Search Results (5,995)

Meteorological and climatological trends are surely changing the way urban infrastructure systems need to be operated and maintained. Urban road traffic fluctuates more significantly under the interference of strong wind–rain weather, especially during tropical cyclones. Deep learning-based methods have significantly improved the accuracy of traffic prediction under extreme weather, but their robustness still has much room for improvement. As the frequency of extreme weather events increases due to climate change, accurately predicting spatiotemporal patterns of urban road traffic is crucial for a resilient transportation system. The compounding effects of the hazards, environments, and urban road network determine the spatiotemporal distribution of urban road traffic during an extreme weather event. In this paper, a novel Knowledge-driven Attribute-Augmented Attention Spatiotemporal Graph Convolutional Network (KA3STGCN) framework is proposed to predict urban road traffic under compound hazards. We design a disaster-knowledge attribute-augmented unit to enhance the model’s ability to perceive real-time hazard intensity and road vulnerability. The attribute-augmented unit includes the dynamic hazard attributes and static environment attributes besides the road traffic information. In addition, we improve feature extraction by combining Graph Convolutional Network, Gated Recurrent Unit, and the attention mechanism. A real-world dataset in Shenzhen City, China, was employed to validate the proposed framework. The findings show that the prediction accuracy of traffic speed can be significantly increased by 12.16%~31.67% with disaster information supplemented, and the framework performs robustly on different road vulnerabilities and hazard intensities. The framework can be migrated to other regions and disaster scenarios in order to strengthen city resilience. Full article

Climate change is elevating temperatures, shifting weather patterns, and increasing frequency and severity of extreme weather events. Despite the urgency with which solutions are needed, relatively few studies comprehensively investigate the effectiveness of alternative flood risk management options under different climate conditions. Specifically, we are interested in a comparison of the effectiveness of resistance, nature-based, and managed retreat strategies. Using an integrated 1D-2D PCSWMM model, this paper presents a comprehensive investigation into the effectiveness of alternative adaptation strategies in reducing flood risks in Eastwick, a community of Philadelphia, PA, subject to fluvial, pluvial, and coastal flood hazards. While addressing the urgent public need to develop local solutions to this community’s flood problems, the research also presents transferable insights into the limitations and opportunities of different flood risk reduction strategies, manifested here by a levee, watershed-scale green stormwater infrastructure (GSI) program, and a land swap. The effectiveness of these options is compared, respectively, under compound climate change conditions, with the spatiotemporal patterns of precipitation and Delaware river tidal conditions based on Tropical Storm Isaias (2020). The hypothesis was that the GSI and managed retreat approaches would be superior to the levee, due to their intrinsic ability to address the compound climate hazards faced by this community. Indeed, the findings illustrate significant differences in the predicted flood extents, depths, and duration of flooding of the various options under both current and future climate scenarios. However, the ideal remedy to flooding in Eastwick is more likely to require an integrated approach, based on more work to evaluate cost-effectiveness, stakeholder preferences, and various logistical factors. The paper concludes with a call for integrating multiple strategies into multifunctional flood risk management. Full article

Urban forests are natural habitat areas within urban ecosystems that enhance physical, mental, and social well-being. By integrating natural and cultural values into the urban landscape, these areas offer individuals opportunities to interact with nature and engage in various recreational activities. Recreational activities increase physical activity levels, help reduce stress, strengthen mental health, and foster social interaction, thereby significantly protecting and improving public health. This study aims to evaluate the recreational performance of urban forests—an essential component of the urban ecosystem—through a multidimensional approach. In this context, ecological (topography, vegetation, water resources, soil structure, climate), physical (accessibility, infrastructure, area size), social (activity diversity, usage intensity, community events), and cultural (landscape values, urban identity, conservation status of cultural landscapes) factors were considered as key indicators. Bursa Atatürk Urban Forest was selected as the study area, and the methodology integrated SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis with weighted multi-criteria decision-making techniques. In addition, the qualitative data obtained were supported by statistical analysis methods to reveal the relationships among the criteria quantitatively. Through this holistic approach, the recreational performance of the urban forest was evaluated scientifically, leading to the conclusion that the area’s strengths should be preserved, its weaknesses improved, and its cultural landscape values managed sustainably. The study provides a valuable decision-support framework capable of guiding strategic planning for the future. Full article

