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Abstract Having a realistic estimation of snow cover by conceptual hydrological models continues to challenge hydrologists. The calibration of the free model parameters is an unavoidable step and the uncertainties resulting from the use of this optimal set remains a source of concern, especially in forecasting applications and climate changes impact assessments. This study seeks to improve the calibration of the conceptual hydrological model GR4J coupled with the Cemaneige snow model, in order to obtain a more realistic simulation of the snow water equivalent (SWE) and to reduce the uncertainty of the free parameters. The performance of the two models was tested over twelve snow-dominated basins in southern Quebec, Canada. Four calibration strategies were adopted and compared. In the first two strategies, the parameters were calibrated against observed streamflow alone using a local and a global algorithm. In the third and fourth strategies the calibration of snow and hydrological parameters was performed against observed streamflow and snow water equivalent (SWE) measured at snow course transects, first separately, and then with a multiobjective approach. An ensemble of equifinal parameters was used to compare the capacity of the global and multiobjective algorithms to improve the parameters identifiability and to assess the impact of parameter equifinality on the temperature sensitivity of spring peak streamflow. The large number of equifinal parameters found during calibration underscores the importance of structural non-identifiability of the coupled GR4J-Cemaneige model. The inclusion of snow observations within a multiobjective calibration improved the simulation of SWE, the identifiability of the parameters and their correlation with basins characteristics. Parameter equifinality caused a small but non negligible uncertainty in the simulated response of spring peak flow to warming temperatures. Parameter equifinality should be considered in climate impact studies in snow-dominated basins where poorly constrained snow parameters can affect the temperature sensitivity of streamflow.

Abstract. Black carbon aerosol (BC), which is emitted from natural and anthropogenic sources (e.g., wildfires, coal burning), can contribute to magnify climate warming at high latitudes by darkening snow- and ice-covered surfaces, and subsequently lowering their albedo. Therefore, modeling the atmospheric transport and deposition of BC to the Arctic is important, and historical archives of BC accumulation in polar ice can help to validate such modeling efforts. Here we present a > 250-year ice-core record of refractory BC (rBC) deposition on Devon ice cap, Canada, spanning the years from 1735 to 1992. This is the first such record ever developed from the Canadian Arctic. The estimated mean deposition flux of rBC on Devon ice cap for 1963–1990 is 0.2 mg m−2 a−1, which is at the low end of estimates from Greenland ice cores obtained using the same analytical method ( ∼ 0.1–4 mg m−2 a−1). The Devon ice cap rBC record also differs from the Greenland records in that it shows only a modest increase in rBC deposition during the 20th century. In the Greenland records a pronounced rise in rBC is observed from the 1880s to the 1910s, which is largely attributed to midlatitude coal burning emissions. The deposition of contaminants such as sulfate and lead increased on Devon ice cap in the 20th century but no concomitant rise in rBC is recorded in the ice. Part of the difference with Greenland could be due to local factors such as melt–freeze cycles on Devon ice cap that may limit the detection sensitivity of rBC analyses in melt-impacted core samples, and wind scouring of winter snow at the coring site. Air back-trajectory analyses also suggest that Devon ice cap receives BC from more distant North American and Eurasian sources than Greenland, and aerosol mixing and removal during long-range transport over the Arctic Ocean likely masks some of the specific BC source–receptor relationships. Findings from this study suggest that there could be a large variability in BC aerosol deposition across the Arctic region arising from different transport patterns. This variability needs to be accounted for when estimating the large-scale albedo lowering effect of BC deposition on Arctic snow/ice.

