Search Results (4,932)

Old urban districts, characterized by complex drainage networks, heterogeneous surfaces, and high imperviousness, are particularly susceptible to flooding during extreme rainfall. In this study, the moat drainage district of Xi’an was selected as the research area. A refined hydrologic–hydrodynamic simulation and an assessment of drainage and flood-retention capacities were conducted based on the coupled GAST–SWMM model. Results show that the model can accurately capture the rainfall–surface–pipe–river interactions and reproduce system responses under different rainfall intensities. The box culvert’s effective regulation capacity is limited to 1- to 2-year return periods, beyond which overflow rises sharply, with overflow nodes exceeding 80% during a 2-year event. The moat’s available storage capacity is 17.20 × 10⁴ m³, sufficient for rainfall events with 5- to 10-year return periods. In a 10-year return period event, the box culvert overflow volume (12.56 × 10⁴ m³) approaches the upper limit, resulting in overtopping. These findings provide a scientific basis for evaluating drainage efficiency and guiding flood control management in old urban districts. Full article

This study investigated the effects of different water management practices on the growth, yield, and grain quality of rice grown under environmentally friendly farming methods in Apgok-Ri, Gungnyu-Myeon, Uiryeong-Gun, from 2022 to 2024. Treatments included mid-season drainage for 2, 3, or 4 weeks (2MD, 3MD, 4MD), followed by either low-level water management (MD-1) or alternate wetting and drying (MD-2), with continuous flooding (CF) as the control. The rice variety was machine-transplanted on 9–10 June, and organic fertilizer (90 kg N/ha) was applied as a basal dressing. Water treatments were initiated in mid-July each year. The highest yield was consistently recorded in the 2MD-2 treatment, with 5.85, 5.74, and 5.38 tons/ha from 2022 to 2024, representing 15.0%, 14.5%, and 7.8% increases over CF, respectively. On average, alternate irrigation (MD-2) resulted in higher yields than low-level water management (MD-1) by 1.19–5.90%. Grain quality was also highest in 2MD-2, showing the greatest percentage of ripened grains each year, whereas CF had the highest proportion of immature and unripe grains. Crude protein content in brown rice was lowest in 3MD-2 (6.12%), followed by 2MD-2 (7.51%). Incidences of major diseases such as sheath blight, rice blast, panicle blight, and bacterial grain blight were highest in the CF treatment. Rice leaf blight was not significantly different in 2022, but was most prevalent in CF in 2023 and 2024. There were no major differences in brown planthopper and false smut incidence, although false smut peaked in CF in 2024. These findings suggest that 2-week mid-season drainage followed by alternate irrigation (2MD-2) is an effective strategy to improve yield, grain quality, and disease resistance in sustainable rice farming systems. Full article

Current lake and reservoir water body extraction algorithms are confronted with two critical challenges: (1) design dependency on specific geographical features, leading to constrained cross-regional adaptability (e.g., the JRC Global Water Body Dataset achieves ~90% overall accuracy globally, while the ESA WorldCover 2020 reaches ~92% for water body classification, both showing degraded performance in complex karst terrains); (2) information loss due to cloud occlusion, compromising dynamic monitoring accuracy. To address these limitations, this study presents a multi-feature fusion and multi-level hierarchical extraction algorithm for lake and reservoir water bodies, leveraging the Google Earth Engine (GEE) cloud platform and Sentinel-2 multispectral imagery in the karst landscape of Bijie City. The proposed method integrates the Automated Water Extraction Index (AWEIsh) and Modified Normalized Difference Water Index (MNDWI) for initial water body extraction, followed by a comprehensive fusion of multi-source data—including Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Red-Edge Index (NDREI), Sentinel-2 B8/B9 spectral bands, and Digital Elevation Model (DEM). This strategy hierarchically mitigates vegetation shadows, topographic shadows, and artificial feature non-water targets. A temporal flood frequency algorithm is employed to restore cloud-occluded water bodies, complemented by morphological filtering to exclude non-target water features (e.g., rivers and canals). Experimental validation using high-resolution reference data demonstrates that the algorithm achieves an overall extraction accuracy exceeding 96% in Bijie City, effectively suppressing dark object interference (e.g., false positives due to topographic and anthropogenic features) while preserving water body boundary integrity. Compared with single-index methods (e.g., MNDWI), this method reduces false positive rates caused by building shadows and terrain shadows by 15–20%, and improves the IoU (Intersection over Union) by 6–13% in typical karst sub-regions. This research provides a universal technical framework for large-scale dynamic monitoring of lakes and reservoirs, particularly addressing the challenges of regional adaptability and cloud compositing in karst environments. Full article

