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Prediction of Rainfall Runoff for Soil Cover Modelling
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- Author / Creator
- Jubinville, Sarah K.
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Surface runoff can be the largest component of the surface water budget that controls the quantity of precipitation that could infiltrate through a soil cover into underlying waste material. Site-specific models are routinely used to predict infiltration; however, the direct measurement of runoff that is required to properly calibrate the model is almost never performed. To date, there does not appear to be a proven reliable procedure for predicting surface runoff based on measurable properties at the soil surface.
This thesis presents a field and laboratory program to characterize the hydraulic properties of a compacted waste rock and overburden soil cover at the Savage River Mine in Australia. A physically based one-dimensional model was developed for predicting surface runoff using the measured rainfall intensity and surface saturated hydraulic conductivity. Runoff predictions from the proposed Savage River Runoff Model (SRR Model) and the SoilCover computer model are compared to measured runoff quantities. Both models are shown to be sensitive to the resolution of the rainfall data used as input. Runoff predictions from both models were also found to vary considerably within the natural variability of surface saturated hydraulic conductivity. In summary, it was concluded that both models are capable of predicting surface runoff volumes within 4%, provided engineering judgment is used when inputting rainfall and measured soil properties. -
- Graduation date
- Spring 2013
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- Type of Item
- Thesis
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- Degree
- Master of Science
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- License
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.