Search Results (690)

High-resolution marine sedimentary archives from active continental margins provide exceptional records of paleo-earthquake histories through the preservation of seismogenic turbidites. A 477cm long gravity core (HOBAB4-S2) retrieved from the southern Okinawa Trough (SOT) off eastern Taiwan at a water depth of 1505 m preserves a ~700-year record (1445–2003 AD) of alternating hemipelagic background sedimentation and rapid event deposits. Chronological control is established through accelerator mass spectrometry (AMS ¹⁴C) radiocarbon dating and excess ²¹⁰Pb profiling. Detailed sedimentological and geochemical analyses identify fifteen turbidite events (T1–T15), which are grouped into three lithofacies: TI (silt turbidites), TII (sandy silt turbidites), and TIII (silty sand turbidites). Temporal correlation demonstrates that the majority of these turbidite beds coincide with documented historical and instrumental earthquakes (M_w ≥ 6.6), confirming seismic shaking as the primary triggering mechanism. Notably, turbidite thickness, basal grain size and recurrence frequency increase during the Little Ice Age (LIA, ~1400–1850 AD), a pattern we attribute to enhanced terrestrial sediment supply driven by intensified typhoon activity, which preconditioned the slope system for seismically induced failure. These findings demonstrate that turbidite sequences in the SOT provide a reliable record of local paleo-earthquake activity, while establishing that their stratigraphic expression is modulated by climatically driven sedimentary preconditioning. This principle is critical to paleoseismic reconstruction in seismically active, storm-prone continental margins globally. Full article

Constructing new reservoirs to ensure a reliable water supply in downstream areas and to alleviate overflow flooding along rivers during floods is an urgent task for the authorities. In this study, we developed a GIS platform that integrates a series of watershed geomorphological and hydrological models to assess the suitability of prospective dam sites. The built-in modules include watershed geomorphological analysis, rainfall analysis, flow analysis, surplus water analysis, and reservoir analysis. Using the digital elevation model, users can obtain the reservoir H-A-V curve at a prospective dam site and the upstream watershed’s geomorphological factors. A topography-based hydrological model was used to estimate available water at the dam site, and surplus water was obtained by subtracting existing water demands and/or environmental flow requirements from the available water series. Exceedance probability analysis was then conducted for the surplus water to evaluate the dam site’s feasibility for new water resources development. The system also provides a reservoir’s useful-life evaluation to determine the time required for sediment accumulation to render the reservoir unable to serve its intended purpose. Moreover, for flood control, the platform includes a built-in module for estimating design discharge for different return periods. The planned Pingxi Reservoir site in New Taipei County, Taiwan, is used as an example in this study. Detailed analytical procedures are presented to demonstrate the use of the proposed integrated GIS platform system to assess the adequacy of prospective dam sites for new water resources development. Full article

This study presents a technical assessment of solar energy systems for integrated agricultural use and rural electrification. A model village comprising 30 households was considered, and high-resolution hourly load profiles were developed to characterize consumption dynamics, including peak demand and sectoral distribution across residential, agricultural, public, healthcare, and commercial users. A 60 kW photovoltaic (PV) system was designed in conjunction with an independent solar thermal installation for hot water supply. The system configuration was established through component sizing and numerical modeling, incorporating heat transfer mechanisms and operational constraints. Time-dependent simulations performed in MATLAB (R2022b) evaluated PV power output, battery storage cycling, and thermal system performance over a 24-h horizon. A comparative analysis of standalone PV, hybrid PV/T, and decoupled PV–thermal configurations was conducted based on performance and operational criteria. The results indicate that separated electrical and thermal subsystems achieve improved cost-effectiveness, enhanced reliability, and reduced maintenance requirements. The proposed approach demonstrates the technical viability of solar-based energy systems for rural applications, supporting energy autonomy, reduced fossil fuel dependence, and sustainable agricultural development. Full article

