Search Results (11,454)

Globally, the number of major floods has been consistently significant in recent years. By using several methods of acquiring and processing geospatial data, this study aimed to develop a digital terrain model that supports the modeling of sudden increases in water levels in a river to provide a true picture of the areas at risk. The main contribution of this research is provided by the method of performing coupled geospatial, hydrological, and hydraulic calculations within the area of interest. This approach includes an analysis of all the hydrotechnical works executed in the riverbed. The research highlights the characteristics of the water flow corresponding to the maximum flows with exceedance probabilities of 10%, 1%, 0.5%, and 0.1%, as well as those associated with maximum discharges resulting from scenarios involving the failure of the storage dam in the area. The research results indicate that the creation of a 3D model at the river basin is probably the most important step in flood risk management, as the results obtained at this stage can also influence other measures that can be applied. Full article

A global database of coastal flooding impacts resulting from extreme sea levels is developed for the present day and for the years 2050 and 2100. The database consists of three sub-datasets: the extreme sea levels, the coastal areas flooded by these extreme sea levels, and the resulting socioeconomic implications. The extreme sea levels consider the processes of storm surge, tide levels, breaking wave setup and relative sea level rise. The socioeconomic implications are expressed in terms of Expected Annual Population Affected (EAPA) and Expected Annual Damage (EAD), and presented at the global, regional and national scales. The EAPA and EAD are determined both for existing coastal defence levels and assuming two plausible adaptation scenarios, along with socioeconomic development narratives. All the sub-datasets can be visualized with a Digital Twin platform based on a GIS-based mapping host. This publicly available database provides a first-pass assessment, enabling users to extract and identify global and national coastal hotspots under different projections of sea level rise and socioeconomic developments. Full article

In recent years, there has been a notable increase in the frequency and intensity of floods and heavy rains, which has resulted in the frequent inundation of rice-growing areas. Flooding during the heading–flowering stages of early rice can result in significant yield losses. To elucidate the response of rice to sediment content, flooding, and drainage processes and their underlying mechanisms, a pot experiment was conducted to investigate the effects of sediment contents (S₁: 0, S₂: 0.10 kg m⁻³, and S₃: 0.25 kg m⁻³), flooding time (F₁: 3 days and F₂: 6 days), and drainage time (D₁: 3 days and D₂: 6 days) during the heading–flowering stage on the oxidation resistance and grain yield of early rice in the Poyang Lake Region. At the same time, an experimental control group (CK) was set up with no sediment, no flooding, or no drainage treatment. The results showed that the flag leaf area of S₁F₁D₂ treatment was diminished by flooding. The relative chlorophyll content (SPAD) reached its lowest value prior to drainage. The treatment of S₂F₂D₁ showed the greatest decrease in SPAD value of 41.57%, which was only 53.88% of that of the control treatment. The activity of superoxide dismutase (SOD), peroxidase (POD), and the content of malondialdehyde (MDA) were observed to increase during the flooding period in comparison to the control treatment. The maximum values for these parameters were recorded at 5.68, 3.09, and 1.9 times higher than those of the control treatment, respectively. However, a decrease was observed after drainage. Furthermore, the occurrence of flooding during the early rice heading–flowering stage resulted in a notable reduction in the grain number per spike and the fruiting rate, consequently leading to a considerable decline in grain yields, with a decrease ranging from 31.81% to 69.96%. The findings indicate that flooding during the heading–flowering stage resulted in a reduction in early rice grain yield yet enhanced the antioxidant capacity of the leaves. Regression analyses indicated that a prediction model for the actual yield after flooding stress at the heading–flowering stage of early rice could be constructed using SFW as the independent variable. The findings of this study provide a theoretical basis for the formulation of a scientific and reasonable drainage scheme with the objective of reducing yield loss following rice flooding in the southern rice-growing region of China. Full article

