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A large portion of Canada is covered by wetlands; mapping and monitoring them is of great importance for various applications. In this regard, Remote Sensing (RS) technology has been widely employed for wetland studies in Canada over the past 45 years. This study evaluates meta-data to investigate the status and trends of wetland studies in Canada using RS technology by reviewing the scientific papers published between 1976 and the end of 2020 (300 papers in total). Initially, a meta-analysis was conducted to analyze the status of RS-based wetland studies in terms of the wetland classification systems, methods, classes, RS data usage, publication details (e.g., authors, keywords, citations, and publications time), geographic information, and level of classification accuracies. The deep systematic review of 128 peer-reviewed articles illustrated the rising trend in using multi-source RS datasets along with advanced machine learning algorithms for wetland mapping in Canada. It was also observed that most of the studies were implemented over the province of Ontario. Pixel-based supervised classifiers were the most popular wetland classification algorithms. This review summarizes different RS systems and methodologies for wetland mapping in Canada to outline how RS has been utilized for the generation of wetland inventories. The results of this review paper provide the current state-of-the-art methods and datasets for wetland studies in Canada and will provide direction for future wetland mapping research. [ABSTRACT FROM AUTHOR]

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Snow is a vital component of the earth system, yet no snow-focused satellite remote sensing platform currently exists. In this study, we investigate how synthetic observations of snow water equivalent (SWE) representative of a synthetic aperture radar remote sensing platform could improve spatiotemporal estimates of snowpack. We use a fraternal twin observing system simulation experiment, specifically investigating how much snow simulated using widely used models and forcing data could be improved by assimilating synthetic observations of SWE. We focus this study across a 24∘×37∘ domain in the western USA and Canada, simulating snow at 250 m resolution and hourly time steps in water year 2019. We perform two data assimilation experiments, including (1) a simulation excluding synthetic observations in forests where canopies obstruct remote sensing retrievals and (2) a simulation inferring snow distribution in forested grid cells using synthetic observations from nearby canopy-free grid cells. Results found that, relative to a nature run, or assumed true simulation of snow evolution, assimilating synthetic SWE observations improved average SWE biases at maximum snowpack timing in shrub, grass, crop, bare-ground, and wetland land cover types from 14 %, to within 1 %. However, forested grid cells contained a disproportionate amount of SWE volume. In forests, SWE mean absolute errors at the time of maximum snow volume were 111 mm and average SWE biases were on the order of 150 %. Here the data assimilation approach that estimated forest SWE using observations from the nearest canopy-free grid cells substantially improved these SWE biases (18 %) and the SWE mean absolute error (27 mm). Simulations employing data assimilation also improved estimates of the temporal evolution of both SWE and runoff, even in spring snowmelt periods when melting snow and high snow liquid water content prevented synthetic SWE retrievals. In fact, in the Upper Colorado River region, melt-season SWE biases were improved from 63 % to within 1 %, and the Nash–Sutcliffe efficiency of runoff improved from -2.59 to 0.22. These results demonstrate the value of data assimilation and a snow-focused globally relevant remote sensing platform for improving the characterization of SWE and associated water availability. [ABSTRACT FROM AUTHOR]

We examined soil properties and accumulation rates over the last ca. 100 years in four swamps and four marshes in southern Canada where these wetlands are common but under increasing anthropogenic pressure. One 50‐cm long core was collected from each wetland and analyzed to determine bulk density (BD) and organic matter (OM). Lead‐210 and cesium‐137 dating were used to estimate sediment accumulation rates. In the datable portion of each core, we determined the organic carbon (Corg), nitrogen (N), Corg/OM, Corg/N, Corg density, Corg stocks, and Corg accumulation rates. All parameters but one—Corg accumulation rates—were significantly different in swamps compared to marshes and between seasonally wet soils and those regularly flooded. Since 1950, Corg stocks varied from 6 to 13.6 kg m−2 with ≈23% more Corg in swamps than in marshes. When hydrology and deeper soils where considered, Corg stocks in regularly flooded wetlands were 60% higher than those of seasonally wet systems, emphasizing the role of hydrology in building up C stocks long‐term. Our measurements are within the wide range reported for similar systems in North America. The average rate of Corg accumulation in the studied wetlands (112 ± 87 g m−2 yr−1) is ≈50% higher than that of oligotrophic/ombrotrophic peatlands, but ≈47% lower than in tidal marshes from eastern Canada. Our study lends support to the case for wetland restoration through re‐wetting as an important nature‐based climate solution for mitigation of GHG emissions in areas where they were drained for agriculture and other purposes. Plain Language Summary: Wetlands are important ecosystems because they have an enhanced capacity to extract carbon dioxide—a greenhouse gas—from the atmosphere and store it in the ground as partly decomposed plant carbon. This ground storage is vital because it keeps carbon dioxide from increasing in the atmosphere where it causes global warming. Among the Earth's wetlands, freshwater marshes and swamps from temperate climates are among the least understood. To address this limitation, we conducted a study in southern Canada, where these wetlands are common but under increasing pressure from farming and urban development. Our results indicate that while marshes (dominated by grasses and sedges) form mostly mineral soils with less carbon stocks than swamps (vegetated with shrubs and trees), which form organic soils, the rate at which they accumulate carbon in their soil is similar. We also show that the wetlands we studied are 50% more effective in storing carbon than the cold climate bogs (vegetated by mosses), but they are less effective than salt marshes which form along the shores of temperate seas. We suggest that if freshwater marshes and swamps are protected, they can be important natural solutions in the mitigation of carbon dioxide emitted by human activity. Key Points: Carbon stocks in eight nutrient‐rich freshwater wetlands ranged 18–40 kg m−2, with organic soils averaging ≈60% more than mineral soilsMean carbon accumulation rate over the last 100 years was 112 g m−2 yr1, with no significant differences between swamps and marshesCarbon accumulation rates were higher than in oligotrophic/ombrotrophic wetlands (bogs) but lower than in tidal salt marshes [ABSTRACT FROM AUTHOR]

