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theses

Storing woodchips in outdoor piles can have potentially deleterious environmental impacts, including risks from fire and pollution of nearby water resources. Thus, being able to predict leachate quantities and monitor water content within woodchip piles would be advantageous for assessing risk, as well as for developing stormwater management practices for wood recycling operations to follow.
In the first part of this thesis, the leachate generated from three experimental piles (~30 m3) of woodchips ground either once or twice was continuously collected over a period of six months. Transient three-dimensional flow through the experimental piles was simulated using the numerical model HYDRUS 3D in order to quantify leachate generation. The Bayesian Markov Chain Monte Carlo algorithm DREAMZS was used to optimize hydraulic flow parameters for a single porosity (SPM) and dual porosity (DPM) model to predict leachate generation based on the water retention and hydraulic conductivity characteristics of the woodchip materials. Model performance statistics verified that both models adequately predicted 6-hour leachate volumes (Nash-Sutcliffe efficiency index: >0.7; Root mean square error: <27 liters per 6-hr), although the DPM was prone to numerical difficulties. The models are most suitable for predicting leachate produced by storm events with less than 1 cm of rainfall in 6-hr. During more intense rainfalls, leachate generation was systematically under predicted on average by about 20%. This information is important for designing leachate collection and control systems based on different design storm criteria. Additionally, the size and the geometry of the woodchip pile along with the initial moisture content of the woodchips are also likely to influence leachate generation.
Direct knowledge of the water content within woodchip piles is useful for avoiding fire hazards and simulating leachate generation. A reflectometry method was used for estimating volumetric water content (θ) in woodchips taking into consideration their particle size distribution (PSD), temperature (T) and the dielectric permittivity of the dry woodchips plus air. The bulk dielectric permittivity of fine, medium and coarse PSDs were measured from dry to saturated water contents with CS616-L reflectometers at approximately 10°, 24°, 37°, 55° and 70° C. Calibration equations were developed using a multivariate power law function fitted to the data with a hierarchical Bayesian inference procedure. As θ and T increased and PSD became coarser the fitted relationships became more uncertain. Overall the method was most accurate for taking measurements in partially saturated fine woodchip mixtures with median particle diameters smaller than 4 mm and at temperatures between 10° C to 37° C.
Building on the topics explored in this thesis, future research is necessary to engineer an optimal woodchip pile configuration that minimizes the risk of fire and reduces how much leachate can be potentially generated. This information is crucial both from a policy- and practice-based viewpoint.

ETD_10193

M.S.

Includes bibliographical references

doi:10.7282/t3-vsnr-ah22

ETD graduate

The author owns the copyright to this work.