Liu, X. and Zhang, Z. and McDougall, K. (2011) Characteristic analysis of a flash flood-affected creek catchment using LiDAR-derived DEM. In: 19th International Congress on Modelling and Simulation (MODSIM 2011): Sustaining Our Future: Understanding and Living with Uncertainty, 12-16 Dec 2011, Perth, Australia.
Text (Published Version)
Flooding occurred across a large area of southern and central Queensland in December 2010 and January 2011. Intense rainfall over the Gowrie Creek catchment caused severe flash flooding through the Toowoomba CBD (Central Business District) on the afternoon of Monday, 10 January 2011, taking lives and damaging the community. Flash floods are sudden and unexpected floods that arise from intense rainfall, generally over a small, steep catchment area. Smaller and steeper catchments have shorter critical storm
duration, and they respond more quickly to rainfall events. The resulting flood wave is characterized by very high water flows and velocities and abrupt water level rises, leading to extremely hazardous conditions. Effective flash flood forecasting for specific locations is a big challenge because of the behaviour of intense thunderstorms. A flash flood forecasting and warning system calls for accurate spatial information on catchment characteristics. A high-resolution DEM is a key spatial dataset for the characterization of a catchment to design possible flood mitigation measures. The characteristics of a catchment have a strong influence on its hydrological response. The nature of floods is dependent on both the intensity and duration of the rainfall and the catchment characteristics such as catchment area, drainage patterns and waterway steepness. Therefore, analysis of catchment characteristics is critical for hydrologic modelling and planning for flood risk mitigation. The analysis of catchment characteristics can support hydrological modelling and planning for flood risk mitigation. For example, the shape indices of sub-catchments can be used to compare the hydrological behaviour of different subcatchments. The longitudinal profiles of the creeks illustrate the slope gradients of the waterways. A hypsometric curve for each sub-catchment provides an overall view of the slope of a catchment and is closely related to ground slope characteristics of a catchment. Airborne light detection and ranging (LiDAR), also referred to as airborne laser scanning (ALS), is one of the most effective means of terrain data collection.
Using LiDAR data for generation of DEMs is becoming a standard practice in the spatial science community. This study used airborne LiDAR data to generate a high-resolution DEM for characteristic analysis of Gowrie Creek catchment in Toowoomba, Queensland, Australia, which was affected by a flash flood in January 2011. Drainage networks and sub-catchment boundaries were extracted from LiDAR-derived DEM. Catchment characteristics including sub-catchment areas and shape indices, longitudinal profiles of creeks and hypsometric curves of sub-catchments were calculated and analysed.
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|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Publisher:||Modelling and Simulation Society of Australia and New Zealand Inc.|
|Item Status:||Live Archive|
|Additional Information (displayed to public):||This publication is copyright. It may be reproduced in whole or in part for the purposes of study, research, or review, but is subject to the inclusion of an acknowledgment of the source. Responsibility for the contents of these papers rests upon the authors and not on the Modelling and Simulation Society of Australia and New Zealand Inc.|
|Depositing User:||Dr Xiaoye Liu|
|Faculty / Department / School:||Historic - Faculty of Engineering and Surveying - Department of Surveying and Land Information|
|Date Deposited:||17 Apr 2012 00:30|
|Last Modified:||15 Feb 2015 23:07|
|Uncontrolled Keywords:||flash flood; digital elevation model; DEM; LiDAR; catchment; hydrology; Gowrie Creek; Toowoomba|
|Fields of Research (FoR):||09 Engineering > 0907 Environmental Engineering > 090702 Environmental Engineering Modelling
04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040604 Natural Hazards
09 Engineering > 0909 Geomatic Engineering > 090903 Geospatial Information Systems
|Socio-Economic Objective (SEO):||D Environment > 96 Environment > 9610 Natural Hazards > 961005 Natural Hazards in Fresh, Ground and Surface Water Environments|
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