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Abstract. The amount and phase of cold season precipitation accumulating in the upper Saint John River basin are critical factors in determining spring runoff, ice-jams, and flooding in downstream communities. To study the impact of winter and spring storms on the snowpack in the upper Saint John River (SJR) basin, the Saint John River Experiment on Cold Season Storms (SAJESS) utilized meteorological instrumentation, upper air soundings, human observations, and hydrometeor macrophotography during winter/spring 2020–21. Here, we provide an overview of the SAJESS study area, field campaign, and existing data networks surrounding the upper SJR basin. Initially, meteorological instrumentation was co-located with an Environment and Climate Change Canada station near Edmundston, New Brunswick, in early December 2020. This was followed by an intensive observation period that involved manual observations, upper-air soundings, a multi-angle snowflake camera, macrophotography of solid hydrometeors, and advanced automated instrumentation throughout March and April 2021. The resulting datasets include optical disdrometer size and velocity distributions of hydrometeors, micro rain radar output, near-surface meteorological observations, and wind speed, temperature, pressure and precipitation amounts from a K63 Hotplate precipitation gauge, the first one operating in Canada. These data are publicly available from the Federated Research Data Repository at https://doi.org/10.20383/103.0591 (Thompson et al., 2022). We also include a synopsis of the data management plan and data processing, and a brief assessment of the rewards and challenges of utilizing community volunteers for hydro-meteorological citizen science.
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Floods are among the most dangerous and destructive hazards in the world. Stormwater Beneficial Management Practices (BMPs) are a set of strategies that can assist in reducing urban floods and their damages by capturing surface runoff and promoting infiltration. Engagement of citizens in the selection of stormwater BMPs may facilitate the decision-making processes and increase the chance of adopting and maintaining them. Due to existence of catastrophic floods in Brazil, implementing BMPs is essential in the urban areas. The objective of this study is to understand the viewpoints of citizens about a set of stormwater BMPs in Brazil. Moreover, we aim to comprehend whether diverging viewpoints about the BMPs can be associated with existence of different layers in the society. For this purpose, online surveys were used to access wide and diverse groups of citizens from different ages, levels of education and income, as well as geographical location. The questions and descriptions of BMPs were prepared in an accessible language, and then disseminated through various platforms. The responses of more than 1000 participants were analyzed using descriptive and statistical methods. Our results show that the participants found the retention and detention basins, as well as permeable pavement as the most efficient BMPs. Moreover, considering the small-scale practices, although lot related BMPs are considered less efficient, citizens are willing to use green roof, bioretention, and rain barrels in their properties. In addition, most of the respondents support public investments on stormwater BMPs. Our analyses show that participants' age and level of education statistically influenced their choice of BMPs and willingness to pay for their maintenance and construction. These results can help Brazilian policy makers to prepare flood management plans by including stormwater BMPs that would be more accepted by the population. In addition, proposing practices that are aligned with citizens’ perceptions creates a sense of responsibility, and is in accordance with the Brazilian New Framework of Sanitation that includes public participation in policy making.
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Airborne LiDAR scanning is a promising approach to providing high-resolution products that are appropriate for different applications, such as flood management. However, the vertical accuracy of airborne LiDAR point clouds is not constant and varies in space. Having a better knowledge of their accuracy will assist decision makers in more accurately estimating the damage caused by flood. Data producers often report the total estimation of errors by means of comparison with a ground truth. However, the reliability of such an approach depends on various factors including the sample size, accessibility to ground truth, distribution, and a large enough diversity of ground truth, which comes at a cost and is somewhat unfeasible in the larger scale. Therefore, the main objective of this article is to propose a method that could provide a local estimation of error without any third-party datasets. In this regard, we take advantage of geostatistical ordinary kriging as an alternative accuracy estimator. The challenge of considering constant variation across the space leads us to propose a non-stationary ordinary kriging model that results in the local estimation of elevation accuracy. The proposed method is compared with global ordinary kriging and a ground truth, and the results indicate that our method provides more reliable error values. These errors are lower in urban and semi-urban areas, especially in farmland and residential areas, but larger in forests, due to the lower density of points and the larger terrain variations.
