The Sendai Framework has outlined four priorities of actions, and these four priorities all require strong support from disaster risk science. This offers new opportunity but also challenges for disaster risk science. The UNISDR Science and Technology Conference on the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030 was held in Geneva in 27–29 January 2016 (Dickinson et al. 2016). Scientists, policymakers, business people, and practitioners at the conference focused on following key questions: (1) In what way would the UNISDR Science and Technology Partnership leverage local, national, regional, and international networks and platforms to advance multidisciplinary research and bring together science, policy, and practice? (2) How is disaster risk understood, and how are risks assessed and early warning systems designed? (3) What data, standards, and innovative practices would be needed to measure and report on risk reduction? (4) What research and capacity gaps exist and how can difficulties in creating and using science for effective disaster risk reduction be overcome? In support, UNISDR also revised DRR-related terminology, and set up monitoring indices for the seven targets listed in the Sendai Framework. In light of these updates, five topics should be addressed as high priority research areas: Dynamics and non-dynamics of disaster systems; disaster response digital systems; disaster response models; integrated disaster risk governance paradigms; and new disaster emergency and risk management systems.
Dynamics and Non-dynamics of Disaster Systems
Disaster systems are typical coupled human–environment systems, or socioecological systems, with the features of giant systems and complex network systems. A regional disaster system can have complex network system behaviors such as disaster swarms, disaster chains, and disaster compounds (Shi, Lu, et al. 2014). A disaster swarm refers to the phenomenon that disasters often occur as spatial and temporal clusters (Shi 1991). It is close to the concept of multi-hazards, and this clustering property mainly depends on the environment of the region. A disaster swarm could be further grouped into a temporal co-occurrence and a spatial cluster of hazards. Disaster chains (or cascading disasters) refer to the triggering or causal relationship between one disaster and other disaster(s). It can be further divided into parallel disaster chains (one-to-many; or ripple behavior), and sporadic disaster chains (one-after-another; or the domino effect) (Shi 1991; Shi, Lu, et al. 2014). The concept of a hazard/disaster compound was proposed by Hewitt and Burton, and indicates “the co-occurrence of multiple disasters that could induce social risks” (Burton et al. 1993; Hewitt 1997). In the Intergovernmental Panel on Climate Change (IPCC) framework, hazard compounds are a special case that result when two or more climate extremes occur together. We have framed disaster compound as the case in which two or more disasters without any causal relationships have occurred simultaneously or consecutively, and induces much larger consequences than the simple summation of each disaster, even if they are not extremes when considered separately (Shi, Lu, et al. 2014). Understanding these complex features of disaster systems is important for further understanding the formation process of hazards and disasters.
The existing literature has obtained some understanding of disasters induced by climate extremes. Knowledge gaps still exist, however, about the complexity of global change, particularly about the impact of climate change on disaster systems. Our earlier studies have shown that climate change impact on disaster has three different components: (1) the trade-off induced by climate trends; (2) uncertainty introduced by climate variability; and (3) the extreme impact associated with climate extremes (Shi, Ye, et al. 2012; Wang et al. 2018). The trade-offs induced by climate trends depend largely on geographical location. For instance, for crops grown in higher latitudes or altitudes, warming climate brings more potential gains than losses. By contrast, in middle-and-lower latitude arid and semi-arid regions, warming would further exacerbate drought, making it even more difficulty to reduce agricultural risks. The impact of climate variability largely depends on the threshold of triggers. Variation of precipitation and temperature without exceeding the prevention capacity of human society could have some effect, but not disaster. Once variations in climate exceed impact prevention capacity, a tipping-point might occur and catastrophic extreme climate and weather disaster could be triggered, causing huge losses and long-run impacts.
Studying multi-hazard, disaster chain, and disaster compound occurrences, and the impacts of climate change in its trend, variability, and extremes have important theoretical and practical meanings in understanding regional hazard mechanisms and disaster processes. Presently, we have only started to study the many features of disaster system dynamics and non-dynamics, that is, their interconnectedness, regionality, complexity, and coupling. In most cases, the existing literature considers one or two features at one time, and mainly focuses on single hazard types. Studies on the dynamics of multi-hazard, disaster chain, and disaster compound events have been very limited. Current studies on the impact of climate change on disasters paid more attention to the impact of climate trend, that is, estimation of loss and of the impacts of global average temperature increase, than that of the changes in climate variability and extremes. Studies about the dynamics of climate change in its mean, variability, and extremes, together forming systemic risk, are also limited. Study of the dynamics of disaster systems continues to rely heavily on complex network system dynamics. There is an urgent need to further establish novel quantitative indices, and deepen our understanding of the mechanisms and processes that are basic to network system dynamics. Study on the non-dynamics of disaster systems, that is, disaster risk related management and policy issues, have largely been limited to statistical analysis.
