Search Results (1,743)

Protection of coastal cultural heritage is among the most urgent global priorities, as these sites face increasing threats from climate change, sea level rise, and human activity. This study emphasises the value of innovative geospatial tools and data ecosystems for timely risk assessment. The role of land administration systems, geospatial documentation of coastal cultural heritage sites, and the adoption of innovative techniques that combine various methodologies is crucial for timely action. The coastal management infrastructure in Greece is presented, outlining the key public authorities and national legislation, as well as the land administration and geospatial ecosystems and the various available geospatial ecosystems. We profile the Hellenic Cadastre and the Hellenic Archaeological Cadastre along with open geospatial resources, and introduce TRIQUETRA Decision Support System (DSS), produced through the EU’s Horizon project, and a Digital Twin methodology for hazard identification, quantification, and mitigation. Particular emphasis is given to the role of Digital Twin technology, which acts as a continuously updated virtual replica of coastal cultural heritage sites, integrating heterogeneous geospatial datasets such as cadastral information, photogrammetric 3D models, climate projections, and hazard simulations, allowing for stakeholders to test future scenarios of sea level rise, flooding, and erosion, offering an advanced tool for resilience planning. The approach is validated at the coastal archaeological site of Aegina Kolona, where a UAV-based SfM-MVS survey produced using high-resolution photogrammetric outputs, including a dense point cloud exceeding 60 million points, a 5 cm resolution Digital Surface Model, high-resolution orthomosaics with a ground sampling distance of 1 cm and 2.5 cm, and a textured 3D model using more than 6000 nadir and oblique images. These products provided a geospatial infrastructure for flood risk assessment under extreme rainfall events, following a multi-scale hydrologic–hydraulic modelling framework. Island-scale simulations using a 5 m Digital Elevation Model (DEM) were coupled with site-scale modelling based on the high-resolution UAV-derived DEM, allowing for the nested evaluation of water flow, inundation extents, and velocity patterns. This approach revealed spatially variable flood impacts on individual structures, highlighted the sensitivity of the results to watershed delineation and model resolution, and identified critical intervention windows for temporary protection measures. We conclude that integrating land administration systems, open geospatial data, and Digital Twin technology provides a practical pathway to proactive and efficient management, increasing resilience for coastal heritage against climate change threats. Full article

Nepal is highly susceptible to natural hazards, including earthquakes, flooding, and landslides, all of which may occur independently or in combination. Climate change is projected to increase the frequency and intensity of these natural hazards, posing growing risks to Nepal’s infrastructure and development. To the authors’ knowledge, the majority of existing geohazard research in Nepal is typically limited to single hazards or localised areas. To address this gap, MiMapper was developed as a cloud-based, open-access multi-hazard mapping tool covering the full national extent. Built on Google Earth Engine and using only open-source spatial datasets, MiMapper applies an Analytical Hierarchy Process (AHP) to generate hazard indices for earthquakes, floods, and landslides. These indices are combined into an aggregated hazard layer and presented in an interactive, user-friendly web map that requires no prior GIS expertise. MiMapper uses a standardised hazard categorisation system for all layers, providing pixel-based scores for each layer between 0 (Very Low) and 1 (Very High). The modal and mean hazard categories for aggregated hazard in Nepal were Low (47.66% of pixels) and Medium (45.61% of pixels), respectively, but there was high spatial variability in hazard categories depending on hazard type. The validation of MiMapper’s flooding and landslide layers showed an accuracy of 0.412 and 0.668, sensitivity of 0.637 and 0.898, and precision of 0.116 and 0.627, respectively. These validation results show strong overall performance for landslide prediction, whilst broad-scale exposure patterns are predicted for flooding but may lack the resolution or sensitivity to fully represent real-world flood events. Consequently, MiMapper is a useful tool to support initial hazard screening by professionals in urban planning, infrastructure development, disaster management, and research. It can contribute to a Level 1 Integrated Geohazard Assessment as part of the evaluation for improving the resilience of hydropower schemes to the impacts of climate change. MiMapper also offers potential as a teaching tool for exploring hazard processes in data-limited, high-relief environments such as Nepal. Full article

