ABSTRACT
For the entire period of recorded time, floods have been a major cause of loss of life and property. Methods of prediction and mitigation range from human observers to sophisticated surveys and statistical analysis of climatic data. In the last few years, researchers have applied computer programs called Neural Networks or Artificial Neural Networks and fuzzy logic to a variety of uses ranging from medical to financial. The purpose of this study is to demonstrate that fuzzy logic based model can be successfully applied to flood forecasting. This study explores the potential of the fuzzy and neuro fuzzy model process for forecasting flood. In this study, a neurofuzzy approach is proposed to forecast flood from hydrologic data of rainfall, temperature, water level, sediment and discharge. The ten years’ hydrologic data recorded on daily basis that were collected from oyan and owena gauging station were trained and used for the models development and simulation.
