Geomatics, Natural Hazards and Risk

Compound, Concurrent, and Cascading Hazards in a Changing Climate: Understanding and Predictability for Enhanced Resilience

Climate change is fundamentally altering the landscape of natural hazards, transforming isolated extreme events into complex networks of compound, concurrent, and cascading disasters. Traditional single-hazard frameworks are increasingly inadequate for understanding and managing events where floods follow droughts, heatwaves trigger wildfires, or hurricanes cascade into infrastructure failures and economic disruptions. These multi-hazard interactions emerge from coupled physical processes operating across temporal and spatial scales, creating risk profiles that exceed the sum of individual hazards. The non-stationarity of both natural systems and human responses adds layers of complexity, as historical patterns no longer reliably inform future expectations.

The intensification and interconnection of climate hazards pose existential challenges to global sustainability, threatening lives, livelihoods, and critical infrastructure systems. Recent disasters demonstrate that cascading failures, where one hazard triggers others or amplifies their impacts, can overwhelm emergency response systems, disrupt supply chains, and compromise food, water, and energy security across regions. Current risk assessment frameworks, largely designed for single hazards, systematically underestimate the true threat posed by compound events, leading to inadequate preparedness and maladaptive responses.

As climate change accelerates, understanding multi-hazard interactions becomes critical for protecting vulnerable communities, designing resilient infrastructure, and maintaining ecosystem services. This research gap directly impedes effective climate adaptation strategies and disaster risk reduction policies. Advancing knowledge of compound hazard dynamics, their predictability, and management strategies is essential for building societal resilience, informing evidence-based policy, and reducing the disproportionate impacts on marginalized populations who face the greatest exposure to cascading climate risks.

This Article Collection addresses the urgent need for integrated scientific approaches that capture the dynamics of interacting climate hazards, their cascading impacts on human and natural systems, and the development of predictive capabilities that can support proactive risk management and resilience building in an era of unprecedented climate change.

The Collection seeks original research, review articles, and technical notes that advance understanding of compound, concurrent, and cascading climate hazards through interdisciplinary perspectives. We particularly encourage submissions that bridge climate science, hydrology, engineering, data science, and social sciences, offering actionable insights for risk management and adaptation. Research highlighting novel datasets, cross-regional comparative studies, and decision-support tools is especially welcome. Key subtopics include:

(1) Mechanistic understanding of multi-hazard drivers, feedbacks, and physical process interactions across scales;

(2) Innovative methodologies including causal inference, machine learning, artificial intelligence, and hybrid process-based modelling approaches;

(3) Integrated Earth observation and remote sensing applications for detecting and monitoring connected hazard events;

(4) Development and validation of early warning systems for joint hazard-impact prediction;

(5) Comprehensive impact assessments on critical infrastructure, socio-economic systems, ecosystems, and recovery pathways; and

(6) Feedbacks between compound hazards and carbon-water-energy cycles under changing climate conditions.

Article Collection Guest Advisors

Dr. Vinnarasi’s research focuses on hydro-climatological extremes under changing climate conditions. She specializes in multivariate hydrological analysis, detection and attribution of extreme events, and regional hydrological modelling to enhance risk assessment and prediction. Her work also advances water accounting and climate-ecological resilience to support adaptive water management and disaster risk reduction. She earned her Ph.D. from the Indian Institute of Technology (IIT) Delhi, her Master’s degree from the Indian Institute of Technology (IIT) Guwahati, and her Bachelor’s degree from TPGIT, Vellore.

Dr. Swain is a Postdoctoral Employee at the Scripps Institution of Oceanography, University of California San Diego, working on equitable California water allocation under climate change through funding from the National Science Foundation (NSF) federal grant and a California Climate Action grant. Her research specializes in the quantitative and probabilistic risk assessment of hydro-climatic compound extremes, with specific focus on characterizing the multivariate dependencies and cascading effects of complex extremes on hydrologic ecosystems and the communities. She earned her Ph.D. in hydrology and climate change from the Indian Institute of Technology, Kharagpur.

Dr. Mondal is a Alfond AI Postdoctoral Research Fellow at the Institute of Experiential AI (IEAI) & Roux Institute at Northeastern University, where he studies hydroclimatic extremes, its drivers and impacts using complex networks, nonlinear dynamics, and machine learning. He earned his Ph.D. in Civil Engineering from Clemson University, focusing on the spatiotemporal interconnectivity of hydroclimatic extremes. His research spans droughts, heatwaves, and large-scale land-surface hydrology, with publications in venues including Nature Communications, Geophysical Research Letters, and Water Resources Research.

Dr. Shushobhit’s research focuses on climate and water systems that drive natural disasters such as floods and droughts, with the aim of improving prediction and reducing societal impacts. His research integrates hydro-climatology and environmental science to support better preparedness and risk mitigation. He is an Assistant Professor at the IIT (ISM), Dhanbad. He earned his PhD and Master’s degrees from the IIT Delhi and his Bachelor’s degree from the NIT Allahabad.

Further Information

­­All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisor for this Collection will not be handling manuscripts.

Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is 31 December 2026.

Please contact Alex Johnson at [email protected] with any queries and discount codes regarding this Article Collection.

Please be sure to select the appropriate Article Collection from the drop-down menu in the submission system.

The Guest Advisors of this Article Collection have declared no conflict of interest relating to this Article Collection.

Article Collection Key Terms

1. Compound climate hazards
2. Multi-hazard interactions
3. Predictability
4. Resilience
5. Multi-hazard risk assessment