The globalization process has further highlighted the regional, interconnective, coupled, and complex features of disaster systems. The system dynamics and non-dynamics of disaster systems not only reveal the “node degree” behavior of their elements, but also their “consilience” behavior (Hu et al. 2017). The consilience of disaster systems can reflect the differences of regional disaster systems not only in their mechanisms and processes, but also the integrated features of their structures and functions. The concept of consilience also makes quantitative analysis and simulation of disaster systems possible. Disaster system dynamics contain mechanisms, processes, and dynamics models. Numerical simulations together with statistical models have often been applied to model the nature of nonlinear dynamic processes. The non-dynamics processes—disaster and disaster risk management schemes and policies—of a disaster system, like many other human–environment systems, have limited quantitative indicators and data to model, and mostly relied on statistical models. The integration and coupled study of the system dynamics and non-dynamics features of disaster systems have always been a tough challenge in disaster risk science research. With the development of the supercomputer, big data, artificial intelligence, visualization, and modern 5G network systems and their application in coupled human–environment systems, a promotion in the integration and coupled study on the system dynamics and non-dynamics of disaster systems is expected, making possible a deeper understanding of the formation processes of hazard and disaster.
Disaster Response Digital Systems
Information systems have played important roles in disaster response. The digital system for disaster response is a critical part in digital Earth systems, including the disaster response system, digital disaster system, and modeled disaster system.
The disaster response system is the system that describes the response of a regional DS at varying scales—community, local place, nation, subregion, region, and the globe—to individual disaster events and regional disasters. These include various types of response activities, such as DRR demonstration communities,Footnote 1 the UNDRR (United Nations Office for Disaster Risk Reduction) disaster resilience scorecard for cities,Footnote 2 WHO-international safe community approach to injury prevention,Footnote 3 and various other types of resources for disaster response.
The digital disaster system is the data center of a regional disaster system, mainly about the construction of and quality standard for information products. Disaster system data centers can be established by expanding the databases created from implementing the Yokohama Strategy, the Hyogo Framework for Action, and the Sendai Framework for Disaster Risk Reduction, and incorporating new data obtained from new technologies and approaches such as earth observation, internet resources, big data processing, and supercomputing. The goal of developing such digital disaster systems and data centers is to turn the observation of individual disaster events from occasional observation into long-term and fixed-site observation, from static observation to dynamic analysis, from human observation to artificial intelligence-supported observation. In this way, it is possible to provide critical data support and management services for global and regional DRR. Such data centers must be capable of receiving data from local sources and the cloud, accessing telecommunication, navigation, and remote sensing data, and assimilating multisource, spatial–temporal data.
The modeled disaster system is the modeling platform for quantitative studies of regional DS mechanisms, processes, and dynamics, loss estimation and modeling for disaster events, disaster risk assessment, and simulation of regional disasters. Based on the support of the disaster response system and data centers, technologies such as cloud computing, geographic information systems, big data visualization, virtual reality and augmented reality, and artificial intelligence can be applied to conduct all-weather, full-element, whole-process, and all-scale integrated simulation via various types of disaster and disaster-risk models.
Disaster Response Models
Disaster response models include those designed models for individual disaster events and for regional disaster systems.
Systematic response model for individual disaster events From the disaster management cycle (Carter 2008), the management of individual disaster events includes the stages of preparedness, prediction and early warning, emergency response, relief, recovery and reconstruction. The Sendai Framework divides the response to a disaster event into five stages: preparedness, emergency, rehabilitation, recovery, and reconstruction (UNISDR 2015). We divide the response to an individual disaster event into three phases: pre-disaster, during-disaster, and post-disaster. These three phases cover the preparedness, emergency response, recovery, and reconstruction stages that form the functional system of integrated disaster risk governance. Of the four stages, preparedness is the key. The response of China to the 2020 novel coronavirus has revealed the drawbacks of an insufficient resources reserve and the weakness in existing prediction and early-warning capability.