The objective of this study was to verify if the consumption of different beverages (such as water, 100% pure fruit juice, and sugar-sweetened beverages (SSBs)) is associated with adolescents’ sleep quality. French-speaking adolescents were recruited in person and online throughout the province of Québec (Canada) from the end of March to early July 2023. Beverage consumption and sleep quality were measured using French versions of validated questionnaires specifically designed for adolescents. A total of 218 adolescents (14–17 years; 55.5% female) completed the online survey. Among caffeinated SSBs, energy drink (rs = −0.16; p = 0.0197) and sugar-sweetened coffee (rs = −0.33; p < 0.0001) intake was correlated with adolescents’ sleep quality. Energy drink consumption (β = −0.0048; p = 0.0005) and being male (β = 0.6033; p < 0.0001) were associated with adolescents’ sleep quality. There was an interaction between sugar-sweetened coffee intake and biological sex that was associated with adolescents’ sleep quality (p = 0.0053). Sugar-sweetened coffee consumption was correlated with adolescent girls’ abilities to go to bed (rs = −0.21; p = 0.0203) and fall asleep (rs = −0.28; p = 0.0020), while in boys, it was only significantly correlated with their abilities to go to bed (rs = −0.27; p = 0.0069). Public health interventions aimed at adolescent boys should primarily target lowering energy drink consumption, while those aimed at girls should prioritize sugar-sweetened coffee intake to possibly improve their sleep quality.

Nature-based Solutions (NbS) for coastal protection have been widely recognized as sustainable, economical, and eco-friendly alternatives to conventional grey structures, particularly under the threat of climate change (Temmerman et al., 2013). Living shorelines are a form of NbS, which incorporate natural elements (such as saltmarshes) that provide flood and erosion risk management benefits. Climate change impacts, such as rising sea levels and reducing sea-ice cover (Savard et al., 2016), are increasingly motivating communities in Canada to consider incorporating living shorelines in coastal protection schemes. The efficacy of wave energy dissipation by vegetation depends on both hydrodynamic conditions and plant characteristics. However, plant parameters, such as standing biomass exhibit seasonal fluctuations, leading to corresponding variations in attenuation capacity (Schulze et al., 2019). Hence, the design of NbS utilizing saltmarsh vegetation must account for seasonal variations to ensure sustained efficacy, especially within the context of Canadian regional climates, which are typically characterized by extended, stormy winters and shorter summer seasons. Few studies have quantified wave attenuation by real saltmarsh vegetation in large-scale laboratory facilities (Möller et al., 2014; Maza et al., 2015; Ghodoosipour et al., 2022), particularly for species native to the east coast of Canada. There is a knowledge gap on how seasonality affects wave attenuation by saltmarsh vegetation and how attenuation varies from the lower marsh to the higher marsh depending on species-specific plant traits. Research is needed to bridge this gap and develop technical guidance for the design of performant living shorelines in Canada.

Peatlands occupy around 13% of the land cover of Canada, and thus play a key role in the water balance at high latitudes. They are well known for having substantial water loss due to evapotranspiration. Since measurements of evapotranspiration are scarce over these environments, hydrologists generally rely on models of varying complexity to evaluate these water exchanges in the global watershed balance. This study quantifies the water budget of a small boreal peatland-dominated watershed. We assess the performance of three evapotranspiration models in comparison with in situ observations and the impact of using these models in the hydrological modeling of the watershed. The study site (~1-km2) is located in the Eastern James Bay lowlands, Quebec, Canada. During summer 2012, an eddy flux tower measured evapotranspiration continuously, while a trapezoidal flume monitored streamflow at the watershed outlet. We estimated evapotranspiration with a combinational model (Penman), a radiation-based model (Priestle...

This paper presents the extension of the monolayer snow model of a semi-distributed hydrological model (HYDROTEL) to a multilayer model that considers snow to be a combination of ice and air, while accounting for freezing rain. For two stations in Yukon and one station in northern Quebec, Canada, the multilayer model achieves high performances during calibration periods yet similar to the those of the monolayer model, with KGEs of up to 0.9. However, it increases the KGE values by up to 0.2 during the validation periods. The multilayer model provides more accurate estimations of maximum SWE and total spring snowmelt dates. This is due to its increased sensitivity to thermal atmospheric conditions. Although the multilayer model improves the estimation of snow heights overall, it exhibits excessive snow densities during spring snowmelt. Future research should aim to refine the representation of snow densities to enhance the accuracy of the multilayer model. Nevertheless, this model has the potential to improve the simulation of spring snowmelt, addressing a common limitation of the monolayer model.