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Hydrological time series often present nonstationarities such as trends, shifts, or oscillations due to anthropogenic effects and hydroclimatological variations, including global climate change. For water managers, it is crucial to recognize and define the nonstationarities in hydrological records. The nonstationarities must be appropriately modeled and stochastically simulated according to the characteristics of observed records to evaluate the adequacy of flood risk mitigation measures and future water resources management strategies. Therefore, in the current study, three approaches were suggested to address stochastically nonstationary behaviors, especially in the long-term variability of hydrological variables: as an overall trend, shifting mean, or as a long-term oscillation. To represent these options for hydrological variables, the autoregressive model with an overall trend, shifting mean level (SML), and empirical mode decomposition with nonstationary oscillation resampling (EMD-NSOR) were employed in the hydrological series of the net basin supply in the Lake Champlain-River Richelieu basin, where the International Joint Committee recently managed and significant flood damage from long consistent high flows occurred. The detailed results indicate that the EMD-NSOR model can be an appropriate option by reproducing long-term dependence statistics and generating manageable scenarios, while the SML model does not properly reproduce the observed long-term dependence, that are critical to simulate sustainable flood events. The trend model produces too many risks for floods in the future but no risk for droughts. The overall results conclude that the nonstationarities in hydrological series should be carefully handled in stochastic simulation models to appropriately manage future water-related risks.
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Research in hydrological sciences is constantly evolving to provide adequate answers to address various water-related issues. Methodological approaches inspired by mathematical and physical sciences have shaped hydrological sciences from its inceptions to the present day. Nowadays, as a better understanding of the social consequences of extreme meteorological events and of the population’s ability to adapt to these becomes increasingly necessary, hydrological sciences have begun to integrate knowledge from social sciences. Such knowledge allows for the study of complex social-ecological realities surrounding hydrological phenomena, such as citizens’ perception of water resources, as well as individual and collective behaviors related to water management. Using a mixed methods approach to combine quantitative and qualitative approaches has thus become necessary to understand the complexity of hydrological phenomena and propose adequate solutions for their management. In this paper, we detail how mixed methods can be used to research flood hydrology and low-flow conditions, as well as in the management of these hydrological extremes, through the analysis of case studies. We frame our analysis within the three paradigms (positivism, post-positivism, and constructivism) and four research designs (triangulation, complementary, explanatory, and exploratory) that guide research in hydrology. We show that mixed methods can notably contribute to the densification of data on extreme flood events to help reduce forecasting uncertainties, to the production of knowledge on low-flow hydrological states that are insufficiently documented, and to improving participatory decision making in water management and in handling extreme hydrological events.
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Abstract An intensity–duration–frequency (IDF) curve describes the relationship between rainfall intensity and duration for a given return period and location. Such curves are obtained through frequency analysis of rainfall data and commonly used in infrastructure design, flood protection, water management, and urban drainage systems. However, they are typically available only in sparse locations. Data for other sites must be interpolated as the need arises. This paper describes how extreme precipitation of several durations can be interpolated to compute IDF curves on a large, sparse domain. In the absence of local data, a reconstruction of the historical meteorology is used as a covariate for interpolating extreme precipitation characteristics. This covariate is included in a hierarchical Bayesian spatial model for extreme precipitations. This model is especially well suited for a covariate gridded structure, thereby enabling fast and precise computations. As an illustration, the methodology is used to construct IDF curves over Eastern Canada. An extensive cross-validation study shows that at locations where data are available, the proposed method generally improves on the current practice of Environment and Climate Change Canada which relies on a moment-based fit of the Gumbel extreme-value distribution.