Glacial lake outburst floods (GLOFs) represent increasingly common and high-magnitude geohazards across the cryosphere of the Tibetan Plateau, particularly under ongoing climate warming and glacier retreat. This study combines multi-temporal remote sensing imagery and detailed Flo-2D hydrodynamic modeling to investigate the erosive dynamics of the 2020 Jinwuco GLOF in Southeastern Tibetan Plateau. Key conclusions include: (1) The 2.35 km-long flood routing channel exhibits pronounced non-uniformity in horizontal curvature, channel width, and cross-sectional shape, significantly influencing flood propagation; five representative cross-sections divide the channel into six distinct segments. (2) Prominent lateral erosion occurred proximally to the dam, attributable to extreme erosive forces and high sediment transport capacity during peak discharge, with horizontal channel curvature further amplifying local impact and erosion. (3) Erosion rates were highest near the dam and in downstream narrow segments, while mid-reach sections with greater width experienced lower erosion. (4) Maximum flow depths reached 28.12 m in topographically confined reaches, whereas peak velocities occurred in upstream and downstream curved sections. (5) The apparent critical erosive shear stress of bank material is controlled not only by soil strength but also by flood dynamics and pre-existing channel morphology, indicating strong feedback between flow dynamics, channel morphology, and critical erosive shear stress of bank material. This study provides a generalized and transferable framework for analyzing GLOF-related erosion in data-scarce high-altitude regions, offering critical insights for hazard assessment, regional planning, and risk mitigation strategies. Full article

Casablanca, Morocco’s largest Atlantic port city, faces increasing exposure to floods, drought, and other risks that align with legacies of urban transformations carried out during the colonial period. This study examines how early-20th-century interventions—including the canalization and burial of the Oued Bouskoura, extensive coastal reclamation, and the implementation of rigid zoning—were associated with a reconfiguration of the city’s hydrology and coincide with persistent socio-spatial inequalities. Using historical cartography, archival sources, and GIS-based overlays of colonial-era plans with contemporary hazard maps, the analysis reveals an indicative spatial correlation between today’s high-risk zones and areas transformed under the Protectorate, with the medina emerging as one of the most vulnerable districts. While previous studies have examined either colonial planning in architectural or contemporary climate risks through technical and governance lenses, this article illuminates historically conditioned relationships and long-term associations for urban resilience. In doing so, it empirically maps spatial associations and conceptually argues for reframing heritage not only as cultural memory but as a climate resource, illustrating how suppressed vernacular systems may inform adaptation strategies. This interdisciplinary approach provides a novel contribution to postcolonial city research, climate adaptation and heritage studies by proposing a historically conscious framework for resilience planning. Full article

The Niland Moving Mud Spring, located near the southeastern margin of the Salton Sea, represents a rare and evolving geotechnical hazard. Unlike the typically stationary mud pots of the Salton Trough, this spring is a CO₂-driven mud spring that has migrated southwestward since 2016, at times exceeding 3 m per month, posing threats to critical infrastructure including rail lines, highways, and pipelines. Emergency mitigation efforts initiated in 2018, including decompression wells, containment berms, and route realignments, have since slowed and recently almost halted its movement and growth. This study integrates hydrochemical, temperature, stable isotope, and tritium data to propose a refined conceptual model of the Moving Mud Spring’s origin and migration. Temperature data from the Moving Mud Spring (26.5 °C to 28.3 °C) and elevated but non-geothermal total dissolved solids (~18,000 mg/L) suggest a shallow, thermally buffered groundwater source influenced by interaction with saline lacustrine sediments. Stable water isotope data follow an evaporative trajectory consistent with imported Colorado River water, while tritium concentrations (~5 TU) confirm a modern recharge source. These findings rule out deep geothermal or residual floodwater origins from the great “1906 flood”, and instead implicate more recent irrigation seepage or canal leakage as the primary water source. A key external forcing may be the 4.1 m drop in Salton Sea water level between 2003 and 2025, which has modified regional groundwater hydraulic head gradients. This recession likely enhanced lateral groundwater flow from the Moving Mud Spring area, potentially facilitating the migration of upwelling geothermal gases and contributing to spring movement. No faults or structural features reportedly align with the spring’s trajectory, and most major fault systems trend perpendicular to its movement. The hydrologically driven model proposed in this paper, linked to Salton Sea water level decline and correlated with the direction, rate, and timing of the spring’s migration, offers a new empirical explanation for the observed movement of the Niland Moving Mud Spring. Full article