Wetland drainage has been pervasive in the North American Prairie Pothole Region. There is strong evidence that this drainage increases the hydrological connectivity of previously isolated wetlands and, in turn, runoff response to snowmelt and rainfall. It can be hard to disentangle the role of climate from the influence of wetland drainage in observed records. In this study, a basin-classification-based virtual modelling approach is described that can isolate these effects on runoff regimes. The basin class which was examined, entitled Pothole Till, extends throughout much of Canada's portion of the Prairie Pothole Region. Three knowledge gaps were addressed. First, it was determined that the spatial pattern in which wetlands are drained has little influence on how much the runoff regime was altered. Second, no threshold could be identified below which wetland drainage has no effect on the runoff regime, with drainage thresholds as low as 10 % in the area being evaluated. Third, wetter regions were less sensitive to drainage as they tend to be better hydrologically connected, even in the absence of drainage. Low flows were the least affected by drainage. Conversely, during extremely wet years, runoff depths could double as the result of complete wetland removal. Simulated median annual runoff depths were the most responsive, potentially tripling under typical conditions with high degrees of wetland drainage. As storage capacity is removed from the landscape through wetland drainage, the size of the storage deficit of median years begins to decrease and to converge on those of the extreme wet years. Model simulations of flood frequency suggest that, because of these changes in antecedent conditions, precipitation that once could generate a median event with wetland drainage can generate what would have been a maximum event without wetland drainage. The advantage of the basin-classification-based virtual modelling approach employed here is that it simulated a long period that included a wide variety of precipitation and antecedent storage conditions across a diversity of wetland complexes. This has allowed seemingly disparate results of past research to be put into context and finds that conflicting results are often only because of differences in spatial scale and temporal scope of investigation. A conceptual framework is provided that shows, in general, how annual runoff in different climatic and drainage situations will likely respond to wetland drainage in the Prairie Pothole Region. [ABSTRACT FROM AUTHOR]

Some wetlands in the northern Great Plains support hundreds to thousands of late-stage tadpoles providing important sources of recruitment to the Wood Frog (Lithobates sylvaticus) population while many other wetlands produce none. Relationships between water quality and late-stage tadpole abundance were determined to identify the water quality parameters associated with tadpole abundance. Water samples were collected, and late-stage tadpole abundances were assessed once each year in late June for 12 years in 26 wetlands. Catch or abundance was the number of tadpoles captured in 30 min with a dip-net. The catch of tadpoles was variable both among wetlands and over the long-term for individual wetlands, and ranged from 0 to several hundred individuals. Wood Frog tadpoles were especially sensitive to sodium and chloride concentrations. At Cl concentrations less than 5 mg/L, occupancy for late-stage tadpoles was 84%, and declined by about 8% for each 5 mg/L increase in Cl to 40.1 mg/L Cl, the maximum concentration associated with the detection of tadpoles. Optimal water quality for late-stage Wood Frog tadpoles included low concentrations of Na (x ¯ = 8.1 mg/L), and Cl (x ¯ = 4.2 mg/L) relative to total dissolved solids and other ions, and high concentrations of phosphorus. In a landscape where ion concentrations in wetlands can range over 3 orders of magnitude, water quality analyses suggest that abundant Wood Frog tadpole populations occur in wetlands dominated by snow-melt runoff with its characteristic low ion concentrations. The present study highlights the importance to amphibian conservation of the water quality environment of tadpole habitat. [ABSTRACT FROM AUTHOR]