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Frequent occurrence of natural disasters has become one of the most serious challenges to human society. As rural communities are the forefront of disasters, enhancing the resilience of rural community is crucial to mitigate the impact of natural disasters and seek rapid recovery. This paper provides an analytical framework for changing trajectories of the resilience of rural communities after disasters. Taking the disaster area affected by the catastrophic debris flow in China as an example, we analyze the changing trajectories of rural community resilience after disaster in three villages with different damage levels from 2010 to 2020 based on the data from key person interviews, the disaster situation and development reports, village work records and farmers' questionnaires. We found that the changes of community resilience after disaster show obvious stages due to the difference in the intensity of effects of government intervention and community self-organization ability during disaster relief reconstruction period and self-recovery period. The resilience of communities with different disaster losses showed an increasing trend. However, during the disaster relief and reconstruction period, the resilience of the severely affected community was improved faster, followed by the most severely affected community, while the resilience of generally affected community was improved more slowly. During the self-recovery period, the resilience of the affected general community was improved faster than that of the other two communities. The evolution process of community resilience reflects the increasing role of self-organizational capacity in post-disaster community development, aligning with the overall global trend in rural community governance. In addition, there is a significant sequence in the improvement speed of different dimensions of community resilience at different stages after disasters. During the disaster relief and reconstruction period, the resilience of community management was improved faster and the resilience of environment was slower. During the self-recovery period, the economic resilience of community was improved faster and the social resilience was improved slower. Finally, some suggestions were put forward to strengthen natural disasters prevention and community resilience in disaster-prone areas. [Display omitted] • Provide an analytical framework for the changing trajectories of the resilience of rural communities after disaster. • Community self-organization ability play an important role in improving community resilience. • There are significant differences in resilience of communities with different disaster losses. • There is an obvious sequence in the improvement speed of different dimensions of community resilience after disaster. [ABSTRACT FROM AUTHOR]

Rapid urbanization and exacerbated natural hazards, for example, floods, have been the big challenges for the sustainable development of many countries. Understanding the coupling coordination between urbanization and flood is important for promoting the sustainable development. However, there are few quantitative studies on the interaction between these two in China which is experiencing accelerated urbanization and climate change. In this paper, we developed an improved coupling coordination degree (CCD) model, applied Moran's I and projection pursuit model based on genetic algorithm to analyze the spatiotemporal distribution and spatial clustering effects of coupling coordination in urbanization–flood disasters system under the context of China's Five-Year Plan for National Economic and Social Development. Our results showed an upward trend of the comprehensive level of urbanization subsystem and a decreasing first and rising later trend of flood disaster subsystem in China from 2001 to 2018. There was a U-shaped relationship between the two subsystems during the research period. From 2001 to 2018, provinces with the moderate and slight uncoordinated development decreased by 9.68% and 16.13%, respectively, while provinces with the barely coordinated development increased by 16.21%. Spatially, there was a remarkable spatial dependency on CCD. The CCD between two subsystems in Northwestern China was higher than that in Southeastern China. Due to the effects of geographic position, rainfall, human activities, and economic development, the low-low (L-L) clusters concentrated in Southeastern China, and the high-high (H–H) clusters appeared in Northwestern China. Our results show that the improved CCD model, along with Moran's I analysis, can provide theoretical basis for policy makers to formulate reasonable measures for promoting the coupling coordination between urbanization and flood disasters. • Spatiotemporal distribution and dynamic evolution of nexus between urbanization and flood disasters were investigated. • Improved CCD model, Moran's I and projection pursuit model based on genetic algorithm were developed. • There was a U-shaped relationship in comprehensive level between urbanization and flood disasters. • CCD between two subsystems in Northwestern China was higher than that in Southeastern China. • There was a remarkable spatial clustering effects in CCD. [ABSTRACT FROM AUTHOR]

