Coupled cryo-hydrogeological modelling of permafrost dynamics at Umiujaq, Quebec, Canada

© Sophie Dagenais, 2018

Coupled cryo-hydrogeological modelling of permafrost

dynamics at Umiujaq, Quebec, Canada

Mémoire

Sophie Dagenais

Maîtrise interuniversitaire en sciences de la Terre - avec mémoire

Maître ès sciences (M. Sc.)

Coupled Cryo-hydrogeological Modelling of

Permafrost Dynamics at Umiujaq, Québec, Canada

Mémoire

Sophie Dagenais

Sous la direction de:

John Molson, directeur de recherche

Jean-Michel Lemieux, codirecteur de recherche

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Résumé

Un modèle numérique bidimensionnel a été développé afin d’évaluer l’impact de l’écoulement d’eau souterraine sur la dynamique du pergélisol dans un contexte de réchauffement climatique au Québec nordique. Le modèle conceptuel développé concerne une butte de pergélisol située dans la zone de pergélisol discontinu à proximité de la communauté Inuite d’Umiujaq, Nunavik, Québec. Le pergélisol s’est mis en place dans une unité gélive de silts marins qui se trouve au-dessus de deux unités de sédiments grossiers de sable et de gravier d’origine fluvio-glaciaire et glaciaire qui forment un aquifère confiné par l’unité de silts et le pergélisol où il y a un écoulement d’eau souterraine. Le code numérique HEATFLOW a été utilisé pour simuler l’écoulement d’eau souterraine couplé à la transmission de chaleur par conduction et advection le long d’une coupe 2D orientée dans la direction de l’écoulement de l’eau souterraine au droit de la butte de pergélisol étudiée. En premier lieu, le modèle a été étalonné manuellement à partir de profils de température mesurés dans la butte au cours des 10 dernières années à l’aide de câbles à thermistances et en tenant compte des flux de chaleur mesurés près de la surface du sol. En second lieu, une deuxième simulation a été réalisée en ne considérant que la transmission de chaleur par conduction et en négligeant ainsi l’écoulement d’eau souterraine. La comparaison entre ces deux simulations révèle le rôle important de l’écoulement d’eau souterraine sur la dynamique du pergélisol à Umiujaq. En effet, cet écoulement transporte l’eau plus chaude des zones de recharge vers l’aquifère confiné, ce qui contribue à réchauffer significativement le système en comparaison avec le cas sans écoulement. Une couche de pergélisol beaucoup plus mince est simulée lorsque l’écoulement d’eau souterraine est considéré dans la modélisation numérique. En outre, selon les résultats des simulations, l’énergie se dissipe le long de la ligne d’écoulement d’eau souterraine sous la base du pergélisol ce qui réduit sensiblement les températures du sol et de surface à proximité des zones de résurgence de l’eau souterraine le long d’un ruisseau en comparaison avec les zones de recharge. Finalement, en troisième lieu, le comportement futur du système simulé sous l’effet des changements climatiques est ensuite prédit en générant un scénario de réchauffement climatique selon une augmentation constante de la température de l’air et des précipitations. Les résultats des simulations suggèrent une dégradation du pergélisol par la base à un taux de 80 cm par année, et par le toit à un taux de 12 cm par année, jusqu’à la disparition complète du pergélisol dans le site d’étude d’ici 2040.

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Abstract

A 2D numerical model has been developed to assess the impacts of groundwater flow on permafrost dynamics under a warming climate in northern Québec. The conceptual model developed herein focuses on a small permafrost mound located in the discontinuous permafrost zone near the Inuit community of Umiujaq, Nunavik, Québec. At the study site, permafrost is found in marine silt overlying a deep confined sand and gravel aquifer with active groundwater flow. To better understand the cryo-hydrogeological system, the HEATFLOW numerical code was used to simulate coupled groundwater flow and heat transport by conduction and advection along a 2D cross-section through the permafrost mound and oriented along the assumed direction of groundwater flow. The model was first calibrated manually using temperature profiles in the permafrost mound measured along thermistor cables over the past 10 years and using observed heat fluxes near the ground surface. A second simulation was then performed assuming only conductive heat transfer and neglecting groundwater flow. A comparison between both simulations reveals the important role of groundwater flow on permafrost dynamics at the Umiujaq site. As groundwater flow brings warmer water from recharge areas into the deep confined aquifer, it contributes significantly to warming of the system relative to conduction alone, and significantly decreases permafrost thickness. However, the simulation showed that thermal energy is also lost along the flowpath below the permafrost base which induces a cooling in the discharge areas in comparison to the recharge areas. The future system behavior is then predicted by taking into account a climate change scenario based on increases in temperature and precipitation. The predictive simulation suggests that permafrost will thaw from the base at a rate of about 80 cm per year, and from the permafrost table at a rate of 12 cm per year, until completely thawed by about 2040.

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Contents

Résumé ... iii

Abstract ... iv

List of tables... vii

List of figures ... viii

Acknowledgments ... xi

Avant-Propos ... xiii

1 Introduction ... 2

1.1 General context ... 2

1.1.1 Review of current literature ... 2

1.1.2 Motivation and Objectives ... 5

1.1.3 Thesis structure ... 6

1.2 Study site ... 7

1.2.1 Location ... 7

1.2.2 Geology and hydrogeology ... 7

1.2.3 Climate ... 10

1.3 Methodology ... 10

1.3.1 Data ... 10

1.3.2 Conceptual model ... 22

2 Numerical model (Taken from Dagenais et al., 2018) ... 29

Résumé ... 30

Abstract ... 31

2.1 Introduction ... 32

2.2 Study site ... 34

2.3 Meteorological and cryo-hydrogeological conditions ... 36

2.3.1 Meteorological data ... 36

2.3.2 Field instrumentation and data ... 37

2.3.3 Hydrogeological data ... 40

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2.4.1 Theoretical approach ... 40

2.4.2 Modelling strategy ... 42

2.5 Conceptual and numerical site model ... 42

2.5.1 Physical system ... 42

2.5.2 Boundary conditions ... 45

2.5.3 Initial conditions ... 47

2.6 Numerical Simulations... 48

2.6.1 Model Calibration ... 48

2.6.2 Sensitivity analysis: Conductive heat transport ... 55

2.6.3 Predicted permafrost thaw under future climate change... 58

2.7 Conclusions ... 60

3 General Conclusions ... 62

Bibliography ... 66

Appendix A: Coupled cryo-hydrogeological modelling of permafrost degradation at Umiujaq, Quebec Canada (Taken from Dagenais et al., 2017) ... 72

Appendix B: Literature review ... 81

Appendix C: Instrumentation and vegetation of the Tasiapik valley watershed ... 84

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List of tables

Table 1.1: Darcy fluxes assessed from hydraulic gradients and the FVPDM method for

Sites 2, 5, and 3. 13

Table 1.2: Thermal conductivities measured with the thermal needle probe, water

content and porosity of three soil samples. 15

Table 1.3: Assumed recharge rates according to the vegetation type and temperature difference between recharge water (Tq) and air temperature (Tair). 28

Table 2.1: Site instrumentation and measured variables. 38

Table 2.2: Physical and thermal properties of the different layers of the model (see

Figure 2.1 and Figure 2.4 for layer stratigraphy). 43

Table 2.3: Assumed parameter values for the Umiujaq model. 44

Table 2.4: Heat exchange layer parameters according to topography and vegetation type. Topography symbols represent local high or local low topography along the

