The Hudson Bay basin is a large contributor of freshwater input in the Arctic Ocean and is also an area affected by destructive spring floods. In this study, the hydrological model MESH (Modelisation Environmentale Communautaire - Surface and hydrology) was set up for the Groundhog River watershed situated in the Hudson Bay basin, to simulate the future evolution of streamflow and annual maximum streamflow. MESH was forced by meteorological data from ERA5 reanalyses in the historical period (1979–2018) and 12 models of the Coupled model intercomparison Project Phase 5 (CMIP5) downscaled with the Canadian Regional Climate model version 5 (CRCM5) in historical (1979–2005) and scenario period (2006–2098). The projections consistently indicate an earlier spring flow and a reduction in the amount of annual maximum streamflow by the end of the 21st century. Under the RCP8.5 scenario, the annual maximum streamflow occurring in the spring is expected to be advanced by 2 weeks and reduced on average from 852 m3/s (±265) in the historical period (1979–2018) to 717m3/s (±250) by the end of the 21st century (2059–2098). Because the seasonal projection of streamflow was not investigated in previous studies, this work is an important first step to assess the seasonal change of streamflow in the Hudson Bay region under climate change.

• Streamflow was satisfactorily simulated by MESH model in Hudson Bay lowlands. • Higher precipitation and streamflow observed in the western watersheds in 1995–2008. • The wet period in 1995–2008 was due to a shift in regional atmospheric circulation. • PDO and EP-NP also influenced this wet period. • Dryer period but sustained streamflow in 2009–2019 due to permafrost thaw. Hudson Bay Lowlands watersheds, Ontario, Canada. The rivers in the Hudson Bay Lowlands are a major source of freshwater entering the Arctic Ocean and they also cause major floods. In recent decades, this region has been affected by major changes in hydroclimatic processes attributed to climate change and natural climate variability. In this study, we used ERA5 reanalysis data, hydrometric observations, and the hydrological model MESH, to investigate the impact of atmospheric circulation on the inter-decadal variability of streamflow between 1979 and 2018 in the Hudson Bay Lowlands. The natural climate variability was assessed using a weather regimes approach based on the discretization of daily geopotential height anomalies (Z500) from ERA5 reanalysis, as well as large scale oceanic and atmospheric variability modes. The results showed an anomalous convergence of atmospheric moisture flux between 1995–2008 that enhanced precipitation and increased streamflow in the western part of the region. This moisture convergence was likely driven by the combination of (i) low pressure anomalies in the East Coast of North America and (ii) low pressure anomalies in western regions of Canada, associated with the cold phase of the pacific decadal oscillation (PDO). Since 2009, streamflow remains high, likely due to more groundwater discharge associated with the degradation of permafrost.

Hydrometeorological events have been the predominant type of natural hazards to affect communities across Canada. While climate change is a concern to all Canadians, Indigenous communities in Canada have been disproportionately more affected by these extreme climate events than non-Indigenous communities. As the impacts of climate change intensify, it becomes increasingly important that high-resolution climate services are made available to Indigenous decision makers for the development of climate change adaptation plans. This paper examined extreme climate trends in the Six Nations of the Grand River reserve, the most populated Indigenous community in Canada. A set of 12 indices were used to evaluate changes in extreme climate events from 1951 to 2013, and 2006 to 2099 under Representative Concentration Pathways (RCP) 4.5 and 8.5. Results indicated that from 1951 to 2013, Six Nations became warmer and wetter with an average temperature increase of 0.7 °C and precipitation increase of 42 mm. Over this period, the frequency and duration of extreme heat and extreme precipitation events also increased, while extreme cold events decreased. In the future (2006 to 2099), temperature is expected to increase by 3 to 6 °C, while seasonal precipitation is expected to increase in winter, early spring, and fall. Projected rate of increase of heatwaves is 0.4 to 1.5 days per year and extreme annual rainfall events is 0.2 to 0.5 mm per year under both RCP scenarios. The climate information and data provide by this study will help Six Nations’ decision makers in planning for climate change impacts.

