ABSTRACT
6.1 Introduction
During the past few decades, physically based or process models based on mathematical descriptions of water motion such as those described in the last few chapters have been widely used in coastal management. Conventionally, the emphasis on computer-aided decision-making tools has been placed primarily on their algorithmic processes, and in particular on the formulation of new models, improved solution techniques, and effectiveness (Leendertse 1967). In a water quality model, which addresses a typical coastal problem, phytoplankton dynamics are based on theories of the dependence of growth and decay factors on physical and biotic environmental variables (e.g. solar radiation, nutrients, flushing) - expressed mathematically and incorporated in advective diffusion equations. Classical process-based modelling approaches can give a good simulation of the water quality variables including algal biomass level, but usually require a lengthy data calibration process. They require a lot of input data and rely upon many uncertain kinetic coefficients. They sometimes make simplified approximations of various interrelated physical, chemical, biochemical, and biological processes (Sacau-Cuadrado et al. 2003; Patel et al. 2004; Arhonditsis and Brett 2005). Difficulties are often encountered in modelling coastal waters with limited data on the water quality and the cost of water quality monitoring. While a large amount of research has already taken place in numerical modelling, a complementary approach to corroborate the numerical results should be welcome owing to computational limitations and uncertainties in modelling the complex physical process of coastal dynamics.
