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Advancements in global satellite missions have revolutionized the assessment of Surface Soil Moisture (SSM) at global to local scales. However, spatio-temporal data discontinuities in specific regions remain a challenge. This study proposes a Machine Learning (ML)-based framework to extend the Soil Moisture Ocean Salinity (SMOS) SSM product both in the spatial and temporal domains, over Canada. In the first phase of the proposed framework, ML models based on Random Forest (RF) and Convolutional Neural Networks (CNN) are trained and validated with SMOS SSM as target and SSM-relevant climatic variables and geophysical variables, obtained from fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA5), for the 2011–2020 period, as predictors. Developed models, when tested on unseen data for the years 2021–2022, suggest slightly better performance of the RF model compared to CNN, with root mean square error (RMSE) of 0.033 and 0.056 respectively; prediction biases mostly noted for regions with large inter-annual variability. The spatial filling of SSM for grid cells that were excluded during the training process, with similar land types as those in the SMOS training data, yields reasonable performance, with RF (RMSE = 0.013) performing better than CNN (RMSE = 0.064). In the second phase, the RF model is selected to extend the SMOS dataset for the 2008–2010 period. The temporal correlation between extended SMOS and ASCAT (Advanced Scatterometer) SSM demonstrates a reasonable association, with correlation coefficient exceeding 0.6. Additionally, spatial correlation analysis reveals similar patterns between the two datasets, with smaller values for the summer season owing to the importance of local processes on SSM during this period. However, extending SMOS SSM spatially for surface types that were not included in the training process such as peatlands, remains a challenge warranting additional studies. The developed framework is robust and can address spatio-temporal discontinuities in other SSM products. [ABSTRACT FROM AUTHOR]

The most rapid climate warming is occurring in northern, permafrost environments. Peatlands of these regions are particularly sensitive to climate warming, with the high ground ice content of peat plateaux resulting in the formation of collapse scars as ground temperatures warm.To quantify the rates of permafrost thaw and associated vegetation changes, we sampled the plant and lichen communities in transects spanning actively thawing collapse scar margins at sites from mid‐Boreal to Low Subarctic conditions, within Canada's Northwest Territories. Seventeen transects were sampled in 2007/08 and 14 of these were resampled 10 years later.The rate of lateral permafrost thaw of collapse scar margins ranged from −6 to 63 cm year−1 (mean: 22.0 cm ± 4.7 cm year−1 (SE)); variability was high and no trends with respect to latitude or temperature gradients were detected.Plant communities displayed a clear gradient from lichen‐ and ericaceous shrub‐dominated peat plateaux, to collapse scars primarily characterized by Sphagnum mosses and graminoids. Both space‐for‐time (distance from collapsing margin) and direct measurement of 10‐year changes showed a successional sequence following permafrost thaw; floating mat communities characterized by Sphagnum riparium or S. balticum proceeded to lawn communities of S. angustifolium and, finally, to hummock communities with Mylia anomala or S. fuscum. This successional sequence was associated with increased water table depth and lower soil water content in plant communities farther from the actively collapsing front, illustrating that peat growth above the water table was driving plant community successional changes.The most rapid plant community succession occurred in recently thawed environments as peat growth propelled the ground surface above the water table while the slowest succession occurred in the collapse scar hummock communities located farthest from the actively collapsing peat plateau margin.Synthesis. In just 10 years, significant vegetation change was detected, in association with both permafrost thaw and subsequent plant community succession. These changes occurred across a broad climatic and latitudinal gradient, from mid‐Boreal to Low Subarctic and have implications for wildlife, global C cycle and indigenous communities who depend on this landscape for harvesting, spiritual and cultural practices. [ABSTRACT FROM AUTHOR]

Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought‐induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi‐day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short‐term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability. Plain Language Summary: This research explores how climate change could impact the water stress experienced by black spruce and tamarack trees in the western boreal forest of Canada. We focused on a key measure called "tree water deficit" to understand if the trees were under stress due to insufficient water. We examined how tree water deficit relates to environmental factors such as temperature, sunlight, and soil moisture. The findings revealed that, on a daily basis, factors like sunlight and temperature cause trees to release more water into the air. However, over longer periods (days to weeks), the amount of water in the soil becomes crucial, suggesting that trees might face water stress during dry spells. So, while trees could grow more on hotter, sunnier days, they could also experience water stress and reduced growth if the soil becomes too dry for an extended period. This study helps us grasp how various factors interact to influence tree water stress in the boreal forest, providing insights important for managing these ecosystems in a changing climate. Key Points: A novel approach to determine environmental controls of tree water deficit across time scales with wavelet analysis and Granger causalitySoil moisture emerges as a significant control of tree water deficit in boreal trees at longer scales (multi‐days)Daily productivity gains with warming will be mitigated by decreased soil water availability in longer periods of tree water deficit [ABSTRACT FROM AUTHOR]

The evolutionary dynamics of tree species are influenced by their specific climatic environments, and their ability to persist is determined by adaptive strategies such as broad climate tolerance, phenotypic plasticity or genetic differentiation. Biogeographical predictions indicate that populations located at the edges of their ranges are more likely to experience heightened vulnerability to climatic fluctuations due to approaching tolerance limits. However, if local phenotypic acclimation or genetic adaptation has taken place, trees near the edge of their range could demonstrate comparable sensitivity to freeze and drought as the rest of the sampled population. Nevertheless, there remains uncertainty regarding the extent of developmental and evolutionary adjustments in climate sensitivity across the entire ranges of many tree species.Here, we document the biogeography of tree growth sensitivity to freeze and soil water and vapour pressure deficits during 1950–2018 using an extensive multi‐species tree‐ring dataset of 35,784 trees at 4535 sites covering boreal, temperate conifer and temperate deciduous forests of Canada. We quantify the relationships between tree radial growth increment and seasonal climate variables and explore factors driving the observed patterns of annual growth and climate sensitivity such as species, regional climate and local site conditions, and tree age and size.Freeze and drought had widespread impacts on tree growth that were contingent on the presence of focal species in interaction with tree size. An indirect growth thermal limitation towards cold/wet edges, occurring through the site moisture conditions, was observed in seven widespread species (e.g. Picea glauca, Picea mariana and Larix laricina). Moreover, six species had negative drought impacts more strongly expressed towards their warm/dry edges (e.g. Abies balsamea, Betula papyrifera and Pseudotsuga menziesii). However, widespread Picea, Pinus and Populus species showed no indication of increased sensitivity to soil water conditions at these edges.Synthesis. Our findings support the idea of evolutionary or acclimatization adjustments in the development of populations in response to long‐term climate conditions experienced in their respective locations. This underscores the importance of incorporating phenotypic and genomic data into future analyses of climate change impacts, which would enhance our ability to predict potential ecological shifts. [ABSTRACT FROM AUTHOR]

When extracting peat for horticultural use, drainage ditches are prepared, a peatland's vegetation is removed, and peat is harvested. These land-use changes dramatically alter the carbon, water, and energy exchanges of the peatland and convert it from a moderate sink to a large source of CO2. We adapted the CoupModel to simulate the soil CO2 emission and its associated abiotic drivers for an ongoing horticultural peat extraction site, located in Riviére-du-loup (RdL), Quebec Canada. The model outputs were first evaluated against three years (2019–2021) of manual chamber measurements of CO2 flux, and soil moisture, soil temperature profiles, and water table depth data. The model was then used to assess the sensitivity of key parameters and changes in climate forcing. CoupModel reproduced the measured soil moisture and temperature profile and showed high agreement with the water table depth and soil CO2 emissions data. Sensitivity analysis showed the importance of soil moisture availability at the soil surface on soil thermal and hydrological conditions, thus soil respiration. The simulated CO2 emission over the three evaluation years was about 168 and 151 g C m−2 y−1 when extended with seven-year of climate data. Emission factors of CO2 generated by CoupModel are lower than the default IPCC Tier 1 emission factor for peatland managed for horticultural extractions in temperate/boreal climate. Results from this modeling work can be used for IPCC Tier 3 emission reporting for the horticultural peat extraction industry, addressing land-use change issues of peatlands, and suggesting climate-smart management practices. [ABSTRACT FROM AUTHOR]

One important problem in implementing a closed-loop irrigation system is the determination of the optimal locations to install the sensors, both vertically and horizontally, such that improved pressure head estimation can be obtained. In this work, we find the best locations of the sensors in terms of degree of observability in an actual field and investigate whether the optimal sensor placement can significantly improve the pressure head estimation performance in actual applications. We investigate the impact of sensor placement in pressure head estimation for an actual agricultural field in Lethbridge, Alberta, Canada. In an experiment on the studied field, 42 watermark sensors were installed at different depths to collect the soil water tension measurements. A three-dimensional agro-hydrological model with heterogeneous soil parameters of the studied field is set up. The modal degree of observability is applied to the three-dimensional system to determine the optimal sensor locations. The extended Kalman filter (EKF) is chosen as the data assimilation tool to estimate the pressure head of the studied field. Pressure head estimation results for different scenarios are obtained and analyzed to investigate the effects of sensor placement on the performance of pressure head estimation in the actual applications. Estimation results indicate that optimally placed sensors reduce the average root mean square error by about 30% compared to the case the sensor positions are selected randomly. [ABSTRACT FROM AUTHOR]