The Bekasi River Basin is highly vulnerable to severe and recurrent flooding, as evidenced by significant infrastructure and environmental damage during major events. This study investigates the catastrophic floods of 2016, 2020, 2022, and 2025 by implementing the Rainfall-Runoff-Inundation (RRI) model to simulate key hydrological processes. After validation using historical water level data, the model performed effectively, achieving the highest coefficient of determination (R² = 0.75) and lowest root mean square error (RMSE = 0.66) at Cileungsi Station. In contrast, the lowest R² = 0.02, and the highest RMSE = 3.74 at Pondok Gede Permai (PGP) Station. The results reveal a concerning trend of worsening 5-year flood events, with the 2025 flood reaching a peak inundation depth exceeding 3 m and affecting an area of 2.97 km², caused by a rainfall threshold of more than 180 mm/day. Furthermore, the model shows a rapid hydrological response, with a time lag of approximately 7 h or less between peak rainfall and flood onset across three monitoring stations. Analysis indicates these severe floods were primarily triggered by heavy rainfall combined with significant land cover changes. The findings provide valuable insights for flood prediction and mitigation strategies in this vulnerable region. Full article

This study evaluated the growth characteristics and yield of rice under various water management strategies in an environmentally friendly paddy field in Korea from 2022 to 2024. The water management treatments included mid-season drainage (MD) lasting for 2, 3, or 4 weeks, followed by either low-level water management (maintaining a 4 cm water depth, denoted as “1”) or alternate wetting and drying irrigation (4 cm irrigation followed by drying, denoted as “2”) until harvest. The conventional treatment consisted of continuous flooding (CF). Treatments with poor yields (4MD1 and 4MD2) were discontinued in subsequent years. The rice cultivar Saecheongmu was transplanted in June, and water management began in July. Among the treatments, CF produced the highest number of mean panicles, whereas the 2MD2 treatment showed the most favorable yield components. The highest mean grain yield was recorded in 2MD2, with values of 5.85, 5.74-, and 5.38-tons ha⁻¹ over the three years—representing a 7.8–15.0% increase compared to CF. Across all treatments, MD1 consistently produced higher yields than MD2. Water use was lowest in 2MD2, achieving a 61.8% reduction compared to CF. Overall, the 2MD2 treatment emerged as the most promising strategy, effectively reducing water use by 61.8% while maintaining high yields comparable to those under continuous flooding. Full article

Proton exchange membrane fuel cells (PEMFCs) are a promising clean energy technology due to their zero gas emissions, low operating temperature, and high efficiency. This review synthesizes research from 2015–2025 on (i) materials-level approaches (advanced/modified PFSA membranes and composite membranes) that improve water retention and ionic conduction, (ii) engineered gas diffusion layers and hydrophobic/hydrophilic gradients (including Janus and asymmetric GDL architectures) that facilitate directional water transport and have been shown to increase peak power density in some reports (e.g., from ≈1.17 to ≈1.89 W·cm⁻² with Janus GDL designs), (iii) flow-field design strategies. This review examines the key aspects of water management in PEMFCs, including their impact on cell performance, the underlying causes of related issues, and the mechanisms of water transport within these cells. Additionally, it discusses the methods and materials used to enhance water management, highlighting recent advancements and potential directions for future research. Topics such as water transport, water flooding, and water control strategies in PEMFCs are also addressed. Both excess water (flooding) and water depletion (dehydration) can negatively influence fuel cell performance and lifespan. Particular attention is given to water dehydration, with a detailed discussion of its effects on the cathode, Anode, gas diffusion layer, catalyst layer, and flow channels. Full article

