Search Results (1,305)

Seasonal design floods and operational water levels are critical for high-efficient water resource utilization. In this study, statistical and rational analyses methods were applied to divide the flood season based on seasonal rainfall patterns. The Mann–Kendall test and Theil–Sen analysis were used to detect trend changes in the observed flow series. Both stationary and nonstationary flood frequency analysis methods were conducted to estimate seasonal design floods. The Three Gorges Reservoir (TGR) in the Yangtze River, China, was selected as the case study. Results show that the TGR flood season could be divided into four periods: the reservoir drawdown period (1 May–20 June), the Meiyu flood period (21 June–31 July), the transition period (1 August–10 September), and the Autumn Rain refill period (11 September–31 October). Trend analyses indicate that the flow series at the TGR dam site exhibited a decreasing trend in recent decades. Upstream reservoir regulation has significantly reduced inflow discharges of TGR, and the nonstationary seasonal 1000-year design floods in the transition period are decreased by about 20%, and the flood control water level could rise from 145 m to 157 m, which can generate 2.288 billion kW h more hydropower (16.57% increase) while maintaining unchanged flood prevention standards. This study provides valuable insights into the TGR operational water level in the flood season and highlights the necessity of considering the regulation impact of upstream reservoirs for design floods and reservoir operational water levels. Full article

Climate change is intensifying hydrological extremes, posing growing threats to the safety and operational reliability of embankment dams worldwide, particularly those in regions susceptible to heavy rainfall and flooding. This study evaluates the overtopping risk for Batu Dam, a critical flood mitigation and water supply structure near Kuala Lumpur, Malaysia, under future climate scenarios, with the aim of informing risk-informed dam safety strategies. Using historical hydrological data (1975–2020) and downscaled climate projections from the CMIP5 database under three Representative Concentration Pathways (RCP4.5, RCP6.0, RCP8.5), we conducted flood routing simulations and probabilistic risk assessments employing the iPRESAS software. Our results demonstrate that the annual probability of overtopping increases substantially under higher-emission scenarios, reaching up to 0.08% by the late century under RCP8.5, driven by increased frequency and intensity of extreme rainfall events. These projections highlight significant spillway capacity limitations and underscore the heightened risk of downstream consequences, including economic losses exceeding RM 200 million and potential loss of life surpassing 2900 individuals in worst-case scenarios. The findings confirm the urgent need for both structural adaptations, such as spillway expansion and crest elevation, and non-structural measures, including enhanced real-time monitoring and early warning systems. This integrated approach offers a robust and replicable framework for strengthening dam safety under evolving climate conditions. Full article

The increasing frequency and severity of natural disasters—such as floods, storms, droughts, and earthquakes—have created a growing demand for temporary housing. These facilities must be rapidly deployed to provide safe, functional living environments for displaced individuals. This study proposes a design methodology for temporary housing exteriors using the text-to-image capabilities of generative artificial intelligence (GenAI) to address urgent post-disaster housing needs. The approach aims to improve both the efficiency and practicality of early-stage design processes. The study reviews global trends in temporary housing and the architectural applications of GenAI, identifying five key environmental factors that influence design: type of disaster, location and climate, duration of residence, materials and structure, and housing design. Based on these factors, hypothetical disaster scenarios were developed using ChatGPT, and corresponding exterior designs were generated using Stable Diffusion. The results show that diverse, scenario-specific design alternatives can be effectively produced using GenAI, demonstrating its potential as a valuable tool in architectural planning for disaster response. Expert evaluation of the generated designs confirmed their ability to adhere to text prompts but revealed a significant gap in terms of architectural plausibility and practical feasibility, highlighting the essential role of expert oversight. This study offers a foundation for expanding GenAI applications in emergency housing systems and supports the development of faster, more adaptable design solutions for communities affected by natural disasters. Full article

As global climate change intensifies the frequency of extreme weather events, urban flood control and disaster reduction efforts face unprecedented challenges. With the limitations of traditional, top-down emergency management becoming increasingly apparent, many countries are actively incorporating community-based participation into flood risk governance. While research in this area is expanding, the specific impact of urban flood inundation severity on residents’ participation in relief efforts remains significantly underexplored. To address this research gap, this study employs the Community Capitals Framework (CCF) and a Gradient Boosting Decision Tree (GBDT) model to empirically analyze 1322 survey responses from Zhengzhou, China, exploring the non-linear relationship between flood severity and public participation. Our findings are threefold: (1) As the most direct source of residents’ risk perception, flood inundation severity has a significant association with their participation level. (2) This relationship is distinctly non-linear. For instance, inundation severity within a 200 m radius of a resident’s home shows a predominantly negative relation with participation level, with the negative effect lessening at extreme levels of inundation. The distance from inundated areas, conversely, exhibits an “S-shaped” curve. (3) Flood severity exhibits a significant reinforcement interaction with both communication technology levels and government organizational mobilization. This indicates that, during public crises like flash floods, robust information channels and effective organizational support are positively related to residents’ transition from passive to active participation. This study reveals the complex, non-linear associations between flood severity and civic engagement, providing theoretical support and practical insights for optimizing disaster policies and enhancing community resilience within the broader context of urban land management and sustainable development. Full article

