Predicting Losses from Landslide and Flood Events in Nepal: A Regression Analysis with Moving Averages Approach

Abstract

Nepal is highly vulnerable to disasters due to its geographical structure, significant temperature variability over short distances, and changing climate. This paper aims to evaluate historical trends and predict future disaster-related losses. The moving average method is used in this study for analysis. The study focuses on data and analysis of two frequently occurring disasters in Nepal. A straight regression line is applied to the number of incidents and various variables (total deaths, missing people, affected families, and injured people) to predict future losses. Since 1971, the number of incidents involving these two disasters, landslide and flood, has been rapidly increasing. A 5-year moving average is employed to analyze the data, revealing a sharp increase in all variables studied. The rapid rise in disaster incidents and associated losses could pose significant challenges for the country. To enhance public safety, information programs should be implemented, and areas should be ranked by their level of danger to mitigate losses.