Applications of Artificial Neural Networks and Fuzzy Logic in Operational Hydrological Forecasting: A Review

Pages:4-6
Neeru Gupta and Deepak Choudhary (Department of Computer Science, Manav Bharti University, Solan, H.P.)

Damage due to flooding has increase in many countries in the last years, and due to the global climate change, which is now recognized as a real threat, an increase in the occurrence of flooding events and especially of flash flooding events is likely to continue into the future. In those conditions and because building new flood defences structures for defending vulnerable areas has serious financial implications, the timely forecasting of floods is becoming more important for flood defence and in general for water management purposes. The complexity of natural systems and of hydrological processes that influence river levels evolutions make the traditional modelling approaches, based on mirroring natural processes with physically based equations very difficult. The paper reviews the applications of neural networks and fuzzy logic in operational hydrological forecasting.