TY - JOUR

T1 - Cost estimation for the monitoring instrumentation of landslide early warning systems

AU - Sapena, Marta

AU - Gamperl, Moritz

AU - Kühnl, Marlene

AU - Garcia-Londoño, Carolina

AU - Singer, John

AU - Taubenböck, Hannes

N1 - Funding Information: This research was funded by the German Federal Ministry of Education and Research as part of the FONA Client II initiative, grant number 03G0883A-F. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.The article processing charges for this open-access publication were covered by the German Aerospace Center (DLR).

PY - 2023/12/24

Y1 - 2023/12/24

N2 - 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 landslide-prone areas increases the associated risks. Landslide early warning systems (LEWSs) are essential for disaster risk reduction, but the monitoring component is often based on expensive sensor systems. This study presents a data-driven approach to localize landslide-prone areas suitable for low-cost and easy-to-use LEWS instrumentation, as well as to estimate the associated costs. The approach is exemplified in the landslide-prone city of Medellín, Colombia. A workflow that enables decision-makers to balance financial costs and the potential to protect exposed populations is introduced. To achieve this, city-level landslide susceptibility is mapped using data on hazard levels, landslide inventories, geological and topographic factors, and a random forest model. Then, the landslide susceptibility map is combined with a population density map to identify highly exposed areas. Subsequently, a cost function is defined to estimate the cost of LEWS monitoring sensors at the selected sites, using lessons learned from a pilot LEWS in Bello Oriente, a neighbourhood in Medellín. This study estimates that LEWS monitoring sensors could be installed in several landslide-prone areas with a budget ranging from EUR5 to EUR41 per person (roughly COP23000 to 209000), improving the resilience of over 190000 exposed individuals, 81% of whom are located in precarious neighbourhoods; thus, the systems would particularly reduce the risks of a social group of very high vulnerability. The synopsis of all information allows us to provide recommendations for stakeholders on where to proceed with LEWS instrumentation. These are based on five different cost-effectiveness scenarios. This approach enables decision-makers to prioritize LEWS deployment to protect exposed populations while balancing the financial costs, particularly for those in precarious neighbourhoods. Finally, the limitations, challenges, and opportunities for the successful implementation of a LEWS are discussed.

AB - 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 landslide-prone areas increases the associated risks. Landslide early warning systems (LEWSs) are essential for disaster risk reduction, but the monitoring component is often based on expensive sensor systems. This study presents a data-driven approach to localize landslide-prone areas suitable for low-cost and easy-to-use LEWS instrumentation, as well as to estimate the associated costs. The approach is exemplified in the landslide-prone city of Medellín, Colombia. A workflow that enables decision-makers to balance financial costs and the potential to protect exposed populations is introduced. To achieve this, city-level landslide susceptibility is mapped using data on hazard levels, landslide inventories, geological and topographic factors, and a random forest model. Then, the landslide susceptibility map is combined with a population density map to identify highly exposed areas. Subsequently, a cost function is defined to estimate the cost of LEWS monitoring sensors at the selected sites, using lessons learned from a pilot LEWS in Bello Oriente, a neighbourhood in Medellín. This study estimates that LEWS monitoring sensors could be installed in several landslide-prone areas with a budget ranging from EUR5 to EUR41 per person (roughly COP23000 to 209000), improving the resilience of over 190000 exposed individuals, 81% of whom are located in precarious neighbourhoods; thus, the systems would particularly reduce the risks of a social group of very high vulnerability. The synopsis of all information allows us to provide recommendations for stakeholders on where to proceed with LEWS instrumentation. These are based on five different cost-effectiveness scenarios. This approach enables decision-makers to prioritize LEWS deployment to protect exposed populations while balancing the financial costs, particularly for those in precarious neighbourhoods. Finally, the limitations, challenges, and opportunities for the successful implementation of a LEWS are discussed.

UR - http://www.scopus.com/inward/record.url?scp=85182990043&partnerID=8YFLogxK

U2 - 10.5194/nhess-23-3913-2023

DO - 10.5194/nhess-23-3913-2023

M3 - Article

AN - SCOPUS:85182990043

VL - 23

SP - 3913

EP - 3930

JO - Natural Hazards and Earth System Sciences

JF - Natural Hazards and Earth System Sciences

SN - 1561-8633

IS - 12

ER -