Systematic response model for regional disasters At the regional scale, disaster response has to strive for a synthesis of prevention, resilience, and relief, with a major focus on prevention. This is also the structural system of integrated disaster risk governance. Prevention is the key in regional disaster response. From the practice of disaster response, prevention refers to the set of measures that include peril identification and survey, disaster governance regionalization, prevention standard determination, and disaster insurance development. The key for resilience includes infrastructure construction, and retrofitting. The key for relief includes rapid disaster assessment and humanitarian aid. The response system for regional disasters is closely related to the developmental disaster risk governance paradigm (see below for more discussion). The efficiency and cost-effectiveness of a response system for regional disasters can be improved via optimization under the rules of effectiveness, efficiency, and equity (Shi 2011b; Hu et al. 2014).
Integrated Disaster Risk Governance Paradigms
Presently, there are plenty of ongoing discussions on the synergetic paradigm of green development and DRR, the collaborative paradigm of regions and sectors to increase DRR resources utilization efficiency, and the consilience paradigm of stakeholder involvement to improve DRR resources utilization effectiveness. The ultimate goal of these paradigms is to improve the efficiency and effectiveness of integrated DRR resources utilization (Hu et al. 2014; Shi 2018).
Synergetic paradigm The synergetic paradigm achieves the balance of development and security (Fig. 4) via effective disaster risk reduction and an overall plan of green development and integrated disaster risk governance in order to promote sustainable development (Shi 2008b). This process is also referred to as managing risk for development (World Bank 2014). It is characterized by the following goals: (1) coordinate the establishment of a resource-saving and environment-friendly society, the promotion of green economy, and progress toward a circular economy; (2) enhance the administrative functions of governments at all levels, and promote the roles of other stakeholdes (entrepreneurs and households) in integrated disaster risk governance (Shi et al. 2006); (3) increase integrated disaster risk governance resource utilization efficiency and effectiveness, optimize the coordination of DRR plans at different levels and sectors, synergize innovative development that is coordinated, green, open, and shared, and that promotes the establishment of “win–win” models for all. The establishment of regional integrated disaster risk governance synergetic paradigm has important supportive roles in improving response capability to regional disasters.
Collaborative paradigm The collaborative paradigm is important in improving the stakeholders’ role in regional integrated disaster risk governance, particularly their capability to respond systematically in individual disaster events. The collaborative paradigm attempts to build up the cooperative relationship of stakeholders in the system via improvement of institutional arrangements, operational mechanisms, and legislation (Shi 1996, 2009) (Fig. 5). The establishment of a regional disaster risk governance collaborative paradigm can effectively guide the improvement of response capability in event-based disaster management systems (Shi et al. 2006).
Consilience paradigm The consilience paradigm involves the integration of “cohesion” and “joining force,” which is the integration of hard and soft power, coupling of the dynamic and non-dynamic elements of systems, and integration of structural and nonstructural measures in the response of stakeholders (governments, the private sector, and individuals and households) to individual disaster events and regional disasters in integrated disaster systems. Consilience is a metrics and description of the “cohesion” and “joining force” capabilities, and is related to system structure and function. In the concept of consilience, cohesion refers to the process by which system components reach consensus, and joining force refers to the process that links system components to form joint forces. Consensus is reached and joint forces are formed in order to resist gradual or sudden hits from external hazards. Consilience refers to four different synergetic principles in disaster management: (1) tolerance (cohesion), namely “united people can move mountains” (traditional Chinese saying, Ren Xin Qi, Tai Shan Yi), “united people are strong” (Qi Min Zhe Qiang); (2) constraint (cohesion), namely “sacrifice a pawn to save a castle” (Qi Zu Bao Ju), “triumph comes when leaders and followers share the same goal” (Shang Xia Tong Yu Zhe Sheng); (3) amplification (joining force), that is, “more hands produce a stronger flame” (Zhong Ren Shi Chai Huo Yan Gao); and (4) diversification (joining force), that is, “ten chopsticks are stronger than one.” Consilience is closely related to the vulnerability, resilience, and adaptability of disaster systems (Shi, Wang, et al. 2014). Consilience can be computed by using consilience degree (Hu et al. 2017). Simulation experiments have shown that a higher consilience degree indicates a greater capability to resist external shocks. Optimization over consilience degree can substantially increase DRR resources utilization efficiency and effectiveness (Hu et al. 2017).
