Search Results (261)

Coastal areas are strategically significant from an ecological, anthropic, and economic point of view, but they are also susceptible to forces causing inundations. Multiple forcings occurring in close succession in space and time amplify the effects of a single force and form a compound event. An example is an atmospheric disturbance that extends from the sea to the mainland, causing a sea storm and a river flood due to heavy rainfall. This condition can occur in geomorphological contexts where the sea and mountains are close to each other, and the river basins are small. Most research on compound events focuses on extreme events; detailed studies of compound events not associated with extreme events and generated by non-exceptional atmospheric disturbances are scarce. Furthermore, there are very few detailed studies focusing solely on compound river floods and sea storms. Consequently, this paper is focused on compound river floods and sea storms generated by atmospheric disturbances regardless of their exceptional or non-typical typology. This analysis includes their forcings, correlation, and effects and is carried out in Calabria, a region of Southern Italy that represents an interesting case study due to its geomorphological, climatic, and hydrological peculiarities, which favor the formation of compound events, and, due to the considerable anthropization of its coastal territories, increases their risk. The main findings concern confirming that the existence of this compound event between river floods and sea storms is generated by the same atmospheric disturbance, the geomorphological conditions under which it occurs, and the main driving forces behind it. Therefore, this study is only the first step in a more in-depth analysis that will also examine the quantitative aspects of these phenomena. This analysis is essential for the planning and management of coastal areas subject to compound events and for ensuring effective mitigation measures. Full article

With global climate changing, numerous cities have a rise in the frequency of heavy rainfall events. Concurrently, the rapid urbanization is increasing the impermeable surfaces, heightening the vulnerability to cope with flooding of urban stormwater drainage systems. This work compared the different retention strategies to mitigate flooding risks by simulating various scenarios using StormDesk 2.0. Additionally, it conducts multi-objective optimization of retention volume reduction, overflow volume reduction, and cost constraints through NSGA-II to obtain adaptation schemes across diverse scenarios. The findings demonstrate that, compared with the maximum area and overflow reduction ratio schemes, the drainage capacity can increase 15% under the adaptation scheme. Furthermore, the investment of the adaptation scheme is the most economical, at 10.59% of the maximum area scheme, and the overflow reduction surpasses that of the maximum area scheme by 45.8%. The most economical unit control cost in the adaptation scheme was USD 64.2/m³, while the full cost reached USD 277,337.9, highlighting its superior cost-benefit. The above results can provide a paradigmatic reference for enhancing stormwater drainage capacity in urban built-up areas. Full article

Short-duration extreme rainfall is a major trigger of flash floods and urban inundation, yet its quantification remains a profound challenge due to the scarcity of high-resolution observations. This review synthesizes how three central paradigms of nonlinear science, multifractal cascade theory, self-organized criticality (SOC) and chaos theory, provide critical insights and practical methodologies for bridging this observational gap. We examine how multifractal temporal downscaling leverages scale-invariance to derive sub-hourly rainfall statistics from coarser data. The SOC paradigm is discussed for its ability to explain the power-law statistics of rainfall extremes and cluster properties, offering a physical basis for estimating rare events. The role of chaos theory and its modern evolution into complex network analysis is explored for diagnosing predictability and spatiotemporal organization. By comparing and integrating these perspectives plus recent developments in stochastic hydrology, this review highlights their collective potential to advance the estimation, understanding, and prediction of short-duration extreme rainfall, ultimately informing improved risk assessment and climate resilience strategies. Full article

Coastal erosion and increasingly severe storms present a growing challenge to the sustainable management of sandy shorelines. This study examines the geomorphological, sedimentological and geochemical responses of the Palanga coastal area in the Lithuanian Baltic Sea to beach nourishment projects implemented between 2006 and 2012. A multi-parameter approach was used, combining cross-shore profile monitoring with grain-size, magnetic susceptibility, mineralogical and geochemical analyses, in order to assess sediment redistribution and post-nourishment adjustments. The results demonstrate that nourishment projects substantially increased beach width, height and sand volume; however, the shoreline response was uneven in space and time. Subsequent years were characterised by gradual sediment redistribution along and across the coast, resulting in partial morphological stabilisation. Elevated concentrations of heavy minerals and trace elements immediately after nourishment indicated short-term enrichment from mineralogically distinct material, which was later diluted by natural reworking. The findings demonstrate that properly designed and monitored nourishment enhances coastal resilience, representing a human-induced adjustment within the prevailing coastal morphodynamic regime. While the socio-ecological effects were not directly evaluated, the identified geoindicators offer insights into the physical sustainability of coastal systems, emphasising the importance of evidence-based, adaptive management in line with the United Nations Sustainable Development Goals (SDGs 11, 13 and 14). Full article

