A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Engineering and Technology

Thesis (M.Eng.) - Asian Institute of Technology, 1992

This study presents two models including theories and numerical procedures to determine the dispersion coefficient, a very important parameter, for the prediction of salinity intrusion in estuarine networks. The First Model (Trial Method) is established based on a trial process to find out the most appropriate form of the dispersion coefficient as a function of specified system parameters. In this model, the problems of formulating an expression for the dispersion coefficient and determining salinity concentration at the river sections are solved simultaneously for the whole river system. The results obtained from this model show that the dispersion coefficient distribution D(x,t) along the main branches of the Mekong river system depends upon the salinity and its gradient and can be represented well by the expression D k s as 3 ax Due to the larger variation in time of the salinity gradient magnitudes when comparing with the salinity concentration magnitudes, the salinity gradient is proved to play the most important role on the mixing process between sea and river water and has a primary effect on the behavior of the dispersion coefficient, while the salinity concentration has a secondary effect on the variation of this coefficient. From the computational results, it can be also seen that there is no large variation in the magnitudes of the relation coefficient k3 although its value depends on a lot of factors. The Second Model (Backward Method) is established to determine discrete values of the dispersion coefficient in terms of nodal dispersion coefficient, using observed data of salinity concentration at internal stations on the river system. The results obtained from this model show that the magnitude order of the dispersion coefficient for Mekong estuarine network varies widely in space and in time; its maximum can reach a value up to 3,500 m2 /s, while the magnitudes fluctuate mainly in the range of 0-1,500 m2 /sec. In general, the magnitudes of the dispersion coefficient vary in the same manner as those of the salinity concentration, i.e. the dispersion coefficient at the stations in the area in dry season increases from January to April and decreases after April.