To address the limitation that single-index evaluation fails to fully reflect the development performance of reservoirs of different types and at various development stages, a multi-index comprehensive evaluation system featuring the workflow of “index screening–weight determination–model evaluation–strategy guidance” was established. Firstly, the grey correlation analysis method (with a correlation degree threshold set at 0.65) was employed to screen 12 key evaluation indicators, including reservoir physical properties (porosity, permeability) and development dynamics (recovery factor, water cut, well activation rate). Subsequently, the fuzzy analytic hierarchy process (FAHP, for subjective weighting, with the consistency ratio (CR) of expert judgments < 0.1) was coupled with the attribute measurement method (for objective weighting, with information entropy redundancy < 5%) to determine the indicator weights, thereby balancing the influences of subjective experience and objective data. Finally, two evaluation models, namely the fuzzy comprehensive decision-making method and the unascertained measurement method, were constructed to conduct evaluations on 308 reservoirs in the Liaohe Oilfield (covering five major categories: integral medium–high-permeability reservoirs, complex fault-block reservoirs, low-permeability reservoirs, special lithology reservoirs, and thermal recovery heavy oil reservoirs). The results indicate that there are 147 high-efficiency reservoirs categorized as Class I and Class II in total. Although these reservoirs account for 47.7% of the total number, they control 71% of the geological reserves (154,548 × 10⁴ t) and 78% of the annual oil production (738.2 × 10⁴ t) in the oilfield, with an average well activation rate of 65.4% and an average recovery factor of 28.9. Significant quantitative differences are observed in the development characteristics of different reservoir types: Integral medium–high-permeability reservoirs achieve an average recovery factor of 37.6% and an average well activation rate of 74.1% by virtue of their excellent physical properties (permeability mostly > 100 mD), with Block Jin 16 (recovery factor: 56.9%, well activation rate: 86.1%) serving as a typical example. Complex fault-block reservoirs exhibit optimal performance at the stage of “recovery degree > 70%, water cut ≥ 90%”, where 65.6% of the blocks are classified as Class I, and the recovery factor of blocks with a “good” rating (42.3%) is 1.8 times that of blocks with a “poor” rating (23.5%). For low-permeability reservoirs, blocks with a rating below medium grade account for 68% of the geological reserves (8403.2 × 10⁴ t), with an average well activation rate of 64.9%. Specifically, Block Le 208 (permeability < 10 mD) has an annual oil production of only 0.83 × 10⁴ t. Special lithology reservoirs show polarized development performance, as Block Shugu 1 (recovery factor: 32.0%) and Biantai Buried Hill (recovery factor: 20.4%) exhibit significantly different development effects due to variations in fracture–vug development. Among thermal recovery heavy oil reservoirs, ultra-heavy oil reservoirs (e.g., Block Du 84 Guantao, with a recovery factor of 63.1% and a well activation rate of 92%) are developed efficiently via steam flooding, while extra-heavy oil reservoirs (e.g., Block Leng 42, with a recovery factor of 19.6% and a well activation rate of 30%) are constrained by reservoir heterogeneity. This system refines the quantitative classification boundaries for four development levels of water-flooded reservoirs (e.g., for Class I reservoirs in the high water cut stage, the recovery factor is ≥35% and the water cut is ≥90%), as well as the evaluation criteria for different stages (steam huff and puff, steam flooding) of thermal recovery heavy oil reservoirs. It realizes the transition from traditional single-index qualitative evaluation to multi-index quantitative evaluation, and the consistency between the evaluation results and the on-site development adjustment plans reaches 88%, which provides a scientific basis for formulating development strategies for the Liaohe Oilfield and other similar oilfields. Full article

