ON THE GENERATION OF DROUGHT EVENTS USING AN ALTERNATING RENEWAL-REWARD MODEL

This research study focused on the hypothesis that extreme drought and high streamflow events come from different independent populations wi th different probability distributions which need to be studied separa tely, rather than considering the streamflow population as a whole. Th e inability of traditional streamflow generator models to consistently reproduce the frequency of occurrence of severe droughts observed in the historical record has been questioned by many researchers. Our stu dy focused on the development of a stochastic event generator model wh ich would be capable of doing so. This was accomplished in a two-step process by first generating the drought event, and then deriving the s treamflows which comprised that event. The model considered for this a nalysis was an alternating renewal-reward procedure that cycles betwee n event on and off times, and is representative of drought or high str eamflow event duration. The reward gained while the event is on or off represents drought severity or high streamflow surplus. Geometric and gamma distributions were considered for drought duration and deficit respectively. Model validation was performed using calculated required capacities from the sequent peak algorithm.