Methodologies of Economic Measurement and Vulnerability Assessment for Application in Landslide Risk Analysis in a Highway Domain Strip: A Case Study in the Serra Pelada Region (Brazil)

Ellen Felizardo Batista,Larissa De Brum Passini,Alessander Christopher Morales Kormann

doi:10.3390/su11216130

Abstract

Landslides are one of the main causes of death caused by disasters in the world. In this study, methodologies to measure landslide costs and to assess vulnerability are presented, with the objective of applying them to landslide risk analyses. The methodologies were applied in a region of Serra do Mar, which is crossed by a highway. The analyses and mappings were implemented in a Geographic Information System (GIS). Through the application of the methodology that considers both direct and indirect costs in the composition of total cost, it was established how much an m2 of a landslide would cost. The composition of direct costs encompassed the damages related to restoration or construction of the highways, infrastructures, unpaved roads, residential and commercial buildings, vegetal cover and agricultural areas. In indirect costs, the economic losses by victims, highway interdiction, and agricultural area profitability were calculated. In the methodology for vulnerability assessment, bodily injuries, structural damages, and functional disturbances resulted from landslides were analyzed. The risk assessment was performed through the junction of the maps of total cost, vulnerability and susceptibility. The results indicate that indirect costs were predominant in cost composition, corresponding to 87% of total costs, in comparison to 13% of the direct costs, stressing the importance of considering indirect costs in economic measurement studies. As a result, it is possible to conclude that studying landslide consequences as economic parameters supports the increasing need of performing risk quantitative analyses. It is also prudent to add that these studies help decision makers in projects of disaster risk mitigation strategies, by allowing the identification of regions with greater economic impacts in case of landslide occurrence.

Highlights

Landslides are one of the main accidents caused by disasters in the world [1,2], resulting in social, environmental, and monetary losses [3]
The following mean values were adopted for the exposed element damages: (i) USD 232.45/m2 for constructing of a double-lane highway, with 7.2 m wide lanes and a roadside 2.5 m wide added to the cost of the project. [50]; (ii) USD 1046.57/m2 for the reinforced concrete infrastructures [50]; (iii) USD 0.27/m2 for reconstructing unpaved roads [51]; (iv) USD 357.35/m2 for the buildings [52]; (v) USD 0.54/m2 for reforesting the vegetal cover with structural and functional characteristics that are similar to the original forests [55]; and (vi) USD 1.85/m2 for the banana crop cultivation [57] for a productive lifespan of six years on the orchard [89]
The loss and damage mapping was performed through the total cost measurement by pixel (1 × 1 m), composed of direct and indirect costs

Summary

Introduction

Landslides are one of the main accidents caused by disasters in the world [1,2], resulting in social, environmental, and monetary losses [3]. Broad analyses of the consequences are fundamental to reduce harmful effects [4] and for sustainable development of areas that are susceptible to landslides [5]. The landslide risk can be determined by the product between (i) danger, that is, the probability or the susceptibility of a dangerous event to occur, (ii) vulnerability, expressed by the damage factor expected, and (iii) the value (economic measurement) of the exposed elements (human beings, residences, among others.) [6,7]. Identifying risk elements and assessing their relations with the danger constitute the most thorough steps of risk analysis. These relations encompass the landslide potential harmful effect, which is extremely important when defining vulnerability [8]. The quantitative assessments allow the identification of regions with greater losses, enabling the possibility to direct the mitigation efforts and increase the risk management effectiveness [9,10]

Objectives

Results

Conclusion