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

Many forecasting applications of science and technology are used to predict future values. Today, the flood peak flow discharges are extensively used on annual basis in risk assessment by collecting quantitative data from several sources. The famous rivers of Pakistan i.e. River Jhelum, River Kabul, River Chenab, and the very famous, considering upper area parts and the lower area parts of the river, the Indus River are the prime sources of flooding. These aforesaid rivers are the prime tributaries of the Indus River System which is the one, from all, most notable rivers of the world and for Pakistan, it is a supreme river. River Indus is Pakistan's longest river with seven (7) different gauge stations, Dams and various barrages, and plays a significant rolein irrigation and maximum generation of power in Pakistan. In the present research the flood risk in the Indus River has been calculated by utilizing the historical peak streamflow discharges recorded data on the daily basis. Nowadays, Adaptive Neuro-Fuzzy Inference System (ANFIS) model which is widely used to analyze these hydrological time series data sets obtained from different gauge stations. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) merges the potentiality of Fuzzy Inference Systems (FIS) and Artificial Neural Networks (ANN) to work out problems of different kinds. For this, the data covered eleven years from 2002 to 2012 daily (6-months each year) streamflow period. From our analysis, the root mean square error (RMSE) shows that the ANFIS model generated more satisfactory results than other models with minimum prediction errors. The ANFIS model is very pliable and has feasibilities of integrating the essence of a fuzzy system for real world.