Comparison of the hydrological time series modeling by the floods in river Indus of Pakistan

Today, in the field of science and technology, huge forecasting applications are used by scholars to forecast future values. Nowadays, using estimating flood for peak flow discharges is very common risk assessment annually quantitative data collections from different resources. The famous longest rivers Pakistan i.e. Indus River other too like Jhelum, Kabul, Chenab prime sources flooding. These tributaries System. Pakistan's river, Indus, connected with seven (7) gauge stations called Dams barrages, they playing a vital role generation electricity also irrigation Pakistan. In this research paper, we calculated streamflow on daily basis. At present, Adaptive Neuro-Fuzzy Inference System (ANFIS) model widely analyze these hydrological time series data. Systems merges potentiality Fuzzy (FIS) Artificial Neural Networks (ANN) work out problems kinds. For purpose, years 2002 2012 (6-months each year) period. our analysis, root means square error (RMSE) shows that ANFIS generated more satisfactory results than models minimum prediction errors. reliable has feasibility integrating essence fuzzy system into real world.1–28