Civil Engineering and Architecture 10(4): 1303-1316, 2022 http://www.hrpub.org DOI: 10.13189/cea.2022.100406 Advanced Techniques of Flood Forecasting, Flood Inundation Mapping and Flood Prioritization of Panam River Basin Monal Patel 1,2,* , Falguni Parekh 2 1 Department of Civil Engineering, PIET, Parul University, Vadodara, India 2 WREMI, Faculty of Technology and Engineering, The Maharaja Sayajirao University of Baroda, Vadodara, India Received January 30, 2022; Revised March 29, 2022; Accepted April 15, 2022 Cite This Paper in the following Citation Styles (a): [1] Monal Patel, Falguni Parekh, "Advanced Techniques of Flood Forecasting, Flood Inundation Mapping and Flood Prioritization of Panam River Basin," Civil Engineering and Architecture, Vol. 10, No. 4, pp. 1303-1316, 2022. DOI: 10.13189/cea.2022.100406. (b): Monal Patel, Falguni Parekh (2022). Advanced Techniques of Flood Forecasting, Flood Inundation Mapping and Flood Prioritization of Panam River Basin. Civil Engineering and Architecture, 10(4), 1303-1316. DOI: 10.13189/cea.2022.100406. Copyright©2022 by authors, all rights reserved. Authors agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License Abstract Floods have been quite possibly the most troubling natural disasters in history, causing significant casualties, loss of life, and collateral destruction. Also, we see a shift in the frequency of rainfall every year due to climate change, which exacerbates flooding. Flood forecasting is essential to provide early warning to the people of flood-prone areas, provide enough time for preparedness, and reduce the damage to lives and properties. The flood inundation simulation is critical in presenting potential impending flooding in the study region. Furthermore, flood prioritization plays a key role in better watershed management. Looking at the present scenario, the machine learning methods like neural networks and fuzzy logic contribute profoundly to the headway of flood forecast frameworks giving better execution and financially savvy arrangements. The flood forecasting models can be developed using ANN, ANFIS and fuzzy logic. The comparative study between the developed models can also be carried out by determining different evaluation parameters. For flood forecasting using ANFIS, it is found that the coefficient of correlation values ranges from 0.85 to 0.95. In order to regulate the extent of the flooded area and the depth of the flooded water, HEC-RAS efficiently develops a flood inundation map. Flood inundation maps can be used to know the regions which are more or less vulnerable to flooding hazards. Keywords Flood, ANN, ANFIS, HEC-RAS, Fuzzy Logic, Panam River Basin, Flood Forecasting, Flood Inundation Mapping and Flood Prioritization 1. Introduction As per the report of UNISDR, 56% of the world population has been affected by floods for the last two decades. India represents one-fifth of worldwide passing because of floods. There is frequent flooding on the Panam river and nearby Panam River. Many villages are situated, frequently damaged due to flooding on the dam's downstream side. Overcrowding is one of the major causes, as people's cities are moving closer to water sources, causing infrastructure and human life to be harmed. Furthermore, we see a shift in the frequency of rainfall every year due to climate change, which exacerbates flooding. When citizens have begun to live around water sources, adequate precautions and conservation measures have been applied to mitigate the morality and other negative consequences. Real-time flood monitoring, which is a challenging method, may be one of the steps. It combines efforts to define topic danger zones, model flooding region relationships, specific flood probabilities, thresholds, and set troubling conditions. Scientists are perplexed because perfect flood forecasts are very tough to