Abstract
The Indian subcontinent is annually affected by floods that cause profound irreversible damage to crops and livelihoods. With increased incidences of floods and their related catastrophes, the design, development, and deployment of an Early Warning System for Flood Prediction (EWS-FP) for the river basins of India is needed, along with timely dissemination of flood-related information for mitigation of disaster impacts. Accurately drafted and disseminated early warnings/advisories may significantly reduce economic losses incurred due to floods. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. HPC, remote sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. The model is open-source, supports geographic file formats, and is capable of simulating rainfall run-off, river routing, and tidal forcing, simultaneously. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta, 9225 sq km) with actual and predicted discharge, rainfall, and tide data. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time.
Highlights
The Indian subcontinent is regularly affected by floods that have a significant impact on life and property
The current study addresses the following issues: forecasting floods, using opensource models, and modelling flood prediction for large river basins
This paper reports the use of open-source tools/packages for data preparation, design, and set up of flood-simulation models and High-Performance Computing (HPC)-based analysis of the simulation results
Summary
The Indian subcontinent is regularly affected by floods that have a significant impact on life and property. Despite their regular occurrence, floods are difficult to predict, especially in India, for a multitude of reasons. The vast and interconnected network of rivers in the Indian subcontinent renders the data, which is minimal in most cases, and coarse, that flood prediction at finer resolution tends to be extremely difficult. As such, do not suit most flood modelling software because of their immense computational requirements. The current study addresses the following issues: forecasting floods, using opensource models, and modelling flood prediction for large river basins. The solutions have limitations of cost-effectiveness and a lack of user-interactive software interface [1]
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