Use of Big Data for Flood Assessment Through HEC-RAS Model: A Study of Purna River of Navsari

Big data has recently become popular all around the world. Data generation in each discipline has substantially improved due to the usage of computer systems. Flooding appears to be the most frequently calamity in a tropical country like India. Flooding in urban coastal areas is caused by heavy rainfall, industrialisation, high population density and urbanisation. The Navsari City, Gujarat, India, located near the Arabian Sea coast affected by a disastrous flood in 2004. In this study, the use of big data is implemented to assess the flood using HEC-RAS 2D hydrodynamic modelling. The big data of past floods would be a foundation for the enlargement of the HEC-RAS 2D flood assessment model. Calibration and validation have been performed to ensure the consistency and adequacy of the model. The outcomes of the model depicted that the R2 of the model was 0.9679 indicating that the observed values are in good agreement with the simulated value. Comparable to most developed and advanced cities in countries such as the Europe, USA, Japan and China who are exploiting the advantages of big data for assessment of flood, monitoring and mitigation, where as in India, the use of big data for assessing flood is very limited. In the said context, this research work is focussed on the use of big data for flood assessment in Navsari. In this study, we have discussed the needs and applicability of flood assessment through HEC-RAS 2D model across the world’s urban coastal areas including Navsari City, accompanied by the important benefits of big data approach.