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Introduction Impacts of climate change on human health receive increasing attention. However, the connections of climate change with well-being and mental health are still poorly understood. Objective As part of the Horizon Europe project TRIGGER, we aim to deepen the understanding of the relationships between climate change and human mental health and well-being in Europe by focusing on environmental and socio-individual determinants. Methods This study is a systematic literature review based on the PRISMA guidelines using Embase, Medline and Web of Science. Results 143 records were retrieved. The results show that climate change and its specific hazards (air pollution, floods, wildfires, meteorological variables, and temperature extremes) impact human well-being and mental health. Discussion Mental health and well-being outcomes are complex, extremely individual, and can be long lasting. Determinants like the living surrounding, human’s life activities as well as socio-individual determinants alter the linkage between climate change and mental health. The same determinant can exert both a pathogenic and a salutogenic effect, depending on the outcome. Knowing the effects of the determinants is of high relevance to improve resilience. Several pathways were identified. For instance, higher level of education and female gender lead to perceiving climate change as a bigger threat but increase preparedness to climate hazards. Elderly, children and adolescents are at higher risks of mental health problems. On the other hand, social relation, cohesiveness and support from family and friends are generally protective. Green and blue spaces improve well-being and mental health. Overall, comparing the different hazard-outcome relationships is difficult due to varying definitions, measurement techniques, spatial and temporal range, scales, indicators and population samples. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/home , identifier CRD42023426758.

Abstract. Developing predictions of coastal flooding risk on subseasonal timescales (2–6 weeks in advance) is an emerging priority for the National Oceanic and Atmospheric Administration (NOAA). In this study, we assess the ability of two current operational forecast systems, the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) and the Centre National de Recherches Météorologiques climate model (CNRM), to make subseasonal ensemble predictions of the non-tidal residual component of coastal water levels at United States coastal gauge stations for the period 2000–2019. These models were chosen because they assimilate satellite altimetry at forecast initialization and attempt to predict the mean sea level, including a global mean component whose absence in other forecast systems complicates assessment of tide gauge reforecast skill. Both forecast systems have skill that exceeds damped persistence for forecast leads through 2–3 weeks, with IFS skill exceeding damped persistence for leads up to 6 weeks. Post-processing forecasts to include the inverse barometer effect, derived from mean sea level pressure forecasts, improves skill for relatively short forecast leads (1–3 weeks). Accounting for vertical land motion of each gauge primarily improves skill for longer leads (3–6 weeks), especially for the Alaskan and Gulf coasts; sea-level trends contribute to reforecast skill for both model and persistence forecasts, primarily for the East and Gulf coasts. Overall, we find that current forecast systems have sufficiently high levels of deterministic and probabilistic skill to be used in support of operational coastal flood guidance on subseasonal timescales.

Atmospheric methane (CH4) concentrations have increased to 2.5 times their pre-industrial levels, with a marked acceleration in recent decades. CH4 is responsible for approximately 30% of the global temperature rise since the Industrial Revolution. This growing concentration contributes to environmental degradation, including ocean acidification, accelerated climate change, and a rise in natural disasters. The column-averaged dry-air mole fraction of methane (XCH4) is a crucial indicator for assessing atmospheric CH4 levels. In this study, the Sentinel-5P TROPOMI instrument was employed to monitor, map, and estimate CH4 concentrations on both regional and global scales. However, TROPOMI data exhibits limitations such as spatial gaps and relatively coarse resolution, particularly at regional scales or over small areas. To mitigate these limitations, a novel Convolutional Neural Network Autoencoder (CNN-AE) model was developed. Validation was performed using the Total Carbon Column Observing Network (TCCON), providing a benchmark for evaluating the accuracy of various interpolation and prediction models. The CNN-AE model demonstrated the highest accuracy in regional-scale analysis, achieving a Mean Absolute Error (MAE) of 28.48 ppb and a Root Mean Square Error (RMSE) of 30.07 ppb. This was followed by the Random Forest (RF) regressor (MAE: 29.07 ppb; RMSE: 36.89 ppb), GridData Nearest Neighbor Interpolator (NNI) (MAE: 30.06 ppb; RMSE: 32.14 ppb), and the Radial Basis Function (RBF) Interpolator (MAE: 80.23 ppb; RMSE: 90.54 ppb). On a global scale, the CNN-AE again outperformed other methods, yielding the lowest MAE and RMSE (19.78 and 24.7 ppb, respectively), followed by RF (21.46 and 27.23 ppb), GridData NNI (25.3 and 32.62 ppb), and RBF (43.08 and 54.93 ppb).