The intensification of extreme hydrologic events, such as flash floods and landslides, has amplified the challenges of ensuring timely and effective emergency response. A key factor in the efficiency of such interventions is the accessibility of affected areas, which often becomes compromised during hazard events. In this context, the present study focuses on the Vărbilău River catchment in Romania, a region highly exposed to frequent flash floods and terrain instability. The research evaluates the spatial accessibility of emergency intervention units. Four major intervention centers were assessed under both normal and constrained scenarios. Accessibility was quantified through travel-time thresholds, incorporating variables such as road quality, network density, topography, and hazard-induced disruptions. Findings indicate that southern localities enjoy relatively short intervention times (less than 10 or between 10 and 20 min) due to favorable terrain and proximity to well-equipped centers. In such cases, the speed on main roads is 50–60 km/h, while the accessibility index is 5. Conversely, northern areas and villages like Lutu Roşu face elevated isolation risks, as single-road access and weak connectivity heighten their vulnerability during floods or landslides. In such cases, speeds reduce to 10 km/h and accessibility is very low, with the accessibility index of 1. Scenario modeling further demonstrated that the loss of key hubs (e.g., Ploieşti or Văleni) severely undermines coverage efficiency, particularly in high-risk zones, where the access times increases over 40 min. These results emphasize the need for dynamic intervention planning, infrastructure reinforcement, and the systematic integration of hazard-prone areas into emergency response strategies. Moreover, the methodological framework developed here can be adapted to other regions exposed to hydrologic hazards. Full article

Climate change is intensifying the frequency and severity of extreme weather events, threatening the resilience of buildings and urban infrastructure. While technical solutions for climate adaptation in buildings are well documented, their economic viability remains a critical, yet underexplored, dimension of decision-making. This novel systematic review analyzes publications with an exclusive focus on climate adaptation strategies for buildings using cost-based evaluation methods. This review categorises the literature into three methodological clusters: Cost–Benefit Analysis (CBA), Life Cycle Costing (LCC), and alternative methods including artificial intelligence, simulation, and multi-criteria approaches. CBA emerges as the most frequently used and versatile tool, often applied to evaluate micro-scale flood protection and nature-based solutions. LCC is valuable for assessing long-term investment efficiency, particularly in retrofit strategies targeting energy and thermal performance. Advanced methods, such as genetic algorithms and AI-driven models, are gaining traction but face challenges in data availability and transparency. Most studies focus on residential buildings and flood-related hazards, with a growing interest in heatwaves, wildfires, and compound risk scenarios. Despite methodological advancements, challenges persist—including uncertainties in climate projections, valuation of non-market benefits, and limited cost data. This review highlights the need for integrated frameworks that combine economic, environmental, and social metrics, and emphasises the importance of stakeholder-inclusive, context-sensitive decision-making. Ultimately, aligning building adaptation with financial feasibility and long-term sustainability is achievable through improved data quality, flexible methodologies, and supportive policy instruments. Full article

Large woody debris (LWD) in river systems serves beneficial ecological functions and poses potential hazards during flood events. Managing LWD requires a balanced understanding of its dynamics. This study employed unmanned aerial vehicles (UAVs) for high-resolution, spatiotemporal monitoring of LWD distribution and mobility along the Oshirarika River in northern Japan. UAV imagery enabled efficient LWD recruitment and transport assessments. The spatial distribution analysis revealed that >90% of LWD was deposited on bar surfaces, underscoring the role of geomorphic features in controlling LWD accumulation. Generalized linear mixed models revealed that the maximum water level and the frequency of its rise above 0.8 m were the most influential predictors of the number of recruited and transported LWD. Additionally, the topographic position—channel, lower bar, or higher bar—exhibited a significant negative association, indicating greater LWD mobility and deposition in lower elevation zones. This trend may be attributed to infrequent high-magnitude flood events, which likely result in relatively limited LWD dynamics in higher bar areas. These findings demonstrate the utility of UAV-based monitoring coupled with GLMMs for capturing the spatial and temporal dynamics of LWD. The ability to link hydrological fluctuations and LWD behavior provides a valuable framework for management and ecological restoration in steep, forested watersheds. Full article

