Infiltration and near surface water flow in seasonally frozen landscapes

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This research program aims to improve our understanding of infiltration and near surface water movement in seasonally frozen ground, in order to better quantify and manage our water resources. The near surface environment is often termed the “critical zone” due to the complex interactions involving water, air, and soil that sustain life. Many critical zone processes are uniquely altered in regions, such as Canada, that experience seasonal freeze-thaw cycles. The ability of water to move into (termed infiltration) and through partially frozen soils is often dramatically altered and difficult to predict. Given that water flow in this zone ultimately governs the magnitude and timing of river flows, groundwater replenishment, and contaminant movement, it is crucial that we understand water movement in frozen landscapes in order to sustainably manage this valuable resource. Novel laboratory and field experiments will fill in key gaps in our understanding of frozen ground hydrology, including the important processes controlling water movement during snowmelt events (both mid-winter and spring melts) and the variability of these processes in space and time. To achieve maximal benefit, the research will focus on poorly understood hydrologic processes, such as rapid water movement during ground thaw and complex feedback mechanisms in different land cover and terrain settings. The scientific knowledge gained will be used to build more realistic numerical (computer) models for quantifying water movement in the critical zone. The models, developed using leading edge numerical tools, will be tested against the newly acquired data to ensure realistic predictions. The research will have immediate application for evaluating hydrologic flows in the vast regions where runoff and groundwater recharge are dominated by snowmelt. Water managers and users will benefit from new tools for predicting surface and subsurface flows (e.g., flood forecasting, groundwater recharge), enabling more sustainable management of water resources. In the long term, the findings will generate more accurate hydrologic models, leading to better prediction and mitigation of adverse impacts from changing climate and land-use in vulnerable, seasonally frozen landscapes.