This study introduces a novel methodology for assessing ice-jam flood hazards along river channels. It employs empirical equations that relate non-dimensional ice-jam stage to discharge, enabling the generation of an ensemble of longitudinal profiles of ice-jam backwater levels through Monte-Carlo simulations. These simulations produce non-exceedance probability profiles, which indicate the likelihood of various flood levels occurring due to ice jams. The flood levels associated with specific return periods were validated using historical gauge records. The empirical equations require input parameters such as channel width, slope, and thalweg elevation, which were obtained from bathymetric surveys. This approach is applied to assess ice-jam flood hazards by extrapolating data from a gauged reach at Fort Simpson to an ungauged reach at Jean Marie River along the Mackenzie River in Canada’s Northwest Territories. The analysis further suggests that climate change is likely to increase the severity of ice-jam flood hazards in both reaches by the end of the century. This methodology is applicable to other cold-region rivers in Canada and northern Europe, provided similar fluvial geomorphological and hydro-meteorological data are available, making it a valuable tool for ice-jam flood risk assessment in other ungauged areas. © 2025 by the authors.

Nature-based solutions (NbS) are increasingly recognized as strategic alternatives and complements to grey infrastructure for addressing water-related challenges in the context of climate change, urbanization, and biodiversity decline. This article presents a critical, theory-informed review of the state of NbS implementation in European water management, drawing on a structured synthesis of empirical evidence from regional case studies and policy frameworks. The analysis found that while NbS are effective in reducing surface runoff, mitigating floods, and improving water quality under low- to moderate-intensity events, their performance remains uncertain under extreme climate scenarios. Key gaps identified include the lack of long-term monitoring data, limited assessment of NbS under future climate conditions, and weak integration into mainstream planning and financing systems. Existing evaluation frameworks are critiqued for treating NbS as static interventions, overlooking their ecological dynamics and temporal variability. In response, a dynamic, climate-resilient assessment model is proposed—grounded in systems thinking, backcasting, and participatory scenario planning—to evaluate NbS adaptively. Emerging innovations, such as hybrid green–grey infrastructure, adaptive governance models, and novel financing mechanisms, are highlighted as key enablers for scaling NbS. The article contributes to the scientific literature by bridging theoretical and empirical insights, offering region-specific findings and recommendations based on a comparative analysis across diverse European contexts. These findings provide conceptual and methodological tools to better design, evaluate, and scale NbS for transformative, equitable, and climate-resilient water governance.

AbstractThe frequency and severity of floods has increased in different regions of the world due to climate change. Although the impact of floods on human health has been extensively studied, the increase in the segments of the population that are likely to be impacted by floods in the future makes it necessary to examine how adaptation measures impact the mental health of individuals affected by these natural disasters. The goal of this scoping review is to document the existing studies on flood adaptation measures and their impact on the mental health of affected populations, in order to identify the best preventive strategies as well as limitations that deserve further exploration. This study employed the methodology of the PRISMA-ScR extension for scoping reviews to systematically search the databases Medline and Web of Science to identify studies that examined the impact of adaptation measures on the mental health of flood victims. The database queries resulted in a total of 857 records from both databases. Following two rounds of screening, 9 studies were included for full-text analysis. Most of the analyzed studies sought to identify the factors that drive resilience in flood victims, particularly in the context of social capital (6 studies), whereas the remaining studies analyzed the impact of external interventions on the mental health of flood victims, either from preventive or post-disaster measures (3 studies). There is a very limited number of studies that analyze the impact of adaptation measures on the mental health of populations and individuals affected by floods, which complicates the generalizability of their findings. There is a need for public health policies and guidelines for the development of flood adaptation measures that adequately consider a social component that can be used to support the mental health of flood victims.

Résumé L'hydrogéomorphologie étudie la dynamique des rivières en se concentrant sur les interactions liant la structure des écoulements, la mobilisation et le transport des sédiments et les morphologies qui caractérisent les cours d'eau et leur bassin‐versant. Elle offre un cadre d'analyse et des outils pour une meilleure intégration des connaissances sur la dynamique des rivières pour la gestion des cours d'eau au sens large, et plus spécifiquement, pour leur restauration, leur aménagement et pour l'évaluation et la prévention des risques liés aux aléas fluviaux. Au Québec, l'hydrogéomorphologie émerge comme contribution significative dans les approches de gestion et d'évaluation du risque et se trouve au cœur d'un changement de paradigme dans la gestion des cours d'eau par lequel la restauration des processus vise à augmenter la résilience des systèmes et des sociétés et à améliorer la qualité des environnements fluviaux. Cette contribution expose la trajectoire de l'hydrogéomorphologie au Québec à partir des publications scientifiques de géographes du Québec et discute des visées de la discipline en recherche et en intégration des connaissances pour la gestion des cours d'eau . , Abstract Hydrogeomorphology studies river dynamics, focusing on the interactions between flow structure, sediment transport, and the morphologies that characterize rivers and their watersheds. It provides an analytical framework and tools for better integrating knowledge of river dynamics into river management in the broadest sense, and more specifically, into river restoration as well as into the assessment and prevention of risks associated with fluvial hazards. In Quebec, hydrogeomorphology is emerging as a significant contribution to risk assessment and management approaches, and is at the heart of a paradigm shift in river management whereby process restoration aims to increase the resilience of fluvial systems and societies, and improve the quality of fluvial environments. This contribution outlines the trajectory of hydrogeomorphology in Quebec, based on scientific publications by Quebec geographers, and discusses the discipline's aims in research and knowledge integration for river management . , Messages clés Les géographes du Québec ont contribué fortement au développement des connaissances et outils de l'hydrogéomorphologie. L'hydrogéomorphologie a évolué d'une science fondamentale à une science où les connaissances fondamentales sont au service de la gestion des cours d'eau. L'hydrogéomorphologie et le cortège de connaissances et d'outils qu'elle promeut font de cette discipline une partenaire clé pour une gestion holistique des cours d'eau.