This study conducts a diagnostic analysis of an extremely heavy rainfall event and its causative factors that occurred in Libya, North Africa on 10 September 2023. The Weather Research and Forecasting (WRF) model was also employed to perform some sensitivity experiments for this heavy rainfall event and further reveal its causes. Results indicate that the primary synoptic system responsible for this extreme precipitation event was an extratropical cyclone (storm) named “Daniel”. During the formation and development of this cyclone, the circulation at the 500 hPa level from the eastern Atlantic to western Asia exhibited a stable “two troughs and one ridge” pattern, with a upper-level cold vortex over the eastern Atlantic, a high-pressure ridge over central Europe, and a cut-off low over western Asia, collectively facilitating the formation and development of this cyclone. As this cyclone moved southward, it absorbed substantial energy from the Mediterranean Sea; following landfall, the intrusion of weak cold air enabled the cyclone to continue intensifying. Meanwhile, the northwest low-level jet stream to the west of the extratropical cyclone moved alongside the cyclone to the coastal regions of northeastern Libya, where it converged with water vapor transport belts originating from the Ionian Sea, the Aegean Sea, and the coastal waters of northeastern Libya. This convergence provided abundant water vapor for the rainstorm event, and under the combined effects of convergence and orographic lifting on the windward slopes of the coastal mountains, extreme precipitation was generated. In addition, the atmosphere over the coastal regions of northeastern Libya exhibited strong stratification instability, which was conducive to the occurrence of extreme heavy precipitation. Although WRF successfully reproduced the precipitation process, the precipitation amount was underestimated. Sensitivity experiments revealed that both the topography in the precipitation area and the sea surface temperature (SST) of the Mediterranean Sea contributed to this extreme heavy precipitation event. Full article

The sediment yield resulting from storm erosion has become a focal point of research and a significant area of interest in the upper reaches of the Yangtze River amid changing environmental conditions. The issue of numerous types of erosivity factors (R) in storm erosion sediment yield models, with unclear applicability. This study examines two classical types of erosivity factors: the rainfall erosivity factor (EI₃₀, Zhang Wenbo empirical formula, etc.) and runoff erosivity power. Four combinatorial forms of erosion dynamic factors, encompassing rainfall and runoff elements, were developed. Based on the rainfall, runoff and sediment data of four stations along the Fu River basin–Pingwu station, Jiangyou station, Shehong station and Xiaoheba station from 2008 to 2018, the correlation between different R factors and sediment transport in different watershed areas was studied, and the semi-monthly sediment transport model of heavy rainfall in the Fu River basin was constructed and verified. The results revealed a weak correlation between the rainfall erosivity factor and the sediment transport modulus, making it unsuitable for developing a sediment transport model. In smaller basin areas, the correlation between the combined erosivity factor and sediment transport modulus was strongest; conversely, in larger basins, the relationship between runoff erosivity power and the sediment transport model was most pronounced. The power function relationship between the erosivity factor and sediment transport modulus yielded a more accurate simulation of sediment transport during the verification period, particularly during rainstorms, surpassing that of SWAT. These findings provide a scientific basis for predicting sediment transport during storms and floods in small mountainous basins. Full article

