Search Results (125)

We investigated the impacts of a rapidly changing hydrometeorological regime on coastal erosion in the shallow, seasonally freezing Sea of Azov from 2000 to 2025. Our comparative approach integrated numerical modeling (SWAN), satellite remote sensing, and long-term field observations at two high-erosion sites: the Northern Site in Taganrog Bay and the Southern Site at the open sea boundary. The results demonstrate that coastal erosion is governed by complex, site-specific interactions rather than direct regional climatic trends. A major regime shift characterized by declining fast ice and increasing storm activity during the extended warm season has amplified coastal vulnerability, particularly after 2010. Despite high long-term average erosion rates at both sites, 1.1 to 1.6 m/year in the north and 1.5 to 1.8 m/year in the south, their annual erosion patterns were largely non-synchronous. The Northern Site is controlled by geological structure and surge phenomena, with peak rates reaching 8.5 m/year, while the Southern Site is governed by storm waves and extreme surges, enduring dynamic loads up to 10.0 tf/m². These results provide complex interaction nature of coastal processes and hydrometeorological components and its response to climate change in periodically freezing sea. These findings are vital for improving vulnerability models and underscore the necessity of site-specific hazard assessments for seasonally freezing coasts under a warming climate. Full article

Torrential flows are hazardous hydro-geomorphological phenomena characterized by sudden water discharge and intense sediment transport. They occur in mountainous areas where hydrometeorological monitoring is often limited or absent. The lack of such data hinders the identification of flow types and sediment transport conditions, reducing the effectiveness of mitigation measures. To address this issue, the current study focuses on geomorphic characteristics of torrential watersheds and identifies indirect indicators of torrential activity. The sedimentological and geomorphic signatures of torrential flows in the lower Damdere River catchment (Eastern Rhodopes Mountains, southern Bulgaria) were characterized. To capture inter-annual variability in torrential activity and differences between the Damdere and its tributary the Duandere, we sampled riverbed deposits. We also sampled areas upstream and downstream of the check dam to assess its influence. Samples were analyzed for grain size distribution, petrography, and mineralogy (X-ray diffraction). Results show contrasting controls on sediment supply and transport: the Duandere delivers relatively coarse material, whereas the Damdere attains higher transport capacity during torrential events. The check dam is largely infilled and exerts only local effects by trapping finer sediments upstream. Downstream, the channel retains its torrential character. Inter-annual comparison upstream of the structure shows sediment fining linked to lower flows. Petrographic and XRD data point to mechanically driven erosion and rapid sediment transfer. The results underline the importance of geological–geomorphological indicators in the lack of long-term monitoring in similar mountain catchments and can support flood risk management. Full article

Mountain regions are highly susceptible to severe hydro-meteorological events. These events induce substantial morphological changes that are preserved in the environment and cause significant economic losses, representing a major challenge for water resource management. Due to their abrupt nature, mitigating the impacts of such events requires preventive measures. The goal of the study was to comprehensively evaluate the impact of severe hydro-meteorological events on the mountain environment of the Ochotnica catchment, considering both environmental and economic aspects, over several years. This multi-year perspective also provided the opportunity to formulate some recommendations for the development of adaptation strategies for extreme hydro-meteorological events in mountain areas. The study demonstrates that delineation of the Maximum Probable Flood (MPF) hazard zone is a key element in building resilience to such events in mountain areas. Information related to the extent and depth of this zone, together with flow velocity, are critical components which may support actions aimed at reducing flood exposure and vulnerability, limiting the negative consequences of extreme hydro-meteorological events in mountain catchments prone to flash floods. Full article

Coastal regions in Mexico face significant exposure to hydrometeorological hazards, often resulting in severe flooding and socioeconomic disruption. This study assesses the hydrometeorological resilience of the Veracruz–Boca del Río Conurbation (VBC), a region comprising two coastal municipalities with shared hazard exposure despite distinct governance structures. The hydrometeorological resilience evaluation employs the City Resilience Index (CRI), developed by Bahena which integrates the Technical Resilience Index (TRI) and the Technical Profile of Resilience (TPR) across nine hierarchical indicators. Results reveal moderate resilience levels—59.83% for Veracruz and 58.32% for Boca del Río—with Disaster Risk Reduction Plans and Vital Services indicators as the strongest contributors, while Risk Assessments and Budget Allocation for Emergency Response indicators scored lowest due to limited municipal data. These findings highlight the need for enhanced data transparency, institutional coordination, and resource allocation in disaster management. Beyond its local significance, this study advances the global understanding of resilience assessment frameworks in data-scarce contexts, offering insights applicable to similar regions worldwide. As the first hydrometeorological resilience assessment for the VBC, this research provides a methodological and empirical foundation for future studies and informs targeted resilience strategies for Mexico’s coastal urban areas. Full article

