Natural Hazards

, Volume 91, Issue 2, pp 491–513 | Cite as

Application of a flood inundation model to analyze the potential impacts of a flood control plan in Mundeni Aru river basin, Sri Lanka

Original Paper
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Abstract

Capturing inundation extent by floods is indispensable for decision making for mitigating hazard. Satellite images have commonly been used for flood mapping, but there are limitations such as unavailability due to satellite’s orbital period or cloud cover. Additionally, it would also be beneficial for policy makers to figure out the impact of water management measures such as water storage options on flood mitigation and irrigation water strengthening. Utilization of flood inundation models would support providing information for these demands. In this study, the rainfall–runoff inundation (RRI) model was applied in a flood-prone basin in eastern Sri Lanka, and its applicability was discussed. The RRI model was capable of simulating discharge and inundation extent during flood events, although it should be noted that the model had been calibrated targeting only the flooding period. Satellite-observed rainfall data corrected with a scale factor were able to be used as the model input to simulate long-term trends in runoff just as well as when gauged rainfall data were applied. The calibrated model was also capable of evaluating flood mitigation effects of existing and proposed water storage options by simulating discharge with and without flood capture operations. By reproducing long-term inflow to the storage facilities using satellite rainfall data, it was possible to determine that water would reach the maximum level of the proposed storage facilities even during low-rainfall years.

Keywords

Satellite data Rainfall–runoff inundation model Storage options Flood mitigation Sri Lanka 

Notes

Acknowledgements

This research was funded by the Japan’s Ministry of Agriculture, Forestry and Fisheries (MAFF), the CGIAR Research Program on Water, Land and Ecosystems (WLE), and the International Water Management Institute (IWMI). We would like to thank Mr. Niranga Alahacoon of IWMI for his kind support on data processing, Dr. Takahiro Sayama of Kyoto University for his kind advice, and also the Department of Irrigation, Sri Lanka, Survey Department of Sri Lanka, and Department of Meteorology, Sri Lanka, for sharing their data.

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.International Water Management Institute (IWMI)Pelawatte, BattaramullaSri Lanka

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