Search Results (2,826)

This study presents the results of a survey on flood risk awareness conducted in the Italian Alps, examining the impacts of a major weather event on public perception and trust. It develops a systems-thinking framework to analyse dynamic feedback loops influencing flood risk management support over time. The survey data collection overlapped with a severe storm event in Central Europe, the storm “Adrian” (also known as “Vaia”). This provided a unique pre- and post-event perspective. Results highlight the critical role of individual knowledge, trust in authorities, and social group dynamics in shaping risk perception processes. The study shows how major weather events can change perceptions, sense of safety, and institutional trust within local communities, and more interestingly, these changes can vary spatially. The findings are summarised using a systems-thinking framework, which helps to identify possible feedback loops between flood risk management interventions and long-term public support. The study emphasizes the importance of forward-looking, systems-thinking approaches in the design, monitoring, and evaluation of flood risk management plans. These approaches allow one to account for often-overlooked dynamics, such as spatially varying feedback loops and counter-intuitive effects, ultimately improving the long-term effectiveness of flood risk management. Full article

This study focuses on the analysis of sediment core retrieved from the deepest part (25 m) of Pirovac Bay. A long sedimentary sequence (7.45 m) supplemented by a shorter sediment core (1.45 m) from a shallower part of the bay was analyzed for sedimentological, mineralogical, geochemical, and micropaleontological (ostracod) parameters. The sediment thickness above the underlying karst paleorelief (karstic bedrock) is up to 12 m. Sediments recorded a transition from a freshwater to a marine environment starting from post-Neapolitan Yellow Tuff tephra sedimentation. First, the floodplain developed in Pirovac Bay, with intermittent pools and ponds, followed by wetland environment. The formation of a shallow freshwater paleolake during the Middle Holocene at 10 cal kyr BP was enabled by the rising sea level and high freshwater input from the karstified underground from the adjacent Lake Vrana (Biograd na Moru). The onset of marine intrusions through the karstified underground is evident with formation of a brackish lake in the Pirovac Bay basin. Marine transgression and flooding of the bay occurred at 7.3 cal kyr BP, evidenced by the geochemical and ostracod parameters, providing crucial insights into the dynamics of coastal inundation under past climate change. Intriguingly, freshwater ostracod species were still present in the marine sediments, brought into the bay from Lake Vrana through surficial canal Prosika and groundwater discharge (numerous estavelles) along the northeastern shores of the bay, proving their mutual influence. This submerged Holocene freshwater paleolake, reported here for the first time, underlines the sensitivity of coastal karst systems to the rise in sea level and serves to stress how important understanding of these processes is for effective management in coastal zone and climate change adaptation strategies. The findings provided evidence supporting the existence of coastal marine basins as freshwater lakes prior to being flooded by seawater as a consequence of the Holocene post-glacial sea level rise. Full article

The INterpolated FLOod Surface (INFLOS) tool was developed to meet the operational needs of the Copernicus Emergency Management Service (CEMS) Rapid Mapping (RM) component, which delivers critical crisis information within hours during and after disasters. With increasing demand for accurate and real-time flood depth estimates, INFLOS provides a rapid, adaptable solution for estimating floodwater depth across diverse flood scenarios, using remotely sensed data and high-resolution Digital Terrain Models (DTMs). INFLOS calculates flood depth by interpolating water surface elevation from sample points along flooded area boundaries, derived from satellite imagery. This tool is capable of delivering flood depth estimates in a rapid mapping context, leveraging a multistep interpolation and filtering process for improved accuracy. Tested across fourteen regions in Europe and South America, INFLOS has been successfully integrated into CEMS RM operations. The tool’s computational optimisations further enhance efficiency, improving computation times by up to 15-fold, compared to similar techniques. Indeed, it is able to process areas of up to 6000 ha in a median time of 5.2 min, and up to 30 min at most. In conclusion, INFLOS is currently operational and consistently generates flood depth products quickly, supporting real-time emergency management and reinforcing the CEMS RM portfolio. Full article