Surface subsidence induced by underground mining in mining areas significantly alters surface topography and hydrogeological conditions, forming depressions and fissures, thereby affecting regional runoff-ponding processes and groundwater infiltration patterns. Accurate assessment of infiltration volumes in subsidence zones under heavy rainfall is crucial for designing underground drainage systems and evaluating water-inrush risks in open-pit to underground transition mines. Taking the surface subsidence area of the Dahongshan Iron Mine as a case study, this paper proposes a rainfall infiltration calculation method based on the precise delineation of surface ponding-infiltration zones. By numerically simulating the subsidence range, the study divides the area into two distinct infiltration characteristic zones under different mining states: the caved zone and the water-conducting fracture zone. The rainfall infiltration volume under storm conditions was calculated separately for each zone. The results indicate that high-intensity mining-induced subsidence leads to a nonlinear surge in stormwater infiltration, primarily due to the significant expansion of the highly permeable caved zone. The core mechanism lies in the area expansion of the caved zone as a rapid infiltration channel, which dominates the overall infiltration capacity multiplication. These findings provide a scientific basis for the design of mine drainage systems and the prevention of water-inrush disasters. Full article

Typhoon Yagi (2024) was a rapidly moving storm that lasted for eight days and made landfall in three locations, producing heavy rainfall over Hainan and Vietnam. This study aims to investigate the dynamical processes contributing to the heavy rainfall, concentrating on enthalpy flux (EF) and moisture flux (MF). The results indicate that both EF and MF increased significantly during the typhoon’s intensification stage and were high at the time of landfall. Before landfalling at Hainan, latent heat flux (LHF) reached 600 W/m², while sensible heat flux (SHF) was recorded as 80 W/m². Landfall at Hainan resulted in a decrease in LHF and SHF. LHF and SHF subsequently increased to 700 W/m² and 100 W/m², respectively, as noted prior to the landfall in Vietnam. The increased LHF led to higher evaporation, which subsequently elevated moisture flux (MF) following the landfall in Vietnam, while the region’s topography further intensified the rainfall. The mean daily rainfall observed over Philippines is 75 mm on 2 September (landfall and passing through), 100 mm over Hainan (landfall and passing through) on 6 September, and 95 mm at over Vietnam on 7 September (landfall and after), respectively. Heavy rainfall was observed over the land while the typhoon was passing and during the landfall. This research reveals that Typhoon Yagi’s intensity was maintained by a well-organized and extensive circulation system, supported by favorable weather conditions, including high sea surface temperatures (SST) exceeding 30.5 °C, substantial low-level moisture convergence, and elevated EF during the landfall in Vietnam. Full article

High-resolution numerical weather prediction requires accurate cloud microphysical initial conditions to enhance forecasting capabilities for high-impact severe weather events such as convective storms. This study integrated Fengyun-2 (FY-2) geostationary satellite data (equivalent blackbody temperature and total cloud cover) and next-generation 3D weather radar reflectivity from the China Meteorological Administration (CMA) to construct cloud microphysical initial fields and evaluate their impact on the CMA-MESO 3 km regional model. An analysis of the catastrophic rainfall event in Henan on 20 July 2021, and a 92-day continuous experiment (May–July 2024) revealed that assimilating cloud microphysical variables significantly improved precipitation forecasting: the equitable threat scores (ETSs) for 1 h forecasts of light, moderate, and heavy rain increased from 0.083, 0.043, and 0.007 to 0.41, 0.36, and 0.217, respectively, with average hourly ETS improvements of 21–71% for 2–6 h forecasts and increases in ETSs for light, moderate, and heavy rain of 7.5%, 9.8%, and 24.9% at 7–12 h, with limited improvement beyond 12 h. Furthermore, the root mean square error (RMSE) of the 2 m temperature forecasts decreased across all 1–72 h lead times, with a 4.2% reduction during the 1–9 h period, while the geopotential height RMSE reductions reached 5.8%, 3.3%, and 2.0% at 24, 48, and 72 h, respectively. Additionally, synchronized enhancements were observed in 10 m wind prediction accuracy. These findings underscore the critical role of cloud microphysical initialization in advancing mesoscale numerical weather prediction systems. Full article