In landslide susceptibility modeling, research has predominantly focused on predicting landslides by identifying predisposing factors, often using inventories primarily based on the highest points of landslide crowns. However, a significant challenge arises when the transported mass impacts human activities directly, typically occurring in the deposition areas of these phenomena. Therefore, identifying the terrain characteristics that facilitate the transport and deposition of displaced material in affected areas is equally crucial. This study aimed to evaluate the predictive capability of identifying where displaced material might be deposited by using different inventories of specific parts of a landslide, including the source area, intermediate area, and deposition area. A sample segmentation was conducted that included inventories of these distinct parts of the landslide in the hydrographic basin of Lake Ilopango, which experienced debris flows and debris floods triggered by heavy rainfall from Hurricane Ida in November 2009. Given the extensive variables extracted for this evaluation (20 variables), the Induced Smoothed (IS) version of the Least Absolute Shrinkage and Selection Operator (LASSO) methodology was employed to determine the significance of each variable within the datasets. Additionally, the Multivariate Adaptive Regression Splines (MARS) algorithm was used for modeling. Our findings revealed that models developed using the deposition area dataset were more effective compared with those based on the source area dataset. Furthermore, the accuracy of models using deposition area data surpassed that of that using data from both the source and intermediate areas. Full article

In low-permeability sandstone reservoirs (LPSR), impermeable interlayers significantly challenge carbon capture, utilization, and storage (CCUS) and enhance oil recovery (CO₂-EOR) processes by creating complex, discontinuous flow units. This study aims to address these challenges through a comprehensive multi-faceted approach integrating geological and microscopic analyses, including core analysis, reservoir petrography, field emission-scanning electron microscopy (FE-SEM), energy dispersive spectroscopy (EDS), and well-logging response analysis, and utilizing three-dimensional (3D) geological modeling. The current comprehensive investigation systematically characterizes interlayer types, petrophysical properties, thickness, connectivity, and their spatial distribution in the reservoir unit. Numerical simulations were conducted to assess the sealing efficiency and the impact of various interlayer materials on CO₂ flooding over a 10-year period. Results indicate the presence of petrophysical and argillaceous interlayers, with optimal sealing occurring in petrophysical barriers ≥ 4 m and argillaceous barriers ≥ 1.5 m thick. CO₂ leakage occurs through preferential pathways that emerge in a side-to-middle and bottom-to-top direction in interbeds, with multidirectional pathways showing greater leakage at the bottom compared to the upper side within barriers. Increased interlayer thickness constraints CO₂ breakthrough but reduces vertical flooding area and production ratio compared to homogeneous reservoirs. Augmented interbed thickness and area mitigate CO₂ breakthrough time while constraining gravity override and dispersion effects, enhancing horizontal oil displacement. These novel findings provide crucial insights for optimizing CCUS-EOR strategies in LPSR, offering a robust theoretical foundation for future applications and serving as a key reference for CO₂ utilization in challenging geological settings of LPSR worldwide. Full article

In an urban region of eastern Tijuana, there are long-standing water runoff sites which community members have identified as having an impact on residents, including contributing to flooding. This community-based participatory research (CBPR) project in collaboration with the Colectivo Salud y Justicia Ambiental (CSJA) used the geospatial surveying tool Survey 123 to conduct community-based monitoring of five runoff sites. Results from 170 completed surveys showed that water runoff was present at these sites on forty-five percent of the days surveyed, although there was no significant relationship between the temporal factors studied and the water quality characteristics surveyed. These findings contribute to the field of border environmental justice by focusing on the understudied issues of runoff and urban flooding as environmental exposures that some communities experience disproportionately. Moreover, while there was a significant relationship between water runoff volume and precipitation events at the water runoff sites, there were sixty-five surveys collected that showed water present when there had been no precipitation event at the site. This finding supports the CSJA members’ assertions that the runoff experienced in the study area is not always connected to precipitation events or pluvial flooding. This project’s results contribute to policy advocacy by countering the policy narrative that this issue is simply a stormwater issue, and by identifying the specific runoff sites to be prioritized in this region. Full article

