Water quality is of significant concern and ultimately critical to every Canadian’s quality of life and security. Canada has diverse and vast landscapes and stressors that impact various waterbodies differentially, with influencing factors including contaminant and nutrient loads from human activity (mining effluent, wastewater, agricultural runoff, plastics), landscape change (wetland drainage, urbanization), and climate change (warming water temperatures, longer open water seasons, extreme hydrological events, intensifying wildfires). Canadian rivers are especially important to the overall biogeochemistry, hydrology, biodiversity, and ultimate health of aquatic and terrestrial ecosystems. While each of Canada’s provinces and territories has extensive river water quality (physical, chemical, biotic) data and monitoring programs; Environment and Climate Change Canada coordinates various national programs that contribute to the collection and consolidation of these data and conducts extensive research into the study and modeling of key river water quality processes. Despite program-specific efforts, there remains poor capacity to predict current and future conditions in monitored and unmonitored Canadian rivers, particularly remote or northern rivers, due to a myriad of factors including lack of coordination among groups and examination of areas in which modeling efforts might be integrated. Herein, we review and analyze the current state of data availability, process studies, and modeling systems for Canadian river water quality. Our synthesis reveals that specific physical processes (water temperature, ice formation, permafrost thaw, sediment dynamics), biogeochemical processes (dissolved oxygen, dissolved organic matter, nutrient cycling, metals/contaminants), and ecological/biological features (biota mass, functional indicators) are well understood, though complex, and are amenable to empirical or mechanistic modeling. Review of this information assists us in identifying opportunities and challenges for developing a national water quality modeling system, that would eventually include similar modeling activities for parallel processes in lakes and integrated watersheds. We identify needs for stronger coordination of monitoring programs in remote areas, recommend use of novel remote sensing technologies, and development of a flexible, iterative “process” for integrated modeling to which stakeholders beyond government can contribute. Such a platform would support short- and long-term predictive models of Canadian water quality and ecosystem health, inform effluent concentration limits, and be an early warning system for source waters.

Wetland ecosystems are sensitive to climate variation, yet tracking vegetation type and structure changes through time remains a challenge. This study examines how Landsat-derived vegetation indices (NDVI and EVI) correspond with lidar-derived canopy height model (CHM) changes from 2000 to 2018 across the wetland landscape of the Peace–Athabasca Delta (PAD), Canada. By comparing CHM change and NDVI and EVI trends across woody and herbaceous land covers, this study fills a gap in understanding long-term vegetation responses in northern wetlands. Findings show that ~35% of the study area experienced canopy growth, while 2% saw a reduction in height. CHM change revealed 11% ecotonal expansion, where shrub and treed swamps encroached on meadow and marsh areas. NDVI and EVI correlated significantly (p < 0.001) with CHM, particularly in shrub swamps (r2 = 0.40, 0.35) and upland forests (NDVI r2 = 0.37). However, EVI trends aligned more strongly with canopy expansion, while NDVI captured mature tree height growth and wetland drying, indicated by rising land surface temperatures (LST). These results highlight the contrasting responses of NDVI and EVI—NDVI being more sensitive to moisture-related changes such as wetland drying, and EVI aligning more closely with canopy structural changes—emphasizing the value of combining lidar and satellite indices to monitor wetland ecosystems in a warming climate.

River ice is a common feature in most Canadian rivers and streams during the cold season. River channel hydraulics under ice conditions may cause higher water levels at a relatively lower discharge compared to the open-water flood events. Elevated water levels resulting from river ice processes throughout fall freeze-over, mid-winter, and spring break-up are important hydrologic events with diverse morphological, ecological, and socio-economic impacts. This study analyzes the timing of maximum water levels (occurring during freeze-over, spring break-up, and open-water periods) and the typology of maximum ice-related events (at freeze-over, mid-winter, and spring break-up) using data from the Canadian River Ice Database. The study also compares annual maximum water levels during the river ice and open-water periods at selected hydrometric stations from 1966 to 2015, divided into two 25-year windows: 1966–1990 and 1991–2015. A return period classification method was applied to define ice-influenced, open-water, and mixed-regime conditions. The results indicate that the majority of ice-influenced maximum water levels occurred during spring break-up (~79% in 1966–1990 and ~69% in 1991–2015), followed by fall freeze-up (~13% and ~23%) and mid-winter break-up (~8% and ~7%) for the two periods, respectively. Among 15 stations analyzed for 1966–1990 and 42 stations for 1991–2015, the proportion of annual maximum water levels dominated by open-water conditions increased from 47% to 55%, while ice-dominated events decreased from 13% to 12%, and mixed-regime events dropped from 40% to 33%. However, a focused comparison of eight common stations revealed minimal change in the distribution of water level-generating events between the two periods. The findings offer valuable insights into the spatial distribution of maximum water level-generating mechanisms across Canada.

Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) is an emerging sensor technique that has become well-established for water level monitoring. While GNSS-IR has previously been employed for monitoring properties of lake ice and sea ice, it has not been applied for monitoring river ice. This paper presents results from monitoring river ice breakup at three sites in Canada. GNSS-IR data was compared to co-located time-lapse camera imagery and it was found that GNSS-IR signal was sensitive to periods where there is rough or broken ice in view of the sensor. Using data from Sentinel-1 and the RADARSAT Constellation Mission (RCM), the first ever comparison of GNSS-IR with Synthetic Aperture Radar (SAR) imagery is presented and a negative correlation of -0.8 is found between the GNSS-IR spectral power and SAR backscatter. Three classification algorithms of varying complexity (K-means clustering, neural network and random forest) are explored for detecting river ice using GNSS-IR. Using a shallow neural network with two hidden layers, an optimal accuracy of up to 94% is achieved over all three sites, or 97% when mixed water-ice conditions are excluded from the analysis. In summary, GNSS-IR has strong potential for ice monitoring applications, including monitoring the formation of ice jams.

This paper delves into the analysis, modeling, and power optimization of energy states in mobile embedded devices using Signal Interpreted Petri Nets (SIPNs). Utilizing a multi-factor authentication device as a case study, we first introduce its essential functions and possible energy states. We propose a taxonomy for classifying these energy states into elementary types based on energy inflow and storage conditions. A primary classification into Optimal, Suboptimal, and Critical energy states is proposed. Furthermore, we explore complex energy states where elementary types overlap, discussing their analysis and optimization using Petri Net hierarchies. These energy states are then modeled and analyzed via SIPN, focusing on properties like reachability and liveness for enhanced power optimization. Ultimately, this research offers a framework for better understanding and optimizing the energy efficiency of mobile embedded systems.

The return of snow accumulation and ablation processes in regenerating forests to pre-disturbance conditions, collectively referred to as hydrological recovery, has been investigated in past decades through manual snow surveys in adjacent open, juvenile, and mature stands. The outcomes of such studies provide a general understanding of hydrological recovery but lack transferability to areas where stand structure and terrain conditions differ from the reference sites. The application of mobile terrestrial LiDAR to investigate peak snow water equivalent (SWE) and ablation rates beneath regenerating trees in a space-for-time substitution study design provides new insights on the process of hydrological recovery in snowmelt forests of British Columbia, Canada. Outcomes of this study better quantify the influence of tree growth on peak SWE and ablation rate at both the tree and stand level for north aspect mixed conifer stands. Recovery of these two processes differ with recovery of Peak SWE beginning when the trees in a stand reach 3 m in height and recovery of ablation rates beginning once trees reach 5 m in height. Additionally, the process of negative ablation recovery in early juvenile stands reported in previous studies is herein clearly observed, providing an improved understanding of forest canopy effects on hydrological recovery in juvenile stands. The methods used in this study, which are internationally applicable, increase transferability of outcomes to stands where canopy characteristics (i.e., height, crown cover, and heterogeneity) are not represented in reference sites.

Downstream impacts of large hydropower dams are often neglected or underestimated, especially for areas situated at long distances from a dam. Naturalization of the flow hydrograph is an important step in assessing hydro-ecological and socio-economic impacts of regulation. Using reservoir inflows, a recently developed, lagged-flow naturalization method is applied to the lower portion of the regulated Peace River, which forms the northern boundary of the Peace-Athabasca Delta (PAD). The PAD is a Ramsar wetland of international importance that depends on overland flooding for recharge of its high-elevation or "perched" basins. Such flooding can be caused by ice jams during the spring breakup of the ice cover or by exceptionally high runoff during open-water flow conditions. Herein, the focus is on the latter type of event and the resulting recharge of basins located within the Peace sector of the PAD. For the period 1972-2017, regulation has reduced open-water flow peaks by similar to 4100 m(3)/s on average, while limiting the possibility of overbank flooding from the Peace River during the summer. Consistent with earlier findings on spring breakup flows, naturalized open-water peaks do not exhibit a temporal trend. Recharge of non-perched basins can also occur with moderately high flows that cause no overland flooding but generate flow reversals in Peace River tributaries. In turn, this mechanism can deliver river water to various basins either directly or via connecting channels. Our results show that flow-based variables that index the hydrological sustenance of non-perched basins have been significantly reduced by regulation.