Flooding is one of the most frequent and destructive natural disasters worldwide, with intensifying socioeconomic and environmental consequences linked to rapid urbanisation and climate change. This review examines flood risk delineation and assessment in Nigeria within a broader Global South perspective, synthesising evidence from peer-reviewed studies that employ remote sensing, GIS-based techniques, and multi-criteria decision analysis. The analysis reveals persistent challenges that undermine effective flood risk management, including incompatible datasets, limited stakeholder participation, and inadequate integration with formal planning systems. To address these gaps, the study introduces the GIS-Integrated Flood Risk Management (GIFRM) Framework, a conceptual model that integrates high-resolution risk mapping, adaptive infrastructure design, sustainable urban planning, and participatory governance. GIFRM advances resilience discourse beyond hazard mapping, offering a practical bridge between science, policy, and implementation by aligning technical geospatial analysis with actionable planning solutions. Comparative case insights from flood-prone countries such as Bangladesh, India, and Kenya highlight transferable strategies, including community-led data integration, modular infrastructure approaches, and localised zoning reforms. The review concludes by critically examining the operational disconnect between advanced geospatial risk assessment and its application in resource-limited, rapidly urbanising settings. It reframes flood risk assessment as an interdisciplinary planning tool with global relevance, delivering lessons for disaster preparedness, urban sustainability, and climate resilience. In the face of escalating hydrometeorological extremes, this research offers applied strategies for embedding GIS technologies into adaptive policy frameworks, positioning flood risk management as a core driver of sustainable development. Full article

Maritime ferries increasingly operate under non-stationary hydro–meteorological conditions that complicate cost planning. This study investigates how short-term weather variability affects expenditures for a ferry on the Gdynia–Karlskrona route. We combine a state-based operational framework (18 discrete states) with a subsystem-level cost model covering navigation, propulsion/steering, loading/unloading, stability control, and mooring/anchoring. Direct and indirect costs are linked to subsystem activity and state duration, while weather is incorporated through hazard categories that scale hourly costs. Expert-elicited rates and observed monthly state durations provide the basis for baseline estimates and hazard scenario simulations. Results reveal a disproportionate cost structure: two open-sea states constitute over 97% of the baseline monthly cost (19,490.19 PLN). Weather hazards further amplify costs, with moderate (1st-degree) and severe (2nd-degree) scenarios producing increases of ~8% and ~20%, respectively, compared to normal conditions. By embedding weather as an endogenous factor in a probabilistic cost model based on a semi-Markov process, the approach enhances predictive fidelity and supports decision-making for climate-resilient planning. These findings suggest that adaptive routing, speed management, and targeted maintenance of the propulsion and steering subsystems during open-sea navigation offer the highest potential for cost resilience. The study provides operators and policymakers with a transparent framework for climate-resilient planning and investment in semi-enclosed maritime corridors. Full article

Urban coastal areas are increasingly vulnerable to compound flooding due to the convergence of extreme rainfall, storm surges, and infrastructure aging, especially in high-density settings. This study proposes and empirically validates a multi-scale strategy for enhancing urban flood resilience in the Macau Peninsula, a densely built coastal city with complex flood exposure patterns. Building on a previously developed network-based resilience assessment framework, the study integrates hydrodynamic simulation and complex network analysis to evaluate the effectiveness of targeted interventions, including segmented storm surge defense barriers, drainage infrastructure upgrades, and spatially optimized low-impact development (LID) measures. The Macau Peninsula was partitioned into multiple shoreline defense zones, each guided by context-specific design principles and functional zoning. Based on our previously developed flood simulation framework covering extreme rainfall, storm surge, and compound events in high-density coastal zones, this study validates resilience strategies that achieve significant reductions in inundation extent, water depth, and recession time. Additionally, the network-based resilience index showed marked improvement in system connectivity and recovery efficiency, particularly under compound hazard conditions. The findings highlight the value of integrating spatial planning, ecological infrastructure, and systemic modeling to inform adaptive flood resilience strategies in compact coastal cities. The framework developed offers transferable insights for other urban regions confronting escalating hydrometeorological risks under climate change. Full article

