The State of Remote Sensing Capabilities of Cascading Hazards over High Mountain Asia.

Dalia Kirschbaum,Jeffrey S Kargel,Dan Shugar,Umesh K Haritashya,Minjeong Jo,David Shean,David R Rounce,C Scott Watson,Eric R Anderson,Pukar Amatya

doi:10.3389/feart.2019.00197

Abstract

Cascading hazard processes refer to a primary trigger such as heavy rainfall, seismic activity, or snow melt, followed by a chain or web of consequences that can cause subsequent hazards influenced by a complex array of preconditions and vulnerabilities. These interact in multiple ways and can have tremendous impacts on populations proximate to or downstream of these initial triggers. High Mountain Asia (HMA) is extremely vulnerable to cascading hazard processes given the tectonic, geomorphologic, and climatic setting of the region, particularly as it relates to glacial lakes. Given the limitations of in situ surveys in steep and often inaccessible terrain, remote sensing data are a valuable resource for better understanding and quantifying these processes. The present work provides a survey of cascading hazard processes impacting HMA and how these can be characterized using remote sensing sources. We discuss how remote sensing products can be used to address these process chains, citing several examples of cascading hazard scenarios across HMA. This work also provides a perspective on the current gaps and challenges, community needs, and view forward towards improved characterization of evolving hazards and risk across HMA.

Highlights

Natural hazard-induced disasters exploit the vulnerabilities in society created by political, historical, and cultural processes (Kelman, 2019)
To provide context for how remote sensing data may inform the interactions between elements in the cascading hazard chains or webs, we provide six case studies across High Mountain Asia (HMA) that represent a range of conditions under which cascading hazard processes have occurred
This work provides a survey of how remote sensing data may inform characterization, mapping, and modeling efforts for cascading hazard processes, chains, and webs across HMA

Summary

INTRODUCTION

Natural hazard-induced disasters exploit the vulnerabilities in society created by political, historical, and cultural processes (Kelman, 2019). Pescaroli and Alexander (2016) contest the simplified “toppling dominoes” perspective of cause-effect They argue that cascades happen nonlinearly and include many amplifying and subsidiary events, where the compounding effects of natural hazard processes can be phenomenologically distinct from the cause, and the impacts can be diverse and far ranging. The disaster had political (Sökefeld, 2012) and geopolitical (Haider, 2012; Butz and Cook, 2015) impacts on a strategic border The potential for such immense losses make it incumbent on the scientific community, policy makers, and those developing Decision Support Systems (DSS) to consider and evaluate physical cascading process chains and webs to better integrate physical models with economic and social models of cascading impacts. It is intended to provide insight into how remote sensing information can help governments advance the Sendai Framework Priorities of understanding disaster risk, strengthening disaster risk governance, and enhancing disaster preparedness (UNISDR, 2015)

BACKGROUND

Findings

CONCLUSION