Mesh grid stability and its impact on flood inundation through (2D) hydrodynamic HEC-RAS model with special use of Big Data platform—a study on Purna River of Navsari city - Pathan, Azazkhan Ibrahimkhan; Agnihotri, Prasit Girish; Patel, Dhruvesh; Prieto, Cristina (Arabian journal of geosciences, 2022)
A thorough examination of flood hydrodynamics is an important step in determining a flood-prone area. The performance of a hydrodynamic model can be evaluated by some important parameters such as flood depth, flow velocity, water surface elevation, and arrival time. However, the mesh grid size is an important factor in achieving the model’s accuracy. Therefore, the major focus of this study is to analyze the impact of the various sizes of mesh grid structures (300, 200, 100, 90, 50, and 30 m) on the inundation depth and its extent using the two-dimensional (2D) hydrodynamic Hydrologic Engineering Centre-River Analysis System (HEC-RAS) model on the river Purna, Navsari. Moreover, the current study also focuses on analyzing the influence of floods under a wide range of data generated during the simulation of the model. Consequently, this Big Data platform has been an assured approach for flood assessment, thereby becoming the backbone for developing a robust HEC-RAS 2D model for its evaluation using the Big Data of the previous flood events. A flood event (4th August 2004) in Navsari city was simulated using varied mesh grids. The results of the model revealed that though no significant differences were recorded in context to the inundation depth and its extent yet there were substantial differences observed in its simulation time. To analyze the accuracy of prediction, different statistical parameters were obtained (i.e. mean, median, STD, R 2 , RMSE, NSE, inundation time, and inundation area). The result obtained from the model unveiled that 50-m-size mesh grid showed more precise results: yielding high R 2 and NSE values (0.9855 and 0.982), low RMSE value (0.450 m), and lesser inundation area (114.61 km 2 ). The outcome of the model depicts that the major flood-prone areas were inundated by 2–4 m depth of water, and it takes 11–13 h to deluge the entire city. The innovative approach adopted in the study to appraise the impact of different sizes of mesh grid structure on the accuracy of flood inundation through the Big Data approach can be useful for the local government to prepare for flood management and resiliency strategies in data-deficient regions.