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Abstract Debris-covered glaciers are an important component of the mountain cryosphere and influence the hydrological contribution of glacierized basins to downstream rivers. This study examines the potential to make estimates of debris thickness, a critical variable to calculate the sub-debris melt, using ground-based thermal infrared radiometry (TIR) images. Over four days in August 2019, a ground-based, time-lapse TIR digital imaging radiometer recorded sequential thermal imagery of a debris-covered region of Peyto Glacier, Canadian Rockies, in conjunction with 44 manual excavations of debris thickness ranging from 10 to 110 cm, and concurrent meteorological observations. Inferring the correlation between measured debris thickness and TIR surface temperature as a base, the effectiveness of linear and exponential regression models for debris thickness estimation from surface temperature was explored. Optimal model performance ( R 2 of 0.7, RMSE of 10.3 cm) was obtained with a linear model applied to measurements taken on clear nights just before sunrise, but strong model performances were also obtained under complete cloud cover during daytime or nighttime with an exponential model. This work presents insights into the use of surface temperature and TIR observations to estimate debris thickness and gain knowledge of the state of debris-covered glacial ice and its potential hydrological contribution.

Abstract Worldwide, there has been an increase in the presence of potentially toxic cyanobacterial blooms in drinking water sources and within drinking water treatment plants (DWTPs). The objective of this study is to validate the use of in situ probes for the detection and management of cyanobacterial breakthrough in high and low-risk DWTPs. In situ phycocyanin YSI EXO2 probes were devised for remote control and data logging to monitor the cyanobacteria in raw, clarified, filtered, and treated water in three full-scale DWTPs. An additional probe was installed inside the sludge holding tank to measure the water quality of the surface of the sludge storage tank in a high-risk DWTP. Simultaneous grab samplings were carried out for taxonomic cell counts and toxin analysis. A total of 23, 9, and 4 field visits were conducted at the three DWTPs. Phycocyanin readings showed a 93-fold fluctuation within 24 h in the raw water of the high cyanobacterial risk plant, with higher phycocyanin levels during the afternoon period. These data provide new information on the limitations of weekly or daily grab sampling. Also, different moving averages for the phycocyanin probe readings can be used to improve the interpretation of phycocyanin signal trends. The in situ probe successfully detected high cyanobacterial biovolumes entering the clarification process in the high-risk plant. Grab sampling results revealed high cyanobacterial biovolumes in the sludge for both high and low-risk plants.

Northern hardwoods are susceptible to a wide range of defects that can reduce the amount of sound wood with desirable qualities, such as the clear sapwood of sugar maple trees. Yet, the rate at which trees decline in quality due to the development of such defects has never been quantified in northern hardwood forests due to a dearth of repeat inventories that record the appearance of defects over time. As a result, it remains uncertain whether, and how, selection management reduces the probability of decline in quality. In this study, we quantify the rate at which trees decline in quality due to the development of defects, and we test several hypotheses regarding the influence of selection management on quality. Our results show that (1) the probability of decline in quality increases as trees grow larger; (2) crown dieback also increases the probability of decline in quality; (3) the probability of decline in quality is slightly lower in managed stands than in unmanaged stands, and (4) the probability of decline in quality increases with the mean annual temperature of the site. Finally, we combined our estimates of the probability of decline in quality with previous estimates of the probability of mortality to assess the overall risk associated with retaining trees of different species, sizes, and vigour profiles. The resulting metric can inform efforts to improve the management of northern hardwood forests by providing an integrated estimate of the risk that the value of a tree will be reduced, or eliminated, due to mortality or decline in quality.

Performing a complete silvicultural diagnosis before a silvicultural treatment generally requires assessing the state of regeneration with the help of an inventory by sampling, particularly for stands dominated by sugar maple (Acer saccharum Marsh.) or yellow birch (Betula alleghaniensis Britt.), in which partial cuts are recommended. This inventory may then be compared to the standard or used in a growth model for saplings (trees for which the diameter measured at 1.3 m above the ground (DBH) varies from 1.1 cm to 9.0 cm). Some of these tools are based on sapling density, while others are based on the stocking of the saplings or on the stocking of total regeneration (combining saplings and seedlings with a DBH ≤ 1.0 cm). We assessed the number of plots required to estimate the density and the stocking of saplings with a given margin of error in 28 stands. The results show that more plots are required than usual in practice to inventory sapling density. The stocking is much easier to estimate precisely.