Extreme climate events—such as heatwaves, floods, and droughts—are increasingly affecting ecosystems, with the global average temperature projected to rise by up to 3 °C (IPCC, 2023) due to anthropogenic greenhouse gas emissions. These changes pose critical challenges to food security, as evidenced by 733 million people facing hunger in 2024. In response, crop modeling considering different climate change scenarios has become a valuable tool to guide the development of climate-resilient agricultural strategies. Despite its nutritional importance and capacity to thrive across diverse environments, Ipomoea batatas (sweet potato) remains understudied in terms of potential spatial distribution forecasting, particularly in regions of high agrobiodiversity such as northwestern South America. Therefore, in this study we modeled the projected distribution of wild and landrace sweet potato genepools in the northern Andes under four future timeframes using seven machine learning algorithms. Our results predicted a 50% reduction in the climatically suitable range for the wild genepool by 2081, coupled with an average altitudinal shift from 1537 to 2216 m above sea level (a.s.l.). For landraces, a 36% reduction was projected by 2080, with a shift from 62 to 1995 m a.s.l. By the end of the century, suitable zones for both wild and cultivated genepools are expected to converge in high-altitude regions such as the Colombian Massif, with additional remnants of wild populations near the mountain range of Farallones de Cali. This modeling approach provides essential insights into the spatial dynamics of I. batatas under climate change, highlighting the need for ex situ conservation planning in vulnerable regions as well as assisted migration to more suitable areas. Future research should integrate edaphic and biotic interaction data to better approach the realized niche of the species and understand potential responses under a niche conservatism assumption, as well as genomic data to account for the species’ intrinsic adaptative potential, overall informing conservation, germplasm mobilization, and pre-breeding strategies that may ultimately secure the role of sweet potato in resilient food systems. Full article

In recent years, the frequent occurrence of extreme weather events has prompted increased global attention to greenhouse gas emissions. This study analyzes the spatio-temporal evolution of carbon emission intensity (CEI) across land use types in China’s 30 provinces from 2009 to 2022. Based on the data from China Rural Statistical Yearbook, China City Statistical Yearbook, China Energy Statistical Yearbook, China Natural Resources Statistical Yearbook, and China Statistical Yearbook, this study aims to reveal the spatio-temporal differentiation patterns of CEI, analyze the decoupling status between development mode and carbon emissions, and establish a three-dimensional collaborative emission reduction framework. Firstly, employing the carbon emission factor method, provincial carbon emissions, sinks, and net emissions are calculated, with intensity levels derived from gross domestic product (GDP). Secondly, spatio-temporal trends and inter-provincial disparities are analyzed using the decoupling index. The spatial effects among the provinces are investigated based on Moran’s I index. The results show that while the overall CEI has declined since 2009, significant regional disparities persist, with the southern provinces showing lower carbon emission intensities compared to the northern and western regions. The spatial analysis reveals a strong aggregation effect, with provinces clustering into high-high (HH) and low-low (LL) regions regarding CEI. This study concludes with policy recommendations for emission reduction and climate change mitigation, emphasizing industrial structure adjustment, enhanced regional coordination, and optimized land use planning. Full article

Phylogeographic studies in Antarctica allow us to understand the demographic events of populations during glacial periods. In this study, the polyplacophoran Tonicina zschaui was analyzed in several localities on the West Antarctic Coast using the mitochondrial gene cytochrome oxidase subunit I (COI). Two genetically distinct populations were identified: one in the Weddell Sea and another across the Antarctic Peninsula and South Shetland Islands. Genetic diversity was generally low to moderate, suggesting limited gene flow and the influence of historical climatic events. Star-like haplotype networks and demographic analyses indicate population contractions during the Last Glaciation followed by postglacial expansion, especially in the Antarctic Peninsula–South Shetland Islands population. Several sites in this region were identified as potential glacial refugia, exhibiting proportionally elevated genetic diversity and exclusive haplotypes. Conversely, the small Weddell Sea population displayed signs of long-term isolation, limited expansion, and low diversity, likely due to stronger environmental constraints and genetic drift. Ocean currents such as the Antarctic Coastal Current, the Antarctic Peninsula Coastal Current and the Weddell Gyre appear to restrict larval dispersal, reinforcing genetic discontinuities. These findings support the hypothesis of glacial survival in localized refugia and postglacial recolonization, a pattern observed in other Antarctic marine invertebrates. Full article