The general unit hydrograph (GUH), recently established by Guo, represents the most advanced hydrograph model today, but how to implement it with hydrologic data is another story. In this work, an effective initial value-based method for estimating the parameters in the GUH model is proposed and applied to the analysis of flood processes. In contrast to the flood-rainfall united fitting method, which heavily depends on the flood records and has a broad range of parameter variations, which makes it practically intractable, the initial value-based method enables the calculation of model parameters directly from the measured rainstorm data and greatly enriches the discharge dataset so that more accurate prediction of flood processes becomes achievable. From the data collected from several watersheds, we find that smaller-shape parameters usually indicate a multi-peak flood process, and the rainfall patterns have a significant impact on flood peaks. These results provide a reliable approach for the prediction of floods in streams with scarce discharge data. Additionally, it is observed that the peak time lags have a notable increase from the southwest to the northeast of Zhejiang. Full article

With the increasing frequency of floods in recent decades, particularly in West Africa, many regions have faced unusual and recurrent flooding events. Communities in flood-prone areas experience heightened insecurity, loss of property, and, in some cases, serious injuries or fatalities. Consequently, flood risk assessment and mitigation have become essential. This comparative study between Niamey and Lokoja employs Geographic Information Systems (GIS) and the Analytical Hierarchy Process (AHP) to delineate flood susceptibility, vulnerability, and risk zones. The study utilized a comprehensive range of thematic layers, with weight percentages assigned to each parameter as follows: 29% for elevation, 24% for slope, 15% for the Topographic Wetness Index (TWI), 9% for drainage density, 9% for distance from rivers, 4% for both precipitation and the Normalized Difference Water Index (NDWI), and 2% each for the Normalized Difference Vegetation Index (NDVI) and soil type. To validate these weightings, a consistency ratio was calculated, ensuring it remained below 10%. The findings reveal that 32% of the Niamey study area is at risk of flooding, compared to approximately 15% in Lokoja. The results highlight a very high flood potential, particularly in areas near the Niger River, with this potential decreasing as elevation increases. Given the current prevalence of extreme weather events in West Africa, it is crucial to employ effective tools to mitigate their adverse impacts. This research will assist decision-makers in quantifying the spatial vulnerability of flood-prone areas and developing effective flood risk assessment and mitigation strategies in the region. Full article

Extreme rainfall analysis is essential for accurate flood hazard assessment. Traditional approaches, such as the use of annual maxima, may overlook seasonal variations and lead to underestimated precipitation extremes, compromising effective flood risk management strategies. This study applies a point process model to uninterrupted daily rainfall records (1901–2023) from the National Observatory of Athens meteorological station in Thiseion. This method analyzes both the frequency of exceedances above a given threshold and the values of those exceedances, incorporating seasonality into the modeling process. Preliminary analysis using annual maxima revealed no statistically significant trend but indicated clear monthly seasonality in precipitation extremes. By incorporating seasonality, the point process method yielded estimates up to 22% higher than those obtained using traditional annual maxima approaches, such as those employed in Greece’s National Flood Risk Management Plans. These findings highlight the need for a revision of current methodologies, which could significantly impact flood risk assessments and management strategies. Full article