Arctic-boreal wetlands, important ecosystems for biodiversity and ecological services, are experiencing hydrological changes including permafrost thaw, earlier snowmelt, and increased wildfire susceptibility. These changes are affecting wetland productivity, species diversity, and biogeochemical cycles. However, given the diverse forms and structures of wetland vegetation communities, traditional wetland maps generated from lower spatial and spectral resolution satellite imagery lack community-level vegetation classification and miss spatially complex patterns. In this study, we built a cloud-based workflow to map wetland vegetation community of the Peace-Athabasca Delta (PAD), Canada, by leveraging high-resolution (5-m) airborne multi-sensor datasets, namely NASA's Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), and a historical LiDAR archive. Validation of our classifications using ground references indicates that classifications derived from AVIRIS-NG have higher accuracies (≥87.9%) than either UAVSAR (65.6%) or LiDAR (75.9%) for mapping wetland vegetation communities. We also show improved classification accuracy when combining information from multiple sensors. In particular, incorporating AVIRIS-NG and UAVSAR datasets substantially reduced omission errors of wet graminoid and wet shrub classes from 29.6% to 20.5% and from 10.8% to 7.5%, respectively. Combining AVIRIS-NG and LiDAR datasets further improves overall accuracy (+2.2%) for most classifications, especially emergent vegetation, wet graminoid, and wet shrub. The best performing model, using features derived from all three sensors, achieved an overall accuracy of 93.5%. The framework established here can be used to leverage extensive airborne AVIRIS-NG and UAVSAR datasets collected across Alaska and northwest Canada to understand the spatial distribution of Arctic-Boreal wetland vegetation communities.

The lower Athabasca River (Canada) has experienced notable declines in streamflow and increasing oil sands development since the 1970s. This study investigates the potential impacts of climate change on navigability using both observed historical and projected future flows derived via hydrological simulations driven by an ensemble of statistically downscaled general circulation model climate data. Our use of proposed indices that form the Aboriginal Navigation Index (ANI) and a new index based on percentage over threshold (POT) occurrences yielded novel insights into anticipated changes to the flow regime. Comparisons of near (2041–2070) and far (2071–2100) future periods with the historical baseline (1981–2010) yielded results that project significant reductions in the 500 m3 s−1 POT during the fall navigability period spanning weeks 34 to 43, as well as reductions in the integrated ANIFall. These results indicate that challenging navigational conditions may become more frequent in the second half of the 21st century, not only during this fall period but also earlier into the summer, due to a shift in the flow regime, with potentially severe impacts on the users of the river channels. Our assessment approach is transferable to other regional study areas and should be considered in water management and environmental flow frameworks.

Abstract Avulsions change river courses and transport water and sediment to new channels impacting infrastructure, floodplain evolution, and ecosystems. Abrupt avulsion events (occurring over days to weeks) are potentially catastrophic to society and thus receive more attention than slow avulsions, which develop over decades to centuries and can be challenging to identify. Here, we examine gradual channel changes of the Peace‐Athabasca River Delta (PAD), Canada using in situ measurements and 37 years of Landsat satellite imagery. A developing avulsion of the Athabasca River is apparent along the Embarras River–Mamawi Creek (EM) distributary. Its opening and gradual enlargement since 1982 are evident from multiple lines of observation: Between 1984 and 2021 the discharge ratio between the EM and the Athabasca River more than doubled, increasing from 9% to 21%. The EM has widened by +53% since 1984, whereas the Athabasca River channel width has remained stable. The downstream Mamawi Creek delta is growing at a discharge‐normalized rate roughly twice that of the Athabasca River delta in surface area. Longitudinal global navigation satellite systems field surveys of water surface elevation reveal the EM possesses a ∼2X slope advantage (8 × 10−5 vs. 4 × 10−5) over the Athabasca River, and unit stream power and bed shear stress suggest enhanced sediment transport and erosional capacity through the evolving flow path. Our findings: (a) indicate that a slow avulsion of the Athabasca River is underway with potentially long‐term implications for inundation patterns, ecosystems, and human use of the PAD; and (b) demonstrate an observational approach for identifying other slow avulsions at river bifurcations globally.