Infrared spectroscopy can separate carbon sugars and amino sugars that have collapsed in soil water very quickly. In this study, the midinfrared (MIR) and near-infrared (NIR) spectra collected from soil water isolates or soil masses are sentenceless, assessing different agricultural groupings of flooded carbon and aminosaccharides. Soil was collected from five fields in two regions in western Canada and two regions in eastern Canada, where least squares backslide (PLSr) was inadequate. The inverted model of DOC recovery at the Eastern Peace River estuary can provide the optical functionality of traditional systems. The introduction of overflow DOCs from various sources rather than distance meters has been found to be a major contributor to the complexity of optical neighborhoods, resulting in a bias in DOC evaluation. The impact of voluntary DOC liability on the relationship between DOC and CDOM can be forgotten at a critical turn in the CDW. A slightly mitigating approach can overlook the impact of voluntary DOC responsibility on the relationship between DOC and CDOM. CDW is responsible for the continued responsibility of the Subei coastal currents for the normal material of the former Yellow Sea Delta, for the warm West Coast currents of the Yellow Sea for the materials of the Yellow Sea, and for the materials of the Changjiang Basin. The results of this study more thoroughly assess the state differences of DOM inputs from different sources within the CDW to determine the magnitude of the impact on DOC evaluation across the East China Sea CDOM. It suggests that it is necessary. [ABSTRACT FROM AUTHOR]

Recently, incentives have been provided in many countries, including Canada and Denmark, to produce biochar for construction usage. This is done because biochar is carbon negative and can help achieve the emission reduction goal of 2030. This technical note aims to analyse the efficiency of biochar in soils with varying grain size distributions for enhancing soil–water characteristic curve (SWCC). The combinations of biochar content and grain size distributions corresponding to the maximum and minimum efficiencies were explored. Artificial neural network-based model for predicting SWCC as a function of soil suction and grain size distribution was developed. A new factor (the ratio of fine (silt + clay) and coarse (sand) content) was proposed for the interpretation of the efficiency of biochar in soils. The newly developed model is able to predict SWCC reasonably well. Biochar amendment is found to influence both dry and wet sides of soils with a clay content lower than threshold content (6–8%). Beyond threshold content, the influence of biochar appears to reduce. However, in the case of high sand content soils (90%), the normalized water content value on the drier side is generally higher as compared to soils with lower sand content. Based on the sensitivity analysis, it was found that the ratio of fine to sand content is the most influential, while biochar content is the least influential. [ABSTRACT FROM AUTHOR]

Detailed knowledge of groundwater storage improves the understanding and management of water resources. Observations from Gravity Recovery and Climate Experiment (GRACE) satellites have provided data on global terrestrial-water-storage (TWS) changes since 2002. Combining GRACE-TWS and land-surface model (LSM) estimates of soil water, snow-water equivalent and surface-water storage provides a method to quantify groundwater storage (Wground). This study examines the Wground seasonal variations and trends for Canada's landmass during the period 2003–2016 using GRACE-TWS and the Canadian LSM EALCO (Ecological Assimilation of Land and Climate Observations) model. The results show the study region has a maximum seasonal variation (ΔWground) of 118 mm (volume equivalent 700 km3), with the maximum/minimum Wground appearing in July/April. Eastern Canada has relatively large ΔWground values, up to 400 mm in Newfoundland. The Prairie region has the smallest value (<50 mm). The western and central regions show the maximum/minimum Wground mostly in spring/fall. In contrast, eastern Canada has the maximum/minimum Wground mostly in fall/spring. South Ontario and the Prairie area show the maximum/minimum Wground in summer/winter. Additionally, the Wground trends over the 14-year study period present large spatial variability, with increasing trends of up to 10 mm/year in eastern Canada and decreasing trends (similar magnitudes) in the west. The increasing trend largely offsets the decreasing trend in the study area, and the overall Wground for the region does not show a significant trend during 2003–2016. Comparison of Wground with groundwater well measurements present similar long-term trends but with a phase difference in seasonal variations. [ABSTRACT FROM AUTHOR]

Groundwater recharge (GR) is a complex process that is difficult to quantify. Increasing attention has been given to unsaturated zone modeling to estimate GR and better understand the processes controlling it. Continuous soil-moisture time series have been shown to provide valuable information in this regard. The objectives of this study were to (i) analyze the processes and factors controlling GR in an unconfined granular aquifer in a cold and humid environment and (ii) assess the uncertainties associated with the use of data from different sources. Soil moisture data monitored over three years at three experimental sites in southern Quebec (Canada) were used to calibrate the HYDRUS-1D model and to estimate ranges of possible GR in a region where groundwater is increasingly used as a source of fresh water. The simulations identified and quantified important factors responsible for the near-surface water balance that leads to GR. The resulting GR estimates from 2016 to 2018 showed marked differences between the three sites, with values ranging from 347 to 735 mm/y. Mean GR for the three sites was 517 mm/y for 2016–2018 and 455 mm/y for the previous 12-year period. GR was shown to depend on monthly variations in precipitation and on soil textural parameters in the root zone, both controlling soil-water retention and evapotranspiration. Monthly recharge patterns showed distinct preferential GR periods during the spring snowmelt (38–45% of precipitation) and in the fall (29% of precipitation). The use of different meteorological datasets was shown to influence the GR estimates. [ABSTRACT FROM AUTHOR]

Reinforced concrete is a commonly used material for constructing basements in low-rise buildings or residential houses in Canada, and as the use of cross-laminated timber (CLT) advances, the door to think of an alternative basement material to offset greenhouse gas emissions associated with reinforced concrete is open. However, the evaluation of CLT durability in below-grade environments, specifically concerning moisture and mould development, remains an unexplored field in research. Hence, this paper aims to analyze CLT's moisture response and mould growth risk in below-grade environments using field and laboratory experiments. A laboratory experiment was carried out to test a waterproofing membrane solution selected to compose the wall assembly in the field experiment. A large-scale experimental CLT basement was built at a cohesive soil site in Edmonton, Canada. The field experiment involved monitoring the relative humidity, temperature, and soil volumetric water content of the CLT panels, which measure 3 m by 6 m in plan and 2 m deep. Data was collected for an extended period from June 2022 to July 2023. The VVT model, developed by Hukka and Viitanen (1999) and updated by Viitanen et al., 2011 to estimate the mould growth level, was used to predict the risk of mould growth. The laboratory experiment showed that the waterproofing membrane is suitable for protection against moisture in a still-water setup. Field experiment results suggested that the primary moisture source was below the basement floor when the floor was finished inadequately. The moisture content of CLT walls was significantly increased by floor flooding and decreased by heating the basement interior. The acceptable mould index of three was surpassed during periods of abundant water below the basement floor due to flood events, showing that the CLT panels were at risk of mould growth development. • CLT use inbasements is in research stage. This paper contains insights for developing future research on this subject. • CLT in basement construction requires robust envelope with waterproofing membranes that perform well below grade. • Elevated moisture levels could pose structural and biological risks to the CLT basement and its occupants. • CLT basement walls take time to dry, and during this period, the walls may be exposed to risky levels of mould growth. [ABSTRACT FROM AUTHOR]

Habitat disturbance can promote the invasion success of alien species, but the underlying mechanisms remain unclear, especially in animal species. Alien species may have trait values that facilitate invasion (ideal weed hypothesis) or greater phenotypic plasticity than native species (plasticity hypothesis), thus promoting their invasion success in disturbed habitats. Invasion success and ultimately alien species dominance in disturbed habitats can also be a direct consequence of competitive exclusion of native species. We performed experiments in controlled conditions to determine which of these mechanisms could explain the invasion success of Arion subfuscus s.l. (hereafter Arion), an alien slug species complex that lives in various disturbed ecosystems of eastern Canada such as managed forests. To do so, we compared the behavioural response of Arion and native sympatric philomycid slugs (hereafter Philomycus) to a decrease in soil moisture content, which often occurs after forest harvesting (i.e. habitat disturbance). We also investigated whether the presence of Arion alters the behaviour of Philomycus , which would indicate that Arion has a greater ability to compete by interference than these native species. Our findings show that Arion did not have higher boldness or locomotor activity (i.e. behaviours that promote invasion success) or greater plasticity than Philomycus , and that the presence of Arion did not affect the behaviour of Philomycus. However, Arion may be able to exploit resources more efficiently than native species since it mainly used the closest refuge from the food source in the present study. These findings are in line with the ideal weed hypothesis but do not support the phenotypic plasticity hypothesis or any role of interference competition in Arion invasion success in disturbed habitats such as harvested forests. Our results also suggest that the direction, but not the magnitude, of behavioural plasticity might be a key aspect in alien species invasion success in disturbed habitats. • Alien slugs were not bolder or more active than native species. • Plasticity of these behaviours was not higher in alien slugs than in native slugs. • Interference competition does not seem to be involved in alien slug invasion success. • Alien slugs may be more efficient in exploiting resources than native species. [ABSTRACT FROM AUTHOR]