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List of figures

Figure 1.1: Umiujaq site location on Hudson Bay and permafrost distribution in Nunavik, Quebec, Canada (adapted from Allard and Lemay 2012). Interpolated depth of the 0°C isotherm is from Lemieux et al. (2008). 8 Figure 1.2: Tasiapik valley watershed, location of groundwater wells from the Immatsiak

network and location of the cross-sections A-A’ (well axis) and B-B’ (numerical model). The background image is from Google Earth 2018. 8 Figure 1.3: Cryo-hydrostratigraphic interpretative cross-section along the Tasiapik valley

watershed (adapted from Fortier et. al. 2014). Note the horizontal scale of

1:10,000 and vertical exaggeration of 1:10. 9

Figure 1.4: Tasiapik valley watershed, permafrost mound and location of the instruments on the mound. Data from instruments that have been faded out on the mound picture are not presented in the current document. 11 Figure 1.5: Hydraulic heads in the groundwater wells at Site 3 and Site 5, from 2012 to

2017 (from the Solinst probes and manual measurements), and monthly

precipitation measured at the SILA station. 12

Figure 1.6: Monthly recharge measured by Murray (2016) at Site 2 for the year 2014-2015, for ground surfaces dominated by shrubs, spruce and lichen. 13 Figure 1.7: Subsurface temperatures measured using thermistor cables from 2002 to

2017 for the mid-winter period (January, February, March) in the left graphs and for the mid-summer period (July, August, September) in the right graphs, averaged over two years, located a) at the edge of the mound, and b) at the

center of the mound (see locations in Figure 1.4). 16

Figure 1.8: Unfrozen water content and temperature in the unsaturated zone in summer and winter 2015 and 2017 from the moisture content and temperature monitoring arrays with a) and b) Water content and c) and d) Temperature, at the side of the mound (left column) and at the center of the mound (right

column). 17

Figure 1.9: Water content as a function of time (2014 – 2017) from the moisture and temperature probes at 0.1 m and 1 m depths, at a) the center of the mound,

and b) the side of the mound. 19

Figure 1.10: Photos of the permafrost mound from the Reconyx camera, and location of the snow poles a) in July 2017, and b) in February 2017. 20 Figure 1.11: Snowpack thickness on the permafrost mound in 2014-2015 for the snow

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Figure 1.12: Heat flux measured at the center and the side of the mound at 8 cm depth

from 2014 to 2015. 21

Figure 1.13: Temperatures at 10 cm depth from the HOBO temperature probes located at the center and beside the mound between 2014 and 2017 22 Figure 1.14: Conceptualized flow system along the cross-section B-B’ (Figure 1.2). 23 Figure 1.15: Watertable heads along the cuesta flowline calculated from the Dupuit

equation 24

Figure 1.16: Input parameters of the heat transfer layer shown for the mid-summer and mid-winter periods with a) layer thickness and zone delimitation and b) heat

flux and recharge rates in mm/year 25

Figure 1.17: Mean annual air temperatures recorded at Kuujjuarapik and Kuujjuaq and estimated temperatures at Umiujaq. The solid lines represent a 5-year moving average to reduce the variability and highlight the trends while the dots represent the mean annual air temperatures. The grey zones represent the

warming periods. 27

Figure 2.1: Location of Umiujaq along the eastern coast of Hudson Bay and permafrost distribution in Nunavik, Québec, Canada (adapted from Allard and Lemay 2012). Interpolated depth of the 0°C isotherm is from Lemieux et al. (2008). 35 Figure 2.2: Tasiapik Valley watershed and 2D cryo-hydrogeologic model cross-section 35 Figure 2.3: Mean annual air temperatures (MAATs) at Kujjuarapik, Kujjuaq and

Umiujaq, according to available data since 1926. The thick solid lines correspond to the five-year running average for each data set. The grey zones represent warming periods before and after a cooling period from 1950 to

1993. 37

Figure 2.4: a) Instrumentation of the permafrost mound (not to scale). b) Observed temperatures from the central thermistor cable (cable B) over time and MAATs from the Umiujaq-A station. The dashed lines are the interpolated depth of the permafrost table and extrapolated depth of the permafrost base.

39 Figure 2.5: Temperature-dependent functions assumed in the model for unfrozen water

saturation (Wu) and relative permeability (kr). For simplicity, the kr function

is shown only for a porosity of 0.35 (coarse sand). 45

Figure 2.6: Conceptualization of the 2D cryo-hydrogeological model showing a) groundwater flow boundary conditions and the intrinsic hydraulic conductivity distribution (unfrozen state; hydraulic conductivities vary with temperature; see Figure 2.5 for kr), and b) heat transport boundary conditions

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Figure 2.7: Field data (solid colored lines) and simulation results (dashed lines) at the side (left column) and at the center of the permafrost mound (right column), showing: a) Subsurface temperatures measured in the field (thermistor cables A on left and B on right; see Figure 2.4a for location) averaged on a four-year basis for the mid-summer period (July, August, September) and model results averaged for the same mid-summer period from 2014-2017, b) Unfrozen water content (m3_/m3_{) at a depth of 0.1 m, c) Ground temperatures at a depth of 0.1 m, and}

d) Heat flux at a depth of 0.08 m. 50

Figure 2.8: Simulated flow field at year 2017 from the calibrated model (Scenario 1) with coupled groundwater flow and heat transport: a) Hydraulic heads and

streamtraces, b) Velocity magnitudes. 52

Figure 2.9: Simulated ground temperatures (in mid-summers of 1950, 1993, and 2017) as a function of depth and distance for: a) Scenario 1 with coupled groundwater flow and advective-conductive heat transport (the calibrated model), and b) Scenario 2 taking into account heat transfer by conduction without groundwater flow. The lower three figures are magnified to focus on the permafrost mound located from 300 to 350 m. The 0 °C isotherm is

identified for comparison purposes. 53

Figure 2.10: Simulated ground temperatures in the central permafrost mound (at 337.5 m; see Profile B in Figure 2.4a and Figure 2.7b) as a function of depth and time: a) Scenario 1 with groundwater flow and advective-conductive heat transport,

and b) Scenario 2 with thermal conduction only. 55

Figure 2.11: Simulated temperature distribution in mid-summer from 2017-2040 under the predictive climate change scenario and including groundwater flow. The simulation begins in 2017 with the calibrated advective-conductive heat

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Acknowledgments

I would like to express my sincere gratitude to all those persons and organizations involved in my research project for their support:

 John Molson, my supervisor, for all technical and moral support during the project. I would like to thank him particularly for his remarkable availability and his receptiveness to all my ideas and initiatives. I appreciated his way of seeing always more solutions than problems, giving me back the necessary motivation in critical stages of the project. I would also like to thank him for providing me the amazing opportunity to present my work in Paris to the Interfrost benchmark meeting. More than all, John has put his trust in me from the beginning and allowed me to work in the most optimal conditions, almost making the other students jealous!

 Jean-Michel Lemieux, my co-director, for his valuable advice and guidance throughout the whole process. I thank him for offering me a stimulating research environment, by questioning my work and always providing new motivating challenges. I’ve gained a lot of experience and valuable knowledge from him, both in the field and in research, and in the academic world.

 Richard Fortier, for his notable experience and rigor, which helped this project (and myself) to stay on the right track. His passion for geophysics and devotion for the Umiujaq project were truly inspiring and motivated me to give my best at every stage of the process. Throughout his thorough reviews and detailed comments, Richard pushed me to deliver high quality material and taught me the importance to always make my work «bullet proof ».

 René Therrien, for all the effort he put into the Umiujaq project and for reviewing my papers when needed. I’m also grateful to him for having so many international connections, which gave me the opportunity to connect with students from all over the globe and put life in our office.