This review evaluates the current state of knowledge on the use of wood fibres and related woody materials as partial substitutes for peat in substrates used for forest nursery production, with particular emphasis on container seedlings. The review was prepared as a structured narrative synthesis of the available literature, focusing on substrate composition, physical and chemical properties, tree seedling growth, root development, water regime, fertilisation, operational handling, economic aspects and remaining research needs. The available evidence shows that wood fibres are technically promising components of peat-reduced growing media, but their performance depends strongly on the raw-material origin, processing method, substrate proportion, tree species, and cultivation management. The most reliable results have been obtained with partial substitution systems, whereas peat-free solutions remain species-specific and require careful optimisation of irrigation, nitrogen supply, pH control, and substrate quality. Although wood-based materials may improve resource efficiency and, under favourable local conditions, reduce substrate costs, wider implementation is constrained by variable material quality, limited standardisation and insufficient operational-scale validation. The main remaining research need is to define species-specific application thresholds and management protocols and to link nursery performance with outplanting success and full production economics under commercial conditions. Full article

Rooftop rainwater harvesting (RWH) offers a practical adaptation option for Mediterranean cities where water scarcity is amplified by seasonal rainfall and climate variability. This study reports early findings from a simplified monthly water balance screening model for a typical residential building, driven by ERA5-Land monthly precipitation for Antalya and İzmir (Türkiye). Scenarios cover roof areas of 250–3000 m² and practical tank capacities of 2–100 m³ under a fixed non-potable demand of 0.20 m³/day. The model tracks monthly storage dynamics and supply demand in order to compute demand coverage and monthly reliability (i.e., fraction of months in which full demand is met). Reliability-based storage thresholds (≥0.80) are derived for four evaluation windows (1996–2010, 2011–2025, 1996–2025, 1950–2025) to explore climate sensitivity. In parallel, a guideline-style sizing which is consistent with the Turkish rainwater harvesting guideline is implemented using a three-day storage rule based on the wettest month potential. To enable a like-for-like comparison, the collection losses are harmonized by setting loss to 0.10 in the simulation and efficiency to 0.90 in the guideline method. The results show stable thresholds for Antalya but stronger period sensitivity in İzmir. They also quantify cases where guideline sizing does not achieve the target reliability under dry season constraints. This approach supports the rapid, climate-aware pre-design of small- to medium-scale urban RWH systems. Full article

Sediment deposition in water diversion channels threatens the operational safety and water supply reliability of large-scale inter-basin water transfer projects. This study investigates the deposition patterns and sediment reduction strategies for the diversion channel of the Shigu Water Source Project, a key intake hub of the Central Yunnan Water Diversion Project on the Jinsha River. A one-dimensional total-load sediment mathematical model (HELIU-2) was used to simulate deposition volume, particle size distribution, and sediment concentration at the pumping station intake under eight design scenarios spanning high-, medium-, and low-sediment years. Results show that over 95% of the deposited sediment in front of the pumping station is finer than 0.05 mm. Dredging reduces the deposition thickness at the pump intake by 13–25% in high-sediment years, significantly enhancing sediment trapping efficiency and reducing both average and maximum sediment concentrations. Longer diversion channels increase total deposition by 9–13% but reduce intake sediment concentration by 2–5% and decrease local deposition thickness by 27–42%, especially in high-sediment years. These findings provide quantitative support for optimizing desilting basin layout, channel length design, and dredging schedules. The proposed modeling framework and mitigation strategies may provide a reference for other large-scale water diversion systems facing similar sedimentation challenges. Full article