During water flooding processes, the high viscosity of heavy oil and significant reservoir heterogeneity often lead to severe water channeling and low sweep efficiency. Addressing the limitations of traditional hydrophobically associating polymer-based profile-control agents—such as significant adsorption loss, mechanical degradation during reservoir migration, resulting in a limited effective radius and short functional duration—this study developed a polymeric graded profile-control agent suitable for highly heterogeneous conditions. The physicochemical properties of the system were comprehensively evaluated through systematic testing of its apparent viscosity, salt tolerance, and anti-aging performance. The microscopic oil displacement mechanisms in porous media were elucidated by combining CT scanning and microfluidic visual displacement experiments. Experimental results indicate that the agent exhibits significant hydrophobic association behavior, with a critical association concentration of 1370 mg·L⁻¹, and demonstrates a “low viscosity at low temperature, high viscosity at high temperature” rheological characteristic. At a concentration of 3000 mg·L⁻¹, the apparent viscosity of the solution is 348 mPa·s at 30 °C, rising significantly to 1221 mPa·s at 70 °C. It possesses a salinity tolerance of up to 50,000 mg·L⁻¹, and a viscosity retention rate of 95.4% after 90 days of high-temperature aging, indicating good injectivity, reservoir compatibility, and thermal stability. Furthermore, within a concentration range of 500–3000 mg·L⁻¹, the agent can effectively emulsify Gudao heavy oil, forming O/W emulsion droplets with sizes ranging from 40 to 80 μm, enabling effective plugging of pore throats of corresponding sizes. CT scanning and microfluidic displacement experiments further reveal that the agent possesses a graded control function: in the near-wellbore high-concentration zone, it primarily relies on its aqueous phase viscosity-increasing capability to control the mobility ratio; upon entering the deep reservoir low-concentration zone, it utilizes “emulsion plugging” to achieve fluid diversion, thereby expanding the sweep volume and extending the effective treatment period. This research outcome provides a new technical pathway for the efficient development of highly heterogeneous heavy oil reservoirs. Full article

While urban green spaces are integral to urban resilience, their long-term dynamics under recurrent flooding have received limited scholarly attention. This study investigates two decades of green space change across 367 counties in the southeastern United States, integrating FEMA disaster records with multi-period land cover data. Employing generalized additive and logistic regression models, the impacts of flood frequency, development intensity, and socioeconomic drivers were assessed. Flood frequency was identified as the primary determinant of urban green space loss. Each additional flood event corresponded to a 0.36% reduction in the five-year green space change rate (p < 0.01), while extreme flood frequency (≥ 10 events) was associated with an 18-fold increase in the odds of long-term degradation. Development intensity exhibited a significant non-linear effect, with loss rates culminating at moderate-to-high intensities. Furthermore, household income functioned as a significant moderator; in extremely flood-prone areas, higher income correlated with enhanced resilience (OR = 0.155, p < 0.05). These findings demonstrate that recurrent floods function as a cumulative pressure. This research highlights the necessity of equitable green infrastructure planning that integrates flood risk with the complex, moderating role of socioeconomic capacity. Full article

