Modeling spatial dependencies of natural hazards in coastal regions: a nonstationary approach with barriers

Abstract

Natural hazards like floods, cyclones, earthquakes, or, tsunamis have deep impacts on the environment and society causing damage to both life and property. These events can cause widespread destruction and can lead to long-term socio-economic disruption often affecting the most vulnerable populations in society. Computational modeling provides an essential tool to estimate the damage by incorporating spatial uncertainties and examining global risk assessments. Classical stationary models in spatial statistics often assume isotropy and stationarity. It causes inappropriate smoothing over features having boundaries, holes, or physical barriers. Despite this, nonstationary models like barrier model have been little explored in the context of natural disasters in complex land structures. The principal objective of the current study is to evaluate the influence of barrier models compared to classical stationary models by analysing the incidence of natural disasters in complex spatial regions like islands and coastal areas. In the current study, we have used tsunami records from the island nation of Maldives. For seven atoll groups considered in our study, we have implemented three distinct categories of stochastic partial differential equation meshes, two for stationary models and one that corresponds to the barrier model concept. The results show that when assessing the spatial variance of tsunami incidence at the atoll scale, the barrier model outperforms the other two models while maintaining the same computational cost as the stationary models. In the broader picture, this research work contributes to the relatively new field of nonstationary barrier models and intends to establish a robust modeling framework to explore spatial phenomena, particularly natural hazards, in complex spatial regions having physical barriers