Search Results (11,340)

This paper explores the feasibility of floating urban development in Italy, given its extensive coastline and inland hydrographic network. The key drivers for floating urban development, as an adaptive approach in low-lying waterfront areas, include the increasing threats posed by rising sea levels and flooding and the shortage of land for urban expansion. However, as not all waterfront areas are suitable for floating urban development, a geographical analysis based on a thorough evaluation of multiple factors, including urban–economic parameters and climate-related variables, led to the identification of a specific area of the Lazio coast, the river Tiber Delta. A comprehensive urban mapping process provided a multifaceted geo-referenced information layer, including several climatic, urban, anthropic, and environmental parameters. Within the GIS environment, it is possible to extract and perform statistical analyses crucial for assessing the impact of flood and sea-level rise hazards, particularly regarding buildings and land cover. This process provides a robust framework for understanding the spatial dimensions of flood and sea-level rise impacts and supporting informed design-making. A research-by-design phase follows the simulation research and mapping process. Several design scenarios are developed aimed at regenerating this vulnerable area. These scenarios seek to transform its susceptibility to flooding into a resilient, adaptive, urban identity, offering climate-resilient housing solutions for a population currently residing in unauthorized, substandard housing within high flood-risk zones. This paper proposes a comprehensive analytical methodology for supporting the design process of floating urban development, given the highly determinant role of site-specificity in such a challenging and new urban development approach. Full article

Typhoon disasters not only trigger secondary disasters, such as rainstorms and flooding, but also bring many negative impacts on the normal operation of urban infrastructure and the safety of people’s lives and property. In order to effectively prevent the risks of typhoon disaster chain, this paper proposes a joint entity and relation extraction model based on RoBERTa-Adv-GPLinker. Then, relying on the ontology theory and methodology, we establish a knowledge graph of typhoon disaster chain. The results show that the joint extraction model based on RoBERTa-Adv-GPLinker outperforms other baseline models in all assessment indexes. Moreover, the constructed knowledge graph of typhoon disaster chain includes secondary disasters and derived disaster impacts. This can largely depict the evolution process of typhoon disaster secondary derivations. On this basis, a risk assessment model of typhoon disaster chain based on Bayesian network is established. Taking Fujian Province as an example, the risk associated with the typhoon disaster chain is assessed, verifying the effectiveness of the method. This study provides a scientific basis for enhancing government emergency response capabilities and achieving sustainable regional development. Full article

Ensuring the ecological water requirements (EWR) suitable for wetlands are upheld is essential for maintaining the stability and health of their ecosystems, a challenge faced by wetlands globally. However, previous studies on EWRs estimation lack a comprehensive consideration of wetlands and still suffer from the problem of rough time scales. Prior studies have predominantly concentrated on its core and buffer zones, neglecting a comprehensive analysis of the wetland’s entirety and failing to account for the seasonal variations in EWRs. To fill this gap, we proposed a novel framework for estimating EWRs wetland’s entirety to guide the development of dynamic water replenishment strategies. The grey prediction model was used to project the wetland area under different scenarios and designed water replenishment strategies. We then applied this framework in a key wetland conservation area in China, the Momoge Wetland, which is currently facing issues of areal shrinkage and functional degradation due to insufficient EWRs. Our findings indicate that the maximum, optimal, and minimum EWRs for the Momoge Wetland are 24.14 × 10⁸ m³, 16.65 × 10⁸ m³, and 10.88 × 10⁸ m³, respectively. The EWRs during the overwintering, breeding, and flood periods are estimated at 1.92 × 10⁸ m³, 5.39 × 10⁸ m³, and 8.73 × 10⁸ m³, respectively. Based on the predicted wetland areas under different climatic conditions, the necessary water replenishment volumes for the Momoge Wetland under scenarios of dry-dry-dry, dry-dry-normal, dry-normal-dry, and normal-normal-normal are calculated to be 0.70 × 10⁸ m³, 0.49 × 10⁸ m³, 0.68 × 10⁸ m³, and 0.36 × 10⁸ m³, respectively. In years characterized by drought, the current water replenishment projects are inadequate to meet the wetland’s water needs, highlighting the urgent need for the implementation of multi-source water replenishment techniques to enhance the effectiveness of these interventions. The results of this study provide insights for annual and seasonal water replenishment planning and multi-source water management of wetlands with similar problems as the Momoge Wetland. With these new insights, our novel framework not only advances knowledge on the accuracy of wetland ecological water requirement assessment but also provides a scalable solution for global wetland water resource management, helping to improve the ecosystem’s adaptability to future climate changes. Full article