Salem, Massachusetts, is one of the oldest cities in the United States (1629) and its coastal location on the Atlantic helped create one of the wealthiest cities in America during the late 18th century, but today its coastal location threatens many of its buildings due to sea level rise and increased storm activity. The House of the Seven Gables, a National Historic Landmark District, consists of five important historic buildings, the most famous being The Turner Ingersoll Mansion (1668), more commonly known as The House of the Seven Gables. Considered one of the most important houses in America, it is also one of the most threatened historic buildings due to its location on Salem’s harbor. The House of the Seven Gables conducted a two-year study funded by Massachusetts Coastal Zone Management to evaluate the risks posed by climate change. This process included the use of data from groundwater monitoring wells and a tidal gauge installed on-site, along with soil samples and a detailed survey base plan including topography and subsurface infrastructure. The project team then used the Massachusetts Coastal Flood Risk Model (MC-FRM) to assess climate change impacts on the site in 2030, 2050, and 2070, and then created a plan for adaptations that should be implemented before those risks materialize. Strategies for adapting to storm surges, increasing groundwater, and intense surface water runoff were evaluated for their effectiveness and appropriateness for the historic site. The conclusion of the study resulted in a five-phase plan ending in the managed retreat of the historic buildings to higher ground on the existing site. This article goes beyond other research that suggests coastal retreats by demonstrating how to quantitatively evaluate current and future coastal issues with predictive models and how to set viable dates for adaptive solutions and a managed retreat. Full article

This study examines the effectiveness of Generalised Additive Models (GAMs) and log-log linear models for estimating the parameters of the generalised extreme value (GEV) distribution, which are then used to estimate flood quantiles in ungauged catchments. This is known as the parameter regression technique (PRT). Using data from 88 gauged catchments in New South Wales, Australia, flood quantiles were estimated for various annual exceedance probabilities (AEPs) of 50%, 20%, 10%, 5%, 2%, and 1%, corresponding to return periods of 2, 5, 10, 20, 50, and 100 years, denoted by Q₂, Q₅, Q₁₀, Q₂₀, Q₅₀, and Q₁₀₀, respectively. These flood quantiles were then used as dependent variables, while several catchment characteristics served as independent variables in the regression. GAMs were employed to capture non-linearities in flood generation processes. This study evaluates different GAMs and log-log linear models, identifying the best ones based on significant predictors and various statistical metrics using a leave-one-out (LOO) validation approach. The results indicate that GAMs provide more accurate and reliable predictions of flood quantiles compared to the log-log linear models, demonstrating better performance in capturing observed values across different quantiles. The absolute median relative error percentage (REr%) ranges from 33% to 39% for the GAMs and from 36% to 45% for the log-log models. GAMs demonstrate better performance compared to the log-log linear models for quantiles Q₂, Q₅, Q₁₀, Q₂₀, and Q₅₀; however, their performances appear to be similar for Q₁₀₀. Full article

This comprehensive review examines chemical and nano-based methods for asphaltene inhibition in the oil industry, focusing on recent developments and challenges. Asphaltene precipitation and deposition remain significant challenges in oil production, affecting wellbore areas, equipment walls, and surface infrastructure. The review analyzes various chemical inhibition mechanisms and evaluation methods, highlighting the emergence of nanotechnology as a promising solution. Metal oxide nanoparticles, organic nanoparticles, and inorganic nonmetal nanoparticles are discussed as effective inhibitors, with particular attention to their performance in different operational conditions, including CO₂ flooding processes. The study reveals that nanoparticles’ effectiveness in asphaltene inhibition is attributed to their large specific surface area, strong adsorption capacity, and unique interaction mechanisms with asphaltene molecules. The review also emphasizes the importance of proper inhibitor selection and concentration optimization, as the effectiveness thereof varies with reservoir conditions and crude oil characteristics. Recent developments in functionalized nanoparticles and their applications in enhanced oil recovery are examined, providing insights into future directions for asphaltene management in the petroleum industry. Full article

