WATER MODELER: A COMPONENT OF A COASTAL ZONE DECISION SUPPORT SYSTEM TO GENERATE FLOOD-RISK MAPS FROM STORM SURGE EVENTS AND SEA-LEVEL RISE

摘要

This paper outlines a new software tool, Water Modeler, which is a component of a Coastal Zone Decision Support System. The Water Modeler can analyze a time series of water-level records (tide gauge observations) to determine the risk associated with a high water level from a storm surge event or long-term sea-level rise. The new tool has been applied in two case studies in Nova Scotia, Canada, where coastal flood-risk maps have been derived from high-resolution LiDAR digital elevation models. The first case study is for Annapolis Royal on the Bay of Fundy side of the province, while the second looks at the Kingsburg area of Lunenburg County on the Atlantic shore. The Saint John, New Brunswick, and Halifax tide gauge records were used for Annapolis Royal and Kingsburg, respectively, in the Water Modeler to examine the risks of coastal flooding. The Groundhog Day storm of 1976, which caused coastal flooding around the Bay of Fundy, was used as a benchmark for Annapolis Royal. At current rates of sea-level rise, 22 cm/century, the average return period of this water level is 43 years (65 percent probability) and there is a very high probability (99 percent) that it will reoccur within 121 years. If relative sea-level rise rates increase to 80 cm/century from climate change, then the average return period reduces to 23 years, and there is a 99 percent probability of reoccurrence within 55 years. The benchmark storm used from the Halifax water record was Hurricane Juan, which occurred in September 2003. The cumulative flood-level probabilities were calculated for this water level and a return period of 95 years was determined, with an average return period of 52 years (65 percent probability) under current sea-level conditions. The combination of geomatics tools, such as high-resolution LiDAR digital elevation models (DEMs) for coastal flood inundation and the Water Modeler to estimate the associated risk, allows coastal communities to better plan for the future.