Predictive applications of Australian flood loss models after a temporal and spatial transfer

Roozbeh Hasanzadeh Nafari,Tuan Ngo

doi:10.1080/19475705.2018.1445666

Abstract

ABSTRACTIn recent decades, considerably greater flood losses have increased attention to flood risk evaluation. This study used data-sets collected from Queensland flood events and investigated the predictive capacity of three new Australian flood loss models to assess the extent of physical damages, after a temporal and spatial transfer. The models’ predictive power is tested for precision, variation, and reliability. The performance of a new Australian flood loss function was contrasted with two tree-based damage models, one pruned and one un-pruned. The tree-based models are grown based on the interaction of flood loss ratio with 13 examined predictors gathered from flood specifications, building characteristics, and mitigation actions. Besides an overall comparison, the prediction capacity is also checked for some sub-classes of water depth and some groups of building-type.It has been shown that considering more details of the flood damage process can improve the predictive capacity of damage prediction models. In this regard, complexity with parameters with low predictive power may lead to more uncertain results. On the other hand, it has also been demonstrated that the probability analysis approach can make damage models more reliable when they are subjected to use in different flooding events.

Highlights

Flood is a common natural disaster in Australia, and a frequently occurring natural phenomenon in the world (Baeck et al 2014; Hasanzadeh Nafari et al 2015; Bhatt et al 2016)
While much effort has gone into hazard investigation, i.e. models of probability and intensity of flood, flood loss estimation models are still subject to a high level of uncertainty (Merz et al 2004; Kreibich and Thieken 2008; Meyer et al 2013)
Loss estimation is needed in cost–benefit analyses of disaster risk reduction measures (Mechler 2016), vulnerability and resilience studies, flood risk analyses, and in the insurance and reinsurance sectors

Summary

Introduction

Flood is a common natural disaster in Australia, and a frequently occurring natural phenomenon in the world (Baeck et al 2014; Hasanzadeh Nafari et al 2015; Bhatt et al 2016). Flood impacts have increased (Kreibich et al 2007; Cheng and Thompson 2016; McMillan et al 2016; Mojaddadi et al 2017), reaching 29% of the total cost of Australian natural disasters (Bureau of Transport Economics 2001). Flood risk evaluation including hazard assessment and estimation of the associated consequences (Ciullo et al 2016; Vojtek and Vojtekova 2016) has attracted growing attention (Raaijmakers et al 2008; Merz et al 2010; Cammerer et al 2013; Kundzewicz et al 2013). While much effort has gone into hazard investigation, i.e. models of probability and intensity of flood, flood loss estimation models are still subject to a high level of uncertainty (Merz et al 2004; Kreibich and Thieken 2008; Meyer et al 2013). Loss estimation is needed in cost–benefit analyses of disaster risk reduction measures (Mechler 2016), vulnerability and resilience studies, flood risk analyses, and in the insurance and reinsurance sectors (de Moel and Aerts 2011).

Methods

Results

Conclusion