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Background: and Purpose: Increasingly frequent meteorological disasters have brought severe challenges that should be urgently handled in the sustainable development. However, meteorological data, loss data, social economic data and so forth relating to meteorological disasters rarely be effectively fused, failing to generate, rapidly and efficiently, economic losses and thus hindering the emergency management of disasters., Methods: A new economic losses evaluation information system has been developed for monitoring severe rainfall and flooding disasters in cities. The data mining method, econometric regression model and input-output model are implemented in the system, on the basis of multi-source data including hourly rainfall, geographical conditions, historical and real-time disaster information, socioeconomic data, and defense countermeasure., Results: Combined with the weather forecast information, this system can has the capability for reporting the real-time direct and indirect economic losses incurred by urban heavy rainfall and flooding disasters, automatically generating defense countermeasure reports for typical rainstorm and flooding points, and providing the spatial distribution of disasters., Conclusions: Finally, the system is conducive to improving the ability to manage disaster emergencies and eventually reducing the economic losses from the disaster., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Since December 2019, the COVID‐19 epidemic has been spreading continuously in China and many countries in the world, causing widespread concern among the whole society. To cope with the epidemic disaster, most provinces and cities in China have adopted prevention and control measures such as home isolation, blocking transportation, and extending the Spring Festival holiday, which has caused a serious impact on China's output of various sectors, international trade, and labor employment, ultimately generating great losses to the Chinese economic system in 2020. But how big is the loss? How can we assess this for a country? At present, there are few analyses based on quantitative models to answer these important questions. In the following, we describe a quantitative‐based approach of assessing the potential impact of the COVID‐19 epidemic on the economic system and the sectors taking China as the base case. The proposed approach can provide timely data and quantitative tools to support the complex decision‐making process that government agencies (and the private sector) need to manage to respond to this tragic epidemic and maintain stable economic development. Based on the available data, this article proposes a hypothetical scenario and then adopts the Computable General Equilibrium (CGE) model to calculate the comprehensive economic losses of the epidemic from the aspects of the direct shock on the output of seriously affected sectors, international trade, and labor force. The empirical results show that assuming a GDP growth rate of 4–8% in the absence of COVID‐19, GDP growth in 2020 would be ‐8.77 to ‐12.77% after the COVID‐19. Companies and activities associated with transportation and service sectors are among the most impacted, and companies and supply chains related to the manufacturing subsector lead the economic losses. Finally, according to the calculation results, the corresponding countermeasures and suggestions are put forward: disaster recovery for key sectors such as the labor force, transportation sector, and service sectors should be enhanced; disaster emergency rescue work in highly sensitive sectors should be carried out; in the long run, precise measures to strengthen the refined management of disaster risk with big data resources and means should be taken. [ABSTRACT FROM AUTHOR]

Due to the climate change and the rapid progress of urbanization, extreme weather disasters such as urban rainstorm and waterlogging are frequent. Therefore, how to find the waterlogging points in the presence of disasters and how to optimize the distribution of urban emergency logistics and reduce the negative impact of disasters have become a hot and difficult issue for government departments and scholars. First of all, the idea and method of using the big data of microblogging to obtain urban rainstorm and waterlogging disasters and public sentiment are put forward. In addition,this thesis constructed the location-routing problem model of urban emergency logistics in the situation of rainstorm and waterlogging disaster, and found out the dynamic emergency distribution path of Nanjing in the situation of waterlogging disaster by using NSGA-III algorithm. Research shows that the risk management of urban rainstorm and waterlogging disasters, together with social media data, is a feasible way to obtain on-site data of disasters and carry out risk assessment of disasters. At the same time, the emergency logistics location-positioning model and algorithm can provide a reference for similar disaster emergency logistics distribution network and the conclusion can provide empirical reference for cities to cope with rainstorm and waterlogging disasters. [ABSTRACT FROM AUTHOR]

Disasters are serious challenges to human development and the sustainability of the planet and, due climate change, natural disasters are becoming more frequent. International aid, which can effectively alleviate resultant losses and sustainable implications, has become an important way for humans to resist disasters cooperatively. Relevant research on how much each country should donate sustainably is barely seen. Against such a background, by taking into account indirect economic loss to and payment ability of donors, this paper proposes a novel framework and detailed input-output model for determining the amount of international aid that countries and multilateral organizations should allocate to disaster-stricken countries. To validate our method, the May 12th Wenchuan earthquake of 2008 is taken as example, and the indirect economic loss to each country is calculated based on the world input-output tables. Assuming that the total amount of aid is unchanged, the greater the indirect economic loss and payment ability are, the larger the amount of aid should be. Otherwise, the smaller the amount of aid should be. Based on the China's Ministry of Foreign Affairs statistics, the results show that among the 41 donors, 6 countries including Indonesia, Australia, South Korea, Spain, Turkey, and Japan donated too much while 23 countries such as India donated too little. Next, the recommended amount of aid is given by considering the indirect economic loss to and payment ability of each country. The advantage of this framework and method line in that the calculation results are objective and concise, while the disadvantage is that the indirect economic loss is relatively large and the recommend donate is uncertain. This paper demonstrates a new perspective for the study of standards for determining the amount of international aid that countries and multilateral organizations should provide to alleviate sustainable implications. [ABSTRACT FROM AUTHOR]