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Floods, intensified by climate change, pose major challenges for flood zone management in Quebec. This report addresses these issues through two complementary aspects: a historical analysis of the evolution of flood zone management in Quebec and the projected impact of the cartographic and regulatory overhaul, as well as an exploration of the imaginary surrounding the flood-prone territory of the city of Lachute, which has faced recurrent floods for decades and yet continues to be inhabited. The historical analysis reveals that the major floods of 1974, 1976, 2017, and 2019 marked significant turning points in Quebec’s risk management, particularly by highlighting gaps in the regulatory framework and flood zone mapping. The adoption of the Act Respecting Land Use Planning and Development (LAU) in 1979 and the Policy for the Protection of Shorelines, Littorals, and Floodplains (PPRLPI) in 1987 represented a shift toward a preventive approach. However, inconsistencies, insufficient updates to maps, and uneven enforcement of standards have hindered their effectiveness. The catastrophic floods of 2017 and 2019 triggered a regulatory overhaul, a modernization of mapping, and measures to strengthen community resilience. In 2022, a transitional regime came into effect to tighten the regulation of activities in flood zones, pending the adoption of a risk-based management framework. However, to this day, the regulatory perimeters proposed in the modernization project fail to account for the adaptive capacities deployed by communities to live with water, thus providing a biased interpretation of flood risk. The second part explores the social and cultural representations associated with Lachute’s flood-prone territory. It highlights the complex relationships that have developed between residents and the Rivière du Nord through successive flooding episodes and the adaptation strategies implemented to cope, particularly by those who have repeatedly experienced flooding. These residents have come to live with overflow events and to (co)exist with water, challenging the persistent notion that flood-prone areas are inherently dangerous. While local strategies are sometimes innovative, they remain constrained by a regulatory framework that disregards the human experience of the territory and the specific ways in which people inhabit exposed areas to learn to manage flood risks. In summary, this report underscores the urgency of a territorialized, risk-based approach to modernizing flood zone management. It also highlights the need to look beyond cartographic boundaries and better integrate human and cultural dimensions into planning policies, as illustrated in the case of Lachute, to more accurately reflect the true level of risk. These reflections aim to promote more coherent, sustainable, and acceptable management, planning, and development of exposed territories in response to the growing challenges posed by climate change.
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Earthquakes pose potentially substantial risks to residents in the Western Quebec seismic zone of eastern Canada, where Ottawa and Montreal are located. In eastern Canada, the majority of houses are not constructed to modern seismic standards and most homeowners do not purchase earthquake insurance for their homes. If a devastating earthquake strikes, homeowners would be left unprotected financially. To quantify financial risks to homeowners in the Western Quebec seismic zone, regional earthquake catastrophe models are developed by incorporating up-to-date public information on hazard, exposure and vulnerability. The developed catastrophe models can quantify the expected and upper-tail financial seismic risks by considering a comprehensive list of possible seismic events as well as critical earthquake scenarios based on the latest geological data in the region. The results indicate that regional seismic losses could reach several tens of billions of dollars if a moderate-to-large earthquake occurs near urban centres in the region, such as Montreal and Ottawa. The regional seismic loss estimates produced in this study are useful for informing earthquake risk management strategies, including earthquake insurance and disaster relief policies.
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In response to extreme flood events and an increasing awareness that traditional flood control measures alone are inadequate to deal with growing flood risks, spatial flood risk management strategies have been introduced. These strategies do not only aim to reduce the probability and consequences of floods, they also aim to improve local and regional spatial qualities. To date, however, research has been largely ignorant as to how spatial quality, as part of spatial flood risk management strategies, can be successfully achieved in practice. Therefore, this research aims to illuminate how spatial quality is achieved in planning practice. This is done by evaluating the configurations of policy instruments that have been applied in the Dutch Room for the River policy program to successfully achieve spatial quality. This policy program is well known for its dual objective of accommodating higher flood levels as well as improving the spatial quality of the riverine areas. Based on a qualitative comparative analysis, we identified three successful configurations of policy instruments. These constitute three distinct management strategies: the “program‐as‐guardian”, the “project‐as‐driver,” and “going all‐in” strategies. These strategies provide important leads in furthering the development and implementation of spatial flood risk management, both in the Netherlands and abroad.