This study focused on three drought-tolerant grasses, namely Miscanthus sinensis ‘Gracillimus’ (Mis), Pennisetum alopecuroides ‘Ziguang’ (Pen), and Elytrigia repens (L.) Nevski ‘Jingcao No. 2′ (Ely), selected from nine species. Despite limited knowledge regarding their tolerance to submergence and responses to this stress, these three grasses were chosen for investigation. The three grass species were exposed to varying durations of submergence (0, 1, 3, 5, 7, 9, and 11 days) in a greenhouse setting. Subsequently, their growth characteristics, physiological traits, and nitrogen accumulation were evaluated. The study found that all three grass species exhibited flood tolerance, with Mis showing the strongest resistance. Under an 11-day flooding treatment, there was no significant trend in the above-ground biomass of Mis. Flooding significantly reduced the root-to-stem ratio, with Pen and Ely exhibiting more pronounced declines than Mis. The chlorophyll content in Mis decreased by 38%, compared to 41% in Pen and 60% in Ely. The root activity of the most affected species dropped by 88.6%, and nitrogen accumulation was inhibited with longer flooding durations. Pen’s nitrogen levels decreased significantly across treatments, while no significant changes were observed in Mis. Ely’s nitrogen assimilation initially increased until T4, after which it began to decline, reflecting similar trends in above-ground biomass. These findings suggest that flood tolerance is linked to nutrient uptake and photosynthetic capacity, highlighting Mis as the most suitable grass species for flood-prone areas and recommending its use in ecological ditch construction in China. This study provides material selection for the construction of ecological ditches. Full article

As cities have expanded into floodplains, the need for their protection has become crucial, prompting the evolution of flood studies. Here, we describe the operational tools, methods and processes used in flood risk engineering studies in the 1970s, and we evaluate the technological progress up to the present day. To this aim, we reference relevant regulations and legislation and the recorded experiences of engineers who performed hydrological, surveying and hydraulic studies in the 1970s. These are compared with the operational framework of a contemporary flood risk assessment study conducted in the Pikrodafni basin in the Attica region. We conclude that, without the technologically advanced tools available today, achieving the level of detail and accuracy in flood mapping that is now possible would have been unfeasible, even with significant human resources. However, ongoing urban development and growth continue to encroach upon flood plains that have existed for centuries, contributing to increased flood risk. Full article

The Qinghai–Tibet Plateau (QTP) serves as the origin for several major rivers in Asia and acts as a crucial ecological barrier in China, characterized by its regional conservation significance. Production activities in the industrial park in this special geographical environment may exacerbate its environmental vulnerability. We examined the spatial and temporal patterns of water quality parameters, identified the factors influencing water quality, and evaluated the associated risks using various analytical methods, including the Boruta algorithm and interval fuzzy number-based set-pair analysis (IFN-SPA). The results showed that the average concentrations in the flood season and dry season were significantly different. The average value of Cd in the flood season belonged to the water quality standard of Class II. Different heavy metals show different spatial distribution characteristics, and the reason for the difference comes from livestock farms and industrial enterprises. The results for the flood season and dry season were different, which further proves that meteorological factors can influence water quality. The risk of heavy metals in different rivers presents different spatial distribution characteristics; for example, the risk of heavy metals in the Sigou River is higher. The water quality assessment results indicate the need to develop a well-structured evaluation framework for managing and controlling river water pollution in the future. Full article