Clean and safe air quality is essential for public health, yet particulate matter (PM) significantly degrades air quality and poses serious health risks. The Gulf Cooperation Council (GCC) countries are particularly vulnerable to frequent and intense dust storms due to their vast desert landscapes. This study presents the first health risk assessment of carcinogenic and non-carcinogenic risks associated with exposure to PM2.5 and PM10 bound heavy metals and polycyclic aromatic hydrocarbons (PAHs) based on air quality data collected during the years of 2016–2018 near Dubai International Airport and Abu Dhabi International Airport. The results reveal no significant carcinogenic risks for lead (Pb), cobalt (Co), nickel (Ni), and chromium (Cr). Additionally, AI-based regression analysis was applied to time-series dust monitoring data to enhance predictive capabilities in environmental monitoring systems. The estimated incremental lifetime cancer risk (ILCR) from PAH exposure exceeded the acceptable threshold (10⁻⁶) in several samples at both locations. The relationship between visibility and key environmental variables—PM1, PM2.5, PM10, total suspended particles (TSPs), wind speed, air pressure, and air temperature—was modeled using three machine learning algorithms: linear regression, support vector machine (SVM) with a radial basis function (RBF) kernel, and artificial neural networks (ANNs). Among these, SVM with an RBF kernel showed the highest accuracy in predicting visibility, effectively integrating meteorological data and particulate matter variables. These findings highlight the potential of machine learning models for environmental monitoring and the need for continued assessments of air quality and its health implications in the region. Full article

This study analyzes the evolution of hydrometeorological risks and severe weather events in Catalonia through an extensive review of 21,312 news reports aired by Televisió de Catalunya (TVC) between 1984 and 2019, 10,686 (50.1%) of which focused on events within Catalonia. The reports are categorized by the type of phenomenon, geographic location, and reported impact, enabling the identification of temporal trends. The results indicate a general increase in the frequency of news coverage of hydrometeorological and severe weather events—particularly floods and heavy rainfall—both in Catalonia and the broader Mediterranean region. This rise is attributed not only to a potential increase in such events, but also to the expansion and evolution of media coverage over time. In the Catalan context, the most frequently reported hazards are snowfalls and cold waves (3203 reports), followed by rainfall and flooding (3065), agrometeorological risks (2589), and wind or sea storms (1456). The study highlights that rainfall and flooding pose the most significant risks in Catalonia, as they account for the majority of the reports involving serious impacts—1273 cases of material damage and 150 involving fatalities. The normalized data reveal a growing proportion of reports on violent weather and floods, and a relative decline in snow-related events. Full article

In the Gulf of California, seabirds carry heavy loads to feed their chicks, making their takeoff capacity crucial for foraging. While some studies explore this, few consider the lift force, induced power, or aerobic vs. anaerobic performance. Moreover, the differences between individuals—such as size or sex—remain largely unexamined, leaving gaps in the understanding of seabird flight efficiency. In this work, the load capacity during takeoff of the Least Storm-Petrel (LSP) and the Black Storm-Petrel (BSP) in Isla Partida Norte, Gulf of California, was analyzed. Forty-nine individuals of the Least Storm-Petrel group and 23 of the Black Storm-Petrel group were evaluated. In both species, the carrying capacity was found to be independent of individual size, but the Least Storm-Petrel managed to take off with a higher proportion of its total mass than the Black Storm-Petrel. Although smaller, LSPs lift more than BSPs, and environmental factors like El Niño also influence seabird performance. This study found that both storm-petrel species were smaller and lighter than previously reported; yet, LSPs carried relatively heavier loads than BSPs. Although BSPs had higher absolute values for mass and lift, LSPs were more energy-efficient. The muscle mass proportions were similar and typical for takeoff. No significant sex-based differences were found. Both species used aerobic and anaerobic takeoff, with anaerobic flight likely being more efficient. Full article