 The local Inuit community, especially the members including the president Ernest Tumic of the Anniturvik landholding corporation of Umiujaq, for giving us access to their land during the field experiments, and to the members of Park Tursujuk for their cooperation.

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 Pierre Therrien for all the technical support he provided, his availability and ability to resolve all my technical problems with a touch of humor. He taught me that not only permafrost can be «Deep Freezed».

 Jasmin Raymond for accepting to review this thesis, and for providing me access to the K2D pro thermal conductivity needle probe. A special thanks to his student Maria Isabelle for supervising me during the experiments at INRS-ETE.

 All my field partners: Renaud Murray, for meticulously transferring his knowledge about the instruments and the study site, Marion Cochand for her great company in the bushes with the mosquitos, Pierre Jamin for his constant cheerfulness and creativity during those long days spent on the permafrost mound and Marie-Catherine Talbot Poulin for her involvement in the campaign logistics.

 My office colleagues: Vinicius for making the working climate more enjoyable and for keeping alive all our plants, Jonathan Fortin for putting at our disposal a coffee machine and popcorn machine, Masoumeh Parkhizar for the great discussions we had between simulations.

 Other students involved in the project, including Philippe Fortier for the detailed analysis of the snow pole photos to extract snow depth data, Britt Albers for the work in progress using my model and the general interest put into my project.

My project was financially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), through a CGS M scholarship, through a Strategic Grant in partnership with the Ministère du Développement Durable, de l’Environnement et la Lutte contre les Changements Climatiques (MDDELCC) of Québec, and through a Discovery Grant to Dr. J. Molson. The northern scientific training program (NSTP) also financed part of the costs for my field work at Umiujaq in 2016 and 2017. The financial and logistical support of the Centre d’études nordiques, Université Laval, and especially its Director Dr. Najat Bhiry, is also greatly appreciated.

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Avant-Propos

This Master’s thesis includes 3 chapters. Chapter 2 of this Master’s thesis is a manuscript in the process of submission to Hydrogeology Journal of which I am the first and principal author. Since the paper content might be modified or updated during the submission process, referring to the final published version is thus recommended. My research project director Dr. John Molson and co-director Dr. Jean-Michel Lemieux are co-authors of this paper, as are professors Dr. Richard Fortier and Dr. René Therrien. I wrote the entire first draft of the paper and made all corrections and improvements in subsequent drafts. I also developed the numerical site model of coupled groundwater flow and heat transfer in a permafrost environment, which is the main subject of the study. Most of the data used for my research was collected at the study site near Umiujaq, Nunavik, during field campaigns in the summers of 2014-2017. With help from others, I collected data myself on the site during the summers of 2016 and 2017. Dr. Richard Fortier was the main investigator and organiser of these field campaigns with the help of Dr. Jean-Michel Lemieux. Dr. John Molson provided valuable support throughout the research period and was the principal reviewer of the paper and thesis. As co-authors, Dr. Jean-Michel Lemieux, Dr. Richard Fortier and Dr. René Therrien also reviewed the manuscript and provided valuable feedback. A paper presented at the 2017 Canadian Geotechnical Society-IAH conference in Ottawa (Dagenais et al., 2017) is included in Appendix A.

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1 Introduction

In the context of the Quebec Government’s Climate Change Action Plan (2006-2012), the Ministère du Développement Durable, de l’Environnement et de la Lutte contre les Changements Climatiques (MDDELCC) of Québec has developed a Groundwater Monitoring Network (RSESQ) to investigate the impact of climate change on groundwater resources. As part of this initiative, a group of researchers from Université Laval in partnership with the Centre d’études nordiques (CEN) has been mandated to develop and maintain a sub-network of the RSESQ in northern Quebec where climate change impacts are occurring at a faster rate than in the south. A portion of this network, called Immatsiak, was implemented in 2012 near the Inuit village of Umiujaq along the east shore of Hudson Bay. Following the deployment of the Immatsiak network, researchers from Université Laval received a Strategic Grant in 2013 from the Natural Sciences and Engineering Research Council of Canada (NSERC) to further investigate the impacts of climate change on groundwater in the north. The main hypothesis of this major research project is that the water released from permafrost thaw, and subsequent increased aquifer recharge, could lead to a new resource of drinking water for northern communities and growing industries in the north, as groundwater is generally safer and more sustainable than surface water from rivers and lakes. The main research goal is to evaluate the present and future impacts of climate change on the groundwater system near Umiujaq and assess the potential of using groundwater as a new reliable resource of drinking water. The present thesis contributes to this broader project and through numerical modelling provides insights into the interaction between groundwater flow and permafrost dynamics.

1.1 General context

1.1.1 Review of current literature

Permafrost covers more than half of Canada’s territory, with depths varying from a few meters to a kilometer in the most northern areas (Zhang et. al., 2006). Considering the recent trend of global warming as observed at high latitudes, permafrost is currently degrading (Intergovernmental Panel on Climate Change IPCC, 2013), particularly in zones where permafrost is thinner and where ground temperatures are closer to 0 degrees (Sjöberg et al., 2015). Permafrost degradation can significantly modify hydrological, thermal and ecosystem dynamics at local and regional scales in northern regions. Considering observed permafrost thaw over the last few decades and its related impacts, there has

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been a renewed interest in cryo-hydrogeological modelling. Until recently, permafrost degradation has been attributed to vertical conduction-dominated heat transfer, where ground temperatures are assumed to be controlled by surface temperature variations and the geothermal gradient. Active groundwater flow, however, can induce heat transfer by advection which can significantly modify the thermal regime in an otherwise conduction-dominated system (Kurylyk et al, 2014a).

Recent developments in coupled groundwater flow and heat transport models have allowed assessment of the role of groundwater flow in permafrost dynamics. Moreover, new insights have been gained into the potential impacts on sub-permafrost thaw in areas of high groundwater flow rates (Kurylyk et al., 2016). However, most recent cryo-hydrogeological studies have mainly focussed on changes in active layer thickness, groundwater discharge and on the general hydrogeological regime (Evans and Ge, 2017; Painter et al., 2016; Atchley et al., 2016; Frederick and Buffet, 2015; Jiang et al., 2012). Only a few studies have assessed the impact of sub-permafrost groundwater flow on permafrost thaw and even fewer have revealed the relative importance of advective heating relative to conduction alone. The most recent studies are briefly reviewed herein while a broader inventory is provided in Appendix B.

Rowland et al. (2011) studied the effect of groundwater flow through a high permeability gravel aquifer on sub-lake talik development using the 2D ARCHY model for coupled groundwater flow and heat transport. They found that it takes about 40% less time for permafrost to thaw under advective/conductive heat transfer versus conduction alone.

Mackenzie and Voss (2013) used the SUTRA-ICE model to investigate the contribution of groundwater flow on permafrost dynamics in an idealized continuous permafrost environment. According to their simulation results, advective heat flux accelerates thaw from both the permafrost table and base by a factor of 3 compared to conduction alone. They suggested that permafrost degradation contributes to enhancing groundwater flow, which acts as a positive feedback for further permafrost thaw. Thawing is more significant closer to recharge zones, and the contribution of advective heat transport decreases as groundwater cools along the flowpath towards discharge areas.

Wellman et al. (2013) used the SUTRA-ICE model to simulate sub-lake talik development at a hypothetical site of thick discontinuous permafrost overlying permeable sediments (K≈510-3 _{to 510}

-4

4 _{m/s). They found that once an open talik develops, sub-lake groundwater flow increases significantly,}

enhancing the permafrost thaw rate due to advection and contributing to lateral expansion of the talik. Taliks were estimated to develop more than twice as fast with groundwater flow recharging or discharging through the lake.