Rising temperatures in the southern Arctic region are leading to shrub expansion and permafrost degradation. The objective of this study is to analyze the surface energy budget (SEB) of a subarctic shrub tundra site that is subject to these changes, on the east coast of Hudson Bay in eastern Canada. We focus on the turbulent heat fluxes, as they have been poorly quantified in this region. This study is based on data collected by a flux tower using the eddy covariance approach and focused on snow-free periods. Furthermore, we compare our results with those from six Fluxnet sites in the Arctic region and analyze the performance of two land surface models, SVS and ISBA, in simulating soil moisture and turbulent heat fluxes. We found that 23% of the net radiation was converted into latent heat flux at our site, 35% was used for sensible heat flux, and about 15% for ground heat flux. These results were surprising considering our site was by far the wettest site among those studied, and most of the net radiation at the other Arctic sites was consumed by the latent heat flux. We attribute this behavior to the high hydraulic conductivity of the soil (littoral and intertidal sediments), typical of what is found in the coastal regions of the eastern Canadian Arctic. Land surface models overestimated the surface water content of those soils but were able to accurately simulate the turbulent heat flux, particularly the sensible heat flux and, to a lesser extent, the latent heat flux. Significance Statement: Isostatic uplift after the last deglaciation led to the emergence of beaches, which represent a large area in the Canadian Arctic. We studied the surface energy budget of such a beach that emerged 6000 years ago in northeastern Canada. Results suggest that evaporation is up to 20% less than at previously studied sites, which is explained by sandy soils retaining little moisture despite abundant precipitation. Deployed numerical models showed difficulties in simulating the soil conditions but proved successful in simulating the surface energy budget after manual adjustments of the soil conditions. These simulation difficulties probably apply to other parts of the Canadian Arctic, possibly leading to errors in meteorological and climate forecasting. [ABSTRACT FROM AUTHOR]

A 3-year study was conducted to determine the irrigation requirements for field tomato production in southwestern Ontario, Canada. Irrigation requirements were ascertained using both a weather-based crop water model, and data from soil moisture sensors. The equivalent irrigation depth applied based on real-time soil moisture measurements among four soil moisture treatments ranged from 102 to 168 mm, 85 to 190 mm, and 58 to 196 mm for 2008, 2009, and 2010, respectively. Using the crop simulation model—AquaCrop, the net irrigation water requirement (NIWR) was estimated as 163–236 mm over the 3-year period. The model overestimated the NIWR compared to the real-time sensor-based measurements. A comparison between these two approaches indicated that a soil moisture depletion of ≤ 45% available water content (AWC) resulted in adequate moisture to meet crop water requirements, and correspondingly produce higher crop yields. From this study, we conclude that real-time soil moisture sensors proved to be very effective for scheduling irrigation of processing tomatoes in Eastern Canada and leads to higher water savings. [ABSTRACT FROM AUTHOR]

Stagnating potato tuber yields in Prince Edward Island (PEI) are a major economic concern. Identification of factors influencing within-field yield variation may provide insight into strategies for overcoming yield limitations. A survey approach was used where soil samples were collected from 49 commercial fields from 2014 to 2017 from a total of 289 sampling points, with points identified as having either "high" or "low" yield, determined by yield monitor as being 5.6–11.2 t ha−1 above or below average field yield, respectively. A suite of 33 measures of soil physical and chemical properties and soil pathogens were measured. Principal component analysis identified three principal components (PCs) which accounted for 85.6% of the total variation. The PC1 (reflecting 42.3% of the total variance) was associated primarily with soil texture (i.e., sand, clay) and parameters which were highly correlated with soil texture. Under the rainfed potato production on sandy-loam soils in PEI, finer soil texture is likely related to increased yield through its effect on improved soil water holding capacity. The PC2 (reflecting 29.0% of the total variance) was primarily associated with soil fertility and the PC3 (reflecting 14.4% of the total variance) was associated primarily with soil organic matter quality and soil structure. Although soil pathogens were measured at levels high enough to impact yield, they did not differ significantly between high and low yield locations. The findings of this study highlight the value in using multivariate approaches to overcome the challenges in identifying factors which control within-field yield variability. [ABSTRACT FROM AUTHOR]

The recent widespread expansion of deciduous shrubs across much of the Arctic has been largely attributed to climate warming. This study investigated decadal growth rates of dwarf birch (Betula glandulosa) across a low Arctic landscape in the continental interior of Canada. Detailed birch cover (100 m2 replicate plots) and individual shrub stature measurement datasets for five representative habitat-types were compared between 2006 and 2016, and evaluated in relation to environmental characteristics. Furthermore, dendrochronologically-based annual growth rates were assessed in relation to the 20-year climate record. Birch height, lateral dimensions, and patch groundcover all increased 20–25% relative to 2006 values, but these increases were similar among the habitat-types. Together, the limited evidence of recent warming at this site, the absence of significant habitat-type growth rate differences, and the lack of correlation between annual climate and stem secondary growth strongly suggest that climate change was not the principal cause. Instead, we propose that release from caribou impacts following the recent severe herd decline may explain the net shrub growth. Individual shrub growth rates were correlated with soil nutrient availability, but the latter was highly variable, suggesting that growth rates are primarily determined by fine-scale rather than habitat-scale spatial heterogeneity in nutrient supply. Together, our results demonstrate that birch growth has been enhanced across a variety of habitat-types in the Daring Lake landscape over the decade since 2006, and suggest that the recent severe caribou herd declines may be at least as significant as climate warming in driving birch shrub expansion in the Canadian central low Arctic. [ABSTRACT FROM AUTHOR]

Profiles of the stable isotope ratios of pore water within the vadose zone provide fingerprints of the history of water percolation into a soil. These profiles, combined with profiles of the volumetric water content, can determine the timing and amount of water that has percolated during specific periods. This study aims to: (1) understand water percolation at two sites in Quebec (Canada) that experience thick snow coverage during the winter season; (2) calculate groundwater recharge rates using the peak-shift method; and (3) estimate the transpiration rate based on the water balance budget. A 7-m-deep borehole was drilled at two sites: one site is sparsely covered by vegetation (S1), while the second underlies a pine forest (S2). For all subsamples, δ18O and δ2H from the soil pore water were analyzed, volumetric water content of the cores was measured, and grain-size analyses to estimate the hydraulic properties were performed. For both boreholes, the winter–spring and summer–autumn periods were determined. Given the limited evapotranspiration occurring during the winter–spring period, recharge rates were high at both sites (71 and 75%), while the summer–autumn period had lower recharge rates of 63% (S1) and 41% (S2). A transpiration rate of 0.7 mm/day was estimated for the pine trees covering site S2. This study provides new field observations for estimating recharge based on water stable isotope profiles in a humid northern region dominated by snowmelt. Moreover, it confirms the accuracy of the peak-shift method for assessing groundwater recharge and estimating transpiration. [ABSTRACT FROM AUTHOR]

Dryland ecosystems may be especially vulnerable to expected 21st century increases in temperature and aridity because they are tightly controlled by moisture availability. However, climate impact assessments in drylands are difficult because ecological dynamics are dictated by drought conditions that are difficult to define and complex to estimate from climate conditions alone. In addition, precipitation projections vary substantially among climate models, enhancing variation in overall trajectories for aridity. Here, we constrain this uncertainty by utilizing an ecosystem water balance model to quantify drought conditions with recognized ecological importance, and by identifying changes in ecological drought conditions that are robust among climate models, defined here as when >90% of models agree in the direction of change. Despite limited evidence for robust changes in precipitation, changes in ecological drought are robust over large portions of drylands in the United States and Canada. Our results suggest strong regional differences in long‐term drought trajectories, epitomized by chronic drought increases in southern areas, notably the Upper Gila Mountains and South‐Central Semi‐arid Prairies, and decreases in the north, particularly portions of the Temperate and West‐Central Semi‐arid Prairies. However, we also found that exposure to hot‐dry stress is increasing faster than mean annual temperature over most of these drylands, and those increases are greatest in northern areas. Robust shifts in seasonal drought are most apparent during the cool season; when soil water availability is projected to increase in northern regions and decrease in southern regions. The implications of these robust drought trajectories for ecosystems will vary geographically, and these results provide useful insights about the impact of climate change on these dryland ecosystems. More broadly, this approach of identifying robust changes in ecological drought may be useful for other assessments of climate impacts in drylands and provide a more rigorous foundation for making long‐term strategic resource management decisions. [ABSTRACT FROM AUTHOR]

Electromagnetic induction (EMI) is a non-destructive technique to measure the apparent electrical conductivity (ECa) of agricultural soils. It has become popular in precision agriculture applications to estimate crop yield from ECa. This study was conducted to relate ECa with soil moisture content (θv) and potato tuber yield under Prince Edward Island (PEI), Canada growing conditions and to establish a two-layered soil model for ECa. During year one, horizontal co-planar (HCP), perpendicular co-planar (PRP), and θv were measured with DUALEM-2 sensor and time domain reflectometry (TDR) probe and correlated with yield measured from 12 m2 grids at 40 locations in each of the two potato fields on PEI. During 2018, vertical electrical sounding was undertaken by raising the DUALEM-2 from ground-level at 0.2 m intervals to a height of 1.6 m to investigate variations in ECa with soil depth. A two-layered soil model was developed using generalized reduction gradients to determine the surficial conductivity and thickness, and subsurface conductivity. ECa variables (HCP and PRP), θv, and yield were significantly correlated and remained consistent throughout the study period, indicating their potential in predicting potato tuber yield. ECa in the fields varied both spatially and laterally with depth. GIS interpolated maps of a representative set of data for HCP and tuber yield (2017 data) showed structured spatial patterns and thus feasibility for delineating management zones. Further studies should examine the potato root zone (0.15–0.3 m) ECa specifically for developing higher layered models, which may be useful for accurate prediction of tuber yield. Non-destructive and accurate yield mapping using DUALEM-2 sensor combined with mathematical modelling of soil ECa layering has potential for use in developing management zones in potato fields. [ABSTRACT FROM AUTHOR]