&lt;p&gt;The applicability of the Canadian Precipitation Analysis products known as the Regional Deterministic Precipitation Analysis (CaPA-RDPA) for hydrological modelling in boreal watersheds in Canada, which are constrained with shortage of precipitation information, has been the subject of a number of recent studies. The northern and mid-cordilleran alpine, sub-alpine, and boreal watersheds in Yukon, Canada, are prime examples of such Nordic regions where any hydrological modelling application is greatly scrambled due to lack of accurate precipitation information. In the course of the past few years, proper advancements were tailored to resolve these challenges and a forecasting system was designed at the operational level for short- to medium-range flow and inflow forecasting in major watersheds of interest to Yukon Energy. This forecasting system merges the precipitation products from the North American Ensemble forecasting System (NAEFS) and recorded flows or reconstructed reservoir inflows into the HYDROTEL distributed hydrological model, using the Ensemble Kalman Filtering (EnKF) data assimilation technique. In order to alleviate the adverse effects of scarce precipitation information, the forecasting system also enjoys a snow data assimilation routine in which simulated snowpack water content is updated through a distributed snow correction scheme. Together, both data assimilation schemes offer the system with a framework to accurately estimate flow magnitudes. This robust system not only mitigates the adverse effects of meteorological data constrains in Yukon, but also offers an opportunity to investigate the hydrological footprint of CaPA-RDPA products in Yukon, which is exactly the motivation behind this presentation. However, our overall goal is much more comprehensive as we are trying to elucidate whether assimilating snow monitoring information in a distributed hydrological model could meet the flow estimation accuracy in sparsely gauged basins to the same extent that would be achieved through either (i) the application of precipitation analysis products, or (ii) expanding the meteorological network. A proper answer to this question would provide us with valuable information with respect to the robustness of the snow data assimilation routine in HYDROTEL and the intrinsic added-value of using CaPA-RDPA products in sparsely gauged basins of Yukon.&lt;/p&gt;

Abstract Low flow conditions are governed by short-to-medium term weather conditions or long term climate conditions. This prompts the question: given climate scenarios, is it possible to assess future extreme low flow conditions from climate data indices (CDIs)? Or should we rely on the conventional approach of using outputs of climate models as inputs to a hydrological model? Several CDIs were computed using 42 climate scenarios over the years 1961–2100 for two watersheds located in Quebec, Canada. The relationship between the CDIs and hydrological data indices (HDIs; 7- and 30-day low flows for two hydrological seasons) were examined through correlation analysis to identify the indices governing low flows. Results of the Mann-Kendall test, with a modification for autocorrelated data, clearly identified trends. A partial correlation analysis allowed attributing the observed trends in HDIs to trends in specific CDIs. Furthermore, results showed that, even during the spatial validation process, the methodological framework was able to assess trends in low flow series from: (i) trends in the effective drought index (EDI) computed from rainfall plus snowmelt minus PET amounts over ten to twelve months of the hydrological snow cover season or (ii) the cumulative difference between rainfall and potential evapotranspiration over five months of the snow free season. For 80% of the climate scenarios, trends in HDIs were successfully attributed to trends in CDIs. Overall, this paper introduces an efficient methodological framework to assess future trends in low flows given climate scenarios. The outcome may prove useful to municipalities concerned with source water management under changing climate conditions.

The water content of wetlands represents a key driver of their hydrological services and it is highly dependent on short- and long-term weather conditions, which will change, to some extent, under evolving climate conditions. The impact on stream flows of this critical dynamic component of wetlands remains poorly studied. While hydrodynamic modelling provide a framework to describe the functioning of individual wetland, hydrological modelling offers the opportunity to assess their services at the watershed scale with respect to their type (i.e., isolated or riparian). This study uses a novel approach combining hydrological modelling and limited field monitoring, to explore the effectiveness of wetlands under changing climate conditions. To achieve this, two isolated wetlands and two riparian wetlands, located in the Becancour River watershed within the St Lawrence Lowlands (Quebec, Canada), were monitored using piezometers and stable water isotopes (δD – δ18O) between October 2013 and October 2014. For the watershed hydrology component of this study, reference (1986–2015) and future meteorological data (2041–2070) were used as inputs to the PHYSITEL/HYDROTEL modelling platform. Results obtained from in-situ data illustrate singular hydrological dynamics for each typology of wetlands (i.e., isolated and riparian) and support the hydrological modelling approach used in this study. Meanwhile, simulation results indicate that climate change could affect differently the hydrological dynamics of wetlands and associated services (e.g., storage and slow release of water), including their seasonal contribution (i.e., flood mitigation and low flow support) according to each wetland typology. The methodological framework proposed in this paper meets the requirements of a functional tool capable of anticipating hydrological changes in wetlands at both the land management scale and the watershed management scale. Accordingly, this framework represents a starting point towards the design of effective wetland conservation and/or restoration programs.

