Getting Ahead of Landslides: Understanding Social and Environmental Interactions to Anticipate Future Urban Landslide Risk

Introduction

Global landslide casualties will rise due to greater exposure, lack of practical measures, and informed policies addressing growing landslide risks.

Urban Population Growth

The global urban population has grown from 30% in 1950 to about 50% today and will likely reach 68% by 2050. This increase will raise the number of people exposed to landslides to 90 million from today's 65 million.

This surge in the urban population and associated landscape modifications, often unplanned, exacerbate landslide risk, especially in the tropics. For example, informal house construction could reduce slope stability, besides exposing inhabitants.

Climate Change Impact

In parallel, anthropogenic climate change could double landslide-relevant rainfall extremes, increasing landslide hazards. Essential interactions among urbanization, demographic composition, rainfall, and landslides are well-known.

However, traditional risk assessments ignore feedback between these risk drivers and discount their future states, hampering proactive risk management due to their focus on historical observations.

Project Objectives

UrbanSlide aims to unravel the complex shaping of landslide risk by studying causal interactions between societal, environmental, and urbanization risk drivers.

Intending to "get ahead of landslides," UrbanSlide will develop a hybrid model integrating process-based and statistical models, both informed by empirical knowledge on social-environmental interactions. A key emphasis is on anticipating the diverse human actions shaping landslide riskscapes.

Expected Outcomes

Eventually, UrbanSlide will quantify potential future landslide risk in the rapidly expanding tropical urban centers to facilitate informed decision-making.

UrbanSlide will fill the fundamental knowledge gap regarding the dynamics of landslide risk emerging from the intricate interplay of the environment and society. The derived quantitative evidence will notably support the design of pro-poor urban landslide risk reduction practices by highlighting the scale and priority regions of future landslide risk.