Inlets through coastal barriers in functionally non-tidal settings have been relatively understudied. Yet, they have morphosedimentary elements and morphodynamic behaviors that are similar to their tidal counterparts, especially microtidal (often wave-dominated) inlets. Increasingly, remote sensing technologies (aerial and satellite imagery, small unmanned aerial vehicles, etc.) are employed as sources of high-definition spatial databases. Such approaches are important in areas with limited access, especially in regions of military conflict, such as along parts of the northern Black Sea coast, Ukraine. For rapid spatial analysis of remotely sensed or archival datasets, image color intensity (ICI) patterns are obtained using grayscale (GS) spectra and a wide range of filter options. Areal and profile-style GS patterns based on relative ICI values are extracted from available imagery, so that in a full 256-value GS spectrum the deepest parts of a channel (inlet throat) will have the lowest (darkest) values (GS < 50). Landward (flood-tidal/bayside) and seaward (ebb-tidal/seaside) deltas will exhibit lighter colors (GS > 100). Exposed siliciclastic/carbonate sand-dominated barriers and shoals will yield the lightest values (GS > 200), with dark vegetation requiring GS inversion. Hypsometric information, as well as key metrics (perimeter and area) can be easily computed using instant tracing tools, without the need for labor-intensive contour outlining. This study is the first example of assessing cross-shore and longitudinal channel morphology of microtidal (USA) and non-tidal (Ukraine) inlets. The approach is also extended to a temporal analysis of inlet closure and a recent re-activation by an intense storm. Full article

In this research, a numerical model for simulating dam break floods was developed utilizing ArcGIS 10.8, 3ds Max 2021, and Flow-3D v11.2 software, with the aim of accurately representing the dam break disaster at Tianchi Lake in Changbai Mountain. The study involved the construction of a Triangulated Irregular Network (TIN) terrain surface and the application of 3ds Max 2021 to enhance the precision of the three-dimensional terrain data, thereby optimizing the depiction of the region’s topography. The finite volume method, along with multi-block grid technology, was employed to model the dam break scenario at Tianchi Lake. To evaluate the severity of the dam break disaster, the research integrated land use classifications within the study area with the simulated flood depths resulting from the dam break, applying the natural breaks method for hazard level classification. The findings indicated that the computational fluid dynamics (CFD) numerical model developed in this study significantly enhanced both the efficiency and accuracy of the simulations. Furthermore, the disaster assessment methodology that incorporated land use types facilitated the generation of inundation maps and disaster zoning maps across two scenarios, thereby effectively assessing the impacts of the disaster under varying conditions. Full article

Recent advancements in Earth Observation sensors, improved accessibility to imagery and the development of corresponding processing tools have significantly empowered researchers to extract insights from Multisource Remote Sensing. This study aims to use these technologies for mapping summer and winter Land Use/Land Cover features in Cuenca de la Laguna Merín, Uruguay, while comparing the performance of Random Forests, Support Vector Machines, and Gradient-Boosting Tree classifiers. The materials include Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission imagery, Google Earth Engine, training and validation datasets and quoted classifiers. The methods involve creating a multisource database, conducting feature importance analysis, developing models, supervised classification and performing accuracy assessments. Results indicate a low significance of microwave inputs relative to optical features. Short-wave infrared bands and transformations such as the Normalised Vegetation Index, Land Surface Water Index and Enhanced Vegetation Index demonstrate the highest importance. Accuracy assessments indicate that performance in mapping various classes is optimal, particularly for rice paddies, which play a vital role in the country’s economy and highlight significant environmental concerns. However, challenges persist in reducing confusion between classes, particularly regarding natural vegetation features versus seasonally flooded vegetation, as well as post-agricultural fields/bare land and herbaceous areas. Random Forests and Gradient-Boosting Trees exhibited superior performance compared to Support Vector Machines. Future research should explore approaches such as Deep Learning and pixel-based and object-based classification integration to address the identified challenges. These initiatives should consider various data combinations, including additional indices and texture metrics derived from the Grey-Level Co-Occurrence Matrix. Full article