Sjoberg et al. (2016) employed the Artic Terrestrial Simulator (ATS) model to understand the importance of groundwater flow on permafrost dynamics in sporadic permafrost environments, using data from a subarctic fen in northern Sweden. They found that permafrost thaw was strongly influenced by lateral groundwater flow in the peat and sand units (K≈510-3 _{to 510}-5 _{m/s), especially}

during spring when hydraulic gradients were higher due to snowmelt and thawing of the active layer.

Luethi et al. (2016) investigated the role of non-conductive heat flux on intra-permafrost talik formation at the Ritigraben rock glacier in the Swiss Alps. Using a 1D snowpack model, they found that a contribution of advective heating by infiltrating water from snowmelt and rainfall, simulated as a heat source, was needed to reproduce observed talik formation at their field site.

On the other hand, a few studies have led to the conclusion that in some cases the contribution of groundwater flow to permafrost thaw is not significant. For instance, Bense et al. (2012) used the 2D numerical finite-element model FLEXPDE to simulate long-term permafrost degradation in an idealized sedimentary basin (K≈ 810-7 _{to 810}-9 _{m/s) under a warming climate, in which groundwater}

flow is driven by topography. They found that advective heat flux induced by groundwater circulation did not contribute to accelerate permafrost degradation, unless extremely high and unrealistic flow rates were considered.

Kurylyk et al. (2016) used SUTRA to investigate the impact of groundwater flow on multi-decadal lateral permafrost thaw in a peat-wetland complex in the Northwest Territories, Canada. Surface processes modeled in 1D with NEST were applied as the upper boundary condition of the 3D coupled subsurface flow and heat transport model. At this site, groundwater flow occurred in a layer of silty clay (K=110-10 _{m/s) beside and below permafrost units which were overlaid by a 3 m thick organic}

layer. They concluded that this low-permeability silt-clay unit impedes groundwater flow thus limiting its contribution to permafrost thaw.

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However, Bense et al.(2012) and Kurylik et al. (2016) have suggested that the contribution of heat advection could be important in regions where recharge is not limited to rainfall, where groundwater flow is strongly focussed (high gradients and/or soil permeability) or where geothermal heat flow anomalies occur. The effect of advective heat transfer could be even more important in discontinuous or sporadic permafrost areas since these environments are particularly vulnerable to climate warming, and where the sporadic permafrost is warmer and thinner than continuous permafrost (McClymont et al., 2013; Sjöberg et al., 2015; Kurylyk et al., 2016).

In addition to thermal conduction, when groundwater flow is significant, the energy required for permafrost thaw comes either from warm recharge water or deep geothermally warmed water (Mackenzie and Voss, 2013). Thus, groundwater flow can have an even greater impact on permafrost evolution close to recharge areas where relatively warm water is flowing from the surface towards permafrost units (Mackenzie and Voss, 2013).

1.1.2 Motivation and Objectives

Recent studies have revealed the potential contribution of groundwater flow to permafrost thaw due to transfer of heat by advection. Considering the current trend in climate warming, including faster thaw rates in northern areas, release of meltwater from permafrost bodies will also enhance groundwater flow, acting as a positive feedback to permafrost degradation. Understanding the role of groundwater flow in permafrost dynamics is thus crucial to help predict thaw rates and future behavior of permafrost under a warming climate.

Despite the recent advances in cryo-hydrogeological modelling, there is still a need to improve current models. In particular, most research to date has been focussed on the impacts of groundwater flow in the active layer, while new questions have arisen regarding potential impacts of groundwater flow on sub-permafrost thaw in areas with high groundwater flow. Also, most studies have been based on idealized field conditions that may not accurately represent local thermal and hydrogeological conditions and properties. The importance of integrating site-specific surface and subsurface thermal and hydrological properties for modelling the thermal regime of shallow and deep permafrost under a warming climate has been identified by Rasmussen (2018). Sites located in the discontinuous and sporadic permafrost zones are of particular interest because they are more vulnerable to increases in

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air temperatures. Another limitation of current studies concerns the integration of surface processes into models of the subsurface thermal regime. Indeed, there is a need for models to more rigorously account for surface insulation due to snow cover and vegetation patterns (Mackenzie and Voss 2013; Kurylyk et al. 2014a; Atchley et al., 2016).

Therefore, the main objective of this project is to better understand the importance of groundwater flow on permafrost degradation by developing a numerical model of fully coupled groundwater flow and heat transfer by conduction and advection. This new insight will be based on field observations of an ice-rich permafrost mound near the Inuit community of Umiujaq, in northern Quebec, Canada. More specifically, this study focuses on permafrost dynamics at the scale of a single permafrost mound located in the discontinuous permafrost zone.

The secondary objectives of this study include:

1. Investigating the role of groundwater flow on permafrost thaw from both the permafrost table and base.

2. Integrating thermal and hydrological data and field observations to increase the accuracy of permafrost degradation predictions.

3. Improving the coupling of surface processes (snow, vegetation, air/ground heat transfer) with the subsurface regime.

1.1.3 Thesis structure

The following part of Chapter 1 describes the study site and presents details concerning the methodology, including a description of the relevant field data and their integration into the model. The second chapter takes the form of a manuscript from Dagenais et al. to be submitted to Hydrogeology Journal:

Dagenais S, Molson J, Lemieux J-M, Fortier R, Therrien R. (2018). Coupled cryo-hydrogeological modelling of permafrost dynamics at Umiujaq, Quebec, Canada, In submission: Hydrogeology Journal.

In Chapter 2, the numerical model is described in detail and the main results and conclusions are provided. The results are based on three different scenarios. The first (calibrated) scenario is used to

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investigate the current thermal regime of permafrost at the study site, simulating the system with coupled groundwater flow and heat transport by conduction and advection. The second scenario is otherwise identical but considers a conduction-only (no groundwater flow) case. For the third scenario, predictions are made on the future behavior of permafrost under a constant increase in air temperature and precipitation, based on predictions of increased air temperature and precipitation from the ArcticNet IRIS (Integrated Regional Impact Study; Allard and Lemay, 2012) for the Umiujaq region. In the third and final chapter, Chapter 3, the research findings are summarized and general recommendations for future studies are formulated.

1.2 Study site

1.2.1 Location

The study site is located near the Inuit community of Umiujaq located just above the 56th _{parallel along}

the eastern coast of Hudson Bay (Figure 1.1). The site lies at the boundary between the discontinuous but widespread permafrost zone and the discontinuous but scattered zone. The field investigations were carried out in a small 2 km2 _{watershed in the Tasiapik Valley, delimited on the west side by a}

cuesta ridge and on the east side by the Umiujaq Hill (Figure 1.2). The valley is drained by a small stream that flows into Tasiujaq Lake. Ice-rich permafrost is found throughout the valley as small mounds called lithalsas, which are delineated in Figure 1.2. A total of nine groundwater wells located at seven different sites, which form part of the Immatsiak network, are distributed along the watershed’s north-south axis.

1.2.2 Geology and hydrogeology

At the end of the Wisconsinian period (~7600-7300 years ago), the Laurentide Ice-sheet covering North America had almost completely disappeared, causing bedrock erosion along weaknesses which, in the Umiujaq area, formed a landscape of valleys surrounded by cuestas culminating up to 250 m in height, as observed today. As the glacier retreated, all land below 270 m was submerged by the Tyrell Sea, connecting Lake Tasiujaq with Hudson Bay. Over the years, the Tyrell Sea deposited fine-grained deep sea sediments above glacial and fluvio-glacial coarse-grained sediments overlying the bedrock. During the period of Quaternary glacio-isostatic rebound, the land gradually emerged, deposits were eroded forming spurs and gullies, and vegetation spread over the land surface.

