Search

The coincidence of floods and coronavirus disease 2019 (COVID‐19) is a genuine multihazard problem. Since the beginning of 2020, many regions around the World have been experiencing this double hazard of serious flooding and the pandemic. There have been 70 countries with flood events occurring after detection of the country's first COVID‐19 case and hundreds of thousands of people have been evacuated. The main objective of this article is to assess challenges that arise from complex intersections between the threat multipliers and to provide guidance on how to address them effectively. We consider the limitations of our knowledge including "unknown unknowns." During emergency evacuation, practicing social distancing can be very difficult. However, people are going to take action to respond to rising waters, even if it means breaking quarantine. This is an emergency manager's nightmare scenario: two potentially serious emergencies happening at once. During this unprecedented year (2020), we are experiencing one of the most challenging flood seasons we have seen in a while. Practical examples of issues and guides for managing floods and COVID‐19 are presented. We feel that a new approach is needed in dealing with multiple hazards. Our main messages are: a resilience approach is needed whether in response to floods or a pandemic; preparation is vital, in addition to defense; the responsible actors must be prepared with actions plans and command structure, while the general population must be involved in the discussions so that they are aware of the risk and the reasons for the actions they must take. This article is categorized under:Engineering Water > Methods [ABSTRACT FROM AUTHOR]

ABSTRACT The objective of this study is to investigate the vulnerability of different land-cover types to climate change. To this end, land-cover specific temperature change factors are quantified for the southern Saskatchewan region using a novel statistical downscaling model: physical scaling ( SP). SP model considers large-scale climate and regional physical characteristics like land-cover, elevation in its formulation and hence can be used to predict future temperature for different land-cover types under changing large-scale climatic and land-cover conditions. The model is validated by assessing its ability to downscale North American Regional Reanalysis ( NARR) derived surface (skin) temperature from an initial resolution of 32 km to 500 m. The downscaled NARR data are evaluated using a cross-validation approach over the period 2006-2013 with reference to MODerate-resolution Imaging Spectroradiometer ( MODIS) derived surface temperature estimates and satisfactory model performance is obtained (average RMSE = 0.03 K). The validated model is used to predict future surface temperature across the study region. Future land-cover projections are derived by downscaling land-use projections for Representative Concentration Pathways ( RCPs) 2.6 and 8.5 made by integrated assessment models: IMAGE and MESSAGE, respectively. An analysis of land-cover specific temperature changes between historical (2006-2013) and future (2081-2100) timelines indicate variations of up to 2 K between different land-cover classes. Vulnerability pattern of different land-cover classes differ significantly between day- and night-time. Further, variations of upto 1 K in projected changes are observed among different forest cover types. Closed shrubland is obtained as the most vulnerable forest-cover class whereas evergreen broadleaf forest is found to be the least vulnerable. [ABSTRACT FROM AUTHOR]