A new flow for Canadian young hydrologists: Key scientific challenges addressed by research cultural shiftsCaroline Aubry-Wake1, Lauren D. Somers2,3, Hayley Alcock4, Aspen M. Anderson5, Amin Azarkhish6, Samuel Bansah7, Nicole M. Bell8, Kelly Biagi9, Mariana Castaneda-Gonzalez10, Olivier Champagne9, Anna Chesnokova10, Devin Coone6, Tasha-Leigh J. Gauthier11, Uttam Ghimire6, Nathan Glas6, Dylan M. Hrach11, Oi Yin Lai14, Pierrick Lamontagne-Halle3, Nicolas R. Leroux1, Laura Lyon3, Sohom Mandal12, Bouchra R. Nasri13, Natasa Popovic11, Tracy. E. Rankin14, Kabir Rasouli15, Alexis Robinson16, Palash Sanyal17, Nadine J. Shatilla9, 18, Brandon Van Huizen11, Sophie Wilkinson9, Jessica Williamson11, Majid Zaremehrjardy191 Centre for Hydrology, University of Saskatchewan, Saskatoon, SK, Canada2 Civil and Environmental Engineering, Massachusetts Institute of Technology, MA, USA3 Department of Earth and Planetary Sciences, McGill University, Montreal QC4 Department of Natural Resource Science, McGill University, Montreal, QC, Canada5 Department of Earth Sciences, Simon Fraser University, Burnaby, BC, Canada6 School of Engineering, University of Guelph, Ontario, ON, Canada7 Department of Geological Sciences, University of Manitoba, Winnipeg, Canada8 Centre for Water Resources Studies, Department of Civil & Resource Engineering, Dalhousie University, Halifax, NS, Canada9 School of Geography and Earth Sciences, McMaster University, Hamilton, ON, Canada.10 Department of Construction Engineering, Ecole de technologie superieure, Montreal, QC, Canada11 Department of Geography & Environmental Management, University of Waterloo, Waterloo, ON, Canada12 Department of Geography and Environmental Studies, Ryerson University, Toronto, ON, Canada13 Department of Mathematics and Statistics, McGill University, Montreal, Qc, Canada14 Geography Department, McGill University, Montreal, QC, Canada15 Meteorological Service of Canada, Environment and Climate Change Canada, Dorval, QC, Canada16 Department of Geography and Planning, University of Toronto, Toronto, ON17 Global Institute for Water Security, University of Saskatchewan.18 Lorax Environmental Services Ltd, Vancouver, BC, Canada.19 Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB, Canada

Abstract. Extreme events are widely studied across the world because of their major implications for many aspects of society and especially floods. These events are generally studied in terms of precipitation or temperature extreme indices that are often not adapted for regions affected by floods caused by snowmelt. The rain on snow index has been widely used, but it neglects rain-only events which are expected to be more frequent in the future. In this study, we identified a new winter compound index and assessed how large-scale atmospheric circulation controls the past and future evolution of these events in the Great Lakes region. The future evolution of this index was projected using temperature and precipitation from the Canadian Regional Climate Model large ensemble (CRCM5-LE). These climate data were used as input in Precipitation Runoff Modelling System (PRMS) hydrological model to simulate the future evolution of high flows in three watersheds in southern Ontario. We also used five recurrent large-scale atmospheric circulation patterns in north-eastern North America and identified how they control the past and future variability of the newly created index and high flows. The results show that daily precipitation higher than 10 mm and temperature higher than 5 ∘C were necessary historical conditions to produce high flows in these three watersheds. In the historical period, the occurrences of these heavy rain and warm events as well as high flows were associated with two main patterns characterized by high Z500 anomalies centred on eastern Great Lakes (HP regime) and the Atlantic Ocean (South regime). These hydrometeorological extreme events will still be associated with the same atmospheric patterns in the near future. The future evolution of the index will be modulated by the internal variability of the climate system, as higher Z500 on the east coast will amplify the increase in the number of events, especially the warm events. The relationship between the extreme weather index and high flows will be modified in the future as the snowpack reduces and rain becomes the main component of high-flow generation. This study shows the value of the CRCM5-LE dataset in simulating hydrometeorological extreme events in eastern Canada and better understanding the uncertainties associated with internal variability of climate.