Nuclear magnetic resonance (NMR) and high-pressure mercury injection (HPMI) have been widely used as common characterization methods of pore-throat. It is generally believed that there is a power function relationship between transverse relaxation time (T₂) and pore-throat radius (r), but the segmentation process of the pore-throat interval is subjective, which affects the conversion accuracy. In this paper, ordered clustering is used to improve the existing segmentation method of the pore-throat interval, eliminate the subjectivity in the segmentation process, and obtain a more accurate distribution curve of the pore-throat. For the three kinds of cores with ordinary-low permeability (K > 1 mD), ultra-low permeability (0.1 mD < K < 1 mD), and super-low permeability (K < 0.1 mD), the pore-throat distribution curves of the cores were obtained by using the improved T₂ conversion method. Then, the oil and gas two-phase displacement experiment was carried out to investigate the degree of recovery and cumulative gas–oil ratio changes during the displacement process. Finally, the converted T₂ spectrum was used to quantify the utilization of different pore sizes. The improved T₂ conversion method not only has better accuracy but also is not limited by the pore-throat distribution types (such as unimodal, bimodal, and multi-modal, etc.) and is suitable for any core with measured HPMI pore-throat distribution and an NMR T₂ spectrum. Combined with the results of core displacement and the degree of pore-throat utilization, it is found that the potential of miscible flooding to improve the recovery degree is in the order of ordinary-low permeability core (18–22%), ultra-low permeability core (25–29%), and super-low permeability core (8–12%). The utilization degree of immiscible flooding to the <10 nm pore-throat is low (up to 35%), while miscible flooding can effectively use the <3.7 nm pore-throat (up to 73%). The development effect of supercritical CO₂ flooding on K < 0.1 mD reservoirs is not good, the seepage resistance of CO₂ is large, the miscible flooding makes it difficult to improve the recovery degree, and the utilization effect of pore-throat is poor. Full article

Tidal marshes play a globally critical role in carbon and hydrologic cycles by sequestering carbon dioxide from the atmosphere and exporting dissolved organic carbon to connected estuaries. These ecosystems provide critical habitat to a variety of fauna and also reduce coastal flood impacts. Accurate characterization of tidal marsh inundation dynamics is crucial for understanding these processes and ecosystem services. In this study, we developed remote sensing-based inundation classifications over a range of tidal stages for marshes of the Mid-Atlantic and Gulf of Mexico regions of the United States. Inundation products were derived from C-band and L-band synthetic aperture radar (SAR) imagery using backscatter thresholding and temporal change detection approaches. Inundation products were validated with in situ water level observations and radiometric modeling. The Michigan Microwave Canopy Scattering (MIMICS) radiometric model was used to simulate radar backscatter response for tidal marshes across a range of vegetation parameterizations and simulated hydrologic states. Our findings demonstrate that inundation classifications based on L-band SAR—developed using backscatter thresholding applied to single-date imagery—were comparable in accuracy to the best performing C-band SAR inundation classifications that required change detection approaches applied to time-series imagery (90.0% vs. 88.8% accuracy, respectively). L-band SAR backscatter threshold inundation products were also compared to polarimetric decompositions from quad-polarimetric Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2) and L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) imagery. Polarimetric decomposition analysis showed a relative shift from volume and single-bounce scattering to double-bounce scattering in response to increasing tidal stage and associated increases in classified inundated area. MIMICS modeling similarly showed a relative shift to double-bounce scattering and a decrease in total backscatter in response to inundation. These findings have relevance to the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission, as threshold-based classifications of wetland inundation dynamics will be employed to verify that NISAR datasets satisfy associated mission science requirements to map wetland inundation with classification accuracies better than 80% at 1 hectare spatial scales. Full article

The reversible use of a volumetric machine as a compressor and expander shows potential for micro-scale compressed air energy storage systems because of lower investment costs and higher operational flexibility. This paper investigates experimentally the reversible use of a 3 kW oil-flooded twin-screw compressor as an expander for a micro-scale compressed air energy storage system to assess its operation while minimizing operating costs and the need for adjustments. As a result, the oil injection was only implemented in the compressor operation since the oil takes part in the compression process, while its use appears optional in expander operation. The results indicate that the compressor exhibited an efficiency in the range of 0.57–0.80 and required an input power from 1 kW up to 3 kW. These values decreased for the expander, whose efficiency was in the range of 0.24–0.38 and the delivered power between 300 and 1600 W. The experimental data allow assessing the operation of such machine in a hypothetical micro-scale compressed air energy storage. The calculation revealed that this machine may operate in this energy storage asset and deliver up to 90% of the power recovered in the charging process when the temperature of the stored air is 80 °C. Full article

