Votre recherche

The Penman-Monteith reference evapotranspiration (ET0) formulation was forced with humidity, radiation, and wind speed (HRW) fields simulated by four reanalyses in order to simulate hydrologic processes over six mid-sized nivo-pluvial watersheds in southern Quebec, Canada. The resulting simulated hydrologic response is comparable to an empirical ET0 formulation based exclusively on air temperature. However, Penman-Montheith provides a sounder representation of the existing relations between evapotranspiration fluctuations and climate drivers. Correcting HRW fields significantly improves the hydrologic bias over the pluvial period (June to November). The latter did not translate into an increase of the hydrologic performance according to the Kling-Gupta Efficiency (KGE) metric. The suggested approach allows for the implementation of physically-based ET0 formulations where HRW observations are insufficient for the calibration and validation of hydrologic models and a potential reinforcement of the confidence affecting the projection of low flow regimes and water availability.

Abstract This paper examines the controlling influence of snow and rain on river ice processes in creeks and streams. Winter precipitation (in the form of rain and snow) has been observed to affect river ice processes and channel parameters of low and high gradient channels in unsuspected ways that can have significant impacts on channel hydraulics, hydrology and habitat. On a low gradient stream, a snowfall event initiated the development of an ice cover by creating unconsolidated snow slush bridges that eventually froze in place. Afterward, both snowfalls and rainfalls in alternation with cold spells dramatically increased the thickening rate of the ice cover well beyond that predicted by classic equations. In a smaller low‐gradient agricultural creek, wind‐blown snow impeded the formation of an ice cover by insulating the flow from cold atmospheric conditions. On steep channels (of different sizes and morphologies), anchor snow slush has been seen to accumulate on the bed substrate. As opposed to anchor ice, anchor snow slush is not believed to require supercooling water conditions to form nor to stay in place. Finally, in a steep headwater creek, a rain‐on‐snow event generated a snow slush flow and multiple snow slush jams. This phenomenon was seen to divert most of the water out of the channel into another watershed and concomitantly signalled a mid‐winter breakup in the greater watershed downstream. These observations suggest that the role of precipitation on small channel winter ice morphology and water flows, levels and currents has been severely underestimated and that any ecological winter studies, hydraulic structure designs and river modelling efforts need to include processes that are sometimes dominated by rain, slush and snow. Copyright © 2012 John Wiley & Sons, Ltd.

Abstract. Seeking more accuracy and reliability, the hydrometeorological community has developed several tools to decipher the different sources of uncertainty in relevant modeling processes. Among them, the ensemble Kalman filter (EnKF), multimodel approaches and meteorological ensemble forecasting proved to have the capability to improve upon deterministic hydrological forecast. This study aims to untangle the sources of uncertainty by studying the combination of these tools and assessing their respective contribution to the overall forecast quality. Each of these components is able to capture a certain aspect of the total uncertainty and improve the forecast at different stages in the forecasting process by using different means. Their combination outperforms any of the tools used solely. The EnKF is shown to contribute largely to the ensemble accuracy and dispersion, indicating that the initial conditions uncertainty is dominant. However, it fails to maintain the required dispersion throughout the entire forecast horizon and needs to be supported by a multimodel approach to take into account structural uncertainty. Moreover, the multimodel approach contributes to improving the general forecasting performance and prevents this performance from falling into the model selection pitfall since models differ strongly in their ability. Finally, the use of probabilistic meteorological forcing was found to contribute mostly to long lead time reliability. Particular attention needs to be paid to the combination of the tools, especially in the EnKF tuning to avoid overlapping in error deciphering.