Earthen archaeological sites are particularly vulnerable to rain and winds, whose effects may compromise their integrity. The Huaca Chotuna (HC; 8th–16th Century AD) is an adobe platform in Peru’s semi-arid Lambayeque region, and it is in an area with exposure to rain and winds associated with the El Niño Southern Oscillation (ENSO) events. Here we present the results from an orthophotogrammetric and morphometric study aimed at quantifying the effects of erosion and deposition at the HC. The novelty of our approach consists of merging topographic, hydrological, and wind parameters to recognize the sector of the HC with exposure to potentially damaging natural climatic phenomena. We identify zones affected by erosion and deposition processes. Results of a diffusion model aimed to estimate the HC sectors where these processes will act in the next century are also presented. Gully erosion from rainfall indicates a vertical erosion rate of approximately 0.2 m/century, demonstrating the low preservation potential of the HC. Rainwater also deteriorates adobe bricks and triggers water/mud flows. Conversely, sediment-laden winds contribute to the partial burial of the HC. The findings highlight significant hazards to the HC’s structural integrity, including gravity instability. The interdisciplinary methodology we adopt offers a key framework for assessing and protecting other earthen sites globally against the escalating impacts of climate change. Full article

With climate change, the frequency and severity of localized heavy rainfalls are increasing. Thus, for urban drainage networks (UDNs), particularly those in aging cities such as Seoul, Republic of Korea, flood risk management challenges are mounting. Conventional design standards typically apply uniform roughness coefficients based on new pipe conditions, neglecting the ongoing performance degradation from physical influences. This study introduces a methodology that systematically incorporates pipe age and size into roughness coefficient scenarios for higher-accuracy 1D–2D rainfall–runoff hydrologic–hydraulic simulations. Eleven roughness scenarios (a baseline and ten aging-based scenarios) are applied across seven UDNs using historical rainfall data. The most representative scenario (S3) is identified using a Euclidean distance metric combining the peak water-level error and root mean square error. For two rainfall events, S3 yields substantial increases in the simulated mean flood volumes (75.02% and 76.45%) compared with the baseline, while spatial analysis reveals significantly expanded inundation areas and increased flood depths. These findings underscore the critical impact of pipe deterioration on hydraulic capacity and demonstrate the importance of incorporating aging infrastructure into flood modeling and UDN design. This approach offers empirical support for updating UDN design standards for more resilient flood management. Full article

Wildfires in Portugal have become increasingly frequent and severe, driven by a combination of fuel accumulation, extreme meteorological conditions, and topographic complexity. This study assesses the applicability of the Hot–Dry–Windy (HDW) index in characterizing fire-weather conditions during five major wildfires: Chamusca (2003), Pedrógão Grande and Lousã (2017), Monchique (2018), and Covilhã (2022). HDW values were computed at sub-daily resolution and compared against a 1991–2020 climatology. This study also evaluates the HDW index as a high-resolution fire danger indicator in Portugal and compares it with the traditional FWI using percentile-based climatology. The findings indicate that during 12 and 15 UTC, HDW in the wildfires in Chamusca (2003) and Lousã (2017) exceeded 180–370 units, suggesting extreme air conditions driven by hot, dry, and windy weather patterns. These values denoted extremely flammable conditions since they were significantly higher than the 95th percentile. A distinct peak at 15 UTC for Pedrógão Grande (2017) topped 140 units (>P95), which is consistent with the ignition timing and a rapid beginning spread. A continuous HDW anomaly that peaked above 200 units between 2 August and 5 August preceded the Monchique (2018) event, suggesting extended heat stress and increased wind contribution. While not as severe as in previous instances, HDW at Covilhã (2022) was above the 75th percentile in the early afternoon (12–18 UTC). Results show that in all cases, HDW values exceeded the 90th and 95th percentiles during the hours of ignition and early fire spread, with the most critical anomalies occurring between 12 UTC and 18 UTC. Spatial analyses revealed regional-scale patterns of HDW exceedance, aligning with observed ignition zones. Comparisons with the Canadian Fire Weather Index (FWI) revealed that while the FWI captured seasonal fuel aridity, the HDW more effectively resolved short-term meteorological extremes, particularly wind and atmospheric dryness. The HDW index was found to identify high-risk conditions even when FWI values were moderate, highlighting its added diagnostic value. These results support the inclusion of HDW in operational fire danger rating systems for Portugal and other Mediterranean countries, where compound fire-weather extremes are becoming more frequent due to climate change. Full article