Extreme precipitation events are one of the common hazards in eastern Texas, generating a large amount of storm water. Water running off urban areas may carry non-point source (NPS) pollution to natural resources such as rivers and lakes. Urbanization exacerbates this issue by increasing impervious surfaces that prevent natural infiltration. This study evaluated the efficacy of rain gardens, a nature-based best management practice (BMP), in mitigating NPS pollution from urban stormwater runoff. Stormwater samples were collected at inflow and outflow points of three rain gardens and analyzed for various water quality parameters, including pH, electrical conductivity, fluoride, chloride, nitrate, nitrite, phosphate, sulfate, salts, carbonates, bicarbonates, sodium, potassium, aluminum, boron, calcium, mercury, arsenic, copper iron lead magnesium, manganese and zinc. Removal efficiencies for nitrate, phosphate, and zinc exceeded 70%, while heavy metals such as lead achieved reductions up to 80%. However, certain parameters, such as calcium, magnesium and conductivity, showed increased outflow concentrations, attributed to substrate leaching. These increases resulted in a higher outflow pH. Overall, the pollutants were removed with an efficiency exceeding 50%. These findings demonstrate that rain gardens are an effective and sustainable solution for managing urban stormwater runoff and mitigating NPS pollution in eastern Texas, particularly in regions vulnerable to extreme precipitation events. Full article

Pavement deterioration is often the result of intense traffic and increased runoff from storms, floods, or other environmental factors. A practical solution to this challenge involves the use of permeable pavements, such as permeable interlocking concrete pavement (PICP), which are designed to effectively manage water runoff while supporting heavy traffic. This research investigates the effectiveness of PICP in two distinct surface patterns: stretcher bond and 45° herringbone, by assessing their performance in terms of water infiltration and runoff using two different methods. The first approach has been conducted experimentally using a laboratory apparatus designed to simulate rainfall. Various conditions were applied during the performance tests, including longitudinal (L-_Slope) and transverse (T-_Slope) slopes of (0, 2, and 4%) and rainfall intensities of (40 and 80 L/min). The second approach has been implemented theoretically using Surfer 2.0 software to simulate the distribution of infiltrated water underneath the layers of PICP. Moreover, the behavior of PICP has been analyzed statistically using artificial neural networks (ANNs). The results indicated that at a rainfall intensity of 40 L/min, equal infiltration was observed in both patterns on 0% and 4% T-_Slope. However, the 45° herringbone PICP showed better infiltration on the 8% T-_Slope. Additionally, at 80 L/min rainfall, equal infiltration was observed in both patterns on 0% L-_Slope for 0% and 4% T-_Slope. The 45° herringbone PICP also demonstrated higher water infiltration on the 8% T-_Slope, and this trend continued as the L-_Slope increased. PICP with a 45° herringbone surface pattern exhibited superiority in reducing runoff compared to the stretcher bond pattern. The statistical models for the stretcher bond and 45° herringbone patterns demonstrate high accuracy, as evidenced by their correlation coefficient (R²) values of 99.97% and 97.32%, respectively, which confirms their validity. Despite the variations between the two forms of PICP, both are strongly endorsed as excellent alternatives to conventional pavement. Full article

This study presents a multi-temporal analysis of vegetation cover changes in the Guayepo stream watershed (Cartagena de Indias, Colombia) for 2000, 2010, and 2020 and their impact on surface runoff generation. Hydrological data from 1974 to 2019 were processed to model intensity–duration–frequency (IDF) curves and simulate heavy rainfall events using six storms of nine-hour duration. Following the Soil Conservation Service guidelines, these were used to estimate runoff flows for return periods of 25, 50, and 100 years via the curve number method in HEC-HMS. Vegetation cover was assessed using the CORINE land cover methodology applied to official land use maps. The analysis revealed a significant loss of natural vegetation: dense forest cover declined dramatically from 14.38% in 2000 to 0% in 2020, and clean pastures were reduced by 46%. In contrast, weedy pastures and pasture mosaics with natural areas increased by 299% and 136%, respectively, reflecting a shift towards more degraded land cover types. As a result of these changes, total runoff flows of the model increased by 9.7% and 4.3% under antecedent moisture conditions I and II, respectively, for the 100-year return period. These findings reveal ongoing degradation of the watershed’s natural cover, linked to expanding agricultural uses and changes in vegetation structure. The decline in forested areas has increased surface runoff, elevating flood risk and compromising the watershed’s hydrological regulation. The study suggests that integrated land management and ecological restoration strategies could be key in preserving hydrological ecosystem services and reducing the negative impacts of land use change. Full article