Near real-time monitoring of post-fire erosion after storm events: a case study in Warrumbungle National Park, Australia
Xihua Yang A D E , Qinggaozi Zhu B D , Mitch Tulau A , Sally McInnes-Clarke A , Liying Sun C and Xiaoping Zhang D
+ Author Affiliations
- Author Affiliations
A New South Wales Office of Environment and Heritage, PO Box A290, Sydney South, NSW 1232, Australia.
B School of Life Sciences, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia.
C Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, PR China.
D State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Shaanxi, 712100, PR China.
E Corresponding author. Email: xihua.yang@environment.nsw.gov.au
International Journal of Wildland Fire 27(6) 413-424 https://doi.org/10.1071/WF18011
Submitted: 30 January 2018 Accepted: 26 April 2018 Published: 5 June 2018
Abstract
Wildfires in national parks can lead to severe damage to property and infrastructure, and adverse impacts on the environment. This is especially pronounced if wildfires are followed by intense storms, such as the fire in Warrumbungle National Park in New South Wales, Australia, in early 2013. The aims of this study were to develop and validate a methodology to predict erosion risk at near real-time after storm events, and to provide timely information for monitoring of the extent, magnitude and impact of hillslope erosion to assist park management. We integrated weather radar-based estimates of rainfall erosivity with the revised universal soil loss equation (RUSLE) and remote sensing to predict soil loss from individual storm events after the fire. Other RUSLE factors were estimated from high resolution digital elevation models (LS factor), satellite data (C factor) and recent digital soil maps (K factor). The accuracy was assessed against field measurements at twelve soil plots across the Park and regular field survey during the 5-year period after the fire (2013–17). Automated scripts in a geographical information system have been developed to process large quantity spatial data and produce time-series erosion risk maps which show spatial and temporal changes in hillslope erosion and groundcover across the Park at near real time.
Additional keywords: geographic information system, rainfall erosivity, remote sensing, soil loss, weather radar.
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