The Western and Central Pacific Ocean (WCPO), the key global purse seine fishing ground for skipjack tuna (Katsuwonus pelamis), sees frequent ENSO events. These events drastically alter marine ecosystems and fishery resource patterns, complicating fisheries management—given skipjack tuna’s high mobility and sensitivity to marine environmental changes. To address this, the study proposes an improved spatial prediction framework that incorporates the MGWR model to capture environmental changes. The spatial regression results generated by the MGWR model are incorporated as the mean-field input for the BME model. Additionally, the interannual standard deviation of skipjack tuna resources is fed into the BME model as a measure of spatial uncertainty. The results indicate that the mean field and uncertainty field exhibit a strong correlation, with an R² of 0.54, an RMSE of 583.32, an MAE of 377.22, and an ME of 334.77. Compared to the single prediction models BME and MGWR, the MGWR-BME integrated framework has improved R² by 12%, 30%, and 13% in the 2021–2023 predictions, respectively. Additionally, its prediction performance for distinguishing El Niño, La Niña, and normal years has significantly improved, with R² increasing from 0.6 to 0.67 in 2021, from 0.34 to 0.62 in 2022, and from 0.30 to 0.40 in 2023. According to the evaluation results based on Kernel Density Estimation (KDE) curves, the model performs well in fitting low values but shows weaker performance in fitting high values. By applying this approach, we have clarified the multiscale driving mechanisms through which marine environmental heterogeneity affects the distribution of skipjack tuna under ENSO conditions. This insight enables fishery managers to more accurately predict the dynamic changes in skipjack tuna fishing grounds under different climatic scenarios, thereby providing a reliable scientific basis for formulating rational fishing quotas, optimizing fishing operation layouts, and implementing targeted conservation measures—ultimately contributing to the balanced development of fishery resource utilization and ecological protection. Full article

The construction of the Xinyang Urban Water Supply Project, centered on the Chushandian Reservoir, required a thorough investigation of high–low runoff encounters between the water source and receiving areas to optimize water allocation and operational scheduling. Based on the hydrological stations at Changtaiguan (CTG) on the main stream of the Huaihe River (HR) in the water source area and Miaowan (MW) on the main stream of the Honghe River in the receiving area, the trends and abrupt change characteristics of monthly runoff from 2014 to 2024 were analyzed using methods such as extremum symmetry mode decomposition (ESMD) and heuristic segmentation, with spatial encounter patterns determined using Copula functions. The results indicate that (1) the runoff in the water source area showed a quasi-6.05-month periodic characteristic on a monthly scale, while the runoff in the receiving area exhibited a quasi-6.72-month periodic characteristic on a monthly scale; (2) the water source area experienced runoff mutation in August 2015 (extreme drought) and June 2024 (extreme precipitation), with the receiving area responding 7 months earlier than the water source area, revealing differences in system vulnerability; (3) synchronous hydrological states were significantly more likely to occur (51.2%) compared with asynchronous conditions (25.2%), with the highest probability of “concurrent drought” (19.8%) and a high-risk “normal water source—receiving area drought” combination (14.1%). These findings provide theoretical and technical support for the optimized scheduling of the Chushandian Reservoir, improving the resilience and adaptability of the Xinyang Urban Water Supply Project to climate fluctuations and extreme hydrological events. Full article

Glacier retreat due to climate change is accelerating worldwide, yet the phenomenon remains abstract for many people, especially those unfamiliar with mountain environments. The Urban Glaciology experiment, conducted during Milan’s internationally renowned “Fuorisalone” 2024 design event, aimed to bridge this perceptual gap by simulating real glacier melt processes in a busy urban square. Three large ice blocks with contrasting surface conditions (i.e., clean, dirty, and debris-covered) were exposed to springtime urban temperatures, mimicking conditions found on Alpine glaciers during summer. Over one week, the blocks produced a total of 748 L of meltwater, with dirty ice melting up to four times faster than debris-covered ice, consistent with established albedo effects. These results confirmed the thermal analogy between Milan’s spring conditions (+15 to +20 °C) and the ablation season on Alpine glaciers. Visitors observed the differential melting in real time, supported by visual indicators, explanatory panels, immersive virtual experiences, and direct interaction with researchers and students. Informal interviews indicated that more than 60% of participants reported a perceptual shift, recognizing for the first time that urban temperatures can replicate glacier melting conditions. By embedding a science-based installation in a major cultural tourism event, the experiment reached a diverse, non-traditional audience—including tourists, designers, and citizens—and encouraged reflection on the implications of glacier loss. The success of this initiative highlights the potential of replicating similar models in other cities to raise awareness of environmental change through culturally engaging experiences. Full article