At present, most oilfields in China have entered the late, high-water-cut stage, commonly facing declining single-well productivity and increasingly pronounced reservoir heterogeneity. Prolonged waterflooding has further exacerbated permeability contrast, yielding complex, hard-to-produce residual-oil distributions. Accordingly, the development of efficient enhanced oil recovery (EOR) technologies has become a strategic priority and an urgent research focus in oil and gas field development. Weak gels, typical non-Newtonian fluids, exhibit both viscous and elastic responses, and their distinctive rheology shows broad application potential for crude oil extraction in porous media. Targeting medium–high-permeability reservoirs with high water cut, this study optimized and evaluated a weak gel system. Experimental results demonstrate that the optimized weak gel system achieves remarkable oil displacement performance. The one-dimensional dual-sandpack flooding tests yielded a total recovery of 72.26%, with the weak gel flooding stage contributing an incremental recovery of 14.52%. In the physical three-dimensional model experiments, the total recovery reached 46.12%, of which the weak gel flooding phase accounted for 16.36%. Through one-dimensional sandpack flow experiments and three-dimensional physical model simulations, the oil displacement mechanisms and synergistic effects of the optimized system in heterogeneous reservoirs were systematically elucidated from macro to micro scales. The optimized system demonstrates integrated synergistic performance during flooding, effectively combining mobility control, displacement, and oil-washing mechanisms. Macroscopically, it effectively strips residual oil in high-permeability zones via viscosity enhancement and viscoelastic effects, efficiently blocks high-permeability channels, diverts flow to medium-permeability regions, and enhances macroscopic sweep efficiency. Microscopically, it mobilizes residual oil via normal stress action and a filamentous transport mechanism, improving oil-washing efficiency and increasing ultimate oil recovery. This study demonstrates the technical feasibility and practical effectiveness of the optimized weak gel system for enhancing oil recovery in heterogeneous reservoirs, providing critical technical support for the efficient development of medium–high-permeability reservoirs with high water cut. Full article

The effective design and operation of hydraulic structures, particularly open channel spillways, are crucial for water resource management and flood risk reduction in dams. A clear understanding of flow properties, such as velocity fluctuations and discharge, across various depths is essential for optimizing performance. In this study, experimental analysis and numerical simulation using FLOW-3D were combined to investigate the hydraulic parameters of a scaled model of the Romaine IV spillway located in Quebec, Canada. Measurements focused on flow properties, including velocity fluctuations at various discharge rates in specific flow depths, at selected points along the spillway. The numerical model was assessed by reproducing experimental geometry, initial water levels, and boundary conditions, and through sensitivity analyses to ensure accurate flow representation. Comparisons of flow rates of 180, 240, and 340 L/s showed that while simulations with the renormalized group (RNG) turbulence model reliably predicted average velocities, they underestimated maximum values and overestimated minimum values, especially at higher discharges. The results highlight the difficulty of accurately capturing velocity extremes in turbulent flows and the need for further model refinement. This was evident from the 60% discrepancy in minimum velocities observed at the channel center. Despite these discrepancies, the study advances our understanding of spillway performance and identifies avenues to improve the accuracy of numerical modeling in hydraulic engineering. Full article

Panama, with nearly 3000 km of coastline and half its population living in coastal zones, faces high vulnerability to sea level rise, flooding, and extreme events. The most vulnerable areas include low-lying coastal provinces such as Panama, Colón, and Chiriquí. This review explores the use of sustainable concrete to address the effects of climate change in Panama towards coastal resilience. The methodology combined a bibliometric analysis using VOSviewer, a systematic literature review (2015–2025) of 99 sources including regulations and technical standards, and a socioeconomic SWOT analysis to assess adoption drivers and barriers. A 2050 permanent inundation map was examined to identify vulnerable areas, and an inventory of concrete-based protection structures was developed. The results highlight that concrete is already used in Panama for coastal resilience through structures such as breakwaters, dolos, and Xbloc units. However, as the country still needs to expand its coastal protection infrastructure, there is a crucial opportunity to implement lower-impact, sustainable concrete alternatives that minimize environmental burdens while ensuring long-term durability and performance. Sustainable options, including supplementary cementitious materials (SCMs), recycled aggregates, and CO₂ injection technologies, demonstrate strong mitigation potential, with national initiatives such as Vertua, Greentec, and Argos pozzolan offering early pathways. The conclusions emphasize the need to expand sustainable concrete applications, integrate nature-based solutions, and strengthen Panama’s regulatory and technical capacity to achieve resilient, low-carbon coastal infrastructure. Full article

