Abstract
Abstract. In New Brunswick flooding occurs typically during the spring freshet, though, in recent years, midwinter thaws have led to flooding in January or February. Municipalities are therefore facing a pressing need to perform risk assessments in order to identify communities at risk of flooding. In addition to the identification of communities at risk, quantitative measures of potential structural damage and societal losses are necessary for these identified communities. Furthermore, tools which allow for analysis and processing of possible mitigation plans are needed. Natural Resources Canada is in the process of adapting Hazus-MH to respond to the need for risk management. This requires extensive data from a variety of municipal, provincial, and national agencies in order to provide valid estimates. The aim is to establish a data warehouse to store relevant flood prediction data which may be accessed thru Hazus. Additionally, this data warehouse will contain tools for On-Line Analytical Processing (OLAP) and knowledge discovery to quantitatively determine areas at risk and discover unexpected dependencies between datasets. The third application of the data warehouse is to provide data for online visualization capabilities: web-based thematic maps of Hazus results, historical flood visualizations, and mitigation tools; thus making flood hazard information and tools more accessible to emergency responders, planners, and residents. This paper represents the first step of the process: locating and collecting the appropriate datasets.
Highlights
The data warehouses (DW) will support multiple operations: (a) Hazus users will be able to access this data for loss estimation and export Hazus results; (b) discover unexpected dependencies and historical correlations of flood prone areas thru On-Line Analytical Processing (OLAP) and knowledge discovery; (c) visualization of flood risk areas through web maps
While other loss estimation software has been limited to repair and replacement costs, Hazus extends its output to include consequential losses (FEMA, 2009)
3.1 Canadian Adaption In August of 2011, the Hazus adaption and co-development agreement was signed by Natural Resources Canada (NRCAN), Defence Research and Development Canada (DRDC), and Federal Emergency Management Agency (FEMA)
Summary
In New Brunswick (NB) the chance of flooding due to snow melt, ice jams, and heavy rainstorms (Environment Canada, 2013) is a concern as many residential areas and extensive infrastructure have been developed close to rivers. Effects of changing weather patterns in New Brunswick include, increasing frequency of winter thaws, intense precipitation, and rising sea level (approximately 30 cm over the past 100 years, and by 2100 a further rise of 50-60 cm is forecasted) (GNB, 2007). Given this variability in weather patterns it is becoming increasingly important for municipal and other levels of government to perform accurate risk-assessments in flood prone and coastal communities. To identify flood risk areas, local inventory data and flood hazard information must be input to Hazus (FEMA, 2009). The DW will support multiple operations: (a) Hazus users will be able to access this data for loss estimation and export Hazus results; (b) discover unexpected dependencies and historical correlations of flood prone areas thru On-Line Analytical Processing (OLAP) and knowledge discovery; (c) visualization of flood risk areas through web maps
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