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L’adaptation au changement climatique est un nouvel enjeu pour la gestion des territoires. Au niveau local, elle apparaît souvent comme une injonction, alors même que, pour l’instant, elle est un concept flou. Elle est présentée comme l’application de bonnes pratiques, mais les questions « qui s’adapte à quoi ? » et « pourquoi ? » demeurent implicites. En explicitant ces éléments, nous proposons de montrer que l’adaptation est une question plurielle et politique. À partir de l’analyse des documents de planification et des plans d’action faisant référence aux changements globaux sur un territoire littoral, nous montrons l’existence de quatre logiques d’adaptation distinctes, plus ou moins transformatrices du système socioécologique, que l’on peut appréhender à partir de la typologie suivante : « contrôler et maintenir », « faire faire », « réguler » et « reconfigurer », qui portent en germe différentes reconfigurations socioéconomiques et politiques. , Since the 2000s, “adaptation” is a new dictate for the management of local territories in France, but its implementation is fairly limited. Adaptation is mainly a semantically unclear and loosely defined concept. Decision-makers could “operationalize” adaptation by simply applying a specific methodology. However, adaptation is not a mere mechanism; it is also a process that implies economic, social and ecological trade-offs for the socio-ecological system. These political dimensions are often unformulated. In order to provide a vehicle to clarify this concept and its political dimensions, we propose a typology of adaptation measures. What does adaptation mean? Adjustment of what (territories, populations, communities, local economies, etc.), to what (climate change, global change) and with what effects? We reviewed local actions and strategic plans related to climate but also to urban planning, flooding and water management on the eastern coastal area of Languedoc Roussillon in Mediterranean France. We conducted and analyzed semi-structured interviews with institutional actors. We analyzed and classified public policy instruments, associated the underlying “logic” (raise limiting factors, create a new awareness, etc.), and their potential effects. Throughout our effort to develop a typology, we have highlighted the political dimensions of adaptation actions and shed a light on trade-offs linked to adaptation choices.
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Watershed management efforts in agriculturally dominated landscapes of North America face nearly two centuries of laws and policies that encouraged habitat destruction. Although streams and wetlands in these landscapes are actively being restored using designs that incorporate science and engineering, watershed drainage laws can constrain action or impact passively restored or naturalized habitat. In general, drainage laws require removal of any riparian vegetation or wood deemed to obstruct flow in streams regulated as drains. We use a case study from Indiana (USA) to introduce the shortcomings of drainage laws for allowing large wood, which is an important habitat feature, to remain in stream ecosystems. Removals of large wood from monitored stream reaches in a regulated drain were associated with subsequent declines in fish biomass. Such legal activities represent an important environmental management problem that exists under drainage laws which apply to streams over a widespread geographic region of North America. Recent litigation in Wisconsin (USA) suggests that if state legislatures fail to update these antiquated laws, the courts may act in favour of science-based management of drains. The statutes and regulations that govern agricultural drainage warrant careful consideration if streams within drainage districts are to be managed to improve ecological function. © 2020 John Wiley & Sons, Ltd.
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Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly (Muñoz-Sabater, 2019a) and monthly (Muñoz-Sabater, 2019b) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.