The compounding effects of hydrometeorological hazards are being driven by climate change. As urban areas expand, this leads to degradation of the surrounding environment and exposes more people to hazards. Growing losses show that conventional approaches to addressing these issues can compound these problems. Over the last few decades, nature-based solutions (NBSs) have become an increasingly popular alternative. These measures, inspired by natural processes, have shown potential for reducing hazards by complementing traditional approaches and providing co-benefits in the form of eco-system services. With the adoption of NBSs becoming a more mainstream approach, there is a need for tools that support the planning and implementation of interventions. Geospatial suitability assessment is a part of this planning process. Existing tools are limited in their application for large-scale measures. This paper intends to improve this by building upon a multi-criteria analysis (MCA)-based approach that incorporates biophysical and land use criteria and conditions for mapping the suitability of large-scale NBSs. The methodology was developed and tested on six sites to assess the suitability of floodplain restoration, retention or detention, afforestation, and forest buffer strips. The resulting suitability maps also show potential for combining two or more measures for greater risk reduction. Full article

Climate change research is increasingly important in regions vulnerable to extreme hydrometeorological events like droughts, which pose significant socio-economic and environmental challenges. This study examines future variability of meteorological drought in northernmost South America using the Standardized Precipitation Index (SPI) and precipitation projections from CMIP6 models. We first evaluated model performance by comparing historical simulations with observational data from the Climate Hazards Group InfraRed Precipitation with Station dataset for 1981–2014. Among the models, CNRM-CM6-1-HR was selected for its superior accuracy, demonstrated by the lowest errors and highest correlation with observed data—specifically, a correlation coefficient of 0.60, a normalized root mean square error of 1.08, and a mean absolute error of 61.37 mm/month. Under SSP1-2.6 and SSP5-8.5 scenarios, projections show decreased rainfall during the wet months in the western Perijá mountains, with reductions of 3% to 26% between 2025 and 2100. Conversely, the Sierra Nevada of Santa Marta is expected to see increases of up to 33% under SSP1-2.6. During dry months, northern Colombia and Venezuela—particularly coastal lowlands—are projected to experience rainfall decreases of 10% to 17% under SSP1-2.6 and 13% to 20% under SSP5-8.5. These areas are likely to face severe drought conditions in the mid and late 21st century. These findings are essential for guiding water resource management, enabling adaptive strategies, and informing policies to mitigate drought impacts in the region. Full article

The efficient and rational development of hydropower in the Lancang–Mekong River Basin can promote green energy transition, reduce carbon emissions, prevent and mitigate flood and drought disasters, and ensure the sustainable development of the entire basin. In this study, based on publicly available hydrometeorological observation data and satellite remote sensing monitoring data from 2001 to 2020, a machine learning model of the Lancang–Mekong Basin was developed to reconstruct the basin’s hydrological processes, and identify the occurrence patterns and influencing mechanisms of water-related hazards. The results show that, against the background of climate change, the Lancang–Mekong Basin is affected by the increasing frequency and intensity of extreme precipitation events. In particular, Rx1day, Rx5day, R10mm, and R95p (extreme precipitation indicators determined by the World Meteorological Organization’s Expert Group on Climate Change Monitoring and Extreme Climate Events) in the northwestern part of the Mekong River Basin show upward trends, with the average maximum daily rainfall increasing by 1.8 mm/year and the total extreme precipitation increasing by 18 mm/year on average. The risks of flood and drought disasters will continue to rise. The flood peak period is mainly concentrated in August and September, with the annual maximum flood peak ranging from 5600 to 8500 m³/s. The Stung Treng Station exhibits longer drought duration, greater severity, and higher peak intensity than the Chiang Saen and Pakse Stations. At the Pakse Station, climate change and hydropower development have altered the non-drought proportion by −12.50% and +15.90%, respectively. For the Chiang Saen Station, the fragmentation degree of the drought index time series under the baseline, naturalized, and hydropower development scenarios is 0.901, 1.16, and 0.775, respectively. These results indicate that hydropower development has effectively reduced the frequency of rapid drought–flood transitions within the basin, thereby alleviating pressure on drought management efforts. The regulatory role of the cascade reservoirs in the Lancang River can mitigate risks posed by climate change, weaken adverse effects, reduce flood peak flows, alleviate hydrological droughts in the dry season, and decrease flash drought–flood transitions in the basin. The research findings can enable basin managers to proactively address climate change, develop science-based technical pathways for hydropower dispatch, and formulate adaptive disaster prevention and mitigation strategies. Full article