The productivity prediction of weakly volatile fractured reservoirs is influenced by reservoir parameters and fluid characteristics. To address the computational challenges posed by complex fractures, an equivalent fracture element method is proposed to calculate equivalent permeability in fractured zones. A three-phase seepage model based on material balance is developed, using the Baker linear model to determine the relative permeabilities of oil, gas, and water while accounting for bound water saturation. Dynamic drainage distance and conductivity coefficients are introduced to calculate production at each stage, with the semi-analytical model solved iteratively for pressure and saturation. Validation against commercial simulation software confirms the model’s accuracy, enabling the construction of productivity curves and analysis of reservoir characteristics and injection scenarios. Results showed that the equivalent fracture element method effectively handled multiphase nonlinear seepage and predicted productivity during water flooding. Productivity was more sensitive to through-fracture models, with production increasing as the fracture extent expanded. Optimal water injection occurred when the formation pressure dropped to 80% of the bubble point pressure, and the recovery efficiency improved with periodic-injection strategies compared to conventional methods. These findings have significant implications for improving oil recovery, optimizing injection strategies, and advancing the design of efficient reservoir management techniques across scientific, practical, and technological domains. Full article

In June 2023, following the breach of the Nova Kakhovka Dam during the Ukraine-Russia war, a comprehensive study was conducted along the Romanian Black Sea coast to assess water quality and mesozooplankton communities. Surface water analyses revealed significant gradients in nutrient levels and salinity, particularly from north to south, influenced by the influx of freshwater and nutrients from riverine sources and the dam breach. Flooding was found to significantly impact nutrient dynamics and species distributions, with increased concentrations of SiO₄ and NO₃ in flooded stations. A strong relationship was observed between environmental factors and biological assemblages, with silicates identified as a key driver. Biodiversity patterns varied across regions, with the Shannon–Wiener Index indicating lower zooplankton diversity in transitional waters, reflecting environmental stress. Statistical methods, including correlation analysis, multidimensional scaling, t-tests, and canonical analysis, were employed to investigate the links between mesozooplankton communities and environmental variables. These findings underscore disruptions in trophic dynamics and ecosystem balance, emphasizing the need for integrated environmental management strategies to mitigate further degradation and foster the ecological recovery of the Black Sea. Full article

The coast is the most dynamic part of the Earth’s surface due to its strategic position at the interface of the land and the sea. It is, therefore, exposed to hazards and specific risks because of the geography as well as the geological and environmental characteristics of different countries. The coastal environment is essentially dynamic and evolving in time and space, marked by waves, tides, and seasons; moreover, it is subjected to many marine and continental processes (forcing). This succession of events significantly influences the frequency and severity of coastal hazards. The present paper aims at describing and characterizing the hazards and vulnerabilities on the Cameroonian coast. Cameroon possesses 400 km of coastline, which is exposed to various hazards. It is important to determine the probabilities of these hazards, the associated effects, and the related vulnerabilities. In this study, in this stable intraplate setting, the methodology used was diverse and combined techniques for the study of the shore and methods for the treatment of climatic data. Also, historical data were collected during field observations and from the CRED website for all the natural hazards recorded in Cameroon. In addition, documents on climate change were consulted. Remotely sensed data, combined with GIS tools, helped to determine and assess the associated risks. A critical grid combining a severity and frequency analysis was used to better understand these hazards and the coastal vulnerabilities of Cameroon. The results show that Cameroon’s coastal margins are subject to natural processes that cause shoreline changes, including inundation, erosion, and accretion. This study identified seven primary hazard types (earthquakes, volcanism, landslides, floods, erosion, sea level rise, and black tides) affecting the Cameroonian coastline, with the erosion rate exceeding 1.15 m/year at Cape Cameroon. Coastal populations are continuously threatened by these natural or man-induced hazards, and they are periodically subjected to catastrophic disasters such as floods and landslides, as experienced in Cameroon. In addition, despite the existence of the National Contingency Plan devised by the Directorate of Civil Protection, National Risk, and Climate Change Observatories, the implementation of disaster risk reduction and mitigation strategies is suboptimal. Full article