Wetlands play a significant role on the hydrological cycle, reducing flood peaks through water storage functions and sustaining low flows through slow water release ability. However, their impacts on water resources availability and flood control are mainly driven by wetland type (e.g., isolated wetland –IW- and riparian wetland –RW-) and location within a watershed. Consequently, assessing the qualitative and quantitative impact of wetlands on hydrological regimes has become a relevant issue for scientists as well as stakeholders and decision-makers. In this study, the distributed hydrological model, HYDROTEL, was used to investigate the role and impact of the geographic distribution of isolated and riparian wetlands on stream flows of the Becancour River watershed of the St Lawrence Lowlands, Quebec, Canada. The model was set up and calibrated using available datasets (i.e., DEM, soil, wetland distribution, climate, land cover, and hydrometeorological data for the 1969-2010 period). Different Wetland Theoretical Location Tests (WTLT) were simulated. Results were used to determine whether stream flow parameters, related to peak flows and low flows, were related to: (i) geographic location of wetlands, (ii) typology of wetlands, and (iii) seasonality. The contribution of a particular wetland was assessed using intrinsic characteristics (e.g., surface area, typology) and extrinsic factors (e.g., location in the watershed landscape and seasonality). Through these investigations, the results suggest, to some extent, that both IWs and RWs impact landscape hydrology. The more IWs are located in the upper part of the watershed, the greater their effect on both on high flow damping and low flow support seems to be. The more RWs are connected to a main stream, the greater their effect is. Our modelling results indicate that local landscape conditions may influence the wetland effect; promoting or limiting their efficiency, and thus their impacts on stream flows depend on a combined effect of wetland and landscape attributes.

Mathematical modelling is a well-accepted framework to evaluate the effects of wetlands on stream flow and watershed hydrology in general. Although the integration of wetland modules into a distributed hydrological model represents a cost-effective way to make this assessment, the added value brought by landscape-specific modules to a model's ability to replicate basic hydrograph characteristics remains unclear. The objectives of this paper were to: (i) present the adaptation of PHYSITEL (a GIS) to parameterize isolated and riparian wetlands; (ii) describe the integration of specific isolated wetland and riparian wetland modules into HYDROTEL, a distributed hydrological model; and (iii) evaluate the performance of the updated modelling platform with respect to the capacity of replicating various hydrograph characteristics. To achieve this, two sets of simulations were performed (with and without wetland modules) and the added-value was assessed at three river segments of the Becancour River watershed, Quebec, Canada, using six general goodness-of-fit indicators (GOFIs) and fourteen water flow criteria (WFC). A sensitivity analysis of the wetland module parameters was performed to characterize their impact on stream flows of the modelled watershed. Results of this study indicate that: (i) integration of specific wetland modules can slightly increase the capacity of HYDROTEL to replicate basic hydrograph characteristics and (ii) the updated modelling platform allows for the explicit assessment of the impact of wetlands (e.g., typology, location) on watershed hydrology.

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.

Abstract This study compares the impacts of climate, agriculture and wetlands on the spatio-temporal variability of seasonal daily minimum flows during the period 1930–2019 in 17 watersheds of southern Quebec (Canada). In terms of spatial variability, correlation analysis revealed that seasonal daily minimum flows were mainly negatively correlated with the agricultural surface area in watersheds in spring, summer and fall. In winter, these flows were positively correlated with the wetland surface area and March temperatures but negatively correlated with snowfall. During all four seasons, spatial variability was characterized by higher daily minimum flow values on the north shore (smaller agricultural surface area and larger wetland surface area) than those on the south shore. As for temporal variability, the application of six tests of the long-term trend analysis showed that most agricultural watersheds are characterized by a significant increase in flows during the four seasons due to the reduction in agricultural area, thus favoring water infiltration, and increased rainfall in summer and fall. On the other hand, the reduction in the snowfall resulted in a reduction in summer daily minimum flows observed in several less agricultural watersheds.