In the process of reservoir water flooding development, the characteristics of underground seepage field have changed, resulting in increasingly complex oil–water distribution. The original understanding of reservoir physical property parameters based on the initial stage of development is insufficient to guide reservoir development efforts in the extra-high water cut stage. To deeply investigate the spatio-temporal evolution of heterogeneity in the internal seepage field of layered reservoirs during water flooding development, water–oil displacement experimental simulations were conducted based on layered, normally graded models. By combining CT scanning technology and two-phase seepage theory, the variation patterns of heterogeneity in the seepage field of medium-to-high permeability, normally graded reservoirs were analyzed. The results indicate that the effectiveness of water flooding development is doubly constrained by differences in oil–water seepage capacities and the heterogeneity of the seepage field. During the development process, both the reservoir’s flow capacity and the heterogeneity of the seepage field are in a state of continuous change. Influenced by the extra resistance brought about by multiphase flow, the reservoir’s flow capacity drops to 41.6% of the absolute permeability in the extra-high water cut stage. Based on differences in the variation amplitudes of oil–water-phase permeabilities, changes in the heterogeneity of the internal seepage field of the reservoir can be broadly divided into periods of drastic change and relative stability. During the drastic change stage, the fluctuation amplitude of the water-phase permeability variation coefficient is 114.5 times that of the relative stable phase, while the fluctuation amplitude of the oil-phase permeability variation coefficient is 5.2 times that of the stable stage. This study reveals the dynamic changes in reservoir seepage characteristics during the water injection process, providing guidance for water injection development in layered reservoirs. Full article

Accurate and near-real-time flood monitoring is crucial for effective post-disaster relief efforts. Although extensive research has been conducted on flood classification, efficiently and automatically processing multi-source imagery to generate reliable flood inundation maps remains challenging. In this study, a new automatic flood monitoring method, utilizing optical and Synthetic Aperture Radar (SAR) imagery, was developed based on the Google Earth Engine (GEE) cloud platform. The Normalized Difference Flood Vegetation Index (NDFVI) was innovatively combined with the Edge Otsu segmentation method, utilizing SAR imagery, to enhance the initial accuracy of flood area mapping. To more effectively distinguish flood areas from non-seasonal water bodies, such as lakes, rivers, and reservoirs, pre-flood Landsat-8 imagery was analyzed. Non-seasonal water bodies were classified using multi-index methods and water body probability distributions, thereby further enhancing the accuracy of flood mapping. The method was applied to the catastrophic floods in Poyang Lake, Jiangxi Province, in 2020, and East Dongting Lake, Hunan Province, China, in 2024. The results demonstrated classification accuracies of 92.6% and 97.2% for flood inundation mapping during the Poyang Lake and East Dongting Lake events, respectively. This method offers efficient and precise information support to decision-makers and emergency responders, thereby fully demonstrating its substantial potential for practical applications. Full article

Impoundment and increased flood duration are some of the most common stressors to declining forested wetlands in coastal Louisiana, USA. One type of restoration that has shown itself to be cost-effective is spoil bank gapping. This type of hydrologic restoration has occurred within the Lac des Allemands swamp of Barataria Basin. After 60 years of impoundment, the hydrogeomorphic processes in the study area were improved. The study area included eight paired 625 m² sites. Basal area growth over the 7-year period varied between 5.93% and 14.39%, with an average of 8.31%, or just over 1% wood growth per year. Post-restoration basal areas indicate that all our study areas are improving. Pooled together, the 2018–2023 years had significantly higher net production than the pre-project 2017 growing season. The distribution between leaf and wood production was remarkably similar within species types across years, with leaf production consistently exceeding wood production, particularly due to Taxodium distichum. Canopy cover has increased by 20 percent since project construction, and as a result, herbaceous cover tends to decrease over time. Full article