No abstract

Abstract. The Thailand floods in 2011 caused unprecedented economic damage in the Chao Phraya River basin. To diagnose the flood hazard characteristics, this study analyses the hydrologic sensitivity of flood runoff and inundation to rainfall. The motivation is to address why the seemingly insignificant monsoon rainfall, or 1.2 times more rainfall than for past large floods, including the ones in 1995 and 2006, resulted in such devastating flooding. To quantify the hydrologic sensitivity, this study simulated longterm rainfall-runoff and inundation for the entire river basin (160 000 km 2 ). The simulation suggested that the flood inundation volume was 1.6 times more in 2011 than for the past flood events. Furthermore, the elasticity index suggested that a 1 % increase in rainfall causes a 2.3 % increase in runoff and a 4.2 % increase in flood inundation. This study highlights the importance of sensitivity quantification for a better understanding of flood hazard characteristics; the presented basin-wide rainfall-runoff-inundation simulation was an effective approach to analyse the sensitivity of flood runoff and inundation at the river basin scale.

PurposeThis paper aims to describe the major causes of massive destruction due to floods in developing countries and to elaborate the usefulness of flood hazard maps under the framework of community‐based flood management.Design/methodology/approachThis paper elaborates the usefulness of flood hazard maps and their application.FindingsIt is a clear perception that flood risk management cannot be treated in isolation – rather it should be a part of community development. In this context, it is essential to build a community's capacity to understand their vulnerabilities, strategies, activities and the role they could play in managing flood risks without relying on external entities. Therefore the proposed community‐based flood hazard‐mapping technique can be a good solution for addressing current issues. The approach will not only focus on the effective development and application of FHM but also it will correct the defects of the top‐down approach in disaster planning and also encourage all stakeholders' participation in an integrated and sustainable manner.Practical implicationsBased on the findings, it is strongly recommended that agencies should adhere and incorporate the idea while developing programs and projects for communities. In addition, It is simple to understand and easy to implement by the community.Originality/valueIt is hoped that the idea will be beneficial and a catalyst to promote a community's response for flood disaster management in developing countries, thereby helping agencies to develop an operational strategy in advance.

A devastating flood disaster occurred in Thailand in 2011. In case of such large‐scale flooding, it is important to predict the dynamics of inundation on a near real‐time basis for safe evacuation. To predict widespread inundation, where both rainfall‐runoff from surrounding mountains and rainfall on floodplains contribute to the event, this paper applied a rainfall‐runoff‐inundation (RRI) model to the entire Chao Phraya River basin (160 000 km2). Near real‐time simulation was conducted for emergency responses with globally available dataset including satellite‐based topography (HydroSHEDS derived from SRTM) and rainfall (TRMM 3B42RT) during the disaster. Post‐flood simulation was also carried out with more local information. The RRI model was found capable of representing the peak inundation extent with an acceptable accuracy and correctly predicting a 1‐month lasting inundation in the lower part of the basin. On the other hand, the prediction overestimated the river discharge by 40% and the inundation water level by 2 m mainly due to the neglect of the evapotranspiration effect. The post‐flood simulation improved its accuracy by up to 10% for river discharges and 1 m for peak inundation water levels, but it did not lead to better agreement of flood extents with those based on the remote sensing. Further study is recommended to improve accuracy for modelling of spatial extent of flooding. Furthermore, sensitivity analysis with different input suggested what information should be prioritised for emergency response‐type flood simulations.