Abstract. Fluvial systems in southern Ontario are regularly affected by widespread early-spring flood events primarily caused by rain-on-snow events. Recent studies have shown an increase in winter floods in this region due to increasing winter temperature and precipitation. Streamflow simulations are associated with uncertainties mainly due to the different scenarios of greenhouse gas emissions, global climate models (GCMs) or the choice of the hydrological model. The internal variability of climate, defined as the chaotic variability of atmospheric circulation due to natural internal processes within the climate system, is also a source of uncertainties to consider. Uncertainties of internal variability can be assessed using hydrological models fed by downscaled data of a global climate model large ensemble (GCM-LE), but GCM outputs have too coarse of a scale to be used in hydrological modeling. The Canadian Regional Climate Model Large Ensemble (CRCM5-LE), a 50-member ensemble downscaled from the Canadian Earth System Model version 2 Large Ensemble (CanESM2-LE), was developed to simulate local climate variability over northeastern North America under different future climate scenarios. In this study, CRCM5-LE temperature and precipitation projections under an RCP8.5 scenario were used as input in the Precipitation Runoff Modeling System (PRMS) to simulate streamflow at a near-future horizon (2026–2055) for four watersheds in southern Ontario. To investigate the role of the internal variability of climate in the modulation of streamflow, the 50 members were first grouped in classes of similar projected change in January–February streamflow and temperature and precipitation between 1961–1990 and 2026–2055. Then, the regional change in geopotential height (Z500) from CanESM2-LE was calculated for each class. Model simulations showed an average January–February increase in streamflow of 18 % (±8.7) in Big Creek, 30.5 % (±10.8) in Grand River, 29.8 % (±10.4) in Thames River and 31.2 % (±13.3) in Credit River. A total of 14 % of all ensemble members projected positive Z500 anomalies in North America's eastern coast enhancing rain, snowmelt and streamflow volume in January–February. For these members the increase of streamflow is expected to be as high as 31.6 % (±8.1) in Big Creek, 48.3 % (±11.1) in Grand River, 47 % (±9.6) in Thames River and 53.7 % (±15) in Credit River. Conversely, 14 % of the ensemble projected negative Z500 anomalies in North America's eastern coast and were associated with a much lower increase in streamflow: 8.3 % (±7.8) in Big Creek, 18.8 % (±5.8) in Grand River, 17.8 % (±6.4) in Thames River and 18.6 % (±6.5) in Credit River. These results provide important information to researchers, managers, policymakers and society about the expected ranges of increase in winter streamflow in a highly populated region of Canada, and they will help to explain how the internal variability of climate is expected to modulate the future streamflow in this region.

Abstract Flooding is a major concern for Canadian society as it is the costliest natural disaster type in Canada. Southern Ontario, which houses one-third of the Canadian population, is located in an area of high vulnerability for floods. The most significant floods in the region have historically occurred during the months of March and April due to snowmelt coupled with extreme rain events. However, during the last three decades, there has been a shift of flooding events to earlier months. The aim of this study was to understand the impacts of atmospheric circulation on the temporal shift of streamflow and high flow events observed in southern Ontario over 1957–2013 period. Predominant weather regimes over North America, corresponding to recurrent meteorological situations, were identified using a discretization of daily geopotential height at 500HpA level (Z500). A regime-normalized hypothetical temperature and precipitation dataset was constructed to quantify the contribution of atmospheric circulation on streamflow response. The hypothetical dataset was used as input in the Precipitation Runoff Modeling System (PRMS), a rainfall-runoff semi-distributed hydrological model, and applied to four watersheds in southern Ontario. The results showed an increase in the temporal frequency of the regime identified here as High Pressure (HP) close to eight occurrences per decade. Regime HP, characterized by a northern position of the polar vortex, is correlated with a positive phase of the NAO and is associated with warm and wet conditions over southern Ontario during winter. The temporal increase in HP contributed more than 40% of the increase in streamflow in winter and 30–45% decrease in streamflow in April. This atmospheric situation also contributed to increase the number of high flows by 25–50% in January. These results are important to improve the seasonal forecasting of high flows and to assess the uncertainty in the temporal evolution of streamflow in the Great Lakes region.