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Figure 1.1: Umiujaq site location on Hudson Bay and permafrost distribution in Nunavik, Quebec, Canada (adapted from Allard and Lemay 2012). Interpolated depth of the 0°C isotherm is from Lemieux et al. (2008).

Figure 1.2: Tasiapik valley watershed, location of groundwater wells from the Immatsiak network and location of the cross-sections A-A’ (well axis) and B-B’ (numerical model). The background image is from Google Earth 2018.

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Permafrost developed in frost-susceptible deposits newly exposed to the cold climate (Fortier et. al., 2018), preferentially in zones of local high topography compared to those of low topography which remained more insulated from cold due to vegetation cover and snow accumulation. The topography of these ice-rich periglacial mounds is defined by initial erosion and further frost heaving due to the formation of segregated ice by cryosuction (Allard and Seguin, 1987). Today, permafrost mounds in the valley reach an elevation of between three to five meters above ground. A 2D cross-section extending from the north to south end of the watershed (orange line in Figure 1.2).

The bedrock is formed of arenites and arkosites of the Pachi Formation and subaerian basaltic flows of the Persillon formation. The bedrock is overlaid by 10-30 m of coarse sand and gravel forming a deep aquifer. In the lower part of the valley, the aquifer becomes confined due to the presence of a 20 meter thick overlying marine silt unit forming an aquitard. A surficial sand layer allows water runoff on top of the permafrost and silt unit, forming a shallow aquifer that completely drains during winter.

Figure 1.3: Cryo-hydrostratigraphic interpretative cross-section along the Tasiapik valley watershed (adapted from Fortier et. al. 2014). Note the horizontal scale of 1:10,000 and vertical exaggeration of 1:10.

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1.2.3 Climate

The local climate at Umiujaq is subarctic and characterized by long cold winters, short cool summers, and relatively low humidity and precipitation. Temperatures generally vary between 20°C in the summer and -30°C in winter. The watershed is located at the boundary separating shrub tundra and forest tundra. Lichen is present in areas of higher topography, such as permafrost mounds and well-drained terrain, while depressions are more commonly filled with shrubs. Mean annual precipitation measured between 2013 and 2016 is about 760 mm/year (Lemieux et al. 2018).

1.3 Methodology

The Umiujaq study site is now characterized by a wide variety of data which have been collected during field campaigns since 2000. The first part of the current project consisted of organising and analysing available data. The location of the cross-section could then be determined and the conceptual model drawn. Finally, the data were integrated into the conceptual and numerical model.

1.3.1 Data

The available data used for this study are listed below and illustrated in Figure 1.4: A. Hydraulic heads in groundwater wells from the Immatsiak network since 2012 B. Darcy fluxes measured with a tracer experiment in groundwater wells in 2016 C. Precipitation data at the SILA weather station since 2012

D. Recharge rates for different vegetation types in 2014-2015 (Murray 2016)

E. Air temperatures and relative humidity from the Umiujaq-A Station located near the Umiujaq airport, since 1993

F. Air temperatures at Site 3 since 2012

G. Physical and thermal properties of different geological formations in the valley H. Temperature profiles in the permafrost mound since 2000

I. Unfrozen water content, snow depths, shallow heat fluxes and surface temperatures at the permafrost mound site since 2014

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The above listed data will be presented in more detail in the following sections.

1.3.1.1 Hydraulic heads

The Immatsiak network is composed of seven sites with nine groundwater wells which have been instrumented with water pressure probes (Solinst Levelogger, Model 3001). The hydraulic heads (relative to sea level) from 2012 to 2017 at the two wells closest to the studied permafrost mound, as well as monthly precipitation from the SILA station, are shown in Figure 1.5Erreur ! Source du renvoi introuvable.. Site 5 is located upstream relative to the studied permafrost mound, while Site 3 is located downstream. During the spring thaw (starting about mid-June), recharge begins and the water level gradually rises in the wells throughout the year until it reaches a peak in winter around January. A period of recession is then observed until the water level reaches its lowest point, usually in early June. Artesian conditions were observed at Site 3 during the winter 2015-2016, which is shown in Figure 1.5 as a static hydraulic head which corresponds to the elevation of the surface well casing. The slight increase of the hydraulic head above the elevation of the well casing at the end of the winter

Figure 1.4: Tasiapik valley watershed, permafrost mound and location of the instruments on the mound. Data from instruments that have been faded out on the mound picture are not presented in the current document.

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period is due to the freezing of water within the upper part of the surface casing which allows a build-up of pressure.

1.3.1.2 Darcy flux

Groundwater fluxes along the axis of the valley were first assessed indirectly with Darcy’s law, using head differences and distances between wells to calculate hydraulic gradients, and using hydraulic conductivities estimated from slug tests (Fortier et al., 2014). Tracer experiments were then also performed in summer 2016 using the Finite Volume Point Dilution Method (FVPDM) (Jamin et. al., 2018), providing direct measurements of Darcy fluxes in three wells. The measured Darcy fluxes are given in Table 1.1 for both methods.

In general, the Darcy fluxes assessed from the gradient method are much lower than from the FVPDM, except for Site 5 where it is only slightly lower. This could be due in part to the high margin of error associated with the gradient method considering the large spacing between wells and the uncertainty on the hydraulic conductivity values. Another hypothesis is that the wells may not be aligned with the main direction of local groundwater flow. Despite these differences, the Darcy fluxes obtained from the FVPDM are considered much more accurate than the gradient method since the FVPDM is a direct measurement (see Jamin et al. for details).

Figure 1.5: Hydraulic heads in the groundwater wells at Site 3 and Site 5, from 2012 to 2017 (from the Solinst probes and manual measurements), and monthly precipitation measured at the SILA station.

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Table 1.1: Darcy fluxes assessed from hydraulic gradients and the FVPDM method for Sites 2, 5, and 3.

1.3.1.3 Recharge

Groundwater recharge was estimated by Murray (2016) using the Darcy method (Healy, 2010), which is based on the Darcy equation in the unsaturated zone:

𝑞 = 𝐾𝑛𝑠𝜕ℎ_𝜕𝑧 [1.1]

where q is the Darcy flux (m/s), Knsis the unsaturated hydraulic conductivity (m/s), and 𝜕ℎ/𝜕𝑧is the vertical hydraulic gradient. Four zones at Site 2 were instrumented to characterize hydraulic conductivities (Appendix C). The corresponding local recharge rate was calculated for three dominant vegetation types: lichen, spruce and shrubs. The recharge per vegetation type is shown in Figure 1.6.

Figure 1.6: Monthly recharge measured by Murray (2016) at Site 2 for the year 2014-2015, for ground surfaces dominated by shrubs, spruce and lichen.

Piezometer _conductivity Hydraulic _A Based on hydraulic gradients (2016) B

Based on FVPDM experiments (2016)

Ratio FVPDM/Gradient

method Darcy Flux Darcy Flux Uncertainty

[m/s] [m/s] [m/s] [m/s] [ - ]

Site 2 (Pz2) 4.9 10-5 8.1 10-7 9.0 10-6 1.4 10-7 (1.5 %) 11 Site 5 (Pz6) 1.6 10-4 _5.6 ₁₀-6 _8.5 ₁₀-6 _3.5 ₁₀-8 _{(0.4 %) 1.5} Site 3 (Pz4) 9.8 10-6 _1.0 ₁₀-7 _6.7 ₁₀-6 _6.9 ₁₀-8 _{(1 %)} 64 A _{Hydraulic conductivity was measured using slug tests (Fortier et al., 2014).}

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1.3.1.4 Physical and thermal properties

Different methods were used in 2014 to estimate hydraulic conductivity of the geological units found in the Tasiapik valley, including Guelph permeameter tests, slug tests in the Immatsiak wells and grain size analysis of various soil samples. Details concerning the methods are provided by Fortier et al. (2014) and the main results are presented in Appendix D.