Traditionally, hydrological models are only calibrated to reproduce streamflow regime without considering other hydrological state variables, such as soil moisture and evapotranspiration. Limited studies have been performed on constraining the model parameters, despite the fact that the presence of a large number of parameters may provide large degree of freedom, resulting in equifinality and poor model performance. In this study, a multi-objective optimization approach is adopted, and both streamflow and soil moisture data are calibrated simultaneously for an experimental study basin in the Saskatchewan Prairies in western Canada. The results of this study show that the multi-objective calibration improves model fidelity compared to the single objective calibration. Moreover, the study demonstrates that single objective calibration performed against only streamflow can fairly mimic the streamflow hydrograph but does not yield realistic estimation of other fluxes such as evapotranspiration and soil moisture (especially in deeper soil layers). [ABSTRACT FROM AUTHOR]

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010–2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon–climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes. [ABSTRACT FROM AUTHOR]

To improve the convergence of multiple-site weather generators (SWGs) based on the brute force algorithm (MBFA), a genetic algorithm (GA) is proposed to search the overall optimal correlation matrix. Precipitation series from weather generators are used as input to the hydrological model, the soil and water assessment tool (SWAT), to generate runoff over the Red Deer watershed, Canada for further runoff analysis. The results indicate that the SWAT model using SWG-generated data accurately represents the mean monthly streamflow for most of the months. The multi-site generators were capable of better representing the monthly streamflow variability, which was notably underestimated by the single-site version. In terms of extreme flows, the proposed method reproduced the observed extreme flow with smaller bias than MBFA, while the single-site generator significantly underestimated the annual maximum flows due to its poor capability in addressing partial precipitation correlations. [ABSTRACT FROM AUTHOR]

[Display omitted] • BW and GW are interlinked through dissimilar physical processes across ecoregions. • GW-BW relationship and their shift were projected under extreme warm and dry events. • In Mountains, future BW declines while GW maintains due to legacy moisture. • In natural lands, BW to GW shift is projected with a lag time and legacy moisture. • In crop lands, remarkable shortages in BW are projected with no shift to GW. As key drivers of terrestrial ecosystems and food production, green water (GW) and blue water (BW) are interlinked through natural and anthropogenic processes. Their relationship has reportedly been non-stationary, with an anticipated shift from BW to GW in the future. However, these potential shifts are poorly characterized, particularly in response to future extreme warm-dry events. To address this gap, we used a process-based agro-hydrological model to project GW-BW interlinkages and their potential shifts across three different ecohydrological regions – mountainous, crop, and natural lands – in the Nelson River Basin, the largest agricultural basin in Canada and a major breadbasket for the world. Our results indicate dissimilarity in the physical processes that link GW and BW across different ecohydrological regions, and therefore, disproportional projected changes in BW and GW. In mountainous and natural lands, with projected decreases in precipitation in extreme warm-dry years of up to 56% and 46% under SSP126 and SSP585 scenarios, BW decreases by 64% and 42% while GW decreases only by 37% and 29%. The decline in GW is expected to be less because of the availability of evaporative water supplied by legacy soil moisture and groundwater contributions from earlier seasons. This available water to supply evaporative demand represents a delayed overall shift of BW to GW. In crop lands, however, results show a significant decrease of precipitation (45%-55%), BW (up to 42%), and GW (up to 42%), with no remarkable shift of BW to GW in extreme warm-dry years in the future. The projected BW and GW declines in crop lands may impose severe water shortages on local and regional food production. Projected declines in BW from the mountains that serve as source water for downstream irrigation may exacerbate such possible shortages. [ABSTRACT FROM AUTHOR]

The retrieval of continuous leaf area index (LAI) in space and time from remote sensing is beneficial for cropland monitoring and management. Synthetic Aperture Radar (SAR) with the advantages of all-weather operation and fine spatial resolutions has been utilized in various agricultural applications. Although the water cloud model (WCM) has been extensively used for LAI estimation over croplands, it is modified for application to crop canopies with large gaps. The requirement of prior information on soil moisture is also a hinderance for the model application. In this study, WCM is theoretically modified to consider the correlation of active microwave propagation through the canopy in downward and upward directions. Such a modification is particularly important for sparse vegetation with large gaps between crop plants in the early stage of the growing season. A parameter with explicit physical meaning, i.e. the full-vegetation backscattering coefficient, was defined to simplify our model scheme and make the model applicable for the whole growing season. In addition, a physics-based SAR data processing scheme is developed to entangle the influences of LAI and soil moisture on SAR backscatter by taking advantage of the multiple polarizations of RADARSAT-2 (R2) SAR data. In this way, LAI was estimated using modified WCM without the prior knowledge of soil moisture. To evaluate LAI retrieved from the R2 datasets (R2 LAI), ground-based LAI measurements were made at the experimental area of SMAPVEX16-MB in Canada with twenty approximately 800 m х 800 m plots in soybeans and corn. R2 LAI was well correlated to these ground-based LAI (n = 15, R2 = 0.63, RMSE = 0.99 m2·m−2 for soybeans; n = 5, R2 = 0.66, RMSE = 1.20 m2·m−2 for corn). LAI was also retrieved from optical data acquired by Sentinel-2/MSI (S2), denoted as S2 LAI. The R2 LAI and S2 LAI are well correlated and achieved coefficients of determination (R2) of 0.76 and 0.71 and root mean square errors (RMSE) of 1.1 and 1.4 m2·m−2 for soybeans and corn, respectively. The seasonal variations of R2 LAI and S2 LAI are generally similar except at the end of the growing season when S2 LAI is considerably larger than R2 LAI. S2 LAI followed the trend of the reduction in leaf chlorophyll content, while R2 LAI reduced only slightly due to the decrease in leaf water content near the end the growing season. R2 LAI represents the total standing leaf area useful for surface energy balance estimation, while S2 LAI responds to green leaf area useful for crop productivity modeling. • The water cloud model (WCM) is modified to consider SAR observation geometry. • RADARSAT-2 dual-polarization data are used to retrieve LAI without prior soil moisture. • A dry-soil edge was proposed as a basis to remove soil moisture influence on LAI retrieval. • Seasonal variations of LAI from RADARSAT-2 and optical Sentinel-2 agree except at the end of the growing season. [ABSTRACT FROM AUTHOR]

• We estimated soil respiration using empirical and machine learning algorithms. • We calibrated algorithms with in-situ and satellite soil moisture and temperature. • Satellite-based soil respiration had comparable accuracy to ground-based estimates. • Algorithms that included soil moisture outperformed those driven solely by temperature. Soil respiration, defined as the total flux of carbon dioxide (CO 2) from the soil to the atmosphere, is a key ecosystem process that affects the regional and global carbon (C) cycles and is highly sensitive to temperature and soil moisture. It is challenging to quantify soil respiration at the ecosystem level from commonly used in-situ soil chamber measurements because of large spatial variability. Methods that provide temporally and spatially continuous estimates of soil respiration at various scales are vital to understand the impact of climate change on soil C stock. In this study, we evaluate three commonly used empirical models and a Random Forest machine learning algorithm applied to satellite derived estimates of land surface temperature (LST) and soil moisture to estimate soil respiration in temperate deciduous and coniferous forests in Canada. The models were calibrated using in-situ soil temperature and moisture and validated against in-situ measurements of soil CO 2 fluxes (gCm−2day−1) from automatic soil chambers. We separately evaluate the performance of nighttime and daytime satellite-based LST and soil moisture observations in modeling soil respiration. The soil respiration models were also evaluated at daily and monthly time scales against in-situ measurements. Results indicate that models based on satellite LST, and soil moisture can explain more than 70% of the variability in observed soil respiration. Nighttime LST at a monthly time scale resulted in consistently higher accuracy than daytime LST in estimating soil respiration. Satellite observations resulted in comparable accuracy in estimating soil respiration as in-situ measurements. Satellite LST and soil moisture observations are indispensable data sources to estimate soil respiration at ecosystem level and its upscaling to regional and global scales. [ABSTRACT FROM AUTHOR]

At high population size, migratory caribou (Rangifer tarandus) are regulated by forage abundance in their summer range. Climate warming likely affects forage availability by increasing productivity and advancing phenology of vegetation. Our objective was to investigate the combined effects of browsing and climate warming on the availability of dwarf birch (Betula glandulosa). We simulated direct (warming, with open-top chambers) and indirect (increased nutrient cycling) effects of climate warming in interaction with simulated browsing (leaf stripping) from 2009 to 2013 in Nunavik, Canada. We measured the effect of treatments on dwarf birch biomass and phenology. Moderate and heavy browsing reduced the estimated biomass of birch leaves by 14% and 34%, respectively. Fertilization did not increase the biomass of birch leaves, but increased the biomass of another forage, Poaceae. The warming treatment advanced the opening of birch leaves by 4 days (95% CI: [3, 6]) in 2011 and 7 [5, 8] days in 2013, the two years colder than average. The absence of significant phenological shifts in warmed plots during warmer springs suggests that established dwarf birches may have reached a threshold in a limiting resource, likely soil moisture, under which they cannot respond to further warming. Our results demonstrate that browsing can reduce forage biomass, but the variability in caribou populations could provide windows of opportunity for shrub growth. [ABSTRACT FROM AUTHOR]

