Flash Flood Prediction Model based on Multiple Regression Analysis for Decision Support System.

Philippines experience frequent flash flooding, usually with insufficient lead time which causes panic and fear to the people. In spite of decades of effort by the government and the private sectors to improve observations and warning, flash floods continue to be one of nature's worst killers. On the average, there is at least one disastrous flood every four (4) years in the Philippines [1]. This paper proposed to develop a technology on Flash Flood Warning System Using SMS with advanced warning information based on prediction algorithm devised by the researcher regarding increasing water level and water speed. These two factors were considered as triggers to the flashflood, thus become components of the regression algorithm devised by the researchers. Based on the training data captured for seven days, the regression equation was developed while the actual/real time data were input to the regression model. Prediction of the current and forthcoming risk on flood is computed by the system based on the model and is sent through SMS to registered users for early warning purposes. [ABSTRACT FROM AUTHOR]