New Disaster Emergency and Risk Management Systems
In the era of globalization, modern disaster risks have wide spatial extent, stronger systemic features, and greater uncertainty and unpredictability than ever before. Disaster risk is no longer a matter of single, one-shot events, but a new societal norm. We have entered the “risk society,” and face the situation of “living with risk” (Beck 1999; UNISDR 2004). It has become an urgent issue in DRR to establish new emergency and risk management systems, which is also a new challenge in disaster risk science research.
New disaster emergency management systems An emergency management system is an important part of the disaster response system and the core of individual disaster event response. Traditional emergency management systems, which consist of ex-ante prevention, during event coping, and ex-post recovery, have been challenged by multi-hazards, disaster chains, and disaster compounds. It has been an arduous task for disaster risk science research to reveal how we can improve the emergency management capacity against large-scale disasters by regrouping disaster management administrations, establishing new schemes, improving legal systems, encouraging applied S&T as well as R&D, restructuring educational and cultural systems, enhancing rescuing systems, empowering social mobilization, and improving guaranteed emergency resources access. New disaster management schemes, administrations, systems, and command and rescue forces must be established to save people’s lives and property from disasters by using science, technology, planning, and management measures. During the response to the 2020 novel coronavirus outbreak, the Chinese government has called for a new emergency management strategy of “strengthening confidence, working together, scientific prevention and control, and targeted implementation” (Zhao et al. 2020).
Globally emergency management systems differ substantially by nations’ administrative system, institutional arrangement, and legal system. China has adopted the emergency management system of “centralized leadership, integrated coordination, management by category, multi-level responsibility, and jurisdiction management,” which places more emphasis on the regional integration of different government authorities. The United States adopted the dual-core (Federal and State administration) system supported with Federal disaster-related agencies, which emphasizes strongly the role of responsible agencies. Japan adopted a system of centralized management with the participation of local governments and departments. Since 1994, Russia has set up its Ministry of Emergency Situations. The department takes full responsibility for commanding and coordinating emergency situations, and reports to the President directly. A successful emergency management system requires an authoritative command system, solid legal support, strong rescue teams, extensive social mobilization, efficient joint defense and joint control mechanisms, strong S&T support, a consilient social environment, and timely and accurate online information services. It requires practical tests to identify which system could be more efficient, and which system could be more effective for various types of emergencies.
New disaster risk management system The UNDRR has emphasized the development strategy of “living with risk.” The dependence and interactions between different types of disaster risks are intensifying in the era of globalization. The occurrence of disaster chains becomes more frequent, with more complicated mechanisms and larger scale impacts than before. Traditional disaster risk management systems based on quantitative measurement and assessment, and an expertise system of single disciplines, are facing a series of challenges stemming from multi-hazards, disaster chains, disaster compounds, and global change. A new disaster risk management system must follow the overall trend in the “risk society.” There are different interpretations of disaster management and disaster governance. In UNDRR’s perspective, disaster management refers to specific actions in DRR, while disaster governance emphasizes institutional arrangements. The International Risk Governance Council (IRGC) has advocated a change from risk management to risk governance. The IRGC proposes to integrate DRR with green development. The Chinese government is promoting holistic national security, that is, an effort to strive for people-centered and coordinated development, prevention-centered and integrated DRR, response with legal and S&T support, and private-sector participation under government leadership. In an era of globalization, more comparative studies are needed to understand how to establish a brand-new disaster risk management system (Hu et al. 2017).
Integrated disaster risk governance needs to pay special attention to modern coupled human–environment system research (Liu et al. 2007) and the human dimensions of disaster vulnerability research (Cutter and Finch 2008). This field could borrow the idea of the Dujiangyan irrigation system from ancient China so that appropriate modification to the local environments can lead to the win–win result of risk reduction and development gains (Yan et al. 2017). It could also consider China’s response strategy to large-scale disasters, that is, to focus on stakeholder cohesion and joining forces, conduct joint defense, and centralize community prevention and governance in order to strengthen confidence, work together, scientifically prevent and reduce disaster risks, and achieve targeted implementation of policies.