Atmospheric reanalysis data provides a numerical description of global and regional water cycles by combining models and observations. These datasets are increasingly valuable as a substitute for observations in regions where these are scarce. They could significantly contribute to reducing losses by feeding flood early warning systems that can inform the population and guide civil security action. We assessed the suitability of two different precipitation and temperature reanalysis products readily available for predicting historic flooding of the La Chaudière River in Quebec: 1) Environment and Climate Change Canada's Regional Deterministic Reanalysis System (RDRS-v2) and 2) ERA5 from the Copernicus Climate Change Service. We exploited a multi-model hydrological ensemble prediction system that considers three sources of uncertainty: initial conditions, model structure, and weather forcing to produce streamflow forecasts up to 5 days into the future with a time step of 3 hours. These results are compared to a provincial reference product based on gauge measurements of the Ministère de l'Environnement et de la Lutte contre les Changements Climatiques. Then, five conceptual hydrological models were calibrated with three different meteorological datasets (RDRS-v2, ERA5, and observational gridded) and fed with two ensemble weather forecast products: 1) the Regional Ensemble Prediction System (REPS) from the Environment and Climate Change Canada and 2) the ensemble forecast issued by the European Centre for Medium-Range Weather Forecasts (ECMWF). Results reveal that the calibration of the model with reanalysis data as input delivered a higher accuracy in the streamflow simulation providing a useful resource for flood modeling where no other data is available. However, although the selection of the reanalysis is a determinant of capturing the flood volumes, selecting weather forecasts is more critical in anticipating discharge threshold exceedances.

There is currently much discussion as to whether probabilistic (top–down) or possibilistic (bottom–up) approaches are the most appropriate to estimate potential future climate impacts. In a context of deep uncertainty, such as future climate, bottom-up approaches aimed at assessing the sensitivity and vulnerability of systems to changes in climate variables have been gaining ground. A refined framework is proposed here (in terms of coherence, structure, uncertainty, and results analysis) that adopts the scenario–neutral method of the bottom–up approach, but also draws on some elements of the top–down approach. What better guides the task of assessing the potential hydroclimatological impacts of changing climatic conditions in terms of the sensitivity of the systems, differential analysis of climatic stressors, paths of change, and categorized response of the scenarios: past, changing, compensatory, and critical condition. The results revealed a regional behavior (of hydroclimatology, annual water balances, and snow) and a differential behavior (of low flows). We find, among others, the plausible scenario in which increases in temperature and precipitation would generate the same current mean annual flows, with a reduction of half of the snow, a decrease in low flows (significant, but differentiated between basins), and a generalized increase in dry events.

In Canada, floods are the most common largely distributed hazard to life, property, the economy, water systems, and the environment costing the Canadian economy billions of dollars. Arising from this is FloodNet: a transdisciplinary strategic research network funded by Canadas Natural Sciences and Engineering Research Council, as a vehicle for a concerted nation-wide effort to improve flood forecasting and to better assess risk and manage the environmental and socio-economic consequences of floods. Four themes were explored in this network which include 1) Flood regimes in Canada; 2) Uncertainty of floods; 3) Development of a flood forecasting and early warning system and 4) Physical, socio-economic and environmental effects of floods. Over the years a range of statistical, hydrologic, modeling, and economic and psychometric analyses were used across the themes. FloodNet has made significant progress in: assessing spatial and temporal variation of extreme events; updating intensity-duration-frequency (IDF) curves; improving streamflow forecasting using novel techniques; development and testing of a Canadian adaptive flood forecasting and early warning system (CAFFEWS); a better understanding of flood impacts and risk. Despite these advancements FloodNet ends at a time when the World is still grappling with severe floods (e.g., Europe, China, Africa) and we report on several lessons learned. Mitigating the impact of flood hazards in Canada remains a challenging task due to the countrys varied geography, environment, and jurisdictional political boundaries. Canadian technical guide for developing IDF relations for infrastructure design in the climate change context has been recently updated. However, national guidelines for flood frequency analyses are needed since across the country there is not a unified approach to flood forecasting as each jurisdiction uses individual models and procedures. From the perspective of risk and vulnerability, there remains great need to better understand the direct and indirect impacts of floods on society, the economy and the environment.