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.

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.

With the growing realization that crystallization processes may evolve through a sequence of different solid forms, including amorphous precursor phases, the development of suitable in-situ experimental probes is essential for comprehensively mapping the time-evolution of such processes. Here we demonstrate that the CLASSIC NMR (Combined Liquid- And Solid-State In-situ Crystallization NMR) strategy is a powerful technique for revealing the transitory existence of amorphous phases during crystallization processes, applying this technique to study crystallization of dl-menthol and l-menthol from their molten liquid phases. The CLASSIC NMR results provide direct insights into the conditions (including the specific time period) under which the molten liquid phase, transitory amorphous phases and final crystalline phases exist during these crystallization processes.

Introduction Studies have shown that, following psychotherapy for posttraumatic stress disorder (PTSD), symptoms and quality of life (QoL) may improve in many patients, but not always to the same extent. Dysfunctional core beliefs, such as personality beliefs (PB), are associated to psychopathology, including PTSD, and could be associated with the types of coping strategies deployed by an individual. Beliefs and coping strategies were also linked to psychotherapeutic outcomes. Objectives (1) To examine the associations between baseline PB as well as pre- and post-treatment coping strategies; (2) To investigate the mediation effects between PB and the changes in QoL, through changes in coping strategies in a cognitive-behavioral psychotherapy (CBT). Method Seventy-one adults with PTSD participating in a correlational/observational CBT study were assessed for PB before a CBT, as well as for coping strategies and QoL, before and after a CBT. Results PB were generally associated with post-treatment distancing coping. Moreover, changes in distancing coping mediated the relationships between avoidant or dependent PB and psychological QoL improvements. Conclusion This is the first study to show the relationships between PB and coping strategies in PTSD patients, and that higher avoidant or dependent PB predicts a lower reduction in the use of distancing coping through psychotherapy, which is associated with less improvement in psychological QoL. Future studies are needed to further define the role of these variables and target more precisely factors that may hamper the treatment effects of CBT for PTSD.

Empirical evidence points out that urban form adaptation to climate-induced flooding events—through interventions in land uses and town plans (i. e., street networks, building footprints, and urban blocks)—might exacerbate vulnerabilities and exposures, engendering risk inequalities and climate injustice. We develop a multicriteria model that draws on distributive justice's interconnections with the risk drivers of social vulnerabilities, flood hazard exposures, and the adaptive capacity of urban form (through land uses and town plans). The model assesses “who” is unequally at-risk to flooding events, hence, should be prioritized in adaptation responses; “where” are the high-risk priority areas located; and “how” can urban form adaptive interventions advance climate justice in the priority areas. We test the model in Toronto, Ontario, Canada, where there are indications of increased rainfall events and disparities in social vulnerabilities. Our methodology started with surveying Toronto-based flooding experts who assigned weights to the risk drivers based on their importance. Using ArcGIS, we then mapped and overlayed the risk drivers' values in all the neighborhoods across the city based on the experts' assigned weights. Accordingly, we identified four high-risk tower communities with old infrastructure and vulnerable populations as the priority neighborhoods for adaptation interventions within the urban form. These four neighborhoods are typical of inner-city tower blocks built in the 20 th century across North America, Europe, and Asia based on modern architectural ideas. Considering the lifespan of these blocks, this study calls for future studies to investigate how these types of neighborhoods can be adapted to climate change to advance climate justice.

Large-scale flood risk assessment is essential in supporting national and global policies, emergency operations and land-use management. The present study proposes a cost-efficient method for the large-scale mapping of direct economic flood damage in data-scarce environments. The proposed framework consists of three main stages: (i) deriving a water depth map through a geomorphic method based on a supervised linear binary classification; (ii) generating an exposure land-use map developed from multi-spectral Landsat 8 satellite images using a machine-learning classification algorithm; and (iii) performing a flood damage assessment using a GIS tool, based on the vulnerability (depth–damage) curves method. The proposed integrated method was applied over the entire country of Romania (including minor order basins) for a 100-year return time at 30-m resolution. The results showed how the description of flood risk may especially benefit from the ability of the proposed cost-efficient model to carry out large-scale analyses in data-scarce environments. This approach may help in performing and updating risk assessments and management, taking into account the temporal and spatial changes in hazard, exposure, and vulnerability.