The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

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 toward improved characterization of evolving hazards and risk across HMA.

Geomorphic and Sedimentary Effects of Modern Climate Change: Current and Anticipated Future Conditions in the Western United States

“…Wood et al (2015) identified over 5,200 landslides in the European Alps using academic and emergency-management publications, a database most useful for identifying changes from 1970 forward rather than for comparing preanthropogenic and synanthropogenic warming landslides. Other, less complete inventories are informative for mechanistic studies, but of limited use in identifying temporal trends and thus the role of changing climate (e.g., Allen et al, 2011 (Burrows et al, 2019;Kirschbaum et al, 2019;Martha et al, 2017;Mondini et al, 2019;Teshebaeva et al, 2019;Williams, Gentine, et al, 2018). Expanded use of these techniques and machine-learning algorithms to predict landslide susceptibility (Bellugi et al, 2015;Bragagnolo et al, 2020;Chang et al, 2019;Marjanović et al, 2011;Sachdeva et al, 2020) and to detect landslides that have already occurred (Ghorbanzadeh et al, 2019;Liu & Wu, 2016) will be essential for compiling future large-scale inventories.…”

Cryosphere hazards in Ladakh: the 2014 Gya glacial lake outburst flood and its implications for risk assessment

“…There is an urgent need to generate glacial lake inventories that include small lakes by using high spatial resolution satellite imagery (Bhambri et al 2016). Moreover, the hydrological connectivity of several lakes may trigger the outburst of other lakes due to cascading effects (Erokhin et al 2018;Kirschbaum et al 2019;Petrakov et al 2020). A sophisticated monitoring concept should also integrate satellite data with high temporal resolution to indicate the development of short-lived lakes on glaciers or on debris landforms with buried ice (Narama et al 2012(Narama et al , 2018 or fast glacial lake growth (Petrakov et al 2020) as also evident in the case of Gya.…”

Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate

“…A global landslide catalog (GLC) quantifies the relationship between landslide occurrence and climate variations [295,296] (see Figure 10). Moreover, satellite approaches are particularly effective in understanding and quantifying cascading hazard processes which are not necessarily induced by heavy rainfall only, but also from seismic activity or snow melt on vulnerable complex terrain [297].…”