• Establishing an assessment method of community resilience from multi-dimensions of social capitals, stakeholders and disaster phases. • Measuring the community resilience using SNA method from the perspective of six important disaster-adapting social capitals. • Proposing 4R implements on enhancing the community resilience in different disaster phases. • Helping to improve disaster management efforts in urban communities, especially those that are collaboratively managed by multi-stakeholders. Facing increasingly frequent disasters, the resilience concept are widely adopted to make up the limitations of traditional community disaster management. The relationships among community stakeholders along with their responsibilities and actions are important social capitals coping with community disaster, which have a significant impact on forming the community resilience. Accordingly, this paper is the first attempt to measure the community resilience using social network analysis (SNA) method from the view of social capitals of stakeholders. Firstly, six key disaster-adapting social capitals in the urban community are identified using systematic literature review (SLR). Then, the social capitals before, during and after the community disaster are calculated based on the SNA to characterize the level of community resilience. Finally, taking a waterlogging disaster in Nanjing city of China, some implements on enhancing the community resilience in different phases are proposed from four aspects: rapidity, robustness, redundancy and resourcefulness. The findings in the case study and the conclusions of this paper provides an easy method to calculate the resilience and social capitals of a community at different stages of a disaster, and also helps to improve disaster prevention and reduction efforts in urban communities, especially those that are collaboratively managed by multi-stakeholders. [ABSTRACT FROM AUTHOR]

Due to the national nutrition crisis and the adjustment of planting structure, millet has once again become a widely planted cash crop in Northern China. However, as the climate warms in recent years, drought has occurred frequently and repeatedly in Northern China, which has seriously threatened millet production safety in this area. Therefore, it is urgent to clarify the hazard of millet drought disaster and provide reference for the formulation of millet disaster prevention and reduction measures. In this paper, combined with the water demand of millet in each growth period, Standardized Precipitation Requirement Index (SPRI) was selected to identify and quantify the drought disaster of millet. Considering the impact of different degrees of drought in different growth periods, a hazard assessment model is constructed to evaluate the hazard of millet drought disaster in Northern China under the background of climate change. The results show that: (1) SPRI can well characterize the drought of millet in Northern China. (2) In the context of climate change, millet drought in Northern China shows a trend of increasing intensity and decreasing frequency, and it is possible that millet drought will be even more severe in the future. (3) Combined with the hazard assessment model, millet drought in Northern China will still be dominated by middle hazard in the future, but the areas with high hazard will gradually increase, mainly distributed in northeast China, central and western Inner Mongolia and northern Gansu. The research results can be of great practical significance for the adjustment of agricultural production structure in the future, especially for the sustainable development of agriculture and the formulation of measures to prevent and resist agricultural disasters. [Display omitted] • We apply SPRI to identify millet drought by considering actual water demand. • Future changes of millet drought evaluated by CMIP6-GCM models. • Hazard assessment model was presented combined with disaster loss coefficient. • The areas with high hazard of millet drought will gradually increase in future. [ABSTRACT FROM AUTHOR]

Upon the occurrence of a disaster, emergency supplies should arrive at disaster areas with different severities in the shortest time. Therefore, it is of pivotal importance to plan and schedule appropriate processes. This paper first elaborates on the principle of ordered arrival of emergency supplies. Then, it establishes a multi-objective multi-constraint emergency material scheduling (EMS) model based on the principle of ordered arrival. Subsequently, a hybrid ant colony optimization (HACO) is proposed to solve EMS. The computational results for 15 multi-depot benchmark instances are reported and the average error between HACO and the best known solution (BKS) is only 0.16% Then, real geological disasters from Hubei province in China are examined as a case study. Experimental results show that HACO performs better than non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective ant colony algorithm (MOACO) in the case study and benchmark instances. • Study a large-scale real landslide disaster. • Establish a multi-objective multi-constraint EMS model. • Propose a HACO to solve the EMS model. • The HACO is tested on benchmarks and disaster network. [ABSTRACT FROM AUTHOR]