Abstract. Spaceborne microwave remote sensing (300 MHz–100 GHz) provides a valuable method for characterizing environmental changes, especially in Arctic–boreal regions (ABRs) where ground observations are generally spatially and temporally scarce. Although direct measurements of carbon fluxes are not feasible, spaceborne microwave radiometers and radar can monitor various important surface and near-surface variables that affect terrestrial carbon cycle processes such as respiratory carbon dioxide (CO2) fluxes; photosynthetic CO2 uptake; and processes related to net methane (CH4) exchange including CH4 production, transport and consumption. Examples of such controls include soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties and land cover. Microwave remote sensing also provides a means for independent aboveground biomass estimates that can be used to estimate aboveground carbon stocks. The microwave data record spans multiple decades going back to the 1970s with frequent (daily to weekly) global coverage independent of atmospheric conditions and solar illumination. Collectively, these advantages hold substantial untapped potential to monitor and better understand carbon cycle processes across ABRs. Given rapid climate warming across ABRs and the associated carbon cycle feedbacks to the global climate system, this review argues for the importance of rapid integration of microwave information into ABR terrestrial carbon cycle science.

The identification of bedforms has an important role in the study of seafloor morphology. The presence of these dynamic structures on the seafloor represents a hazard for navigation. They also influence the hydrodynamic simulation models used in the context, for example, of coastal flooding. Generally, multiBeam EchoSounders (MBES) are used to survey these bedforms. Unfortunately, the coverage of the MBES is limited to small areas per survey. Therefore, the analysis of large areas of interest (like navigation channels) requires the integration of different datasets acquired over overlapping areas at different times. The presence of spatial and temporal inconsistencies between these datasets may significantly affect the study of bedforms, which are subject to many natural processes (e.g. tides; flow). This paper proposes a novel approach to integrate multisource bathymetric datasets to study bedforms. The proposed approach is based on consolidating multisource datasets and applying the Empirical Bayesian Kriging interpolation for the creation of a multisource Digital Bathymetric Model (DBM). It has been designed to be adapted for estuarine areas with a high dynamism of the seafloor, characteristic of the fluvio-marine regime of the Estuary of the Saint-Lawrence River. This area is distinguished by a high tidal cycle and the presence of fields of dunes. The study involves MBES data that was acquired daily over a field of dunes in this area over the span of four days for the purpose of monitoring the morphology and migration of dunes. The proposed approach performs well with a resulting surface with a reduced error relative to the original data compared to existing approaches and the conservation of the dune shape through the integration of the data sets despite the highly dynamic fluvio-marine environments.

A three-dimensional large eddy simulation model is used to simulate the turbulent flow dynamics around a circular pier in live-bed and clear-water scour conditions. The Navier–Stokes equations are transformed into a σ-coordinate system and solved using a second-order unstructured triangular finite-volume method. We simulate the bed evolution by solving the Exner-Polya equation assisted by a sand-slide model as a correction method. The bedload transport rate is based on the model of Engelund and Fredsœ. The model was validated for live-bed conditions in a wide channel and clear-water conditions in a narrow channel against the experimental data found in the literature. The in-house model NSMP3D can successfully produce both the live-bed and clear-water scouring throughout a stable long-term simulation. The flow model was used to study the effects of the blockage ratio in the flow near the pier in clear-water conditions, particularly the contraction effect at the zone where the scour hole starts to form. The scour depth in the clear water simulations is generally deeper than the live-bed simulations. In clear-water, the results show that the present model is able to qualitatively and quantitatively capture the hydrodynamic and morphodynamic processes near the bed. In comparison to the wide channel situation, the simulations indicate that the scour rate is faster in the narrow channel case.