Abstract This study explores the potential impacts of climate change on soil erosion in an agricultural catchment in eastern Canada. The Modified Universal Soil Loss Equation (MUSLE) was used to calculate the sediment yields from the Acadie River Catchment for the historical 1996–2019 period. The runoff variables of the MUSLE were obtained from a physically based hydrological model previously built and validated for the catchment. Then, the hydrological model was perturbed using climate change projections and used to assess the climate sensitivity of the sediment yield. Two runoff types representing possible modes of soil erosion were considered. While type A represents a baseline case in which soil erosion occurs due to surface runoff only, type B is more realistic since it assumed that tile drains also contribute to sediment export, but with a varying efficiency throughout the year. The calibration and validation of the tile efficiency factors against measurements in 2009–2015 for type B suggest that tile drains export the sediments with an efficiency of 20% and 50% in freezing and non-freezing conditions, respectively. Results indicate that tile drains account for 39% of the total annual sediment yield in the present climate. The timing of highest soil erosion shifts from spring to winter in response to warming and wetting, which can be explained by increasing winter runoff caused by shifting snowmelt timing towards winter, a greater number of mid-winter melt events as well as increasing rainfall fractions. The large uncertainties in precipitation projections cascade down to the erosion uncertainties in the more realistic type B, with annual sediment yield increasing or decreasing according to the precipitation uncertainty in a given climate change scenario. This study demonstrates the benefit of conservation and no-till pratices, which could reduce the annual sediment yields by 20% and 60%, respectively, under any given climate change scenario.

Adaptation to climate change is a challenge that is complex and involves increasing risk. Efforts to manage these risks involve many decision-makers, conflicting values, competing objectives and methodologies, multiple alternative options, uncertain outcomes, and debatable probabilities. Adaptation occurs at multiple levels in a complex decision environment and is generally evaluated as better–worse, not right–wrong, based on multiple criteria. Identifying the best adaptation response is difficult. Risk management techniques help to overcome these problems. Here, risk management is presented as a decision-making framework that assists in the selection of optimal strategies (according to various criteria) using a systems approach that has been well defined and generally accepted in public decision-making. In the context of adapting to climate change, the risk management process offers a framework for identifying, assessing, and prioritizing climate-related risks and developing appropriate adaptation responses. The theoretical discussion is illustrated with an example from Canada. It includes (a) the assessment of climate change-caused flood risk to the municipal infrastructure for the City of London, Ontario, Canada, and (b) analysis of adaptation options for management of the risk in one of the watersheds within the City of London – Dingman Creek.

Extreme rainfall intensity–duration–frequency (IDF) relations have been commonly used for estimating the design storm for the design of various urban water infrastructures. In recent years, climate change has been recognized as having a profound impact on the hydrologic cycle. Hence, the derivation of IDF relations in the context of a changing climate has been recognized as one of the most challenging tasks in current engineering practice. The main challenge is how to establish the linkages between the climate projections given by climate models at the global or regional scales and the observed extreme rainfalls at a local site of interest. Therefore, our overall objective is to introduce a new statistical modeling approach to linking global or regional climate predictors to the observed daily and sub-daily rainfall extremes at a given location. Illustrative applications using climate simulations from 21 different global climate models and extreme rainfall data available from rain gauge networks located across Canada are presented to indicate the feasibility, accuracy, and robustness of the proposed modeling approach for assessing the climate change impact on IDF relations.

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.