The spatial variability in soil physical and hydraulic properties for a managed podzol was assessed using soil apparent electrical conductivity (ECa). Two EMI sensors, the multi-coil (MC) and multi-frequency (MF), were adopted for measurement of ECa on a silage- corn experimental plot in western Newfoundland, Canada. Results demonstrated a significant relationship between the ECa mean relative differences (MRD) and the soil moisture content MRD (R2 = 0.33 to 0.70) for both MC and MF sensors. The difference in depth sensitivity between MC and MF sensors accounted for the variation (0.015 to 0.09) in ECa standard deviation of the relative differences. A significant linear relationship was found between the ECa MRD and sand (R2 = 0.35 and 0.53) or silt (R2 = 0.43), but not with clay (R2 = 0.06 and 0.16). The spatial variability of the ECa-based predictions (CV = 3.26 to 27.61) of soil properties was lower than the measured values (CV = 5.56 to 41.77). These results inferred that the temporal stability of ECa might be a suitable proxy to understand the spatial variability of soil physical and hydraulic properties in agricultural podzols. [ABSTRACT FROM AUTHOR]

The St. Denis National Wildlife Area is located in the seasonally frozen and semi-arid Canadian Prairies, close to Saskatoon, Saskatchewan. The site has a hummocky terrain and is underlain by clay-rich glacial tills. Though the site is only 4 km 2 it contains hundreds of wetlands containing ponds which range in size, in permanence (from ephemeral to permanent), and in their interactions with groundwater (recharge and discharge ponds are present). The site was established as a research area in 1968 and has long-term records of hydrological observations, including meteorological, snow, soil moisture, surface water (ponds) and groundwater data. Some records, notably the pond level and chemistry data, span the period 1968 to present. Other datasets, notably water level observations from networks of piezometers, have been collected sporadically at different locations and times. Some datasets are collected manually on an annual basis, including pond surveys and snow surveys. Meteorological data have been collected by automatic weather stations since 1989 and have been maintained and upgraded over time, with a flux tower added to the site in 2011. Automatically logged soil moisture profiles and collocated piezometers have been running since 2013. A lidar survey from 2005 provides a 1 m resolution digital elevation map (DEM) of the site and surrounding landscape. The compiled data are available at 10.20383/101.0115 (Bam et al., 2018). [ABSTRACT FROM AUTHOR]

Long records of hillslope runoff and nutrients are rare – on seasonally frozen ground they are almost non-existent. The Swift Current hillslopes at the Swift Current Research and Development Centre on the Canadian Prairies provide such a long-term hydrological record. Runoff, runoff nutrient concentration, snowpack, soil moisture, and soil nutrient concentration were monitored on the three 5 ha hillslopes over a 50-year period (1962–2011). Runoff from the hillslopes was generated episodically during snowmelt and occasional rainfall events. Edge-of-field runoff was measured with a 0.61 m H-flume. Daily runoff nutrient concentration data are available for nitrate (March 1971–April 2011), ammonium (February 1996–April 2011), and orthophosphate (March–April 1971; June 1991–April 2011). Snowpack data (snowpack depth, density and water equivalent) were determined via manual snow surveys carried out several times each winter, between January and March, between 1965 and 2011 Gravimetric soil moisture content was measured in October and April each year between 1971 and 2011 at five depth intervals (0–15, 15–30, 30–60, 60–90, and 90–120 cm) at nine points on each hillslope. We summarize these hillslope data in two publically-available repositories: 1) 1962–2011 data on runoff, runoff nutrients, snowpack, soil moisture, soil nutrients, and crop and tillage practices at https://doi.org/10.23684/hhn5-rz52; and 2) digital elevation data at https://doi.org/10.20383/101.011. Complete climate data recorded at a Environment and Climate Change Canada meteorological station located 390 m from the three hillslopes are publically-available at http://climate.weather.gc.ca/. [ABSTRACT FROM AUTHOR]

The impact of climate change on agricultural systems is a major concern as it can have a significant effect on the world food supply. The objective of this study was to evaluate climate change impacts on crop production and nitrate leaching in two distinct climatic zones in Canada. Spring wheat (Triticum aestivum L.) was selected for the semiarid regions of Western Canada (Swift Current, SK) and maize (Zea mays L.) was chosen for the more humid regions of central Canada (Woodslee, ON). Climate scenarios were based upon simulations from a Canadian Regional Climate Model (CanRCM4) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) and crop simulations were conducted using the Decision Support System for Agrotechnology Transfer (DSSAT) model. Compared to the baseline climate scenario, wheat yields increased by 8, 8, 11, 15%, whereas maize yields decreased by 15, 25, 22, 41% under RCP4.5 2050s (2041–2070), RCP4.5 2080s (2071–2100), RCP8.5 2050s and RCP8.5 2080s scenarios, respectively. Annual nitrate leaching increased by 19, 57, 73, 129% at Swift Current and by 84, 117, 208, 317% at Woodslee under the four scenarios, respectively. Adaptation measures suggested that fertilizer N rate for spring wheat should be increased to 80–100 kg N ha-1 to obtain optimal yields although this will result in an additional risk of 5–8 kg N ha-1 nitrate leaching at Swift Current. The fertilizer N rate of 150 kg N ha-1 was found to be suitable for high maize yields at Woodslee. New wheat and maize cultivars with long growing seasons would enable crop growth to match the phenological stage and hence maintain high crop yields to adapt to increased temperatures in the future. [ABSTRACT FROM AUTHOR]

To address certain limitations with their current operational model, Environment and Climate Change Canada recently developed the Soil, Vegetation, and Snow (SVS) land surface model and the representation of subsurface hydrological processes was targeted as an area for improvement. The objective of this study is to evaluate the ability of HydroSVS, the component of SVS responsible for the vertical redistribution of water, to simulate soil moisture under snow-free conditions when using flux-tower observations of evapotranspiration as forcing data. We assessed (1) model fidelity by comparing soil moisture modelled with HydroSVS to point-scale measurements of volumetric soil water content and (2) model complexity by comparing the performance of HydroSVS to that of HydroGeoSphere, a state-of-the-art integrated surface and subsurface hydrologic model. To do this, we performed one-dimensional soil column simulations at four sites of the AmeriFlux network. Results indicate that under Mediterranean and temperate climates, HydroSVS satisfactorily simulated soil moisture (Nash-Sutcliffe efficiency between 0.26 and 0.70; R 2  ≥ 0.80), with a performance comparable to HydroGeoSphere (Nash-Sutcliffe efficiency ≥0.60; R 2  ≥ 0.80). However, HydroSVS performed weakly under a semiarid climate while HydroGeoSphere performed relatively well. By decoupling the magnitude and sourcing of evapotranspiration, this study proposes a powerful diagnostic tool to evaluate the representation of subsurface hydrological processes in land surface models. Overall, this study highlights the potential of SVS for hydrological applications. [ABSTRACT FROM AUTHOR]

The accurate simulation of crop evapotranspiration (ET) and volumetric soil moisture (SM) is key for agro-environmental simulation of rainfed crops. We compared two ET calculation methods available in the STICS crop model, i.e., the crop coefficient (FAO-56, CC) and the resistance (Shuttleworth and Wallace, SW) methods, over six contrasting rainfed grain corn growing seasons. The ET predictions using the SW method were in good agreement with eddy covariance ET measurements and overall ET predictions were slightly higher than observations by 3% while the CC method overestimated ET by 18%. STICS better predicted daily ET for wet years than for dry years. Ten-day corn ET showed that the SW method performed better when transpiration was dominant (nRMSE of 21.3%) than otherwise (nRMSE of 47.2%). The choice of ET calculation methods had little impact on SM predictions, which are computed in STICS using a tipping bucket approach. SM predictions over the entire soil profile were good for both wet (nRMSE of 15.1%) and dry (nRMSE of 18.2%) years. Larger discrepancies between measured and predicted SM were observed in the surface layer (0–10 cm). A new method was proposed to improve crop model simulations of the soil water transport in the shrinkage cracks during dry years, named Improving Shrinkage Cracks Impact (ISCI). The ISCI method enhanced the performance of SM predictions in the surface soil layer, for which nRMSE decreased to 29.7% for 2002, 18.1% for 2010 and 10.4% for 2018 in comparison with SM results without the use of ISCI method. The steps for implementing ISCI method in crop models using the tipping bucket approach for computing soil moisture are presented. • Two evapotranspiration calculation methods using STICS crop model were compared. • The resistance method predicted corn evapotranspiration better than the crop coefficient one. • Surface soil moisture predicted by STICS departed from observations during dry growing season. • We proposed a new method to account for the impact of shrinkage cracks on surface soil moisture. [ABSTRACT FROM AUTHOR]

This study examines the influence of snow and soil moisture initialization on sub-seasonal potential and actual prediction skill of Canadian Climate Model version 3 (CanCM3) predictions of springtime (April-May) near surface air temperature. Four series of ten-member ensemble forecasts, initialized on 1st April where each series use different land surface initialization, were performed for the 20 year period 1986-2005. Potential predictability of temperature for extratropical Northern Hemisphere land is assessed using synthetic truth and signal-to-noise methods, and compared with actual prediction skills determined through validation against an ensemble mean of six reanalysis products. These metrics are computed for the forecasted 15 days averaged values of temperature at 15, 30 and 45 days lead times. Three of the four land surface initializations considered are intended to be realistic. These are obtained from the Canadian LAand Surface Scheme (CLASS) land surface component of the climate model driven off line with bias-corrected meteorological fields, with and without rescaling to the climate model's land climatology, and from climate model runs where the atmospheric component is constrained by reanalysis fields. A fourth land surface initialization that is intended to be unrealistic consists of a 'scrambled' version of that obtained from rescaled offline-driven CLASS, in which each ensemble member is assigned values from a year other than the one being forecasted. Comparisons of forecasts using the scrambled and corresponding realistic land initializations indicate that the latter show higher potential predictability overall especially over North America and parts of Eurasia at all lead times. The higher potential predictability is primarily attributed to correct initialization of land surface variables, in particular the snow water equivalent, and the frozen and liquid components of soil moisture. Our results also indicate that predictability is governed mainly by forecast signals, with high forecast noise also playing a role. Actual skills, though lower than potential predictability, likewise show a positive influence of realistic land initialization. [ABSTRACT FROM AUTHOR]