This study analyses the impacts of winter storms on beach response, as well as the subsequent recovery during spring and summer, at a dissipative sandy beach in Brandon Bay, Ireland. Shoreline dynamics were assessed through the integration of field data from five survey campaigns conducted between October 2021 and November 2022 with a 1D Xbeach (version 1.23) numerical model. Cross-sectional profiles were measured at seven locations, revealing pronounced erosion during winter, followed by recovery in calmer seasons, especially in the lower beach zone. The model effectively simulated short-term storm-induced morphological changes, demonstrating that rates of shoreline retreat and profile alteration are higher in the eastern bay, where wave energy is greater. Most morphological changes occurred between the low and high astronomical tide marks, characterized by upper beach erosion and lower beach accretion. Models were subsequently employed to examine future climate scenarios, including sea level rise and increased storm intensity. The projections indicated an exponential increase in erosion rates, correlated with higher storm wave heights and frequencies. These results highlight the dynamic response of dissipative beaches to extreme events and reinforce the necessity for adaptive coastal management strategies to address the escalating risks posed by climate change. Full article

This review examines South Africa’s escalating flood vulnerability through a synthesis of over 80 peer-reviewed articles, historical records, policy reports, and case studies. Using a PRISMA-guided analysis, the study identifies key climatic drivers, including extreme rainfall from tropical–temperate interactions, cut-off lows, and La Niña conditions that interact with structural weaknesses such as inadequate drainage, poorly maintained stormwater systems, and rapid urban expansion. Apartheid-era spatial planning has further entrenched risk by locating marginalised communities in floodplains. Governance failures like weak disaster risk reduction (DRR) policies, fragmented institutional coordination, and insufficient early warning systems intensify flood vulnerabilities. Catastrophic events in KwaZulu-Natal (KZN) and the Western Cape (WC) illustrate the consequences exemplified by the April 2022 KZN floods alone, which caused over 450 deaths, displaced more than 40,000 people, and generated damages exceeding ZAR 17 billion. Nationally, more than 1500 flood-related fatalities have been documented in the past two decades. Emerging resilience pathways include ecosystem-based adaptation, green infrastructure, participatory governance, integration of Indigenous knowledge, improved hydrological forecasting, and stricter land-use enforcement. These approaches can simultaneously reduce physical risks and address entrenched socio-economic inequalities. However, significant gaps remain in spatial flood modelling, gender-sensitive responses, urban–rural disparities, and policy implementation. The review concludes that South Africa urgently requires integrated, multi-scalar strategies that combine scientific innovation, policy reform, and community-based action. Embedding these insights into disaster management policy and planning is essential to curb escalating losses and build long-term resilience in the face of climate change. Full article

Understanding the evolutionary and geographic trajectories of crop wild relatives is vital for enhancing agro-biodiversity and advancing climate-resilient agriculture. This study focuses on ten Vicia L. taxa—comprising five species, four varieties, and one subspecies—of significant agricultural importance in Türkiye. An integrative molecular framework was applied, incorporating nuclear ITS sequence data, ITS2 secondary structure modeling, phylogenetic network analysis, and time-calibrated biogeographic reconstruction. This approach revealed well-supported clades, conserved secondary structural elements, and signatures of reticulate evolution, particularly within the Vicia sativa L. and V. villosa Roth. complexes, where high genetic similarity suggests recent divergence and possible hybridization. Anatolia was identified as both a center of origin and a dispersal corridor, with divergence events estimated to have occurred during the Late Miocene–Pliocene epochs. Inferred migration routes extended toward the Balkans, the Caucasus, and Central Asia, corresponding to paleoenvironmental events such as the uplift of the Anatolian Plateau and the Messinian Salinity Crisis. Phylogeographic patterns indicated genetic affiliations between Turkish taxa and drought-adapted Irano-Turanian lineages, offering valuable potential for climate-resilient breeding strategies. The results establish a molecularly informed foundation for conservation and varietal development, supporting sustainability-oriented innovation in forage crop systems and contributing to regional food security. Full article