Background Given the important role that municipalities must play in adapting to climate change, it is more than ever essential to measure their progress in this area. However, measuring municipalities’ adaptation progress presents its share of difficulties especially when it comes to comparing (on similar dimensions and over time) the situation of different municipal entities and to linking adaptation impacts to local actions. Longitudinal studies with recurring indicators could capture changes occurring over time, but the development of such indicators requires great emphasis on methodological and psychometric aspects, such as measurement validity. Therefore, this study aimed to develop and validate an index of adaptation to heatwaves and flooding at the level of municipal urbanists and urban planners. Methods A sample of 139 officers working in urbanism and urban planning for municipal entities in the province of Quebec (Canada) completed an online questionnaire. Developed based on a literature review and consultation of representatives from the municipal sector, the questionnaire measured whether the respondent’s municipal entity did or did not adopt the behaviors that are recommended in the scientific and gray literature to adapt to heatwaves and flooding. Results Results of the various metrological analyses (indicator reliability analysis, first order confirmatory factor analysis, concurrent validity analysis, and nomological validity assessment analysis) confirmed the validity of the index developed to measure progress in climate change adaptation at the municipal level. The first dimension of the index corresponds to preliminary measures that inform and prepare stakeholders for action (i.e., groundwork adaptation initiatives), whereas the second refers to measures that aim to concretely reduce vulnerability to climate change, to improve the adaptive capacity or the resilience of human and natural systems (i.e., adaptation actions). Conclusion The results of a series of psychometric analyses showed that the index has good validity and could properly measure the adoption of actions to prepare for adaptation as well as adaptation actions per se. Municipal and government officials can therefore consider using it to monitor and evaluate adaptation efforts at the municipal level.

Summary Probable maximum snow accumulation (PMSA) is one of the key variables used to estimate the spring probable maximum flood (PMF). A robust methodology for evaluating the PMSA is imperative so the ensuing spring PMF is a reasonable estimation. This is of particular importance in times of climate change (CC) since it is known that solid precipitation in Nordic landscapes will in all likelihood change over the next century. In this paper, a PMSA methodology based on simulated data from regional climate models is developed. Moisture maximization represents the core concept of the proposed methodology; precipitable water being the key variable. Results of stationarity tests indicate that CC will affect the monthly maximum precipitable water and, thus, the ensuing ratio to maximize important snowfall events. Therefore, a non-stationary approach is used to describe the monthly maximum precipitable water. Outputs from three simulations produced by the Canadian Regional Climate Model were used to give first estimates of potential PMSA changes for southern Quebec, Canada. A sensitivity analysis of the computed PMSA was performed with respect to the number of time-steps used (so-called snowstorm duration) and the threshold for a snowstorm to be maximized or not. The developed methodology is robust and a powerful tool to estimate the relative change of the PMSA. Absolute results are in the same order of magnitude as those obtained with the traditional method and observed data; but are also found to depend strongly on the climate projection used and show spatial variability.

Pesticide transport by surface runoff depends on climate, agricultural practices, topography, soil characteristics, crop type, and pest phenology. To accurately assess the impact of climate change, these factors must be accounted for in a single framework by integrating their interaction and uncertainty. This paper presents the development and application of a framework to assess the impact of climate change on pesticide transport by surface runoff in southern Quebec (Canada) for the 1981-2040 period. The crop enemies investigated were: weeds for corn (Zea mays); and for apple orchard (Malus pumila), three insect pests (codling moth (Cydia pomonella), plum curculio (Conotrachelus nenuphar) and apple maggot (Rhagoletis pomonella)) and two diseases (apple scab (Venturia inaequalis) and fire blight (Erwinia amylovora)). A total of 23 climate simulations, 19 sites, and 11 active ingredients were considered. The relationship between climate and phenology was accounted for by bioclimatic models of the Computer Centre for Agricultural Pest Forecasting (CIPRA) software. Exported loads of pesticides were evaluated at the edge-of-field scale using the Pesticide Root Zone Model (PRZM), simulating both hydrology and chemical transport. A stochastic model was developed to account for PRZM parameter uncertainty. Results of this study indicate that for the 2011-2040 period, application dates would be advanced from 3 to 7 days on average with respect to the 1981-2010 period. However, the impact of climate change on maximum daily rainfall during the application window is not statistically significant, mainly due to the high variability of extreme rainfall events. Hence for the studied sites and crop enemies considered, climate change impact on pesticide transported in surface runoff is not statistically significant throughout the 2011-2040 period.