15 Mar 2023
 | 15 Mar 2023
Status: a revised version of this preprint is currently under review for the journal NHESS.

Cost estimation for the monitoring instrumentalization of Landslide Early Warning Systems

Marta Sapena, Mortiz Gamperl, Marlene Kühnl, Carolina Garcia-Londoño, John Singer, and Hannes Taubenböck

Abstract. Landslides are socio-natural hazards. In Colombia, for example, these are the most frequent hazards. The interplay of climate change and the mostly informal growth of cities in high-hazard areas increases the associated risks. Early warning systems (EWSs) are essential for disaster risk reduction, but the monitoring component is often based on expensive sensor systems. This study aims to develop a cost-effective method for low-cost and easy-to-use EWS instrumentalization in landslide-prone areas identified based on data-driven methods. We exemplify this approach in the landslide-prone city of Medellín, Colombia. We introduce a workflow to enable decision-makers to balance financial costs and the potential to protect exposed populations. To achieve this, we first mapped city-level landslide susceptibility using data on hazard levels, landslide inventories, geological and topographic factors using a random-forest model. We then combine the landslide susceptibility map with a population density map to identify highly exposed areas. Subsequently, a cost function is defined to estimate the cost of EWS-monitoring sensors at the selected sites, using lessons learned from a pilot EWS in Bello Oriente, a neighbourhood in Medellín. Our study estimates that EWS monitoring sensors could be installed in several landslide-prone areas in the city of Medellín with a budget ranging from €5 to €41 per person (roughly COP 23,000 to 209,000), improving the resilience over 190,000 exposed individuals, 81 % of whom are located in precarious neighbourhoods; thus, they are a social group of very high vulnerability. We provide recommendations for stakeholders on where to proceed with EWS instrumentalization based on five different cost-effective scenarios. Finally, we discuss the limitations, challenges, and opportunities for the successful implementation of an EWS. This approach enables decision-makers to prioritize EWS deployment to protect exposed populations while balancing the financial costs, particularly for those in precarious neighbourhoods.

Marta Sapena et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2023-41', Anonymous Referee #1, 26 Mar 2023
    • AC1: 'Reply on RC1', Marta Sapena Moll, 13 Jun 2023
  • RC2: 'Comment on nhess-2023-41', Anonymous Referee #2, 05 May 2023
    • AC2: 'Reply on RC2', Marta Sapena Moll, 13 Jun 2023

Marta Sapena et al.

Marta Sapena et al.


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Short summary
A new approach for the deployment of Early Warning Systems (EWSs) in landslide-prone areas is proposed. We combine data-driven landslide susceptibility mapping and population maps to identify high-risk locations. We estimate the cost of monitoring sensors and demonstrate that EWSs could be installed with a budget ranging from €5 to €41 per person in Medellín, Colombia. We provide recommendations for stakeholders and outlines the challenges and opportunities for successful EWS implementation.