The Yangtze River Delta (YRD) is one of the most developed regions in China. This is also a flood-prone area where flood disasters are frequently experienced; the situations between the people–land nexus and the people–water nexus are very complicated. Therefore, the accurate assessment of flood risk is of great significance to regional development. The paper took the YRD urban agglomeration as the research case. The driving force, pressure, state, impact and response (DPSIR) conceptual framework was established to analyze the indexes of flood disasters. The random forest (RF) algorithm was used to screen important indexes of floods risk, and a risk assessment model based on the radial basis function (RBF) neural network was constructed to evaluate the flood risk level in this region from 2009 to 2018. The risk map showed the I-V level of flood risk in the YRD urban agglomeration from 2016 to 2018 by using the geographic information system (GIS). Further analysis indicated that the indexes such as flood season rainfall, urban impervious area ratio, gross domestic product (GDP) per square kilometer of land, water area ratio, population density and emergency rescue capacity of public administration departments have important influence on flood risk. The flood risk has been increasing in the YRD urban agglomeration during the past ten years under the urbanization background, and economic development status showed a significant positive correlation with flood risks. In addition, there were serious differences in the rising rate of flood risks and the status quo among provinces. There are still a few cities that have stabilized at a better flood-risk level through urban flood control measures from 2016 to 2018. These results were basically in line with the actual situation, which validated the effectiveness of the model. Finally, countermeasures and suggestions for reducing the urban flood risk in the YRD region were proposed, in order to provide decision support for flood control, disaster reduction and emergency management in the YRD region.

Water, energy and food are the basic resources for human survival and development. The coordination development of water-energy-food (W-E-F) is of great significance to promote regional sustainable development. In this study, Northwest China (Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang) was selected as the research case, and an evaluation index system was constructed to assess the vulnerability and coordination of water-energy-food (W-E-F) system based on PSR model. Then, a coupled model based on cloud-matter element model and coordination degree model was proposed. The cloud-matter element model was adopted to evaluate the vulnerability level of W-E-F system. The coordination degree model was employed to calculate the coordination degrees of W-E-F system. The results showed that, from 2006 to 2015, the vulnerability levels of W-E-F system in Northwest China were mostly at Level 1. The coordination degrees of W-E-F system belonged to the transitional development level (II) in most years. The vulnerability and coordination problems of W-E-F system in Northwest China were severe. The comprehensive vulnerability index values of W-E-F system were generally on the rise, but far from reaching a good level. Moreover, the comprehensive vulnerability index values and coordination degrees of W-E-F system in Northwest China do not match well. Finally, the countermeasures and suggestions to improve the coordinated development of water resource, energy and food in Northwest China were put forward.2 of 25 scholars and relevant departments. Research on W-E-F system has become an important topic in the field of sustainable development [4].Vulnerability, as an important research object, has been put on the research agenda by international scientific programs and institutions such as IHDP, IPCC, IGBP [5][6][7]. It has become the frontier and hotspot of global environmental change and sustainable scientific research. In 1999, the United Nations Development Programme (UNDP) formally put forward the concept of "economic vulnerability" [8]. After that, the research object of vulnerability has gradually expanded from the natural ecological environment system to the complex system which includes the natural, social, economic and institutional factors. Cutter [9] summarized the related concepts of vulnerability, pointing out that social vulnerability is a natural risk and social response within a specific region or geographical scope, and stressing the imbalance of social preparedness, response, recovery and adaptation to disasters. The United Nations International Strategy for Disaster Reduction (UNISDR) defined vulnerability as the extent to which the attributes of communities, systems or property and the environment are damaged by disaster-causing factors. It was considered that vulnerability was related to various natural, social, economic and environmental factors, and has certain temporal and spatial attributes [10]. Chen et al. [11] indicated that social vulnerability influenced people's ability to make full pre-disaster preparatio...

The coupling and coordination development of the environment and economy (CC2E) is one of the most vital issues to sustainable development. This paper adopted the coupling coordination model, projection pursuit algorithm, and random forest model to explore the spatial-temporal evolution and influencing factors of the CC2E in the Yangtze River Delta from 2015 to 2019, respectively. The results showed that: (1) The degree of coupling coordination (DCC) of the CC2E in most cities of the Yangtze River Delta has risen from primary coordination to intermediate coordination. (2) In the spatial perspective, the distribution of DCC is correlated with geographical location. The value of DCC in the western region was significantly lower than that of the eastern cities. (3) The influencing factors results showed that the GDP in the economic subsystem and the annual average concentration of PM2.5 in the environmental subsystem were the most influencing factors of DCC in the Yangtze River Delta. The established index system of CC2E and the measurements of CC2E provide a new idea for how to achieve sustainable development. Meanwhile, this study can provide recommendations for formulating the environmental protection and economic development policy.

Effective management of rainstorm risk is essential for reducing regional rainstorm disaster risks and losses. In this paper, we discussed the influencing factors of urban rainstorm disaster (URSD) risk from four aspects and then constructed the index system of URSD risk assessment which includes 16 influencing factors. Furtherly, important indexes were extracted as the input of deep belief nets (DBN) model after analyzing the types and risk characteristics of URSD. As well as a coupling risk assessment model of URSD based on random forest and deep belief nets (RF-DBN) was established due to the capacity of highdimensional data processing of RF and robustness of DBN. To test the validity of this risk assessment model, it was applied to evaluate the rainstorm disaster risk in 11 districts of Nanjing, China, from May to September during 2009 and 2017. Finally, the risk grade map of rainstorm disaster in Nanjing was drawn and the corresponding countermeasures for the regulation and control of URSD were put forward. The results show that the rainstorm risk in Nanjing is generally high during the period of rainy season and the risk of rainstorm disaster has egional features during the flood season.