Landslide hazard assessment and mapping at national scale for Malawi

Abstract

Malawi, a landlocked country characterized by its mountainous terrain crisscrossed by the Great Rift Valley and Lake Malawi, is facing an increasing threat of landslides primarily triggered by heavy rainfall from tropical cyclones and depressions. While there are general landslide susceptibility maps available on a global and continental scale, Malawi lacks its own specific landslide hazard maps that take into account regional nuances, different types of landslides, and their triggering factors. However, factoring in these parameters is essential for accurately quantifying hazards. This contribution aims to fill this gap by proposing hazard maps that consider both spatial and temporal probabilities of landslide events. The methodology employed here is based on quantifying the probability of failure at both spatial and temporal levels, following the guidelines set forth by the Joint Technical Committee – 1 for slopes and landslides (JTC-1). To enhance the accuracy of the landslide inventory, a combination of literature review, visual remote sensing, and field surveys was used. This comprehensive data collection approach included information on the types of landslides, their activity levels, and the periods during which they are most likely to be triggered. Subsequently, susceptibility analyses were conducted for various types of landslides using a data-driven approach. Temporal analyses were carried out, taking into consideration two key factors: (i) the recurrence time of different phenomena, such as debris-flows, debris-slides, and slides from 1946 to 2019, and (ii) the rainfall patterns induced by various tropical meteorological events, as defined by the World Meteorological Organization and Meteo-France. the computation of exceedance probabilities based on the Poisson distribution, predicting the likelihood of landslide reactivation for six different return periods, ranging from 1 to 100 years, following various typical meteorological events. Subsequently, susceptibility analyses were conducted for various types of landslides using a data-driven approach. Temporal analyses were carried out, taking into consideration two key factors: (i) the recurrence time of different phenomena, such as debris-flows, debris-slides, and slides from 1946 to 2019, and (ii) the rainfall patterns induced by various tropical meteorological events, as defined by the World Meteorological Organization and Meteo-France. the computation of exceedance probabilities based on the Poisson distribution, predicting the likelihood of landslide reactivation for six different return periods, ranging from 1 to 100 years, following various typical meteorological events. Ultimately, this methodology facilitates the development of various spatio-temporal landslide risk scenarios on a national scale.