Abstract. This study investigates the ability of long short-term memory (LSTM) neural networks to perform streamflow prediction at ungauged basins. A set of state-of-the-art, hydrological model-dependent regionalization methods are applied to 148 catchments in northeast North America and compared to an LSTM model that uses the exact same available data as the hydrological models. While conceptual model-based methods attempt to derive parameterizations at ungauged sites from other similar or nearby catchments, the LSTM model uses all available data in the region to maximize the information content and increase its robustness. Furthermore, by design, the LSTM does not require explicit definition of hydrological processes and derives its own structure from the provided data. The LSTM networks were able to clearly outperform the hydrological models in a leave-one-out cross-validation regionalization setting on most catchments in the study area, with the LSTM model outperforming the hydrological models in 93 % to 97 % of catchments depending on the hydrological model. Furthermore, for up to 78 % of the catchments, the LSTM model was able to predict streamflow more accurately on pseudo-ungauged catchments than hydrological models calibrated on the target data, showing that the LSTM model's structure was better suited to convert the meteorological data and geophysical descriptors into streamflow than the hydrological models even calibrated to those sites in these cases. Furthermore, the LSTM model robustness was tested by varying its hyperparameters, and still outperformed hydrological models in regionalization in almost all cases. Overall, LSTM networks have the potential to change the regionalization research landscape by providing clear improvement pathways over traditional methods in the field of streamflow prediction in ungauged catchments.

Natural disasters have been demonstrated to cause devastating effects on economic and social development in China, but little is known about the relationship between natural disasters and income at the household level. This study explores the impact of natural disasters on household income, expenditure, and inequality in China as the first study of this nature for the country. The empirical analysis is conducted based on a unique panel dataset that contains six waves of the Chinese Household Income Project (CHIP) survey data over the 1988–2018 period, data on natural disasters, and other social and economic status of households. By employing the fixed effects models, we find that disasters increase contemporaneous levels of income inequality, and disasters that occurred in the previous year significantly increase expenditure inequality. Natural disasters increase operating income inequality but decrease transfer income inequality. Poor households are found to be more vulnerable to disasters and suffer significant income losses. However, there is no evidence to suggest that natural disasters significantly reduce the income of upper- and middle-income groups. These findings have important implications for policies aimed at poverty alleviation and revenue recycling, as they can help improve economic justice and enhance resilience to natural disasters.

Agricultural activities can result in the contamination of surface runoff with pathogens, pesticides, and nutrients. These pollutants can enter surface water bodies in two ways: by direct discharge into surface waters or by infiltration and recharge into groundwater, followed by release to surface waters. Lack of financial resources makes risk assessment through analysis of drinking water pollutants challenging for drinking water suppliers. Inability to identify agricultural lands with a high-risk level and implement action measures might lead to public health issues. As a result, it is essential to identify hazards and conduct risk assessments even with limited data. This study proposes a risk assessment model for agricultural activities based on available data and integrating various types of knowledge, including expert and literature knowledge, to estimate the levels of hazard and risk that different agricultural activities could pose to the quality of withdrawal waters. To accomplish this, we built a Bayesian network with continuous and discrete inputs capturing raw water quality and land use upstream of drinking water intakes (DWIs). This probabilistic model integrates the DWI vulnerability, threat exposure, and threats from agricultural activities, including animal and crop production inventoried in drainage basins. The probabilistic dependencies between model nodes are established through a novel adaptation of a mixed aggregation method. The mixed aggregation method, a traditional approach used in ecological assessments following a deterministic framework, involves using fixed assumptions and parameters to estimate ecological outcomes in a specific case without considering inherent randomness and uncertainty within the system. After validation, this probabilistic model was used for four water intakes in a heavily urbanized watershed with agricultural activities in the south of Quebec, Canada. The findings imply that this methodology can assist stakeholders direct their efforts and investments on at-risk locations by identifying agricultural areas that can potentially pose a risk to DWIs.

