Hydraulic and water quality model for a river network - Tucci, Carlos Eduardo Morelli (1978)
A river network system consisting of branches and loops is sometimes complicated by downstream effects from tides, lakes, and because of this, management of water quality, sediment control, and floods, in such rivers is a difficult task. Development of tools to aid in the management decision-making process is an important area of research; ultimately resulting in more reliable results. River behavior can be modeled in detail (one-, two-, or three-dimensional models) with a digital computer using numerical methods. Usually the level of detail is determined by the size of the system. Large system models are restricted in size and detail due to the high cost and storage requirements of the computer. A model was developed to simulate the hydraulic behavior and water quality of a river network on a one-dimensional representation. The two complete St. Venant equations and the transport equation were solved by the finite difference method. The transport equation utilizes the advection, dispersion, and source and sink terms. The system of equations resulting from use of an implicit scheme was solved by a modified Gauss elimination procedure. The model can simulate biochemical oxygen demand, dissolved oxygen, or any other conservative substance. The basic equations are solved; thus, the simulation of other substances can be added to the model by including the mathematical description of the reaction processes in the source and sink terms of the transport equation. The hydraulic module of the model was adjusted and verified with data from the Jacui Delta, Brazil. Good agreement between the calculated results and the observed data resulted. The water quality model was tested under hypothetical conditions for the same Delta in order to demonstrate the utility of the mathematical model in making decisions at the management level. This model is a mathematical method that can be used in large systems of variable complexity to help in understanding their processes, controlling data measurements, and reaching sound management decisions.