An accurate and timely decision is crucial in any emergency situation. This paper presents a recognition decision making model that adopts the temporal data mining
approach in making decisions. Reservoir water level and rainfall measurement were used as the case study to test the developed computational recognition-primed decision (RPD) model in predicting the amount of water to be dispatched represented by the number of spillway gates. Experimental results indicated that new events can be predicted from historical events. Patterns were extracted and can be transformed into readable and descriptive rule based form