Urban water insecurity is an increasingly critical challenge in rapidly urbanizing regions of the Global South, driven by population growth, environmental degradation, infrastructure limitations, and institutional constraints. Kathmandu Valley, Nepal, exemplifies these interconnected pressures. This study presents a systematic review of 45 peer-reviewed and selected grey literature sources published between 2000 and 2025, conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were included if they examined drinking water contamination, public health risks, household coping practices, wastewater-related exposure, or governance dynamics in Kathmandu Valley, Nepal. Findings were synthesized using a narrative thematic approach. The review identifies widespread contamination across municipal supply systems, groundwater, tanker water, traditional water sources, and household-stored water. Microbial contamination, particularly total coliforms, fecal coliforms, and Escherichia coli, emerged as the most consistently reported and immediate public health concern. Chemical and physicochemical contaminants, including ammonia, iron, arsenic, nitrate, and turbidity, were also widely reported, especially in shallow and deep groundwater systems. Seasonal dynamics further influenced exposure risks, with increased microbial contamination during monsoon periods and greater dependence on alternative and less regulated water sources during dry seasons. The findings further indicate that unsafe water exposure is associated with a substantial burden of waterborne diseases and emerging risks such as antimicrobial resistance. Although household water treatment practices reduced contamination in some cases, risks often persisted due to recontamination during storage and handling. These burdens disproportionately affected marginalized and peri-urban populations with limited access to safe and reliable water infrastructure. The review also highlights persistent governance challenges, including institutional fragmentation, weak regulatory enforcement, inadequate infrastructure investment, and growing dependence on informal water supply systems. Together, these conditions contribute to a hybrid urban water system in which formal and informal sources coexist without consistent quality control. Overall, the evidence demonstrates that water insecurity in Kathmandu Valley is a systemic condition shaped by the interaction of environmental contamination, unequal exposure, household coping limitations, and fragmented governance. By integrating environmental, public health, and governance evidence, this review advances understanding of urban water insecurity in rapidly urbanizing contexts and highlights the need for integrated, equity-oriented, and governance-informed interventions. These findings have broader relevance for cities across the Global South experiencing similar environmental and infrastructural pressures. Full article

The discharge of pesticide residues (PRs) from agricultural activities into water bodies has raised concerns about their toxicity to humans and the ecosystem. Traditional methods such as adsorption, membrane filtration, biological treatment, and conventional filtration usually result in incomplete removal of PRs. Currently, removal of PRs using advanced oxidation processes, particularly metal oxide-based photocatalysts, is considered a promising way. This review provides a comprehensive overview of recent advances in the photocatalytic degradation of PRs using TiO₂-based photocatalysts (T-BPs), the most widely investigated metal-oxide photocatalyst systems. First, we discuss the distribution, types, and negative impacts of major PRs on humans and the ecosystem. Next, we explore modification methods to enhance the properties of T-BPs, including light absorption behavior, charge separation rate, and photocatalytic degradation performance toward PRs. Afterward, this review carefully examines current challenges, such as complex water matrices, T-BP stability, energy supply for photocatalysis, and toxicity reduction. Finally, we highlight key future research directions, like the development of visible light-driven photocatalysts, enhanced mineralization efficiency, reduced secondary environmental risks, and the design of highly reliable catalyst and reactor systems for sustainable large-scale applications. Full article

Estimation of rice crop yield at the village level is essential because village is the Insurance Unit (IU) for rice crop in many regions in India, and timely and accurate yield information at this scale supports timely and transparent claim settlements for farmers and supports local agricultural planning. To achieve this, a multi-source satellite data-based machine learning approach was used to estimate rice yield at the village level using optical and SAR data, climatic data and land surface model-derived parameters in Kakinada of Andhra Pradesh, India. The predictor dataset included seasonal cumulative rainfall, seasonal Normalized Difference Vegetation Index (NDVI)-Max, seasonal NDVI-Mean, seasonal Land Surface Water Index (LSWI)-Max, seasonal LSWI-Mean, season total Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) and season total Root Zone Soil Moisture (RZSM), and season total backscatter of the Sentinel-1 VH polarization were used to represent crop greenness, moisture status, photosynthetic activity, soil water availability, canopy structure, and seasonal water supply. For model development and validation, village-level rice yield data from 2017 to 2023 was used, which was collected through Crop Cutting Experiment (CCE) at the maturity stage of Kharif season. In this study, four machine learning models such as Random Forest (RF), Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and Gradient Boosting (GB) were evaluated. The multi-source satellite data and yield data for the period 2017–2021 were used to train the models, which were independently tested on 2022 data and then applied to predict the rice yield in 2023. Leave-One-Year-Out (LOYO) cross-validation was also conducted on the 2017–2022 data to assess temporal robustness and generalization capability across years. Among the evaluated models, Random Forest exhibited the best overall performance. For the independent test year 2022, RF achieved an R² of 0.465, RMSE of 415.34 kg ha⁻¹, MAE of 322.22 kg ha⁻¹, and MAPE of 10.36%. For the prediction year 2023, RF achieved improved accuracy with an R² of 0.838, RMSE of 325.75 kg ha⁻¹, MAE of 262.21 kg ha⁻¹, and MAPE of 7.68%. Further, LOYO cross-validation also showed the robustness of RF, achieving the highest mean R² of 0.702 and mean RMSE of 384.73 kg ha⁻¹. The results illustrate that multi-source satellite data combined with machine learning can be a reliable and operationally useful tool in predicting village-level rice yield, which can be used for crop insurance claim settlement. Full article