In this study, we used the Disaggregation based on Physical And Theoretical scale Change (DISPATCH) algorithm under very wet soil conditions in Western Canada for the disaggregation of coarse resolution 40-km soil moisture derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The algorithm relies on the Soil Evaporative Efficiency (SEE), which was estimated using the 1-km resolution data from the MODerate resolution Imaging Spectoradiometer (MODIS). The study aimed to: (i) evaluate DISPATCH under wet soil conditions, (ii) test the linearity/non-linearity of the relationship between soil moisture and SEE, and (iii) propose a more robust procedure to calibrate the SEE model under very wet soil conditions. The disaggregated soil moisture values were compared to 0–5 cm in situ measurements and the soil moisture derived from the L-MEB (L-band Microwave Emission of the Biosphere) model from airborne brightness temperature at 1.4 GHz collected during the Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) field campaign. The results show a correlation between 0.7 and 0.8 and bias values ~ 0 m 3 /m 3 . The DISPATCH algorithm shows better disaggregation results under very wet soil conditions when a non-linear relationship is considered between SEE and soil moisture instead of a linear model. This is mainly due to the small variability of surface temperature inside the area covered by the SMOS pixel under very wet soil conditions, and the difficulty in accurately estimating the maximum soil temperature ( Ts max ), which is a driving factor for SEE. A sensitivity analysis was conducted and it shows that the linear model performs well only if Ts max can be determined more accurately. The possibility to determine Ts max using high resolution MODIS data over a larger area than the SMOS pixel is examined and discussed in the paper. [ABSTRACT FROM AUTHOR]

• Boreal forest soils store about four times more SOC under continuous permafrost. • Permafrost and soil moisture control SOC stocks and quality of mineral soils. • SOC stocks of boreal mineral forest soils can be predicted from mid-infrared spectroscopy. High-latitude soils store a large amount of the global soil organic carbon (SOC). The SOC stocks in mineral soils under different permafrost conditions, however, are underrepresented in global carbon databases. We sampled mineral forest soils under continuous and discontinuous to sporadic permafrost conditions on the Canadian Boreal and Taiga Plain. We determined the SOC stocks in the upper 60 cm of 94 soil pits across eleven sites (5–9 pits per site) and SOC quality using 13C isotopic signatures, C:N ratios and composition of aliphatic/aromatic and cellulose/lignin-like compounds obtained from mid-infrared spectra analyses. Lastly, we evaluated the prediction of SOC stocks in these soils using mid-infrared spectra and partial least square regression modelling (PLSR). The SOC stocks were on average four times higher in soils under continuous permafrost conditions (93.7–203.8 Mg SOC ha−1 in 0–45 cm) compared to soils under discontinuous to sporadic permafrost conditions (26.7–60.2 Mg SOC ha−1 in 0–60 cm). In addition, the SOC stocks were larger at moist and wet locations compared to dryer locations and varied significantly between sites, stressing the importance of small-scale geomorphic differences in controlling SOC in boreal mineral forest soils. Continuous permafrost SOC had a lower degree of decomposition compared to soils under discontinuous and sporadic permafrost. This indicates a potentially large proportion of SOC in boreal mineral soils to be vulnerable to warming associate increases in decomposition. The combination of mid-infrared with PLSR was suitable to predict the SOC stocks (R2 > 0.8) with an average uncertainty of 14–23%, which was less than the observed spatial variability of the field replicates (29–41%). Mid-infrared spectroscopy can thus offer an alternative to fill SOC data gaps of high latitude mineral forest soils and reduce uncertainties originating from the limited number of currently available SOC observations of Canadian boreal mineral forest soils. [ABSTRACT FROM AUTHOR]

Studies were conducted to examine the effects of row spacing and stubble height on surface soil water content, water use, yield, and water use efficiency of canola and wheat in the drier regions of the Canadian prairies. For this purpose, randomized complete block design trials were implemented separately in canola and wheat fields at Central Butte and Swift Current in the Brown soil zone of southwestern Saskatchewan. At each experimental site, two factors and two levels for each factor, i.e., 30- and 60-cm row spacing and 15- and 30-cm stubble heights, were included. Wider row spacing and taller stubble generally increased soil water content for the surface 0–30 cm soil depth, and taller stubble often had greater spatial variability of surface soil water content at both locations. Row spacing or stubble height had minimal effect on water use for both crops at both locations over the two years (2012 and 2013). Yield and water use efficiency of 30-cm row spacing were 1.3–1.6 (Central Butte) and 1.0–1.2 (Swift Current) times greater than those of 60-cm row spacing. Stubble height had little effects on yield and water use efficiency. There were no interactions of row spacing and stubble height on water use, yield, and water use efficiency for either crop. Overall, 30-cm row spacing and 30-cm stubble tended to increase surface soil water content, yield, and water use efficiency for most crop type, year, and site combinations. [ABSTRACT FROM AUTHOR]

Soil moisture from Soil Moisture Ocean Salinity (SMOS) passive microwave satellite data was assessed as an information source for identifying regions experiencing climate-related agricultural risk for a period from 2010 to 2013. Both absolute soil moisture and soil moisture anomalies compared to a 4-yr SMOS satellite baseline were used in the assessment. The 4-yr operational period of SMOS was wetter than the 30-yr climate normal in many locations, particularly in the late summer for most regions and in the spring for the province of Manitoba. This leads to a somewhat unrepresentative baseline that skews anomaly measures at different parts of the growing season. SMOS soil moisture does, however, show a clear trend where extremes are present, with drier-than-average conditions during periods that drought and dry soil risks were identified and wetter-than-average conditions when flooding and excess moisture were present. Areas where extreme weather events caused crop losses were identifiable using SMOS soil moisture, both at the provincial and regional scales. The variability in soil moisture between at-risk areas and normal areas is very small but consistent, both geographically and over time, making SMOS a good real-time indicator for risk assessment. [ABSTRACT FROM AUTHOR]

• We evaluated a land surface scheme (CLASS) for its simulation of transpiration. • CLASS adequately simulates daily transpiration over the growing season in the boreal forest. • CLASS daily transpiration was however underestimated during the tree rehydration period. • CLASS overestimated transpiration during droughts. • A new equation that increases CLASS sensitivity to decreasing soil water was proposed and tested. Transpiration, a key component of the hydrological cycle, contributes greatly to the climate system by transferring large amount of water from soils to the atmosphere. Its correct representation within Land Surface Schemes in climate models is crucial to provide accurate and reliable climate projections. In this study, transpiration simulated by the Canadian Land Surface Scheme (CLASS) was compared to long-term observations of sap flow measurements in two boreal forest sites of eastern Canada dominated by balsam fir and black spruce. In general, CLASS adequately models daily transpiration during the growing season for most of the years at both sites. During the tree rehydration period (preceding the growing season), modeled transpiration was greatly underestimated because of overestimating the duration of the snowpack, the latter restricting transpiration. Moreover, CLASS did not capture the impact of extreme events on tree physiology and maintained high transpiration rates during a heat stress and a drought. During both observed and simulated drought events, transpiration modeled using CLASS was overestimated, due to insensitivity to substantial decreases in soil water content; modeled transpiration being strictly controlled by atmospheric variables (vapour pressure deficit and radiations). Thus, we also proposed and implemented a new equation that was able to increase the sensitivity of CLASS to decreasing soil water content. However, this equation needs to be further tested on different sites and tree species. [ABSTRACT FROM AUTHOR]

• A new lysimeter facility dedicated to studying soil ecosystem services is introduced. • Replicate weight measurements were used to assess variability of the water balance. • Lysimeters measured precipitation to a high precision (±2.4% of the mean over 120-days). • Data processing procedures added a minimal amount of uncertainty to water balance sums. • Spatial variations were not driven by intrinsic soil core differences. Diversifying annual crop rotations is postulated to promote soil ecosystem services through reduction of greenhouse gas emissions, control of soil evaporation, moderation of soil freeze-thaw cycles, increases in soil organic carbon, and reduced nutrient leaching, all of which are processes that are impacted by the water balance. A newly-installed facility with large monolithic weighing soil lysimeters dedicated to studying changes in soil ecosystem services induced by rotation diversification was installed in June 2016 in Elora, ON, Canada. The high-precision lysimeters, nine for each of two different soils (silt loam, loamy sand) are a closed system to fully evaluate water balance components. In the first year of operation, the lysimeters were not subject to any diversification treatments. This provided an opportunity to study water budget components (precipitation, P ; evapotranspiration, ET ; change is soil storage, Δ S ; drainage, D) measured by the 9 replicate lysimeters for each soil type. The objectives of this study were to 1) determine the total uncertainty of P , ET , Δ S and D induced by data smoothing and gap filling data procedures; and 3) characterize the spatial variability of water budget components for the baseline year. Cumulative sums of water balance variables from data processing procedures found that the adaptive window and adaptive threshold (AWAT) data smoothing method introduced minimal errors (0.2 to 1.9%). Filling missing data gaps using data from replicate lysimeters, i.e., lysimeters of the same soil type and agronomy, introduced errors of only 0.3 to 0.5% for P and ET (120-day sums). There was greater uncertainty for D and Δ S (10.8% and 2.1%, respectively) because of the variability in D. P showed a small degree of spatial variation across all 18 lysimeters, with variations being 1.5% of the mean cumulative sums when using data with no gaps, which demonstrated the high precision of the lysimeter measurements. Spatial variability of evapotranspiration (ET) was higher (6.1% for the silt loam and 5.7% for the loamy sand), but within the range of variability estimated for similar lysimeter facilities. The differences in plant cover on individual lysimeters were the main source of variation for ET and Δ S. Results inform future comparisons of water budget components for other lysimeter sites and demonstrate the suitability of this facility for examining the complex impacts of crop diversification on soil ecosystem services, providing a basis for future evaluations of water balance components. [ABSTRACT FROM AUTHOR]

