Abstract
Climate change, urbanization, and many anthropogenic activities have intensified the floods in today’s world. However, poor attention was given to mitigation strategies for floods in the developing world due to funding and technical limitations. Developing flood inundation maps from historical flood records would be an important task in mitigating any future flood damages. Therefore, this study presents the predictive capability of the Rainfall-Runoff-Inundation (RRI) model, a 2D coupled hydrology-inundation model, and to build flood inundation maps utilizing available ground observation and satellite remote sensing data for Kalu River, Sri Lanka. Despite the lack of studies in predicting flood levels, Kalu River is an annually flooded river basin in Sri Lanka. The comparative results between ground-based rainfall (GBR) measurement and satellite rainfall products (SRPs) from the IMERG satellite have shown that SRPs underestimate peak discharges compared to GBR data. The accuracy and the reliability of the model were assessed using ground-measured discharges with a high coefficient of determination (R2 = 0.89) and Nash–Sutcliffe model efficiency coefficient (NSE = 0.86). Therefore, the developed RRI model can successfully be used to simulate the inundation of flood events in the KRB. The findings can directly be applied to the stakeholders.
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Data Availability
The datasets are available from the corresponding author on reasonable request.
Code Availability
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Herath, R.D., Pawar, U., Aththanayake, D.M. et al. Rainfall-runoff-inundation (RRI) model for Kalu River, Sri Lanka. Model. Earth Syst. Environ. 10, 1825–1839 (2024). https://doi.org/10.1007/s40808-023-01877-1
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DOI: https://doi.org/10.1007/s40808-023-01877-1