An EU-funded project was implemented to enhance efficiency and reliability in the water supply system of Antalya city in Türkiye to support climate change adaptation by reducing Non-Revenue Water (NRW). Extensive fieldwork and targeted actions of continuous Minimum Night Flow monitoring, Active Leakage Control, pressure management, and replacement of aging meters were applied to identify and reduce NRW. The project demonstrated that the commonly used percentage water loss indicator in Türkiye, the regulatory performance indicator, is biased and that the Infrastructure Leakage Index provides a more accurate performance measure. Training and experience-sharing workshops were conducted for district, provincial, and metropolitan municipalities in addition to an international regional conference, strengthening institutional capacity for sustainable water loss management. The project demonstrated that substantial gains in efficiency, reliability, and climate resilience can be achieved through integrated water loss management, advanced monitoring technologies, and performance-based evaluation frameworks. Full article

In many orographically complex monsoon basins, rain gauge networks are sparse and lack the long-term continuous records required for reliable precipitation probability analysis. Traditional regional frequency analysis assumes spatially uniform precipitation across the analysis zone, which is inadequate for basins with steep rainfall gradients and strong seasonal variability. Gridded precipitation products (GPPs) provide spatially continuous, long-term records that enable grid-cell-level probability distribution fitting. However, GPPs may exhibit local biases and errors, and statistical evaluation against gauge observations is necessary before application. This study was conducted in the Phetchaburi–Prachuap Khiri Khan River Basin, western Thailand, a region with steep orographic and coastal rainfall gradients. Four GPPs, namely CHIRPS, CHELSA, WorldClim, and PERSIANN-CCS-CDR, were evaluated against gauge observations. The best-performing product, after monthly bias correction, was then used to generate spatially continuous monthly exceedance probability maps using grid-cell gamma distribution fitting. CHELSA showed the best overall performance across all evaluation metrics (correlation coefficient (r) = 0.908, percent bias (PBIAS) = 7.0%, root mean square error (RMSE) = 48.3 mm), passing the Kolmogorov–Smirnov (KS) goodness-of-fit test at all 96 station-months. CHIRPS and WorldClim showed satisfactory overall performance but exhibited localized biases in complex terrain, whereas PERSIANN-CCS-CDR substantially overestimated wet-season rainfall, limiting its suitability for this basin. Spatial precipitation patterns varied markedly between monsoon regimes, shifting from a dominant west-to-east orographic gradient during the southwest monsoon to a less differentiated advective pattern during the northeast monsoon. Furthermore, analysis at the 75% exceedance probability level showed that mean-based effective rainfall overestimated reliable water supply in high-variance months, leading to underestimation of supplemental irrigation demand. The generated maps provide spatially explicit dependable rainfall estimates across the basin, supporting probabilistic agricultural water management at multiple planning scales in orographically complex monsoon basins. Full article

Investments in urban water supply should be informed by resilience management frameworks that consider traditional reliability requirements, community preparedness during system disruptions, and sustainability goals in long-term planning. Grounded in a framework (WARATA) that integrates these aspects, this paper presents a stepwise, performance-based theoretical approach to resilience quantification, supported by explanations and practical guidance. For instance, in addition to the piped infrastructure components, emergency supply options and human resources should be incorporated within the system boundaries (Step 1), and water supplied to users is recommended as a single performance measure (Step 2). During disruptions, performance at user nodes is influenced by operational rules for resource allocation (Step 3), which must be implemented in the required computer model for simulating performance (Step 4). Equations for computing withstanding, absorptive, restorative, adaptive, and transformative capabilities as time-based metrics are proposed (Step 5), enabling the analysis of results from the bottom up (Step 6) to inform resilience management. Using illustrations of performance curves at individual system nodes, this paper advocates for extended system boundaries that bridge the gap between infrastructure and community resilience; discusses challenges with the modeling of dynamic, adaptive performances; and emphasizes the importance of assessing temporal distances to fail-safe and safe-fail thresholds during disturbances. Pending case study validation and integration into tools for predictive and real-time analyses of options, the quantification approach could support infrastructure and emergency response planning and management, ultimately ensuring sustainable system designs with equitable resilience outcomes. Full article