[Display omitted] • Adaptive multi-paddock grazing enhances water infiltration in grassland soils. • Longer rest following early season cattle grazing aids water infiltration. • Water infiltration is negatively associated with bulk density on grazed grasslands. • Litter accumulation enhances water infiltration under adaptive grazing management. The maintenance of hydrologic function on grazing lands is an important management objective to sustain forage production during low moisture supply, safeguard other ecosystem goods and services and build resilience to a warming climate. Hydrologic function can be influenced by grazing patterns, as represented by variation in the timing, intensity and frequency of livestock use. While rotational, adaptive grazing (a short-duration, multi-paddock grazing system that emphasises plant recovery between grazing events) is growing in popularity and has the potential to influence grassland hydrological processes such as water infiltration, few studies have comprehensively examined infiltration in relation to on-ranch grazing practices. We examined water infiltration in grasslands on 52 ranches (set up as matched pairs) to examine whether adaptive grazing alters water infiltration in the Great Plains of western Canada, as compared to conventional grazing management employed on neighbouring ranches. We also used producer survey information to test for the influence of ongoing nuanced grazing practices on water infiltration rates, over and above the biophysical effects of soil texture, soil bulk density and plant litter, as well as cultivation history and climate. Overall, adaptive grazing, and specifically the use of higher rest-to-grazing ratios early in the growing season (prior to August 1), led to increased water infiltration in grassland soils. Water infiltration was positively associated with increased litter mass under adaptive grazing, whereas higher bulk density (and sandier) soils were associated with decreased infiltration rates. This study highlights the potential of specialised rotational grazing systems using cattle to improve soil hydrologic function in grazed grasslands. [ABSTRACT FROM AUTHOR]

• The CRHM-created Boreal Hydrology Model performed quite well on simultaneously simulating runoff, snow water equivalent, soil liquid water content and evapotranspiration (ET) with minor parameter calibration. • The basin hydrological variables showed quite different sensitivities to perturbations of precipitation (P) and temperature (T). Annual runoff was more sensitive to rising P than warming T, but annual ET was more sensitive to warming T. • Perturbed P and T had distinctively different influences on the streamflow regime. Increased P enhanced the intra- and inter-annual variabilities of basin runoff, whilst rising T resulted in the inverse changes. • Effects of warming on annual runoff and snow processes could be compensated for to varying degrees by the effects of increases in P. Hydrological processes over and through frozen and unfrozen ground were simulated in the well instrumented boreal forest basin of White Gull Creek, Saskatchewan, Canada using a model created using the flexible Cold Regions Hydrological Modelling (CRHM) platform. The CRHM-created Boreal Hydrology Model was structured and initially parameterized using decades of process hydrology research in the southern boreal forest with minor parameter calibration, and generally produced quite good performance on simultaneously reproducing the measurements of runoff, snow water equivalent (SWE), soil liquid water content and eddy correlation flux tower observations of evapotranspiration (ET) over two decades. To examine the sensitivity of basin hydrology to perturbed climate inputs, air temperature (T) inputs were set up by linear increments in the reference observation of up to +6 ℃, and precipitation (P) inputs were generated by multiplying the reference observed P from 70% to 130%. The model results showed that the basin hydrological variables showed quite different sensitivities to perturbations of P and T. The volume of annual runoff and the annual runoff coefficient increased more rapidly with rising P, at rates of 31% and 16% per 10% increase in P, but decreased by only 3.8% and 4.7% per 1 ℃ of warming. Annual ET increased rapidly with temperature, by 7% per 1 ℃ of warming and therefore drove the streamflow volumetric changes with warming, but increased only 1% per 10% increase in P. Perturbations of P and T had distinctively different influences on the streamflow regime. Increased P enhanced the intra- and inter-annual variabilities of basin runoff, reduced the relative contribution of winter runoff to annual runoff and increased the relative contribution of summer runoff; whilst rising T resulted in the inverse changes in the streamflow regime. Effects of warming on some hydrological processes could be compensated for to varying degrees by the effects of increases in P. Reductions in the annual runoff volume and runoff coefficient caused by warming up to 6 ℃ could be compensated for by increases of <20% in P. However, the maximum increase in P (+30%) examined could only compensate for the changes in snow processes caused by warming of less than 4 ℃ and snow-cover duration decreases with 1 ℃ warming could not be compensated for by any precipitation increase considered. These results inform the vulnerability of boreal forest hydrology to the first-order changes in P and T and provide guidance for further climate impact assessments for hydrology in the southern boreal forest in Canada. [ABSTRACT FROM AUTHOR]

• Regional-scale modelling of ecosystem (R eco) and autotrophic respiration (R a). • Temperature and dissolved oxygen (DO) levels mostly influence R eco and R a. • Water-filled pore space has lowest influence on R eco , R a and soil respiration (R s). • Soil and air temperature and DO contributes >65% for R eco , R a and R s simulation. • First time R eco , R a modelling using the Soil and Water Assessment Tool (SWAT). Ecosystem respiration (R eco) and its components, the autotrophic respiration (R a) and soil respiration (R s) are the essential indicators of the global carbon cycle. They are represented as functions of either temperature or soil moisture, or a combination of both in the widely-used Earth System Models (ESMs). Thus, it is difficult to evaluate the influence of other environmental factors (such as, precipitation, soil temperature, dissolved oxygen level and oxidation reduction potential (ORP)) on R a , R s and R eco. Here we introduced microbially mediated, detailed carbon cycle processes within our mechanistic model to address this issue. Dominance analysis using a multivariate approach was performed to find out the influence of individual environmental factors on R a , R s and R eco in the cold climate regions of Athabasca River Basin (ARB), Canada. Contribution of the 6 predictor variables, including air temperature, precipitation, soil temperature, water-filled pore space (WFPS) used as a proxy of soil moisture, dissolved oxygen level, and ORP, on R a , R s and R eco were estimated based on the R2 values originated from multiple regression analyses. Our results showed that the prevailing temperature (both air and soil) and dissolved oxygen levels are the major influencing factors on R a , R s and R eco. WFPS is found to be the least influential factor on respiration estimation. Output of this study can be used to consider the crucial roles of environmental drivers in R a , R s and R eco estimation in the development of future ESMs. [ABSTRACT FROM AUTHOR]

Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets. Image 1 • Multiple models showed variability in meeting water quality goals. • There was agreement among models that some practices can reduce phosphorus loads. • Reducing dissolved reactive phosphorus is more difficult than total phosphorus. • Reaching water quality goals requires substantial adoption of conservation practices. • Stakeholder guidance improved scenario development, interpretation, and outreach. [ABSTRACT FROM AUTHOR]

Soil salinity restricts plant growth, affects soil water balance and nitrous oxide (N 2 O) fluxes and can contaminate surface and groundwater. In this study, the Denitrification Decomposition (DNDC) model was modified to couple salt and water balance equations (SALT-DNDC) to investigate the effect of salinity on water balance and N 2 O fluxes. The model was examined against four growing seasons (2008–11) of observed data from Lethbridge, Alberta, Canada. Then, the model was used to simulate water filled pore space (WFPS), salt concentration and the N 2 O flux from agricultural soils. The results show that the effects of salinity on WFPS vary in different soil layers. Within shallow soil layers (<20 cm from soil surface) the salt concentration does not affect the average WFPS when initial salt concentrations range from 5 to 20 dS/m. However, in deeper soil layers (>20 cm from soil surface), when the initial salt concentration ranges from 5 to 20 dS/m it could indirectly affect the average WFPS due to changes of osmotic potential and transpiration. When AW is greater than 40%, the average growing season N 2 O emissions increase to a range of 0.6–1.0 g-N/ha/d at initial salt concentrations (5–20 dS/m) from a range of 0.5–0.7 g-N/ha/d when the salt concentrations is 0 dS/m. The newly developed SALT-DNDC model provides a unique tool to help investigate interactive effects among salt, soil, water, vegetation, and weather conditions on N 2 O fluxes. Image 1 • SALT-DNDC simulates effects of root zone salinity on water balance and N 2 O fluxes. • The salt leaching patterns depend on soil salinity, rainfall depths and frequency. • Due to soil salinity, plant transpiration and soil evaporation balance each other. • N 2 O emission depends on soil available water, soil moisture and salt concentration. [ABSTRACT FROM AUTHOR]

