ABSTRACT
Stochastic models of change are models in which there is some specified amount of uncertainty about the results taken on by particular variables which represent the output of the model. The model-builder might incorporate a degree of randomness in the nature, timing and magnitude of discharge events in the tributary systems in relation to supposed precipitation-event frequencies. In stochastic modelling there are constraints on the degree of uncertainty, but emphasis is on the ‘aggregate’ success of the model which does not stand or fall by its component parts. The simulation models involve processes whereby the systems involved develop in time and space in accordance with probabilistic laws. Such processes are called stochastic processes. The processes were formalized in terms of computer operations which basically selected random numbers by electronic means. The models in which time and state change at sharply defined regular intervals are easier to understand and mathematically less complicated.