Thermal conductivity at the study site was measured on undisturbed soil samples collected during the summer of 2016. Three samples of coarse sand, sandy silt and silt were respectively collected at 60, 20, and 60 cm depths in the active layer. The thermal conductivity was measured in the laboratory using a KD2Pro thermal conductivity meter (Decagon Devices) and a TR-1 sensor. The measurement range of the TR-1 sensor is from 0.10 to 4.00 W/(mK) with an accuracy of ±10%. The thermal conductivity of the original moist sample is first measured at room temperature (23 °C). A total of 9, 16 and 17 measurements were made, respectively, for samples 1 to 3, with a waiting time between each measurement of about one hour. Calibration was performed by comparing the experimental determination of the thermal conductivity of a standard material to its known value. The calibration factor is calculated with the following equation:

𝐶 = λ𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙

λ𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑 [1.2]

where 𝜆materialis the known thermal conductivity of the calibration material, and 𝜆measured is the thermal conductivity of that material measured with the thermal needle probe apparatus. All thermal conductivities measured on the samples are then multiplied by this factor. The measured thermal conductivity of the wet sample is assumed equal to the mean of the conductivities of the different media (air, water, material). The thermal conductivity of the dry material is then obtained using equation 1.3:

λ_𝑑𝑟𝑦= (λ_𝑤𝑒𝑡−λ_𝑤∗ 𝑆 ∗ 𝜃 −λ_𝑎∗ (1 − 𝑆) ∗ 𝜃)/(1 − 𝜃) [1.3]

where λ𝑑𝑟𝑦, λ𝑤𝑒𝑡, λ_𝑤, and λ_𝑎 are the thermal conductivities respectively, of the dry material, wet material, water, and air, S is the saturation, and θ is the porosity. The saturation and porosity are calculated using dry weights and volumes of the different samples, assuming a solid density of 2600

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kg/m3 _{and a liquid density of 1000 kg/m}3_{. The estimated thermal conductivities, water content, and}

porosities of the samples are given in Table 1.2.

Table 1.2: Thermal conductivities measured with the thermal needle probe, water content and porosity of three soil samples.

1.3.1.5 Temperature profiles

Four thermistor cables were installed in the permafrost mound. The thermistors (44033RC Precision Epoxy NTC type) have a precision of ±0.1°C (Measurement Specialties Inc., 2008). Hourly readings and recording were obtained with a Campbell Scientific AM16/32 relay multiplexer and a Campbell Scientific CR10X Datalogger. The average temperature profiles for the thermistor cables located at the center of the mound and on the edge of the mound, from 2002 to 2017, are shown in Figure 1.7. The temperatures are averaged over two years in summer (July, August, September) and mid-winter (January, February, March). Over the 15-year monitoring period, the interpolated active layer thickness increased from 2 meters in 2002 to nearly 4 meters in 2017. The extrapolated permafrost base reached a minimum depth of 19.7 m in 2009, but increased to 21 m in 2017. Based on the measured temperatures at the permafrost base, the geothermal heat fluxes between the permafrost and the deep aquifer vary between 0.2 and 0.7 W/m2_.

No Sample Depth Thermal conductivity of solids

(W/mK) content Water Porosity

1 Coarse sand 60 cm 3.04 28% 38%

2 Sandy silt 20 cm 2.76 20% 37%

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Figure 1.7: Subsurface temperatures measured using thermistor cables from 2002 to 2017 for the mid-winter period (January, February, March) in the left graphs and for the mid-summer period (July, August, September) in the right graphs, averaged over two years, located a) at the edge of the mound, and b) at the center of the mound (see locations in Figure 1.4).

a)

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1.3.1.6 Soil moisture and temperature probes

The soil moisture and temperature of the unsaturated zone was monitored with Decagon 5TM probes which were installed at various depths in 2014 and connected to Decagon EM50 data loggers. Ten probes were installed both on the top and at the side of the mound in the silt unit. The unfrozen (volumetric) water contents (m3

w/m3total) and temperatures measured in the unsaturated zone are

shown in Figure 1.8 for mid-summer and mid-winter 2015 and 2017, both at the side of the mound

Figure 1.8: Unfrozen water content and temperature in the unsaturated zone in summer and winter 2015 and 2017 from the moisture content and temperature monitoring arrays with a) and b) Water content and c) and d) Temperature, at the side of the mound (left column) and at the center of the mound (right column).

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(Figure 1.8a and Figure 1.8c) and on top of the mound (Figure 1.8b and Figure 1.8d). The accuracy for the measurement of volumetric water content varies from ±0.01 to ±0.02 m3_/m3 _{while it is ±1°C}

for the temperature.

A general increase of the unfrozen water content and temperature in the unsaturated zone was observed between 2015 and 2017, especially during the mid-summer period. On top of the mound, which is more exposed to climate variations, temperatures are generally warmer in the summer and colder in the winter while unfrozen water content is generally lower than at the side of the mound. The variation of water content as a function of time on the top and the side of the mound for the shallow and deep probes is shown in Figure 1.9. The daily air temperature is illustrated by a pale gray line while a spline smoothing function used to reduce noise is shown by a dark gray line. At the center of the mound, significant seasonal variations are observed, with clear peaks around May consistent with the time where the temperature rises above 0 °C and the ground thaws. A delay of about 4 months occurs between the peaks observed at 0.1 m depth and those at 1 m depth. Beside the mound, the seasonal variations are attenuated, especially at a depth of 1 m where the water content remains around 0.3 throughout the whole year. The unfrozen water content generally remains higher at the side of the mound since water drains from the top of the mound and accumulates in the side depressions.

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Figure 1.9: Water content as a function of time (2014 – 2017) from the moisture and temperature probes at 0.1 m and 1 m depths, at a) the center of the mound, and b) the side of the mound.

a)

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1.3.1.7 Snow cover

Five snow poles were installed on the mound, as well as an automated camera (RECONYX PC800 HyperFire Professional Semi-Covert IR) which takes daily pictures of the snow poles at 10:00, 11:00, 12:00, 13:00 and 14:00. Examples of photos taken during summer (July) and winter (February) are shown in Figure 1.10 which also shows the location of the snow poles.

The visible snow pole length was measured in each photo from summer 2014 to summer 2015, providing an estimate of snowpack distribution on and around the mound throughout the year. The assessed thicknesses of snow cover for the five poles are presented in Figure 1.11. The snow starts to

SP3

SP1

SP2

B

A

Figure 1.10: Photos of the permafrost mound from the Reconyx camera, and location of the snow poles a) in July 2017, and b) in February 2017.

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accumulate around November and melts completely by around May on the top of the mound, while it stays until June in the side depressions which are less exposed to wind and solar radiation. A maximum thickness of snow cover of about 1.6 m is reached at the end of March.

