Modelling rainfall erosivity for dynamic hillslope erosion estimation in events of wildland fires, snowmelt, and extreme rainfall

Publication Type:
Thesis
Issue Date:
2018
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Rainfall erosivity and soil erosion have being significantly affected by more frequent extreme weather events and ongoing climate change. Projected warmer and drier climate in Australia will change the erosion rates through more intensive storm events, more severe and frequent wildfire and less snowmelt. To estimate the near real-time rainfall erosivity and erosion change, it is essential to link the extreme weather events and hillslope erosion model in response to provide effective ecosystem and environment management. In this study, I selected two case study areas in southeast Australia to assess the effect of extreme weather events on hillslope erosion modelling (e.g. Warrumbungle National Park (WNP) and NSW and ACT Alpine region). Radar rainfall data (1km, 10-min), calibrated by rain gauges rainfall were applied to estimate the near real-time rainfall erosivity on a daily basis. There was a positive correlation between radar-based and gauged rainfall. The highest rainfall erosivity was estimated as 826.76 MJ mm ha-1 hr-1 for a single storm event. The modelled average annual rate of hillslope erosion appears to be declining due to the vegetation recovery after the wildfire. Six extreme rainfall indices (ERIs) were selected to assess the extreme rainfall impact on rainfall erosivity over 60 years. In comparison with the result from Australia Bureau of Meteorology, it is possible to estimate the approximately erosivity value from ERIs especially to where without radar or gauged rainfall data. Snow and temperature projections for the 60 years derived from NARCliM were applied to adjust the snowmelt runoff and rainfall erosivity model during the melting season. Weekly measurements of snow depth and snow water equivalent at three filed sites in the Snowy Mountains were obtained to assess the snowmelt-adjusted rainfall erosivity model. Snowmelt in spring is estimated to increase the rainfall erosivity by 12.95% for baseline. However, the snow impact is projected to be 24.84% for the near future and then less (1.63%) for the fat future due to the projected higher temperature and less snow depth into NARCliM. The erosion amount and change is comprehensively derived from various factors, includes rainfall erosivity, groundcover, slope length and steepness and soil erodibility. These factors always combine and interact to influence and accelerate the mechanism of the erosion process under more frequent and more extreme weather events. The current outcomes would effectively enhance the capability of government, and provide adaptation and mitigation strategies in responding to a changing climate.
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