In late 2023 the Surface Water and Ocean Topography (SWOT) satellite mission will release unprecedented high-resolution measurements of water surface elevation (WSE) and water surface slope (WSS) globally. SWOT's exciting Ka-band near-nadir wide-swath interferometric radar (InSAR) technology could transform studies of surface water hydrology, but remains highly experimental. We examine Airborne SWOT (AirSWOT) data acquired twice over Canada's Peace-Athabasca Delta (PAD), a large, low-gradient, ecologically important riverine wetland complex. While noisy and susceptible to "dark water" (low-return) data losses, spatially averaged AirSWOT WSE observations reveal a broad-scale water-level decline of ~44 cmn (σ =271 cm) between 9 July and 13 August 2017, similar to a ~56 cm decline (σ=33 cm) recorded by four in situ gauging stations. River flow directions and WSS are correctly inferred following filtering and reach-averaging of AirSWOT data, but ~10 km reaches are essential to retrieve them. July AirSWOT observations suggest steeper WSS down an alternate flow course (Embarras River–Mamawi Creek distributary) of the Athabasca River, consistent with field surveys conducted the following year. This signifies potential for the Athabasca River to avulse northward into Mamawi Lake, with transformative impacts on flooding, sedimentation, ecology, and human activities in the PAD. Although AirSWOT differs from SWOT, we conclude SWOT Ka-band InSAR observations may detect water level changes and avulsion potentials in other low-gradient deltas globally.

In recognition of the 75th anniversary of the Canadian Water Resources Association (CWRA) in 2022, a Special Issue was proposed to summarize achievements, challenges and future opportunities in themes directly related to Canadian water resources and their management. The solicited papers align with the aim of the CWRA to stimulate public awareness and understanding of Canada’s water resources and provide new or increased knowledge on Canada’s water. With growing concerns over impacts on water resources from a wide range of stressors, the support of a national conversation, as well as sharing knowledge and perspectives on water resources across Canada, has become increasingly important and urgent. This Special Issue presents seven papers that review and/or provide historical sketches from ‘75 years’ of work conducted in Canada across select sub-disciplines of hydrology and water resources.

The Peace–Athabasca Delta (PAD) in western Canada is one of the largest inland deltas in the world. Flooding caused by the expansion of lakes beyond normal shorelines occurred during the summer of 2020 and provided a unique opportunity to evaluate the capabilities of remote sensing platforms to map surface water expansion into vegetated landscape with complex surface connectivity. Firstly, multi-source remotely sensed data via satellites were used to create a temporal reconstruction of the event spanning May to September. Optical synthetic aperture radar (SAR) and altimeter data were used to reconstruct surface water area and elevation as seen from space. Lastly, temporal water surface area and level data obtained from the existing satellites and hydrometric stations were used as input data in the CNES Large-Scale SWOT Simulator, which provided an overview of the newly launched SWOT satellite ability to monitor such flood events. The results show a 25% smaller water surface area for optical instruments compared to SAR. Simulations show that SWOT would have greatly increased the spatio-temporal understanding of the flood dynamics with complete PAD coverage three to four times per month. Overall, seasonal vegetation growth was a major obstacle for water surface area retrieval, especially for optical sensors.

We examined annual runoff from 20 meso‐scale catchments over 25 years, to elucidate how interactions between physiography and long‐term weather patterns influence the magnitude of spatial–temporal thresholds in annual runoff responses in water‐limited, low‐relief, glaciated continental Boreal landscapes. Annual runoff ranged over 2 orders of magnitude (<3 to >300 mm) among catchments receiving similar annual precipitation. Threshold relationships were observed with cumulative regional moisture deficits that reflected spatial–temporal differences in effective storage and antecedent moisture among catchments with differing portions of glacial‐deposit and land‐cover types. The importance of the glacial‐deposit texture and forest‐peatland cover on runoff behavior among catchments varied with weather patterns and catchment antecedent moisture states. Dry states yielded low annual runoff that ranged by 2 orders of magnitude (0–80 mm), with higher values in catchments with predominantly coarse‐textured deposits. During near normal antecedent moisture, annual runoff remained low (<10 mm) in catchments associated with fine‐textured, hummocky landforms and deciduous forests. Annual runoff >10 mm was observed only in catchments with extensive peatlands. Infrequent wet states resulted in increased runoff in all catchments; however, ranges in maximum runoff were associated with heterogeneity in catchment landforms and land covers. Integrating cumulative precipitation with the proportion of glacial‐deposit and land‐cover types within catchments can (a) represent water cycling and regional sink‐source dynamics controlling runoff and (b) provide an effective management framework for predicting climate and land use impacts on regional runoff in water‐limited, low‐relief, glaciated landscapes such as the Boreal Plain.

The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1 year after launch) will provide discharge for all river that reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge time series. We expect that discharge uncertainty will be less than 30% for two‐thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage‐constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge time series will be dominated by random error and are expected to be estimated within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.