Urban flood damage is increasing globally, particularly in major cities. Factors contributing to flood risk include urban environmental changes, such as watershed development and precipitation variations caused by climate change. Rapid urbanization and weather anomalies further complicate flood management and damage mitigation. Additionally, detailed analyses at small spatial units (e.g., roads, buildings) remain insufficient. Hence, urban flood analysis considering such spatial variations is required. This study analyzed flood risk in Ulsan, Korea, under a severe flood scenario. Land cover changes from the 1980s to 2010s were examined in 10-year intervals, along with the frequency of heavy rainfall and high river water levels that trigger severe floods. Flood risk was structured as a matrix of likelihood and impact. The results revealed that land cover changes, influenced by development policies or regulations, had a minimal impact on urban flood risk, which is likely because effective drainage systems and stringent urban planning regulations mitigated their effects. However, the frequency and intensity of extreme precipitation events had a substantial effect. These findings were validated using a comparative analysis of an inundation damage trace map and flood range simulated by a physical model. The 10 m grid resolution and time-series likelihood-and-impact framework used in this study can inform budget allocation, resource mobilization, disaster prevention planning, and decision-making during disaster response efforts in major cities. 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

Ilha de Moçambique is an island off the northern coast of Mozambique, covering an area of 1.5 km². Recognized as a UNESCO World Heritage Site since 1991, the island is currently under threat due to the increasing frequency and intensity of extreme weather events caused by climate change. Cyclonic events and pluvial floods have led to the progressive degradation of buildings and are compromising the integrity of the site. Furthermore, the island’s economic and social vulnerability is also worsening. The article aims to critically review the strategic planning approaches adopted for climate adaptation on Ilha de Moçambique. The objective is to identify and assess the planning instruments implemented to protect coastal urban heritage in light of contemporary challenges. Methodologically, a literature review is conducted based on the analysis of a collection of plans dedicated to adapting to climate change and heritage preservation. The results reveal that current planning approaches remain fragmented and insufficient, reducing their practical impact. There is a notable absence of planning instruments specifically designed to integrate cultural heritage preservation with urban climate adaptation. In conclusion, although some initiatives are underway, significant gaps persist in the strategic planning framework, underscoring the urgent need for inclusive integrated and adaptive measures to safeguard the island’s urban heritage and community in the long term. Full article

The increasing frequency and magnitude of flood-related disasters has led to adopting advanced flood models to provide a better understanding of flood vulnerability, particularly for human lives. Human flood vulnerability assessment is a primary objective when planning and designing in urban areas. Results of a numerical model in the coastal hamlet of Solanas (Sardinia, IT), in terms of water velocity and depth, have been processed using the empirical method of the regional legislation (RAS), as suggested by the National Network for Environmental Protection. Vulnerability maps and statistical parameters were compared and benchmarked with the DEFRA method, which is largely used in the UK and is regarded as a state-of-the-art empirical approach. The main findings from the benchmark results between the DEFRA and RAS methods suggest that the applicability threshold of the RAS method can significantly underestimate the pedestrian vulnerability to urban flood in Solanas, and this paper suggests a preliminary step in improving that method could be a tentative threshold value of 0.10 m depth to assure a more realistic evaluation of human vulnerability in Solanas. Full article

In regional flood frequency analysis (RFFA), the formation of homogeneous regions is commonly regarded as a necessary condition for reliable regional flood estimation. However, achieving true homogeneity is often challenging in practice. This study investigates the formation of homogeneous regions by applying two region delineation approaches—fixed regions and the region-of-influence (ROI) method—accompanied by the widely used heterogeneity measure (H₁) proposed by Hosking and Wallis. The analysis utilizes data from 201 stream gauging stations across southeast Australia, evaluating a total of 1211 candidate regions. The computed H₁-statistics range from 13 to 30 for fixed regions and from 6 to 30 for ROI-based regions, indicating a consistently high level of heterogeneity across the study area. This suggests that the assumption of homogeneity may not be realistic for many parts of southeast Australia. Moreover, regression equations developed for regional flood estimation yield absolute median relative errors between 29% and 56%, with a median of 39% across return periods from 2 to 100 years. These findings underscore the limitations of relying solely on homogeneity in regional flood modelling and highlight the need for more flexible and robust approaches in RFFA. The outcomes of this research have significant implications for improving flood estimation practices and are expected to contribute to future enhancements of the Australian Rainfall and Runoff (ARR) national guidelines. 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

