Impact-based flood forecasting in India: evaluation of FHIM-India for fluvial flood impacts in Kerala

Recent advances in ensemble meteorological forecasting, hydrological modelling, and flood inundation mapping have substantially improved flood hazard prediction. However, major gaps persist in translating hazard information into understandable, trusted, and actionable warnings based on the impacts of flood events, limiting the effectiveness of early warning–early action systems. A key challenge lies in linking hydrological hazard forecasts with exposure and vulnerability information to support impact-based decision-making. 

Constructing and evaluating flood disaster risk forecasts remains a complex and uncertain process, particularly due to the multi-dimensional and spatially heterogeneous nature of vulnerability and exposure data. Impact-based Forecasting (IbF) of flooding seeks to address these challenges by explicitly connecting flood hazard forecasts to potential societal impacts in space and time. 

FHIM-India – Flood Hazard Impact Model for India – is an impact-based flood forecasting framework that integrates ensemble numerical weather predictions, distributed hydrological modelling (Grid-to-Grid), and hydrodynamic flood simulations (SynxFlow) with exposure and vulnerability datasets. Here, FHIM-India is evaluated for fluvial flood impacts in the state of Kerala, south-western India using over 30 years of recorded impacts. 

The FHIM-India framework is repurposed to generate daily flood impact hindcasts for multiple districts in Kerala over the period 1991–2022 using observed rainfall data as input. Modelled impact indicators related to affected population and property are evaluated against reported historical impact data. The performance of the impact-based hindcasts is assessed relative to warnings derived using fixed rainfall threshold-based approaches. 

Results indicate that FHIM-India improves the identification and spatial discrimination of mid- to high-severity flood events compared with warnings based on fixed rainfall thresholds. The framework demonstrates strong potential for use in operational impact-based flood forecasting to support early warning systems and risk-informed decision-making.