Extreme rainfall events are frequently associated with regions of complex topography, where terrain-induced convergence and uplift enhance storm development. Understanding the interaction between surface relief and atmospheric dynamics is essential for improving severe weather forecasting and hazard mitigation. Storm “Daniel”, which affected Greece from 4–7 September 2023, produced extreme rainfall and widespread flooding in the Thessaly region—a landscape characterized by significant elevation gradients. This study investigates the spatial relationship between lightning activity and terrain elevation, aiming to assess whether deep convection was preferentially triggered over mountainous regions or followed specific orographic patterns. High-resolution elevation data (SRTM 1 Arc-Second Global DEM) were used to calculate the mean elevation around each lightning strike across four spatial scales (2 km, 5 km, 10 km, and 20 km). Statistical analysis, including correlation coefficients and third-degree polynomial regression, revealed a non-linear relationship, with a distinct peak in lightning frequency at mid-elevations (~200–400 m). These findings suggest that topographic features at local scales can significantly modulate convective initiation, likely due to a combination of mechanical uplift and favorable thermodynamic conditions. The study integrates geospatial techniques and statistical modeling to provide quantitative insights into how terrain influences the formation, location, and intensity of thunderstorms during high-impact weather events. Full article

The interaction between humans and water has historically shaped landscapes, in which rivers played a central role in the development of territories. Among the infrastructures developed to manage water resources, watermills had always represented a key element of minor cultural heritage, reflecting centuries of adaptation to environmental, economic, and technological conditions. Although once central to river landscapes, these structures are now largely forgotten and at risk of being lost, particularly in Italy’s inner areas affected by rural depopulation, climate change, and natural hazards. The case analyzed in this paper, part of a larger research project, focuses on the analysis of watermills in the Aterno River valley in the Abruzzo region of central Italy. This fragile mountainous area is currently threatened by natural hazards and depopulation. The aim is to fill the gap in documentation on this “minor heritage,” which has been identified and cataloged, along a timeline of its vulnerabilities, starting from historical cartography, integrated with a localized field survey within a geographic information system. The GIS facilitates the cross-referencing of historical, geospatial, and environmental data, including hydrogeological and flood risk information. The results demonstrate how water, once a resource, has become a vulnerability factor and highlights the fragility of these historic artifacts, contextualized within the surrounding landscape. Full article

This study evaluates GPM-IMERG (Global Precipitation Measurement-Integrated Multi-satellite Retrievals) and CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) satellite precipitation data in Türkiye’s Akçay Sub-Basin by comparing them with rain gauge observations from the Finike and Elmali meteorological stations. Statistical metrics including Pearson’s correlation coefficient, Nash-Sutcliffe Efficiency (NSE), and Root Mean Square Error (RMSE) were used to assess performance. The study also examines distributional fit via the Kolmogorov–Smirnov (K-S) test and evaluates extreme rainfall detection accuracy using metrics like Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI). Results indicate that GPM-IMERG agrees well with rain gauge observations at the monthly scale (Pearson = 0.943; RMSE = 50.81 mm), but shows reduced accuracy at the daily scale (Pearson = 0.592; RMSE = 12.45 mm). The K-S test showed that the Beta distribution best fits monthly rainfall (threshold = 253.39 mm), while the Weibull distribution suits daily rainfall (threshold = 5.34 mm). GPM-IMERG achieved a POD of 0.778 and FAR of 0.222 for monthly extremes, while daily performance was lower (POD = 0.478; FAR = 0.388). These findings highlight the value of comparing satellite and ground-based data to improve flood risk assessment and enhance climate resilience in data-scarce basins. Full article

Meteorological hazards threaten sustainable development by affecting human safety, economic stability, and food security. Climate change increases extreme weather frequency, underscoring the urgency for comprehensive evaluation frameworks. However, existing frameworks rarely integrate multiple impact dimensions, limiting their practical utility. To address this gap, our core objective is to develop two novel index series, a single-hazard composite impact index (SHCI) and a multi-hazard composite impact index (MHCI), employing entropy weighting to integrate demographic and economic factors, enabling a more holistic assessment of meteorological hazard impacts in China. Analysis of 2004–2021 data on drought, rainstorm and flood (RF), hail and lightning (HL), typhoon, and low-temperature freezing (LTF) revealed decreases in the national MHCI and SHCI. Key results include the following: (1) the relative MHCI decreased by 74.8%, exceeding 61.21% of absolute MHCI; (2) nationally, 2010, 2013, and 2016 had high MHCI values, and Sichuan has the most extreme hazard years (three) among all the provinces; and (3) provincially, Ningxia has the highest absolute and relative MHCI, while SHCIs varied spatially. These findings provide specific references for climate adaptation planning and the optimization of hazard risk reduction strategies. The methodology offers a versatile framework for multi-hazard risk assessment in nations experiencing climatic and demographic transitions. Full article