This study addresses the persistent issue of urban waterlogging in Wujin District, Changzhou City, Jiangsu Province, using a comprehensive approach integrating an optimized drainage network and low-impact development (LID) measures. Utilizing the Storm Water Management Model (SWMM), calibrated with extensive hydrological and hydraulic data, the model was refined through genetic algorithm-based optimization to enhance drainage efficiency. Key results indicate a substantial reduction in the average duration of waterlogging from 7.43 h to 3.12 h and a decrease in average floodwater depth from 21.27 cm to 8.65 cm. Improvements in the drainage network layout, such as the construction of new stormwater mains, branch drains, and rainwater storage facilities, combined with LID interventions like permeable pavements and rain gardens, have led to a 56.82% increase in drainage efficiency and a 63.88% reduction in system failure rates. The implementation effectively minimized peak flood flow by 25.38%, reduced runoff, and improved groundwater recharge and rainwater utilization. The proposed solutions offer a replicable, sustainable framework for mitigating flooding in urban environments, enhancing ecological resilience, and ensuring the safety and quality of urban life in densely populated areas. Full article

The combined operation of hydropower and renewable energy impacts the hydropower operation efficiency, which exhibits different effects while the reservoir is deployed various regulation abilities. This study attempts to investigate the effect of reservoir regulation storage on the average daily water consumption rate. A case study of the integration of hydro–wind–photovoltaic located in Western China shows the differences mentioned above and explains the mechanism of the effect on the daily water consumption rate. It was concluded that (1) with increasing penetrations of renewable energy (from 0 to 90%), the daily water consumption rate mostly displays a trend of descent and then ascent; (2) with the increasing regulation ability of the reservoir (from 0.8 to 5.35 × 10⁸ m³), the water consumption rate increases in the dry season but decreases in the flood season; (3) the hydropower output and net water head are two factors that cause the water consumption rate to rise and fall; and (4) a balance point between the net water head rise and the output reduction is pointed out. The findings of this study provide technique support for the research of water utilization efficiency during the renewable energy mix. Full article

Identifying the tectonic setting of rocks is essential for gaining insights into the geological contexts in which these rocks were formed, aiding in tectonic plate reconstruction and enhancing our comprehensive understanding of the Earth’s history. The application of machine learning algorithms helps identify complex patterns and relationships between big data that may be overlooked by binary or ternary tectonomagmatic discrimination diagrams based on basalt compositions. In this study, three machine learning algorithms, i.e., Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost), were employed to classify the basalts from seven diverse settings, including intraplate basalts, island arc basalts, ocean island basalts, mid-ocean ridge basalts, back-arc basin basalts, oceanic flood basalts, and continental flood basalts. Specifically, for altered and fresh basalt samples, we utilized 22 immobile elements and 35 major and trace elements, respectively, to construct discrimination models. The results indicate that XGBoost demonstrates the best performance in discriminating basalts into seven tectonic settings, achieving accuracies of 85% and 89% for the altered and fresh basalt samples, respectively. A key innovation of our newly developed tectonic discrimination model is the establishment of tailored models for altered and fresh basalts. Moreover, by omitting isotopic features during model construction, the new models offer broader applicability in predicting a wider range of basalt samples in practical scenarios. The classification models were applied to investigate the Carboniferous to Permian evolution in the Western Tianshan Orogen (WTO), revealing that the subduction of Tianshan Ocean ceased at the end of Carboniferous and the WTO evolved into a post-collisional orogenesis during the Permian. Full article