1.3.1.8 Heat flux

Two Heat Flux Plates (HFPs) (Hukseflux HFP01SC) were installed in the center and the side of the mound at a depth of 8 cm. The plates are coupled with a pair of thermistors buried at depths of 2 cm and 6 cm which are connected to an automated datalogger system consisting of a Campbell Scientific AM16/32 relay multiplexer and a Campbell Scientific CR10X Datalogger. These HFPs generate a small voltage proportional to the temperature gradient measured between the thermistors, which is then divided by a sensitivity value to get heat flux values (W/m2_{). The sensitivity, provided for each}

plate on a calibration certificate, is entered in the datalogger system to allow self-calibration. The calibrated heat flux data, as well as air temperatures, are shown in Figure 1.12.

The heat flux varies between -1 and 2 W/m2 _{(negative values represent heat loss from the ground}

while positive values are heat gain). Negative heat fluxes are observed between November and June when the air temperature is lower than the ground surface. Heat fluxes on the top and the side of the mound are similar during the summer. The insulating effect of the thick snow cover on the side of the mound is clearly visible in winter where the heat flux is much lower on the side of the mound than on the top.

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1.3.1.9 Surface temperature

Ten surface temperature probes (HOBO Water Temperature Pro v2 connected to a U22-001 Data Logger) were buried 10 cm below the ground surface, recording a measurement every hour with an accuracy of ±0.21°C. Two probes, one located on the center of the mound and the other on the side of the mound, as well as the air temperatures, are presented in Figure 1.13.

Surface temperatures observed on top of the mound show large seasonal variations with temperatures reaching -20°C in the winter, while temperatures observed on the side of the mound are clearly affected by the insulating effect of snow cover with surface temperatures barely below the freezing point. Surface temperatures are similar in the summer at the two locations, due in part to the fact that both probes are located in zones where vegetation is very limited which does not provide a shade effect in summer.

1.3.2 Conceptual model

The conceptual model of the permafrost mound was developed in a 2D vertical section transverse to the valley, situated between the watershed boundaries (cross-section B-B’ in Figure 1.2). Lying approximately perpendicular to the axis containing the 9 wells of the Immatsiak network (cross-section A-A′ in Fig 1.2), the 2D model (cross-section is assumed to correspond to the main groundwater

Figure 1.13: Temperatures at 10 cm depth from the HOBO temperature probes located at the center and beside the mound between 2014 and 2017

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flow directions toward the central stream. The 2D cross-section was extracted from the 3D geological model developed by Banville (2016), extending from ground surface to depths varying from 40 to 210 m (the bottom boundary is located at 40 m below sea-level). More details concerning the mesh, initial conditions and boundary conditions are provided in Chapter 2. The current section provides more details on how observed data were integrated into the model.

1.3.2.1 Flow system and flow boundaries

The conceptual flow model is based on the hypothesis that groundwater flows from the cuesta towards the small stream, transverse to the orientation of the wells. Apparent fractures in the rock on the top of the cuesta and water seepage observed after rain events along the cuesta ridge are evidence that water infiltrates through the top fractures, flows below the ridge and recharges the deep sand aquifer at the base of the cuesta. Infiltration at the base of the cuesta is particularly focussed due to the presence of colluvium connected to the deep aquifer (Lemieux et. al., 2018). The conceptualized flow system is shown in Figure 1.14.

Based on temperature profiles located at the Umiujaq airport further along the back-slope of the cuesta, the depth to the permafrost in the cuesta is estimated to be about 20 m. Thus, groundwater is assumed to flow on top of the permafrost units and a 20 m deep unsaturated zone is assumed.

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Considering the lack of data available on the left side of the cross-section, the Dupuit equation is used to estimate the watertable elevations (hydraulic head (h)) along the flow line through the cuesta (Dupuit 1863): ℎ2 _{= ℎ} 1 2₋(ℎ12−ℎ22)𝑥 𝐿 + 𝑤 𝐾(𝐿 − 𝑥)𝑥 [1.4]

where h1 and h2 are the steady-state heads at the respective left and right limits of the flowline through

the cuesta, L is the distance between h1 and h2, K is the hydraulic conductivity of the aquifer, w is the

recharge and x is the distance along the flowpath (0 < x < L). Assuming h1 = 228 m, h2 = 94 m, with

K = 1×10-5 _{m/s and w = 6×10}-9 _{m/s, the calculated heads are shown in Figure 1.15. The head h1 at}

the leftmost watertable point is fixed at 20 m below ground surface, while the rightmost bounding head h2 corresponds to the ground surface elevation at the bottom of the cuesta. The remaining part

of the watertable along the 2D section is assigned a transient recharge rate except for two fixed heads which correspond to observed surface water elevations along the cross-section, including the central stream. The flow system is assumed saturated.

1.3.2.1 Heat transport system and boundary conditions

The top heat transport boundary corresponds to ground surface, which is represented using a heat transfer layer allowing spatially-variable thermal parameters along the longitudinal axis which control heat exchange between the ground and atmosphere. The exchange layer can incorporate ground surface conditions and mass and energy exchange processes, including snowpack, vegetation and heat

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transfer across the air-ground interface. To handle spatial variation at the ground-atmosphere interface, the conceptual model for the Umiujaq site is divided into 7 zones according to vegetation type (lichen, bush or spruce) and topography (locally high or low). Net heat fluxes, layer thicknesses and recharge rates were assigned for each of the 7 zones and for each of the four seasons. These zones and associated parameters are presented in Figure 1.16 for summer and winter periods.

The ‘net’ heat flux is used to represent independent thermal fluxes that are not accounted for in the heat exchange layer based on the air-soil temperature gradient (ex. solar radiation). The thickness of the heat transfer layer is defined based on the estimated snow depths on the top and side of the studied mound.

1.3.2.2 Meteorological data

Past and present climate

Considering that the simulations start in 1900 (see Chapter 2 for details) and no climatological data are available at Umiujaq for that time (the village was only founded in the early 1980’s), mean annual air temperatures (MAATs) were estimated based on data from Kuujjuarapik and Kuujjuaq. The air temperatures estimated at the study site for the period from 1900 to 2017 were based on 4 series of data:

Period 1 (1900-1925): A constant value equal to the MAAT estimated in 1926.

Figure 1.16: Input parameters of the heat transfer layer shown for the mid-summer and mid-winter periods with a) layer thickness and zone delimitation and b) heat flux and recharge rates in mm/year

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Period 2 (1926-1949): Temperatures recorded at Kuujjuarapik over this period were decreased by the mean difference between known MAATs at Kuujuarapik and Umiujaq between 1993 and 2017. The mean difference between the MAAT (1993-2017) at Umiujaq and Kuujjuarapik is 0.3°C. The MAAT at Umiujaq between 1926 and 1950 was then calculated by subtracting 0.3°C from the temperatures recorded at Kuujjuarapik.

Period 3 (1950-1992): A linear interpolation between air temperatures recorded at Kuujjuarapik and Kuujjuaq based on known MAATs between 1993 and 2017. Mean annual air temperatures, over the period 1993-2017, of -2.9°C, -3.2°C and -4.5°C were calculated respectively for Kuujjuarapik, Umiujaq and Kuujjuaq. A correlation was made between the 3 locations by calculating a differential ratio. The MAAT values at Umiujaq between 1950 and 1993 were then interpolated between values recorded at Kuujjuarapik and Kuujjuaq, proportionally to this ratio. Once the MAATs had been estimated over the entire simulation period, the daily mean temperatures for each year were then calculated with a cosine curve, oscillating around the estimated MAAT over a period of 365 days. The function amplitude was assumed constant over time and equal to 18°C, which corresponds to the mean half-difference between the maximum and minimum monthly temperatures recorded at all three locations.

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The resulting estimated MAATs at Umiujaq from 1900 to 2017 are shown in Figure 1.17. The solid lines represent a 5-year moving average.