Flash floods, exacerbated by climate change and land use alterations, are among the most destructive natural hazards globally, leading to significant damage and loss of life. In this context, the Flash Flood Potential Index (FFPI), which is a terrain and land surface-based model, and Google Earth Engine (GEE) were used to assess flood-prone zones across North Macedonia’s watersheds. The presented GEE-based assessment was accomplished by a custom script that automates the FFPI calculation process by integrating key factors derived from publicly available sources. These factors, which define susceptibility to torrential floods, include slope (Copernicus GLO-30 DEM), land cover (Copernicus GLO-30 DEM), soil type (SoilGrids), vegetation (ESA World Cover), and erodibility (CHIRPS). The spatial distribution of average FFPI values across 1396 small catchments (10–100 km²) revealed that a total of 45.4% of the area exhibited high to very high susceptibility, with notable spatial variability. The CHIRPS rainfall data (2000–2024) that combines satellite imagery and in situ measurements was used to estimate peak 24 h runoff and discharge. To improve the accuracy of CHIRPS, the data were adjusted by 30–50% to align with meteorological station records, along with normalized FFPI values as runoff coefficients. Validation against 328 historical river flood and flash flood records confirmed that 73.2% of events aligned with moderate to very high flash flood susceptibility catchments, underscoring the model’s reliability. Thus, the presented cloud-based scenario highlights the potential of the GEE’s efficacy in scalability and robustness for flash flood modeling and regional risk management at national scale. Full article

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. Full article

The Mw 7.8 Gorkha Earthquake of 25 April 2015 triggered over 25,000 landslides across central Nepal, with 4775 events concentrated in Gorkha District alone. Despite substantial advances in landslide susceptibility mapping, existing studies often overlook the compound role of post-seismic rainfall and lack robust spatial validation. To address this gap, we validated an ensemble machine learning framework for co-seismic landslide susceptibility modeling by integrating seismic, geomorphological, hydrological, and anthropogenic variables, including cumulative post-seismic rainfall. Using a balanced dataset of 4775 landslide and non-landslide instances, we evaluated the performance of Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) models through spatial cross-validation, SHapley Additive exPlanations (SHAP) explainability, and ablation analysis. The RF model outperformed all others, achieving an accuracy of 87.9% and a Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) value of 0.94, while XGBoost closely followed (AUC = 0.93). Ensemble models collectively classified over 95% of observed landslides into High and Very High susceptibility zones, demonstrating strong spatial reliability. SHAP analysis identified elevation, proximity to fault, peak ground acceleration (PGA), slope, and rainfall as dominant predictors. Notably, the inclusion of post-seismic rainfall substantially improved recall and F1 scores in ablation experiments. Spatial cross-validation revealed the superior generalizability of ensemble models under heterogeneous terrain conditions. The findings underscore the value of integrating post-seismic hydrometeorological factors and spatial validation into susceptibility assessments. We recommend adopting ensemble models, particularly RF, for operational hazard mapping in earthquake-prone mountainous regions. Future research should explore the integration of dynamic rainfall thresholds and physics-informed frameworks to enhance early warning systems and climate resilience. Full article

Floods are the biggest hydrometeorological disaster, affecting millions annually. Thus, flood hazard assessment is crucial and plays a pivotal role in rational water management. This study was undertaken to evaluate flood hazards through the application of MCDM methods and a bivariate statistical model integrated with GIS. The methodologies applied were AHP, fuzzy AHP, and the frequency ratio. Eight flood-related criteria were considered—elevation, flow accumulation, geology, slope, land use/land cover (LULC), distance from the drainage network, drainage density, and rainfall index—for the construction of a Flood Hazard Map for each methodology, with the aim to delineate the regions within the study area most prone to flooding. The results demonstrated that around 34% of the Chalkidiki regional unit presents a high and very high hazard to the occurrence of floods. The comparison of the maps generated using DSC demonstrated that all models are capable of delineating high and very high hazard areas with overlap values varying from 0.8 to 0.98. The validation results indicated that the models exhibit sufficient performance in flood hazard mapping with AUC-ROC scores of 66.6%, 65.7%, and 76.5% for the AHP, FAHP, and FR models, respectively. Full article

This study analyzes the evolution of hydrometeorological risks and severe weather events in Catalonia through an extensive review of 21,312 news reports aired by Televisió de Catalunya (TVC) between 1984 and 2019, 10,686 (50.1%) of which focused on events within Catalonia. The reports are categorized by the type of phenomenon, geographic location, and reported impact, enabling the identification of temporal trends. The results indicate a general increase in the frequency of news coverage of hydrometeorological and severe weather events—particularly floods and heavy rainfall—both in Catalonia and the broader Mediterranean region. This rise is attributed not only to a potential increase in such events, but also to the expansion and evolution of media coverage over time. In the Catalan context, the most frequently reported hazards are snowfalls and cold waves (3203 reports), followed by rainfall and flooding (3065), agrometeorological risks (2589), and wind or sea storms (1456). The study highlights that rainfall and flooding pose the most significant risks in Catalonia, as they account for the majority of the reports involving serious impacts—1273 cases of material damage and 150 involving fatalities. The normalized data reveal a growing proportion of reports on violent weather and floods, and a relative decline in snow-related events. Full article