Modelling the flood-risk extent using LISFLOOD-FP in a complex watershed: case study of Mundeni Aru River Basin, Sri Lanka

Abstract

Abstract. Flood management is adopting a more risk-based approach, whereby flood risk is the product of the probability and consequences of flooding. Two-dimensional flood inundation modeling is a widely used tool to aid flood-risk management. The aim of this study is to develop a flood inundation model that uses historical flow data to produce flood-risk maps, which will help to identify flood protection measures in the rural areas of Sri Lanka. The LISFLOOD-FP model was developed at the basin scale using available historical data, and also through coupling with a hydrological modelling system, to map the inundation extent and depth. Results from the flood inundation model were evaluated using Synthetic Aperture Radar (SAR) images to assess product accuracy. The impacts of flooding on agriculture and livelihoods were analyzed to assess the flood risks. It was identified that most of the areas under paddy cultivation that were located near the middle and downstream part of the river basin are more susceptible to flood risks. This paper also proposes potential countermeasures for future natural disasters to prevent and mitigate possible damages.

Applications of Satellite-Based Rainfall Estimates in Flood Inundation Modeling—A Case Study in Mundeni Aru River Basin, Sri Lanka

“…Heavy rains at the beginning of 2011 seriously affected residents and agricultural production across parts of northeastern Sri Lanka. In the MRB, a major flood event on 3 February 2011 induced broad-spread inundation, mostly in the downstream part of the basin, with the water depth reaching approximately 2 m (Figure 2; [26]). A further flood affected eastern Sri Lanka in December 2012.…”

Evaluating flood extent mapping of two hydraulic models, 1D HEC‐RAS and 2D LISFLOOD‐FP in comparison with aerial imagery observations in Gorgan flood plain, Iran

“…These models have even been applied in large‐scale flood‐extent mapping case studies (e.g. Mukolwe, Dibaldassarre, Werner, & Solomatine, 2014), also in basin‐scale flood‐risk management studies (Amarnath, Umer, Alahacoon, & Inada, ).…”

“…Remote sensing with its spatial and temporal coverage has been a very useful tool for mapping inundation (Liu, Sahli, Meng, Huang, & Lin, ; Notti et al, ; Rosser, Leibovici, & Jackson, ). The performance of the simplified 2D models in simulating the flood extent has been judged using inundation maps observed from satellite images in several studies (e.g., Amarnath et al, ; Wood et al, ).…”

Application of the WRF Model Rainfall Product for the Localized Flood Hazard Modelling in a Data-Scarce Environment

“…The WRF design storms' appropriateness in simulating the ood extent will be compared with the results from the IDF-AB ood model results through pixel-by-pixel comparison using F statistical measures, which has been used in many ood extent studies (Schubert and Sanders, 2012;Yan et al, 2014;Amarnath et al, 2015). Speci cally, the simulated ood extent maps using the WRF design storms are compared with AB2 year/AB10 year using a simple aggregate performance measure, F, following a similar procedure presented in several ood extent studies (Aronica et al, 2002;Horritt and Bates, 2002;Amarnath et al, 2015). The F is calculated as:…”