This study investigates the multifaceted factors influencing the success of government-funded construction projects and addresses the challenges posed by climate-induced flooding, proposing integrated solutions encompassing structural vulnerability, system capacity, and organizational preparedness. By examining the challenges faced by coastal infrastructure, such as aging infrastructure, sea-level rise, and extreme weather events, this research seeks to identify strategies that enhance resilience and minimize the impact of flooding on coastal communities. The study presents a systematic review of 80 scholarly articles integrating quantitative and qualitative findings. Utilizing the PRISMA guidelines, the review highlights structural analysis, hydraulic modeling, and organizational surveys, to assess the resilience of coastal infrastructure systems. The results of this study offer actionable insights for policymakers, infrastructure managers, and coastal communities, facilitating informed decision-making and promoting climate-resilient development. Coastal regions around the world are increasingly vulnerable to climate-induced hazards such as sea level rise, storm surges, and intense flooding events. Among the most at-risk assets are transport infrastructure and buildings, which serve as the backbone of urban and regional functionality. This research paper presents a multidimensional assessment framework that integrates structural vulnerability, system capacity, and organizational preparedness to evaluate the resilience of coastal infrastructure. Drawing upon principles of resilience such as robustness, redundancy, safe-to-fail design, and change-readiness, the study critically reviews and synthesizes existing literature, identifies gaps in current assessment models, and proposes a comprehensive methodology for resilience evaluation. By focusing on both transport systems and building infrastructure, the research aims to inform adaptive strategies and policy interventions that enhance infrastructure performance and continuity under future climate stressors. Full article

The Yangtze River Basin (YRB) is highly vulnerable to both floods and droughts, with precipitation playing a key role in driving these hydrological extremes. Understanding and reducing uncertainty in precipitation estimates is therefore crucial for effective water management and hazard mitigation. The study evaluated the error characteristics of daily precipitation estimates from three datasets (CRA40, IMERG, and SM2RAIN) using the triple collocation (TC) approach. A least-squares merging framework was then applied to integrate these datasets and generate merged precipitation estimates with improved accuracy and reduced uncertainty over the YRB. Results showed that all examined datasets exhibited higher fractional root-mean-squared error (fRMSE) in the source region of the Yangtze River, indicating a greater influence of random errors and reduced sensitivity to precipitation changes in this area. Among the datasets, SM2RAIN exhibited the weakest agreement with ground-based measurements, while IMERG performed best in capturing extreme precipitation events. CRA40 and the TC-based merged precipitation estimates exhibited overall higher accuracy, with a station-average correlation coefficient of approximately 0.71. Despite comparable accuracy, the merged precipitation data is relatively more robust than CRA40, with a lower average error standard deviation of 2.07 mm. Full article

The growing frequency of extreme rainstorms has increasingly exposed tunnels to flooding risks, underscoring the urgent need for effective flood prevention and drainage measures. In this context, an evaluation framework for tunnel flood hazards was developed based on three criteria—hazard-inducing factors, hazard-formative environment, and disaster-bearing body—encompassing nine specific indicators. This study employs the Decision Making Trial and Evaluation Laboratory (DEMATEL) method to construct a causal analysis model and assess the interrelationships and influence levels of risk factors associated with tunnel flooding disasters. Rainfall intensity (C1), rainfall duration (C2), ground elevation (C4), road slope (C5), and impervious surface area (C6) exhibit high causal values, acting as external input factors that drive the occurrence of tunnel flooding incidents. Conversely, water depth (C3), tunnel drainage capacity (C7), emergency flood control measures (C8), and infrastructure aging (C9) display high centrality values, serving as internal factors that reflect the tunnel’s flood prevention capability and determine the extent of disaster losses. Simply enhancing tunnel drainage capacity from the perspective of internal factors alone is insufficient; optimizing the tunnel’s flood resilience requires a combined consideration of both internal and external factors. Full article