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Land surface hydrology controls runoff production and the associated transport of sediments, and a wide variety of anthropogenic organic chemicals, and nutrients from upland landscape areas and hillslopes to streams and other water bodies. Based on interactions between landscape characteristics and precipitation inputs, watersheds respond differently to different climatic inputs (e.g. precipitation and solar radiation). This study compares the hydrologic responses of the MidAtlantic watersheds, and identifies the landscape and climatic descriptors that control those responses. Our approach was to select representative watersheds from the Mid-Atlantic region, group the watersheds by physiographic province and ecoregion, and then collect landscape, climate, and hydrologic response descriptor data for each selected watershed. For example, we extracted extensive landscape descriptor data from soil, land use and land cover, and digital elevation model geographic information system (GIS) databases. After sufficient data was collected, we conducted a variety of studies to determine how different landscape and climatic descriptors influence the hydrologic response of Mid-Atlantic watersheds. This report is comprised of four main parts. Part I describes the selection of the representative study watersheds and the determination of representative physical landscape descriptors for each watershed using geographic information system analysis tools. Part II characterizes the climate and associated hydrologic responses of the study watersheds. To select climate descriptors that are good predictors of hydrologic response, we examined a large number of candidate descriptors. Based on our examination, we selected dryness index and mean monthly rainfall as the best hydrologic response predictors. In Part II, we also present the results of our study hydrologic response comparisons of the study watersheds using a water balance approach. The water balance approach was based on comparisons of precipitation, streamflow, and evapotranspiration at annual, monthly, and daily time scales. These comparisons revealed that elevation and latitudinal position strongly influence hydrologic response. The results also showed that mountainous watersheds of the Appalachian Plateau, Ridge and Valley, and Blue Ridge Physiographic Provinces have more streamflow and less evapotranspiration than watersheds located in the Piedmont Province, and that snowmelt contributes a large portion of streamflow. Part III presents relationships we derived between landscape-climatic descriptors and the hydrologic response descriptors. Flow duration indices (Q1...Q95) were used to represent the hydrologic responses of the study watersheds. In Part III, we also present comparisons of the hydrologic responses of the study watersheds at high flow condition, represented by the Q1 index, medium flow condition represented by the Q50 index, and low flow condition represented by the Q95 index. These comparisons revealed that: the Appalachian Plateau, ridge-dominated Ridge and Valley, and Blue Ridge watersheds have the highest Q1 and Q50 indices; the valley-dominated Ridge and Valley watersheds have the lowest Q50 index, and the Piedmont watersheds have the lowest Q1 index and a relatively high Q95 index. Finally, Part IV discusses some of the implications of the study results for watershed management. We also present applications of the research for hydrologic modeling and watershed assessment.
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According to our survey about climate risk perceptions, institutional investors believe climate risks have financial implications for their portfolio firms and that these risks, particularly regulatory risks, already have begun to materialize. Many of the investors, especially the long-term, larger, and ESG-oriented ones, consider risk management and engagement, rather than divestment, to be the better approach for addressing climate risks. Although surveyed investors believe that some equity valuations do not fully reflect climate risks, their perceived overvaluations are not large.
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Abstract As losses from extreme weather events grow, many governments are looking to privatize the financing and incentivization of climate adaptation through insurance markets. In a pure market approach to insurance for extreme weather events, individuals become responsible for ensuring they are adequately covered for risks to their own properties, and governments no longer contribute funds to post‐disaster recovery. Theoretically, insurance premiums signal the level of risk faced by each household, and incentivize homeowners to invest in adaptive action, such as retrofitting, or drainage work, to reduce premiums. Where risk is considered too high by insurance markets, housing is devalued, in theory leading to retreat from risky areas. In this review article, we evaluate the suitability of private insurance as a mechanism for climate adaptation at a household and community level. We find a mismatch between social understandings of responsibility for climate risks, and the technocratic, market‐based home insurance products offered by private insurance markets. We suggest that by constructing increasingly individualized, technical, and calculative evaluations of risk, market‐based models of insurance for extreme weather events erode the solidaristic and collective discourses and practices that support adaptive behavior. This article is categorized under: Vulnerability and Adaptation to Climate Change > Institutions for Adaptation
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In undertaking what we believe is the first national-scale study of its kind, we provide methodologically transparent, statistically robust insights into associations and potential unfolding effects of house and contents under-insurance. We identify new dimensions in the complex relationship between householders and insurance, including the salience of interpersonal – and likely institutional – trust. Under-insurance is (re)produced along socio-economic and geographical lines, with those of lower socio-economic status or living in cities more likely to be under-insured. Should a disaster strike, such communities are likely to suffer further disadvantage, especially if governments continue to shift the responsibility for risk onto households. Our findings support the observation that insurance can contribute to increasing socio-economic urban polarisation in light of natural disasters. We conclude by considering how under-insurance may contribute to growing urban social stratification, as well as how it may produce situated ethical and political responses that exceed neoliberal aspirations.