The “flood” algorithm code with instruction and details are publicly available at https://github.com/rskelly/flood and as supporting information. The DEM of the PAD is available at https://open.canada.ca/data/en/dataset/03568324-1a8b-4c00-8650-f5c35f6e0bff. Data S1. Supporting Information. Video 1. Broadscale Simulations Video 2. Single Basin Simulation Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Large‐scale, intensive agriculture is a critical activity supporting global food production, yet it has taken a significant toll on the equally critical ecosystem services supplied by global biodiversity. This is particularly true for the planet's most threatened ecosystems: freshwaters. As one of the world's largest agricultural producers, Canada is also home to much of the world's freshwater. As Canada's agricultural capacity expands under climate warming into more northerly latitudes—and in some cases regions with large carbon sinks—it is imperative that this sectoral shift is accompanied by careful management to avoid exacerbating ecosystem service losses. Across Canada, agricultural practices vary in terms of their impact on freshwater ecosystems. Agricultural water extraction, storage behind dams, diversions, dredging and clearing of riparian vegetation can impact more naturalized flow regimes. This review explores the influence of managed low flows on ecosystem functioning in man‐made drainage/irrigation ditch systems. We examine how low flows in these systems can impact ecosystem functions in agricultural watersheds with fragmented natural capital. We provide management options to protect ecosystem functions under a changing climate, recognizing that in agro‐ecosystems, drainage/irrigation ditch systems provide a critical remnant habitat to support biodiversity in otherwise depauperate landscapes.

Boreal lakes ecosystems can remain partially or completely covered by ice and snow during an important portion of the year. Alterations of lake and river ice properties can deteriorate the conditions of local ice roads, negatively influencing Nordic communities and economical activities. Monitoring of lake ice characteristics and dynamics is therefore crucial. In this study, Sentinel-1 Synthetic Aperture Radar (SAR) satellite imagery is exploited to evaluate changes in the ice regime over shallow and deep high-latitude lakes during the winters of 2018 and 2019. The methodology proposed, based on the combined analysis of SAR intensity and interferometric coherence maps, enables the extraction of important characteristics of ice dynamics. Overall, the lake ice thickness change derived from Differential Interferometric SAR (D-InSAR) increases with the lake depth. The D-InSAR-derived mean rate of growth, in general, agrees with the one estimated from records of in-situ ice thickness measurements. The methodology presented herein could be temporally extended to support the understanding of historical and current climate conditions. This could be done by using archived and newly available imagery to improve lake ice models.

Voting is the foundation of a democratic society. In most countries, citizens have to go physically to elections, i.e., to a voting booth to make their decisions with pen and paper. In crisis, like pandemics, war times and other catastrophes, this may be impossible. But there are other examples, like concurrent events on the election day, that create problems. For example, in Berlin, on 2021 German election day, the city marathon took place on the same day, which lead to traffic jams that hindered timely delivery of voting paper. A solution to these challenges is electronic voting (E-Voting), where people can vote digitally from home on a specific device (or even on their smartphones). Actually, IT security mechanisms, like blind signatures, anonymity networks, homomorphic encryption and zero Knowledge Proofs exist, to name just a few, which have already been combined to create secure E-Voting infrastructures. We want to enhance these solutions with an additional feature we call ballot-changing. The three main benefits of our architecture are, firstly, limiting Distributed Denial of Service attacks (DDoS), secondly, the possibility of changing one’s previous vote (ballot-changing), and thirdly, individual auditability, i.e., every voter can make sure that the election result is correct and that their vote has been counted.

Study region: This study is focused on the lower Athabasca Basin in northwestern Canada that has experienced rapid expansion of oil sands development. Study focus: The goal of this study is to enhance the understanding of the regional role of the lower Athabasca Basin areas in overall runoff delivery to the downstream Peace-Athabasca Delta. The Cold-regions Hydrological Indicators of Change framework was applied to examine key hydro-ecological relevant indicators influencing the delta. New hydrological insights for the region: Our novel approach yielded new insights that should be considered in water management. Primarily, a combined flow magnitude and relative flow contributions analysis by geography provides an improved understanding of contrasting runoff generation changes, in terms of opposing responses occurring within a basin. For instance, open-water low flows emanated from the upper regions and a generally increasing tendency from the lower regions. Furthermore, peak summer flows generally experienced decreases from the upper and portions of the lower basin, while contrary increasing tendencies emerged for the east bank of the lower Athabasca River mainstem. Moving beyond the traditional approach of looking only at the climate, landscape and geology were considered as potential causal factors for divergent runoff generation responses. Our approach is transferable to other regional studies.