This study focuses on assessing flash flood risks in Northeastern Thailand, particularly within the Lam Saphung, Phrom, and Chern River Basins, which are highly susceptible to flash floods and debris flows. Using the HEC-RAS hydraulic model integrated with GIS tools, the research analyzes historical and scenario-based flood events to evaluate the impact of land use changes and hydrological dynamics. The model was calibrated and validated with statistical metrics such as R² values ranging from 0.745 to 0.994 and NSE values between 0.653 and 0.893, indicating strong agreement with the observed data. This study also identified high-risk areas, with up to 5.49% and 5.50% increases in flood-prone areas in the Phrom and Chern River Basins, respectively, from 2006 to 2019. Key findings highlight the critical role of proactive risk management and targeted mitigation strategies in enhancing community resilience. The integration of advanced hydraulic modeling with detailed datasets enables precise flood hazard mapping, including flood depths exceeding 1.5 m in certain areas and high-risk zones covering up to 105.2 km² during severe flood events. These results provide actionable insights for emergency response and land use planning. This research significantly contributes to hydrological risk assessments by advancing modeling techniques and delivering practical recommendations for sustainable flood management. The outcomes are particularly relevant for stakeholders, including urban planners, emergency management officials, and policymakers, who aim to strengthen resilience in vulnerable regions. By addressing the complexities of flash flood risk assessments with robust quantitative evidence, this study not only enhances the understanding of flood dynamics, but also lays the groundwork for developing adaptive strategies to mitigate the adverse impacts of flash floods, safeguarding both communities and infrastructure in the region. Full article

“Whence the strength?” This compelling question, posed by Aaron Antonovsky in 1979, sets the stage for understanding the role of sense of coherence (SOC), a human-focused psychosocial concept, in fostering resilience amidst escalating climate-induced disasters such as hurricanes, floods, and earthquakes. This paper is the first step in a larger research agenda aimed at exploring how the human experience of disasters, guided by Antonovsky’s SOC framework, can be better integrated into disaster recovery planning and design, laying the theoretical foundation for subsequent studies. This paper examines which supports help people stay resilient during disasters, focusing on the role of SOC in recovery. By integrating Antonovsky’s SOC concept with Hobfoll’s Conservation of Resources (COR) theory, it also draws from other published works on stress and disaster recovery to explore how disaster recovery planning and design can be improved. The findings indicate that the post-disaster recovery phase presents a critical window for implementing policies that address vulnerabilities in disaster-prone communities and enhance long-term resilience. Methodologically, this paper advocates for an interdisciplinary approach, suggesting that both quantitative and qualitative insights are vital for capturing human experiences in disaster contexts. Ultimately, this paper presents a framework for integrating human dimensions of resilience into disaster recovery planning. Full article

The surface integrity of a machined component is crucial for its service life part. One of the main final specifications that a machined part is inspected for is the surface integrity metrics, including surface residual stresses, surface microhardness, surface roughness, and microstructure. In this paper, the cutting fluid is strategically targeted to utilize heat energy effectively in the primary, secondary, and tertiary shear zones to positively affect the surface integrity metrics and machining mechanics. In this study, a lower quantity of the cutting fluids is targeted at the high-temperature zones to reduce the machining temperatures, thereby effectively simulating the effect of a ‘flood coolant’. The cutting fluid is applied simultaneously as a targeted Minimum Quantity Fluid (MQF) on the cutting tool’s flank and rake faces to improve the surface integrity metrics and chip formation. Also, this study analyzes the effect of the cutting fluid composition, the type of cutting fluid, and the amount of fluid quantities. The machining-induced surface integrity metrics are analyzed to understand the effects of targeted minimum quantity fluid application. The impact of the targeted application of cutting fluid on machining mechanics metrics, such as cutting forces and chip formation, is analyzed. Applying a targeted MQF application at the flank face of the cutting tool leads to higher compressive subsurface principal residual stresses. The results indicate that using MQF on both the flank and rake faces simultaneously enhances the surface integrity. The effect of a cutting fluid jet on the flank face is modeled to highlight the thermophysical properties that are crucial for selecting the appropriate cutting fluid to lower the machining-induced temperatures. With targeted MQF application, the fluid jet acts as a dynamic and external chip control mechanism. Overall, effectively managing temperatures in machining could enhance subsurface residual stresses and surface roughness using various cutting fluid combinations. Also, this paper presents a targeted cutting fluid application that improves the microstructural formation, enhancing chip control and producing machined surfaces and components with better surface integrity. Full article

