Bohai Bay. A new data-driven model called Support Vector Machine (SVM) based on structural risk minimization principle was presented, which minimized a bound on a generalized risk. In the eutrophication model, the Principal Component Analysis (PCA) was used to identify the model inputs. After data scaling, cross-validation via parallel grid search and genetic algorithm were respectively employed to select the optimal parameters of SVM. The model performance was evaluated by means of the squared correlation coefficient R² and the Root Mean Square Error (RMSE). The results suggest that parameters optimization is very important and necessary for SVM, and SVM-GA (Genetic Algorithm integrated with SVM) possesses slightly better searching optimization ability. It was shown that this optimized SVM techniques could be applied to predict the concentration of Chlorophyll_a in Bohai Bay and capture the non-linear information in eutrophication processes.

An extended form of Boussinesq-type equations for nonlinear water waves

An extended form of Boussinesq-type equations with improved nonlinearity is presented for the water wave propagation and transformation in coastal areas. To improve the nonlinearity of lower order Boussinesq-type equations,without including higher order derivative terms, an extended form of Boussinesq-type equations is derived by a generalized method. The Stokes-type analysis of the extended equations shows that the accuracy of the second order and third order nonlinear characteristics is improved greatly. The numerical test is also carried out to investigate the practical performance of the new equations under different wave conditions. Better agreement with experimental data is found in the regions of strong nonlinear wave-wave interaction and harmonic generation.

A Statistical Method of Wind Field Based on the Form of Energy and Its Application in Bohai Bay Water Exchange

The conclusion has been generally accepted by the people that wind has an significant impact on the water exchange. But the amount of data is too large. So we must find a better method to resolve this situation. Some typical cases were set up, and using numerical methods the different influence of wind parameters on the water exchange were analyzed. The simulative results showed that the wind direction is the key factor whether the water exchange would be affected by the wind; the wind speed is related to the speed of water exchange; and the period has a little effect on the water exchange to some degree. By using the conclusion above, a effective method was obtained to deal with these large amounts of data. The wind data was homogenized at different time scales on the form of energy, and then the data was used to simulate the water exchange in the Bohai bay. The final results showed that the process of water exchange by using the month energy wind and the season energy wind separately is very close to the process by using the real wind.

The Simulation of the Chlorophyll-A by Using the CA-SVM Method and Its Application in Bohai Bay

Ecological environment is complex in Bohai Bay. Accompanied by the development of economy, pollution control problems have been put on agenda. Based on the remote sensing data, this article establishes a non-deterministic model to predict the concentration of Chlorophyll-a in Bohai Bay by using the combined model of cellular automata and support vector machine. Several programme are built, and their prediction results are compared with the remote sensing data. Through analysis and comparison, the most suitable prediction programme was obtained, and the main impact factors were got that affected the Chlorophyll-a concentration.

An Improvement on Wetting and Drying Method for Moving Boundary in Shallow Water Flow Models

In order to deal with the moving boundary hydrodynamic problems on the tidal flats in shallow water flow models, a new wetting and drying (WD) method based on the “predicted depth of water” has been proposed. In this new WD method, a formula is firstly deduced to determine the threshold, as critical water depth, which should be preset before simulations. Then the new WD method is tested with three typical cases. The results show that the new WD method with threshold determined by the formula in this paper can simulate the wetting and drying process with smooth manner and achieve effective estimation of the retention volume at shallow water body.