Studies show associations between prenatal maternal stress (PNMS) and child autism, with little attention paid to PNMS and autism in young adulthood. The broad autism phenotype (BAP), encompassing sub-clinical levels of autism, includes aloof personality, pragmatic language impairment and rigid personality. It remains unclear whether different aspects of PNMS explain variance in different BAP domains in young adult offspring. We recruited women who were pregnant during, or within 3 months of, the 1998 Quebec ice storm crisis, and assessed three aspects of their stress (i.e., objective hardship, subjective distress and cognitive appraisal). At age 19, the young adult offspring (n = 33, 22F / 11M) completed a BAP self-report. Linear and logistic regressions were implemented to examine associations between PNMS and BAP traits. Up to 21.4% of the variance in BAP total score and in BAP three domains tended to be explained by at least one aspect of maternal stress, For example, 16.8% of the variance in aloof personality tended to be explained by maternal objective hardship; 15.1% of the variance in pragmatic language impairment tended to be explained by maternal subjective distress; 20.0% of the variance in rigid personality tended to be explained by maternal objective hardship and 14.3% by maternal cognitive appraisal. Given the small sample size, the results should be interpreted with caution. In conclusion, this small prospective study suggests that different aspects of maternal stress could have differential effects on different components of BAP traits in young adults.

Abstract Studies have shown that prenatal maternal stress (PNMS) affects brain structure and function in childhood. However, less research has examined whether PNMS effects on brain structure and function extend to young adulthood. We recruited women who were pregnant during or within 3 months following the 1998 Quebec ice storm, assessed their PNMS, and prospectively followed‐up their children. T1‐weighted magnetic resonance imaging (MRI) and resting‐state functional MRI were obtained from 19‐year‐old young adults with ( n  = 39) and without ( n  = 65) prenatal exposure to the ice storm. We examined between‐group differences in gray matter volume (GMV), surface area (SA), and cortical thickness (CT). We used the brain regions showing between‐group GMV differences as seeds to compare between‐group functional connectivity. Within the Ice Storm group, we examined (1) associations between PNMS and the atypical GMV, SA, CT, and functional connectivity, and (2) moderation by timing of exposure. Primarily, we found that, compared to Controls, the Ice Storm youth had larger GMV and higher functional connectivity of the anterior cingulate cortex, the precuneus, the left occipital pole, and the right hippocampus; they also had larger CT, but not SA, of the left occipital pole. Within the Ice Storm group, maternal subjective distress during preconception and mid‐to‐late pregnancy was associated with atypical left occipital pole CT. These results suggest the long‐lasting impact of disaster‐related PNMS on child brain structure and functional connectivity. Our study also indicates timing‐specific effects of the subjective aspect of PNMS on occipital thickness.

The climate crisis not only has significant impacts on biodiversity and the physical health of humans, but its ramifications are also affecting people’s mental health. Eco-anxiety, or the emotions that emerge with the awareness of climate change and the apprehension of its detrimental effects, has been investigated in adults and adolescents, but much less attention has been given to the impacts on children’s mental health and well-being. Initial evidence confirms that youth are significantly concerned about climate change, but few studies have investigated the resulting emotional responses of children and the role of their parents in tempering these, especially using qualitative methodologies. The present study used a descriptive qualitative design with a convenience sample of parents and child dyads, assessed separately. Children’s ( n = 15, ages 8–12 years) experiences were explored using semi-structured interviews and their parents’ ( n = 12) perceptions were captured using a survey with closed and open-ended questions. A reflexive thematic analysis was used to analyze the interview data, and content analysis was used to investigate parent-child experiences. Three themes emerged from the thematic analysis: 1. children’s understanding of climate change, 2. their emotional reaction to climate change, and 3. their coping mechanisms to deal with these emotions. The comparative content analysis revealed that parents who were aware that their children had concerns about climate change, had children who used more adaptive coping mechanisms. The results of this qualitative study contribute to a better understanding of children’s emotional experience of the awareness of climate change in Canada and how they cope with these emotions. Furthermore, the results provide insight into the role parents might play in helping their children cope with their feelings.