Efficient water resource management is critically important for arid regions such as southern Kazakhstan. This paper presents a hybrid Internet of Things (IoT) and Vision-based Internet of Things (VIoT) architecture for real-time monitoring of water levels in irrigation channels. The proposed system integrates an ultrasonic water-level sensor, an IP camera with edge-based computer vision processing on a Raspberry Pi, wireless communication, an autonomous solar power supply, and discharge estimation using Manning’s equation. The VIoT subsystem applies image processing techniques, including gauge calibration, Canny edge detection, and pixel-to-metric conversion, to automatically estimate water level from captured video frames. Water-level measurements obtained from IoT sensors and video-based analysis are combined through synchronised data fusion to improve monitoring accuracy and reliability. The hybrid approach leverages the complementary strengths of IoT and VIoT by combining continuous quantitative sensing with visual verification capabilities. Field experiments conducted on the Merke River in the Zhambyl region of Kazakhstan over a 14-day observation period demonstrated stable real-time operation with RMSE = 0.311 cm, MAE = 0.279 cm, and Pearson r = 0.99 between the ultrasonic sensor and the vision-based estimates. Sensitivity analysis indicated that water level is the most influential parameter in Manning-based discharge estimation, confirming the importance of accurate level detection. The proposed system improves reliability by cross-checking independent data sources, making it applicable to monitoring water levels in agricultural regions. Full article

With the rapid development of clean and low-carbon energy systems, non-metallic pipelines have become increasingly important in urban gas distribution, water supply, and emerging energy-transport applications, including hydrogen service. As a critical joining technology that governs system integrity and long-term operational safety, electrofusion welding requires a comprehensive and mechanism-oriented understanding beyond empirical process control. In this study, a review is conducted on research published over the past decade in the field of electrofusion welding of non-metallic pipelines, with emphasis on fundamental technical issues including the formation and evolution of temperature fields, characteristics of the molten fusion zone and defect development, and thermo-mechanical coupling with residual stress generation. Based on a synthesis of the literature, the review clarifies the global research landscape, core research communities, and underlying knowledge structure. The results indicate a clear transition of the field from empirically driven parameter optimization toward a mechanism-based and process-controllable paradigm centered on temperature field evolution, fusion zone development, and thermo-mechanical behavior. Current research hotspots converge on HDPE material adaptability, welding process regulation, and the long-term reliability of welded joints. Building on these insights, future research directions are discussed, including mechanism-driven process design, intelligent defect identification based on multi-source data, and full-life reliability assessment under service conditions. This review provides a theoretical framework to support process optimization and engineering application of electrofusion welding in non-metallic pipeline systems. Full article

In recent decades, flood drought abrupt alternation (FDAA) events have intensified markedly in the middle and lower reaches of the Yangtze River Basin (MLYRB), exposing limitations of the conventional single flood-limited water level (FLWL) operation of the Three Gorges Reservoir. To better address drought risk during the flood season, this study develops a phased and graded drought-limited water level (DLWL) operation framework. FDAA events were identified using a hybrid method combining the Short-term Flood-Drought Abrupt Alternation Index and the Standardized Runoff Index. A multi-objective optimization model solved by NSGA-III was employed to determine staged DLWLs across five operational periods with tiered thresholds prioritizing urban, ecological, and irrigation water demands. Results show that FDAA events are mainly concentrated in June–October and have intensified significantly since 2010. Compared with conventional operation, the optimized DLWL framework substantially improves irrigation water supply reliability and reservoir fullness, while maintaining urban and ecological water supply security. Validation during typical wet years indicates that the proposed strategy introduces no evident reduction in flood control safety. Full article