In many flood-prone areas, it is essential for emergency responders to use advanced computer mode... more In many flood-prone areas, it is essential for emergency responders to use advanced computer models to assess flood risk and develop informed flood evacuation plans. However, previous studies have limited understanding of how evacuation performances are affected by the arrangement of evacuation shelters regarding their number and geographical distribution and human behaviors regarding the heterogeneity of household evacuation preparation times and route searching strategies. In this study, we develop an integrated socio-hydrological modeling framework that couples (1) a hydrodynamic model
Urban resilience, as an emerging research focus in urban studies, is the capability of an urban s... more Urban resilience, as an emerging research focus in urban studies, is the capability of an urban system to adapt to the uncertainties and disturbances faced by modern cities. Numerical characterization of an urban system’s resilience can be performed with urban resilience indicators. Moreover, as cities evolve with intensive socio-economic interactions, the performances of urban indicators are heavily dependent on the scale of these interactions; these relationships are conceptualized as urban scaling laws. Therefore, this study explores the scaling patterns of urban resilience, analyzing the scaling relationship between different resilience indicators and urban population size, as well as the spatial–temporal evolutions of the scaling patterns. The empirical case is based on 267 prefectural-level cities in China. The results show resilience indicators demonstrate scaling patterns on both spatial and temporal scales. Moreover, the scale-adjusted metropolitan indicator (SAMI) differs ...
Scientifically assessing the economic impact of major public health emergencies, containing their... more Scientifically assessing the economic impact of major public health emergencies, containing their negative effects, and enhancing the resilience of an economy are important national strategic needs. The new coronavirus disease (COVID-19) has, to date, been effectively contained in China, but the threat of imported cases and local risks still exist. The systematic identification of the virus's path of influence and intensity is significant for economic recovery. This study is based on a refined multi-regional general equilibrium analysis model, which measures the economic and industrial impacts at different epidemic risk levels in China and simulates development trends and the degree of damage to industries and the economy under changes to supplies of production materials and product demand. The results show that, at the macroeconomic level, China's GDP will decline about 0.4% to 0.8% compared to normal in 2020, with an average drop of about 2% in short-term consumption, an average drop in employment of about 0.7%, and an average increase in prices of about 0.9%. At the industry level, the epidemic will have the greatest short-term impact on consumer and laborintensive industries. For example, the output value of the service industry will fall 6.3% compared to normal. Looking at the impact of the epidemic on the industrial system, the province most affected by the epidemic is Hubei, which is the only province in China in the level-1 risk category. As the disease spread outward from Hubei, there were clear differences in the main industries that were impacted in different regions. In addition, simulation results of recovery intensity of regional economies under the two epidemic response scenarios of resumption of work and production and active fiscal stimulus policies show that an increase in fiscal stimulus policies produces a 0.3% higher rate of gross regional product growth but it causes commodity prices to rise by about 1.8%. Measures to resume work and production offer a wider scope for industrial recovery.
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Papers by Naliang Guo