In dam operations, sudden discharges during extreme rainfall events can pose severe flood risks to downstream communities. This study developed a dam discharge-based river water level forecasting model using a data-driven deep learning approach, long short-term memory (LSTM). To enhance predictive performance, physics-based HEC-RAS simulation outputs, including extreme events, were incorporated as additional inputs. The Seomjin River Basin in South Korea, which recently experienced severe flooding, was selected as the study area. Hydrological data from 2010 to 2023 were utilized, with 2023 reserved for model testing. Forecasts were generated for four lead times (3, 6, 12, and 24 h), consistent with the operational flood forecasting system of the Ministry of Environment, South Korea. Using only observed data, the model achieved high accuracy at upstream sites, such as Imsil-gun (Iljung-ri, R² = 0.92, RMSE = 0.27 m) and Gokseong (Geumgok Bridge, R² = 0.91, RMSE = 0.35 m), for a 6-h lead time. However, performance was lower at Gurye-gun (Songjeong-ri, R² = 0.72, RMSE = 1.48 m) due to the complex influence of two dams. Incorporating enhanced inputs significantly improved predictions at Gurye-gun (R² = 0.91, RMSE = 1.17 m at 3 h). Overall, models using only observed data performed better at upstream sites, while enhanced inputs were more effective in downstream or multi-dam regions. The 6-h lead time yielded the highest overall accuracy, highlighting the potential of this approach to improve real-time dam operations and flood risk management. Full article

Coastal wetlands provide crucial ecosystem services, including habitats for wildlife, carbon storage, greenhouse gas emission reduction, storm surge and flood protection, water purification, recreation, and nature-based tourism. Their protection and restoration are therefore of growing importance to conservationists, scientists, local communities, and policymakers. This paper analyses the European Union’s (EU) policy framework, alongside international and regional agreements relevant to wetland conservation and restoration, focusing on coastal ecosystems. Drawing on policy content analysis, it assesses how 36 EU policies and multilateral agreements support or limit coastal wetland restoration and conservation efforts in Europe. The findings reveal two key gaps: first, an absence of a consistent definition of coastal wetlands within the EU policy framework; and second, the limited number of explicit policy references to these ecosystems. These shortcomings restrict opportunities for their effective inclusion in action plans and undermine coordinated conservation and restoration efforts. Most binding targets and objectives addressing coastal wetlands stem from EU policies and multilateral agreements on nature conservation, including regional sea conventions. This reliance risks overlooking opportunities within other policy sectors. While EU climate policies increasingly recognise the importance of wetland restoration, they often do so through non-binding provisions and voluntary action. To unlock the full potential of coastal wetlands for biodiversity and climate benefits, it is essential to embed coastal wetlands more explicitly within policy targets and to leverage emerging opportunities within the EU policy framework to further upscale coastal wetland restoration. Full article

Rainfall-driven non-point source (NPS) pollution has become a critical issue for water environment management in urban watershed systems. However, single-model use is limited to fully represent the intricate processes of rainfall-correlated NPS pollution generation and dispersion for effective decision-making. This study develops a novel cross-scale, multi-factor coupled model framework to characterize hydrologic and NPS pollution responses to different rainfall events in Shenzhen, China, a representative worldwide metropolis facing challenges from rapid urbanization. The calibrated and validated coupled model achieved remarkable agreements with observed hydrologic (Nash–Sutcliffe efficiency, NSE > 0.81) and water quality (NSE > 0.85) data in different rainfall events and demonstrated high-resolution dynamic changes in flow and pollutant transfer within the studied watershed. In an individual rainfall event, heterogeneous spatial distributions of discharge and pollutant loads were found, highly correlated with land use types. The temporal change pattern and risk of flooding and NPS pollution differed significantly with rainfall intensity, and the increase in the pollutants (mean 322% and 596%, respectively) was much larger than the discharge (207% and 302%, respectively) under intense rainfall conditions. Based on these findings, a decision-support framework was established, featuring land-use-driven spatial prioritization of industrial hotspots, rainfall-intensity-stratified management protocols with event-triggered operational rules, and integrated source-pathway-receiving end intervention strategies. The validated model framework provides quantitative guidance for optimizing infrastructure design parameters, establishing performance-based regulatory standards, and enabling real-time operational decision-making in urban watershed management. Full article