Utilities that operate nuclear power plants are increasingly using probabilistic risk assessments (PRAs) to make day-to-day decisions on design, operations, and maintenance and to support risk-informed applications. These applications require high-quality and complete PRAs to ensure that the decisions and proposed changes are technically well-founded. Such PRAs include the modeling and quantification of PRA models for accident sequences initiated by internal floods and high-energy line breaks. To support PRA updates and upgrades for such sequences, the Electric Power Research Institute (EPRI) has sponsored ongoing research to develop and refine guidance and generic data that can be used to estimate initiating event frequencies for internal flood- and high-energy line break-induced accident sequences. In 2023, EPRI published the fifth revision of a generic database for these initiating event frequencies. This revision produced advancements in the methodology for passive component reliability, including the quantification of aging effects on pipe rupture frequencies and the capability to adjust these frequencies to account for enhancements to integrity management strategies associated with leak inspections and non-destructive examinations. The purpose of this paper is to present these enhancements and illustrate their application with selected examples. 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

Urban historic districts play a vital role in shaping the cultural identity and heritage of cities. However, many of these areas face challenges such as aging buildings and deteriorating infrastructure. At the same time, the increasing frequency of extreme rainfall has led to a rise in flood events, placing these vulnerable districts at greater risk. Therefore, it is essential to carry out a comprehensive and objective assessment of their resilience to flood disasters. This study establishes a G-IC model for evaluating the resilience of urban historic districts to flood disasters based on the game combination empowerment-improved cloud model method. The proposed method has been demonstrated in the Soviet-style building complex of the Daye Steel Plant in Huangshi and reveals that the driving force layer exhibits weak resilience; the pressure and state layers show general resilience; the impact and response layers demonstrate weak resilience; and the overall resilience of the district is categorized as weak. The consistency of the results was verified by calculating the cloud similarity, which shows that the constructed new model has certain rationality and feasibility, and the evaluation results are relatively accurate. The findings offer valuable insights for policy-making and support for decision-makers in local government departments. Full article

The intensification of global climate change has led to an increased frequency of extreme rainfall and temperature events, posing severe threats to China’s ecosystems and socio-economic systems. This study, based on multi-year daily precipitation, monthly surface air temperature, and daily near-surface temperature datasets, employs multi-year averaging, EOF mode analysis, Mann–Kendall testing, and R/S analysis. By selecting heavy-rain days, rainfall amount, rainfall intensity, and drought indices, it explores the spatiotemporal evolution and driving mechanisms of extreme rainfall, drought, and compound events across China. The analysis of extreme rainfall reveals that precipitation in China shows a “more in the southeast, less in the northwest; abundant in the southeast, sparse in the northwest” pattern. EOF analysis identifies two spatial modes for rainfall parameters, the “Eastern Coordination Mode” and the “North–South Antiphase Mode,” corresponding to heavy rainfall days, rainfall amount, and rainfall intensity. The Mann–Kendall test shows that some regions in the eastern monsoon zone have experienced a significant increase in heavy rainfall parameters, while certain areas in the northeast, southern China, and northwest have also undergone significant changes. By contrast, parts of the southwest have seen a decrease. R/S analysis reveals that the Hurst index is high in the eastern monsoon region, indicating a strong likelihood of continued upward trends in the future, while regions in the western arid and semi-arid zones and parts of the Tibetan Plateau exhibit stronger randomness in trends, leading to more alternating drought and flood events. The analysis of the drought index (SPI-3) reveals synchronized drought patterns in the central-eastern and northern regions, with “synergistic consistency,” “Northwest–Northeast Antiphase,” and “Northern–Central-South Antiphase” characteristics. The Mann–Kendall test indicates a “north-wet, south-dry” differentiation, with significant wetting in the northern regions and parts of the Tibetan Plateau, and significant drying in the central-eastern and southwestern regions. R/S analysis shows high Hurst indices across most of the northwest and northern regions, indicating stronger drought persistence, while coastal areas in the east are more prone to dry–wet transitions. In terms of compound events, high-temperature and heavy rainfall events have increased from northwest to southeast over the past 40 years, with southern China experiencing more than 200 days of such events. Significant changes have been observed in the eastern and southern coastal regions, with high Hurst indices and strong persistence in the eastern coastal areas. Low-temperature and heavy rainfall events are more frequent in the eastern coast and southwestern regions, with higher Hurst indices in the eastern and central regions, indicating strong persistence. Full article