Canada is one of the top wheat grain exporters, with a share of more than 10% in the world wheat market. The majority of Canadian wheat production takes place in the Prairies where 6.2 million ha of the area is seeded to spring wheat. The climate is semiarid with an estimated precipitation deficit of about 300 mm during the crop growing season, indicating that water is the primary limiting factor for crop production. In this study, three DSSAT-Wheat models (CSM-CERES, -CROPSIM, -NWHEAT) were used to quantify the impacts of water management practices on crop water stress and wheat yields. The models were evaluated individually and as an ensemble against observed wheat performance using three field experiments conducted to investigate irrigation, rainfed, and summer fallow impacts on wheat yields. The results showed that all three wheat models well simulated grain yield gains with irrigation and summer fallow that conserved additional soil water. Statistically, the multimodel ensemble improved the accuracy in simulating grain yields and biomass of spring wheat under both irrigated and rainfed conditions. The improvements could not be linked to eco-physiological processes in crop systems, and the increased simulation accuracy was likely due to the offsetting effects of simulation bias and errors from the individual models. Water input (precipitation + irrigation) of 400 mm was sufficient to reach the highest yield of spring wheat cultivars in the Canadian Prairies. Irrigation of 200 mm was able to alleviate most of the crop water stress in the study region. Further simulation scenarios showed that irrigating spring wheat when soil moisture was below 50% of available water capacity (AWC) for plants led to high yield, low irrigation rates, and reduced evaporation for different soil textures. Combined with improved drought tolerance varieties, this irrigation regime provides good prospects for increasing wheat yield and water use efficiency. • Wheat models in DSSAT are evaluated on the impacts of irrigation and summer fallow. • A multimodel ensemble improves simulation accuracy. • Total water inputs of 400 mm maximize spring wheat yield in the Canadian Prairies. • Irrigation of 200 mm mostly overcomes drought stress for wheat in the Prairies. • Irrigating at soil moisture below 50% AWC at 0–40 cm improves water efficiency. [ABSTRACT FROM AUTHOR]

Deciduous shrub encroachment in tundra ecosystems affects the soil microclimate and, in turn, could affect soil nutrients and microbial processes. Although numerous effects of shrubs on tundra ecosystem properties have been described, there has been little focus on the mechanisms through which they impact tundra functioning. In alpine tundra of northern Canada, we examined 1) the effects of the living shrub canopy and separated them from 2) the effects of increases in litter quantity and quality. In this 4-year study we experimentally manipulated shrub presence (shrub present or removed) and litter quantity (none, natural abundance, and 2x natural abundance) in a fully factorial design. Shrub presence affected soil temperatures by increasing winter and decreased summer soil surface temperatures by about 0.8 °C and 0.6 °C respectively, and also decreased mid-summer soil moisture. Shrub presence also affected both nutrient cycling and microbial processes including decreased summer available nitrogen (N), increased N-immobilization, increased microbial biomass as well as variable effects on potential exoenzyme activity. Increased litter inputs had few significant effects on tundra ecosystems, although additional litter increased both soil C:N ratios and microbial biomass. Our results indicate that shrub encroachment is likely to affect tundra soil properties primarily through mechanisms associated with the presence of the living shrub rather than from the accompanied changing litter quality and quantity. Because of opposing effects of shrubs between seasons and years, we encourage an increased focus on the mechanisms through which shrubs may affect tundra ecosystem functions and year round assessments of these processes. • Shrub canopy presence increases winter but reduces summer soil temperatures. • There were few ecosystem effects of increasing shrub litter quality and quantity. • Shrub presence directly influenced nutrient cycling and microbial processes. [ABSTRACT FROM AUTHOR]

• Vapour pressure deficit and solar radiation are the main drivers of sap flow. • Soil water did not control sap flow during a drought event. • Presence of strong diel hysteresis in boreal tree species of eastern Canada. On vegetation-covered land surfaces, tree transpiration, compared to soil and canopy evaporation, is a major process that sends large amounts of water back to the atmosphere. While the driving forces of tree transpiration have been studied over a range of tree species across an array of ecosystems, no work has been done on balsam fir and black spruce in the humid boreal forest of eastern Canada.We thus studied the relationships between environmental variables and sap flow velocity (as a proxy for transpiration) for these two boreal tree species located at two forest sites in Quebec, Canada over multiple growing seasons (2004 to 2013 for balsam fir and 2006 to 2009 for black spruce). Our results showed that daily sap flow had a strong non-linear relationship with vapour pressure deficit (VPD) for both species. Sap flow was also strongly correlated to solar radiation (Rad) for both species although with slightly weaker relationships than for VPD. Other variables such as daily maximum temperature and precipitation explain a smaller portion of the variance in sap flow while soil water content (SWC) and wind speed had almost no effect. An analysis of the relationships between sap flow and VPD/Rad on an hourly basis over multiple years showed strong diel hysteresis for both species. Contrary to what has been previously proposed, the magnitude of this hysteresis does not seem to relate to the degree of iso/anisohydricity. Finally, our investigation of sap flow relationships to environmental variables during a drought period at the balsam fir site showed that sap flow was only slightly reduced despite a significant decrease in SWC. On the other hand, VPD and Rad remained the main drivers of sap flow. This study emphasizes that VPD and Rad are indeed the major drivers of transpiration during the growing season as well as during drought in humid boreal region. [ABSTRACT FROM AUTHOR]

Wildfires are a concerning issue in Canada due to their immediate impact on people's lives, local economy, climate, and environment. Studies have shown that the number of wildfires and affected areas in Canada has increased during recent decades and is a result of a warming and drying climate. Therefore, identifying potential wildfire risk areas is increasingly an important aspect of wildfire management. The purpose of this study is to investigate if remotely sensed soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to identify potential wildfire risk areas for better wildfire management. We used the National Fire Database (NFDB) fire points and polygons to group the wildfires according to ecozone classifications, as well as to analyze the SMOS soil moisture data over the wildfire areas, between 2010–2017, across fourteen ecozones in Canada. Timeseries of 3-day, 5-day, and 7-day soil moisture anomalies prior to the onset of each wildfire occurrence were examined over the ecozones individually. Overall, the results suggest, despite the coarse-resolution, SMOS soil moisture products are potentially useful in identifying soil moisture anomalies where wildfire hot-spots may occur. [ABSTRACT FROM AUTHOR]

Soil moisture is a critical indicator for climate change and agricultural drought, but its measurement is challenging due to large variability with land cover, soil type, time, space and depth. Satellite estimates of soil moisture are highly desirable and have become more widely available over the past decade. This study investigates and compares the performance of four surface soil moisture satellite datasets over Canada, namely, Soil Moisture and Ocean Salinity Level 3 (SMOS L3), versions 3.3 and 4.2 of European Space Agency Climate Change Initiative (ESA CCI) soil moisture product and a recent product called SMOS-INRA-CESBIO (SMOS-IC) that contains corrections designed to reduce several known sources of uncertainty in SMOS L3. These datasets were evaluated against in situ networks located in mostly agricultural regions of Canada for the period 2012 to 2014. Two statistical comparison methods were used, namely, metrics for mean soil moisture and median of metrics. The results suggest that, while both methods show similar comparisons for regional networks, over large networks, the median of metrics method is more representative of the overall correlation and variability and is therefore a more appropriate method for evaluating the performance of satellite products. Overall, the SMOS products have higher daily temporal correlations, but larger biases, against in situ soil moisture than the ESA CCI products, with SMOS-IC having higher correlations and smaller variability than SMOS L3. The SMOS products capture daily wetting and drying events better than the ESA CCI products, with the SMOS products capturing at least 75% of observed drying as compared to 55% for the ESA CCI products. Overall, for periods during which there are sufficient observations, both SMOS products are more suitable for agricultural applications over Canada than the ESA CCI products, even though SMOS-IC is able to capture soil moisture variability more accurately than SMOS L3. [ABSTRACT FROM AUTHOR]

• After six months litter C was found in all soil fractions. • Similar amounts of litter C in the mineral fraction at six months and five years. • Sand content and precipitation best predict litter C formed in mineral fraction. • We found a positive feedback between new litter-derived SOM and soil C content. Understanding the mechanisms controlling the formation and persistence of soil organic matter (SOM) is important for managing soil health and sustainable food production. The formation of SOM and the degree to which it is protected from decomposition are important for determining the long-term persistence of SOM. We used soils collected in a 13C-labelled litter decomposition study established at agricultural sites in Canada to understand the formation and persistence of newly-formed SOM. The ten agricultural sites spanned a wide range of soil carbon contents, texture, and climatic conditions. We fractionated the soil to isolate water extractable organic matter (WEOM), free light POM (fPOM), sand-sized and occluded particulate organic matter (oPOM), and silt and clay sized particles, referred to as mineral-associated organic matter (MAOM). Quantitative isotope tracing was used to determine the litter-derived C in all fractions. We performed these analyses early (six months after incubation) and later (five years after incubation) in the decomposition process to evaluate factors that control the formation and persistence of POM and MAOM. After six months litter-derived C was found in all fractions, but after five years it had declined in all fractions except the MAOM. Formation of MAOM was related to high mean annual precipitation and low sand content, whereas occluded POM formation was related to high soil C content. Persistence of MAOM and POM during the incubation were associated with low soil temperature and high soil C content. There was no consistent indication that formation of MAOM occurred from the decomposition of POM, suggesting that MAOM and POM are formed by two separate pathways. This has important implications for SOC models, which assume that plant-derived C passes through a sequence of pools, becoming more stable along the way. [ABSTRACT FROM AUTHOR]