Disaster losses and expenses are increasing rapidly in coastal regions, highlighting the pressing need for effective mitigation strategies. The voluntary buyout program is an effective approach to reducing risks of future flooding, often funded by federal grants after disasters. However, following a disaster, decision-making tends to be reactive, potentially leading to a haphazard selection of properties and households for program participation. It is crucial for local governments in charge of these programs to be informed about who may or may not benefit from program participation when deciding which properties to select and prioritize. Therefore, incorporating social equity in those decisions prevents unintended consequences for program participants. The present research addresses this complexity by raising the critical question of how local practitioners can evaluate equity considerations of using federal grants for buyout projects. With a mixed-methods research design, we offer systematic guidelines for supporting local practitioners in evaluating the equity considerations of using funding for buyouts, ultimately leading to improved outcomes for households. By acknowledging the potential of buyouts in mitigating flood exposure and recognizing its equity implications, this study uses advanced hazard models, buyout practitioners and experts’ insights, data on buyout funding, and findings from past research to support local practitioners in making equitable prioritization and selection of households by developing a decision framework. Full article

At present, the protection of the ecological water environment in Min River Basin has achieved certain results, but certain problems remain that require strengthened ecological protection and environmental management. Understanding the connection between water quality factors and exploring the factors affecting water quality are of great significance in determining the pollution status of watershed water and promoting the comprehensive management of watershed water quality. In this study, water quality data collected from 20 monitoring stations were used to qualitatively and quantitatively evaluate the quality of waters in the watershed. Then, the joint distribution of water quality factors was constructed using the C-vine copula method, and the main influencing factors of water quality were explored using the D-vine copula structure. This approach facilitated the current study of the integrated status of water quality pollution. The results and conclusions of the current study are as follows: (1) A total of four tree structure levels were constructed using the model. The indicators with the strongest correlation with water quality were total phosphorus during the flood season and total nitrogen during the dry season. (2) After the introduction of condition variables, dissolved oxygen exhibited the strongest correlation with the rest of the variables during the flood season. Moreover, the permanganate index was most strongly correlated with the rest of the variables during the dry season. (3) Pollution discharges and industrial structure had a large impact on water quality. In particular, urban wastewater discharge, the share of primary industry, and per capita GDP were key drivers of water quality. Reducing urban wastewater discharge and optimizing industrial structure are beneficial for improving water quality. The research results have certain guiding significance for allowing Fujian to achieve water environment protection and sustainable development. Full article

This study coupled precision agriculture with agroecology to improve the agricultural systems’ sustainability in a climate variability context, characterized by fewer rainy days and more extreme events. A three-year comparative analysis was carried out in a durum wheat rotation, divided into two plots of 2.5 ha each, one managed with conventional methods (CP, sunflower as intermediate crop) and another managed with an agroecological approach (AE, field bean as green manure crop), featuring prescription maps for site-specific mineral fertilization. The statistical analysis of durum wheat parameters, soil characteristics, and economic variables was conducted alongside the examination of climatic data. In AE soil, the exchangeable calcium was statistically different from CP soil (6044 mg kg⁻¹ and 5660 mg kg⁻¹, respectively). Cation exchange capacity was significantly higher in AE (32.7 meq 100 g⁻¹), compared to CP (30.9 meq 100 g⁻¹). In AE, wheat yield (2.36 t ha⁻¹) was higher than in CP (2.07 t ha⁻¹), despite extreme rainfall causing flooding in some parts of the AE plot. The economic balance was only 6% in favor of CP (EUR + 2157), confirming the AE approach’s resilience (EUR + 2027), despite the higher costs of cover cropping and site-specific fertilization. The novelty of integration between “smartish” precision agriculture and agroecology allows for sustainable management. Full article