Abstract. In the boreal forest of eastern Canada, winter temperatures are projected to increase substantially by 2100. This region is also expected to receive less solid precipitation, resulting in a reduction in snow cover thickness and duration. These changes are likely to affect hydrological processes such as snowmelt, the soil thermal regime, and snow metamorphism. The exact impact of future changes is difficult to pinpoint in the boreal forest, due to its complex structure and the fact that snow dynamics under the canopy are very different from those in the gaps. In this study, we assess the influence of a low-snow and warm winter on snowmelt dynamics, soil freezing, snowpack properties, and spring streamflow in a humid and discontinuous boreal catchment of eastern Canada (47.29° N, 71.17° W; ≈ 850 m a.m.s.l.) based on observations and SNOWPACK simulations. We monitored the soil and snow thermal regimes and sampled physical properties of the snowpack under the canopy and in two forest gaps during an exceptionally low-snow and warm winter, projected to occur more frequently in the future, and during a winter with conditions close to normal. We observe that snowmelt was earlier but slower, top soil layers were cooler, and gradient metamorphism was enhanced during the low-snow and warm winter. However, we observe that snowmelt duration increased in forest gaps, that soil freezing was enhanced only under the canopy, and that snow permeability increased more strongly under the canopy than in either gap. Our results highlight that snow accumulation and melt dynamics are controlled by meteorological conditions, soil freezing is controlled by forest structure, and snow properties are controlled by both weather forcing and canopy discontinuity. Overall, observations and simulations suggest that the exceptionally low spring streamflow in the winter of 2020–2120 was mainly driven by low snow accumulation, slow snowmelt, and low precipitation in April and May rather than enhanced percolation through the snowpack and soil freezing.

Given that flooding episodes are occurring at a greater rate due to climate change, individuals must adopt certain adaptation behaviors to prevent or mitigate the anticipated or negative impact of such events. However, few studies have assessed if and how households and individuals have actually taken action in this regard. Because some individual beliefs can be linked to facilitating factors and barriers to action, a better understanding of the adoption of adaptive behaviors requires a combined analysis of individual psychosocial factors. The purpose of this study was to develop a better understanding of the reasons underlying the adoption of behaviors related to structural adaptation to flooding by people living in or near flood-prone areas in the Province of Québec (Canada). Results of a series of structural equation modeling showed that behavioral, normative and control beliefs were all significant predictors of the respondents' intention to adopt structural flood protective behaviors, with normative beliefs being the strongest. By identifying the best psychosocial predictors of the adoption of such behaviors, the results of this study provide valuable insights regarding the most effective factors to be used in public health messages to promote the adoption of behaviors related to structural adaptation to flooding.

Abstract Climate change is predicted to increase the frequency and intensity of floods in the province of Quebec, Canada. Therefore, in 2015, to better monitor the level of adaptation to flooding of Quebec residents living in or near a flood-prone area, the Quebec Observatory of Adaptation to Climate Change developed five indices of adaptation to flooding, according to the chronology of events. The present study was conducted 4 years later and is a follow-up to the 2015 one. Two independent samples of 1951 (2015) and 974 (2019) individuals completed a questionnaire on their adoption (or non-adoption) of flood adaptation behaviors, their perception of the mental and physical impacts of flooding, and their knowledge of the fact that they lived in a flood-prone area. The results of the study demonstrated the measurement invariance of the five indices across two different samples of people over time, ensuring that the differences (or absence of differences) observed in flood-related adaptive behaviors between 2015 and 2019 were real and not due to measurement errors. They also showed that, overall, Quebeckers’ flood-related adaptive behaviors have not changed considerably since 2015, with adaptation scores being similar in 2019 for four of the five flood indices. Moreover, the results indicated an increase in self-reported physical and mental health issues related to past flooding events, as well as a larger proportion of people having consulted a health professional because of these problems. Thus, this study provides a better understanding of flood adaptation in Quebec over the past 4 years and confirms that the five adaptive behavior indices developed in 2015 are appropriate tools for monitoring changes in flood adaptation in the province. Finally, our results showed that little has changed in Quebeckers’ adoption of adaptive behaviors, highlighting the need for awareness raising in order to limit the impacts that climate change will have on the population.