Predicted climate

Projected changes in climate variables over the Nunavik-Nunatsiavut region have been computed by the Ouranos research consortium (Allard and Lemay, 2012) based on the Canadian Regional Climate Model (CRCM) (Caya et al., 1995; Caya and Laprise, 1999; Plummer et al., 2006; Music and Caya, 2007). Ouranos applied the SRES A2 greenhouse gas increase scenario to project changes in various climate variables in the Nunavik-Nunatsiavut region, such as air temperatures, precipitation, degree-days of thawing and freezing, snow depth, etc. For the purpose of this study, only changes in air temperatures, as well as precipitation during winter (October to April) and summer (May to September), were considered. For the Umiujaq region, the study predicts a temperature increase of 4°C in winter and 1.7°C in summer, as well as a precipitation increase of 25%, between the 1971-2000 period (referred as the current climate conditions) and the 2041-2070 period.

Based on the temperature and precipitation increase projected by Ouranos (Allard and Lemay, 2012), a mean temperature increase of 0.09°C/year in winter and 0.02°C/year in summer was estimated for

Figure 1.17: Mean annual air temperatures recorded at Kuujjuarapik and Kuujjuaq and estimated temperatures at Umiujaq. The solid lines represent a 5-year moving average to reduce the variability and highlight the trends while the dots represent the mean annual air temperatures. The grey zones represent the warming periods.

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the Umiujaq site between 2017 and 2050, as well as an annual precipitation increase of 0.5%. The calculated increments are applied in the model over each simulated year.

Recharge

Based on the vegetation map from Provencher-Nolet (2014) (Appendix B), the percentage occupied by each vegetation type along the cross-section was assessed as follows: lichen (50%), shrubs (30%) and spruce (20%). Rock covered with vegetation is assumed to have the same recharge values as lichen, while lakes and road surfaces are assumed to have zero recharge. The year is divided into four periods starting with mid-summer (July, August, September). Monthly recharge values calculated by Murray (2016) were then summed over the respective periods and according to the vegetation type. The estimated total mean annual recharge, weighted according to vegetation cover along the cross-section, is about 300 mm/yr. The resulting values are presented in Table 1.3.

Table 1.3: Assumed recharge rates according to the vegetation type and temperature difference between recharge water (Tq) and air temperature (Tair).

Recharge (mm) /Period

Vegetation Type Weighted Total Tq - Tair

Lichen Bush Spruce (mm) (°C)

Mid-summer 153 118 87 129 -2.0

Oct. – Dec. 123 78 60 97 -1.4

Mid-winter 1 1 6 2 0.0

Apr. – Jun. 65 119 78 72 -1.7

Total (mm/yr) 343 316 231 300

-Rain water temperature varies throughout the year, being cooler than the air temperature during the summer. The temperature of recharge water can be estimated as the wet-bulb temperature, which can be calculated with Equation 1.5 (Stull, 2011), based on the dry-bulb temperature (air temperature) and relative humidity measured at Umiujaq:

𝑇𝑞= 𝑡𝑎𝑛−1[0.15(𝑅𝐻 + 8.31)1 2⁄ ] + 𝑡𝑎𝑛−1(𝑇 + 𝑅𝐻) + 0.004(𝑅𝐻)3 2⁄ 𝑡𝑎𝑛−1(0.02𝑅𝐻) − 4.69 [1.5]

where Tq is the recharge temperature, RH is the relative humidity in percent and T is the air

temperature. The difference between air temperature and rain temperature is then averaged over the four seasons and applied in the model.

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2 Numerical model (Taken from Dagenais et al., 2018)

S. Dagenais(1,2)_{, J. Molson}(1,2,*)_{, J-M. Lemieux}(1,2)_{, R. Fortier}(1,2)_{, and R. Therrien}(1,2)

1. Département de géologie et de génie géologique, 1065 avenue de la Médecine, Université Laval, Québec (Québec), Canada, G1V 0A6

2. Centre d’études nordiques, Université Laval, Québec (Québec), Canada, G1V 0A6. *Corresponding author

Reference: Dagenais S, Molson J, Lemieux J-M, Fortier R, Therrien R. (2018). Coupled cryo-hydrogeological modelling of permafrost dynamics at Umiujaq, Québec, Canada, In submission: Hydrogeology Journal.

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Résumé

Un modèle numérique bidimensionnel de l’écoulement de l’eau souterraine, de la transmission de chaleur par conduction et advection, et du changement de phase qui prennent place dans un environnement pergélisolé a été développé pour une butte de pergélisol riche en glace dans la vallée Tasiapik à Umiujaq au Nunavik (Québec), Canada. La dégradation des buttes de pergélisol dans cette vallée située en zone de pergélisol discontinu a été attribuée à la tendance au réchauffement climatique observée au Nunavik au cours des deux dernières décennies. Les flux de chaleur à la base du pergélisol déterminés à partir des températures du sol mesurées avec des câbles à thermistances sont plus de dix fois supérieurs au gradient géothermique estimé dans la région. Un modèle numérique basé sur une coupe verticale extraite d’un modèle géologique tridimensionnel de la vallée a été produit. Ce modèle a été étalonné avec des profils de température et de flux de chaleur qui ont été mesurés dans la butte de pergélisol du site d’étude. Les simulations avec et sans écoulement d’eau souterraine ont montré que la transmission de chaleur par advection joue un rôle critique dans la dynamique du pergélisol et explique les flux de chaleur importants observés à la base du pergélisol. La transmission de chaleur par advection dans l’aquifère sous la base du pergélisol est à l’origine d’une augmentation des températures du sol en amont de la butte tandis que, dans la zone de résurgence en aval, l’eau souterraine après avoir perdu une partie de sa chaleur maintient le sol à des températures plus froides que celles résultant de la conduction thermique seule. En se basant sur un scénario de réchauffement climatique attendu dans la région d’ici 2050, selon les résultats de la simulation, le mollisol devrait s’épaissir et la base du pergélisol devrait se rapprocher de la surface d’environ 80 cm par année alors que le pergélisol devrait disparaître du site d’étude autour de 2040.

Mots clés: Écoulement d’eau souterraine, Pergélisol, Changements climatiques, Modélisation numérique, Nunavik

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Abstract

A 2D cryo-hydrogeological numerical model of groundwater flow, coupled with advective-conductive heat transport with phase change in a permafrost environment, has been developed for an ice-rich permafrost mound in the Tasiapik Valley in Nunavik (Québec), Canada. Permafrost is thawing in this valley due to the trend of climate warming observed in Nunavik over the last two decades. Ground temperatures measured along thermistor cables in the permafrost mound show that permafrost degradation is occurring both at the permafrost table and base. Moreover, derived heat fluxes at the permafrost base are up to ten times higher than the expected geothermal heat flux. The numerical model, based on a vertical cross-section extracted from a 3D geological model of the valley, was first calibrated using observed temperatures and heat fluxes from the permafrost mound. Comparing simulations with and without groundwater flow, advective heat transport due to groundwater flow in the sub-permafrost aquifer is shown to play a critical role in permafrost dynamics and can explain the high apparent heat flux at the permafrost base. Advective heat transport leads to warmer subsurface temperatures in the recharge area while the cooled groundwater arriving in the downgradient discharge zone maintains cooler temperatures than those resulting from thermal conduction alone. Predictive simulations incorporating a regional climate change scenario suggest the active layer thickness will increase by about 12 cm/yr, while the depth to the permafrost base will decrease by about 80 cm per year. Permafrost within the valley is predicted to completely thaw by around 2040.