Climate change-induced alterations in monsoon patterns have exacerbated flooding challenges in Balochistan, Iran. This study addresses the urgent need for improved flood prediction methodologies in data-scarce arid regions by integrating the Muskingum–Cunge model with advanced optimization techniques. Particle swarm optimization (PSO) and harmony search (HS) algorithms were applied and compared across eight major rivers in Balochistan, each with distinct hydrological characteristics. A comprehensive multi-metric evaluation framework was developed to assess the performance of these algorithms. The results demonstrate PSO’s superior performance, particularly in complex terrain conditions. For instance, at the Kajou station, PSO improved the Coefficient of Residual Mass (CRM) by 0.01, efficiency (EF) by 0.92, Agreement Index (d) by 0.98, and Normalized Root Mean Square Error (NRMSE) by 0.10 compared to HS. Correlation coefficients ranging from 0.6558 to 0.9645 validate the methodology’s effectiveness in data-scarce environments. This research provides valuable insights into algorithm performance under limited data conditions and offers region-specific parameter optimization guidelines for similar geographical contexts. By advancing flood routing science and providing a validated framework for optimization algorithm selection, this study contributes to improved flood management in regions vulnerable to climate change. Full article

An urban rain flood park refers to a park built with ecological function as the guide. The aim of this study is to examine the social benefits of urban stormwater landscapes. By establishing an evaluation model, conducting field research and analysis, comparing parks, and applying mathematical model analysis, the feedback from various user groups is assessed. The purpose is to explore whether ecologically oriented urban stormwater parks offer superior social benefits and to provide references for optimizing the benefits of urban stormwater park design. The paper selects Yanweizhou Park, Zhejiang Jinhua, a representative of innovative design practices in an urban rainwater park in China, as a case study for evaluation research and introduces the traditional park, Wuzhou Park, for comparison. The results show that Yanweizhou Park, which is designed based on ecology as the first principle, is still highly evaluated in terms of social performance. People think that ecological parks are more representative of the urban image. The eco-park is more popular with young people and more dispersed in activities. Both types of parks suffer from insufficient infrastructure construction. Full article

Shale oil, a critical unconventional energy resource, has received substantial attention in recent years. However, systematic research on developing shale oil using mixed gases remains limited, and the effects of various gas compositions on crude oil and rock properties, along with their potential for enhanced oil recovery, are not yet fully understood. This study utilizes PVT analysis, SEM, and core flooding tests with various gas mixtures to elucidate the interaction mechanisms among crude oil, gas, and rock, as well as the recovery efficiency of different gas types. The results indicate that increasing the mole fraction of CH₄ substantially raises the oil saturation pressure, up to 1.5 times its initial value. Pure CO₂, by contrast, exhibits the lowest saturation pressure, rendering it suitable for long-term pressurization strategies. CO₂ shows exceptional efficacy in reducing interfacial tension, though the viscosity reduction effects of different gases exhibit minimal variation. Furthermore, CO₂ markedly modifies the pore structure of shale through dissolution, increasing porosity by 2% and enhancing permeability by 61.63%. In both matrix and fractured cores, the recovery rates achieved with mixed gases were 36.9% and 58.6%, respectively, demonstrating improved production compared to single-component gases. This research offers a theoretical foundation and novel insights into shale oil development. Full article