Search Results (14,017)

Distributed energy systems have gained increasing popularity due to their plethora of benefits. However, their evaluation in terms of reliability mostly concerns the time frequency domain, and, thus, merits associated with the spatial scale are often overlooked. A recent study highlighted the benefits of distributed production over centralized one by establishing a spatial reliability framework and stress-testing it for decentralized solar photovoltaic (PV) generation. This work extends and verifies this approach to wind energy systems while also highlighting additional challenges for implementation. These are due to the complexities of the non-linear nature of wind-to-power conversion, as well as to wind turbine siting, and turbine model and hub height selection issues, with the last ones strongly depending on local conditions. Leveraging probabilistic modeling techniques, such as Monte Carlo, this study quantifies the aggregated reliability of distributed wind power systems, facilitated through the capacity factor, using Greece as an example. The results underscore the influence of spatial complementarity and technical configuration on generation adequacy, offering a more robust basis for planning and optimizing future wind energy deployments, which is especially relevant in the context of increasing global deployment. Full article

With climate change, the frequency and severity of localized heavy rainfalls are increasing. Thus, for urban drainage networks (UDNs), particularly those in aging cities such as Seoul, Republic of Korea, flood risk management challenges are mounting. Conventional design standards typically apply uniform roughness coefficients based on new pipe conditions, neglecting the ongoing performance degradation from physical influences. This study introduces a methodology that systematically incorporates pipe age and size into roughness coefficient scenarios for higher-accuracy 1D–2D rainfall–runoff hydrologic–hydraulic simulations. Eleven roughness scenarios (a baseline and ten aging-based scenarios) are applied across seven UDNs using historical rainfall data. The most representative scenario (S3) is identified using a Euclidean distance metric combining the peak water-level error and root mean square error. For two rainfall events, S3 yields substantial increases in the simulated mean flood volumes (75.02% and 76.45%) compared with the baseline, while spatial analysis reveals significantly expanded inundation areas and increased flood depths. These findings underscore the critical impact of pipe deterioration on hydraulic capacity and demonstrate the importance of incorporating aging infrastructure into flood modeling and UDN design. This approach offers empirical support for updating UDN design standards for more resilient flood management. Full article

This study illustrates the complex interaction between environmental parameters and carbonate distribution in marine sediments along the Tarfaya–Boujdour coastline (26–28° N) of Northwest Africa. Analysis of 21 surface sediment samples and their associated bottom water properties (salinity, temperature, dissolved oxygen, nutrients) reveals CaCO₃ content ranging from 16.8 wt.% to 60.5 wt.%, with concentrations above 45 wt.% occurring in multiple stations, especially in nearshore deposits. Mineralogy indicates a general decrease in quartz, with an arithmetic mean and standard deviation of 52.5 wt.% ± 19.8 towards the open sea, and an increase in carbonate minerals (calcite ≤ 24%, aragonite ≤ 10%) with depth. Sediments are predominantly composed of fine sand (78–99%), poorly classified, with gravel content reaching 6.7% in energetic coastal stations. An inverse relationship between organic carbon (0.63–3.23 wt.%) and carbonates is observed in upwelling zones, correlated with nitrate concentrations exceeding 19 μmol/L. Hydrological gradients show temperatures from 12.41 °C (offshore) to 21.62 °C (inshore), salinity from 35.64 to 36.81 psu and dissolved oxygen from 2.06 to 4.21 mL/L. The weak correlation between carbonates and depth (r = 0.10) reflects the balance between three processes: biogenic production stimulated by upwelling, dilution by Saharan terrigenous inputs, and hydrodynamic sorting redistributing bioclasts. These results underline the need for models integrating hydrology, mineralogy and hydrodynamics to predict carbonate dynamics in desert margins under upwelling. Full article

The construction of the Xinyang Urban Water Supply Project, centered on the Chushandian Reservoir, required a thorough investigation of high–low runoff encounters between the water source and receiving areas to optimize water allocation and operational scheduling. Based on the hydrological stations at Changtaiguan (CTG) on the main stream of the Huaihe River (HR) in the water source area and Miaowan (MW) on the main stream of the Honghe River in the receiving area, the trends and abrupt change characteristics of monthly runoff from 2014 to 2024 were analyzed using methods such as extremum symmetry mode decomposition (ESMD) and heuristic segmentation, with spatial encounter patterns determined using Copula functions. The results indicate that (1) the runoff in the water source area showed a quasi-6.05-month periodic characteristic on a monthly scale, while the runoff in the receiving area exhibited a quasi-6.72-month periodic characteristic on a monthly scale; (2) the water source area experienced runoff mutation in August 2015 (extreme drought) and June 2024 (extreme precipitation), with the receiving area responding 7 months earlier than the water source area, revealing differences in system vulnerability; (3) synchronous hydrological states were significantly more likely to occur (51.2%) compared with asynchronous conditions (25.2%), with the highest probability of “concurrent drought” (19.8%) and a high-risk “normal water source—receiving area drought” combination (14.1%). These findings provide theoretical and technical support for the optimized scheduling of the Chushandian Reservoir, improving the resilience and adaptability of the Xinyang Urban Water Supply Project to climate fluctuations and extreme hydrological events. Full article

This study aims to analyze the relationships between concerns and sentiments of stakeholders and the drought stage in a semi-arid region of Ceará from Language Technologies based on Artificial Intelligence. The dataset comprises 36 meeting minutes of water management bodies (2007–2024), of which 17 correspond to dry periods and 19 to normal periods (reservoir volume > 50%). Natural Language Processing (NLP) techniques were applied to generate word clouds, and sentiment analysis was performed using a Large Language Model (Llama 3.2, 3B). Sentiment scores were compared with reservoir volume data. Results show that both perceptions and themes differed between drought and normal phases, with higher water availability coinciding with more positive sentiments. A moderate positive correlation was found between sentiment and reservoir volume (r = 0.53, p = 0.00095, 95% CI [0.24, 0.73]). Statistical tests confirmed differences between periods (Welch’s t-test, p = 0.0018; Mann-Whitney, p = 0.0039). Box-plot analyses indicated that over 75% of sentiments were positive in normal phases, while about 65% were negative in drought phases. These findings highlight the sensitivity of human perceptions to hydrological conditions and point to the potential of LLMs as innovative instruments for integrating qualitative data into complex socio-environmental analyses. Full article

Preferential flow in coal mining subsidence areas leads to shallow soil moisture loss, vegetation reducing and ecological degradation. However, the factors influencing the development of preferential flow remain unclear. This study analyzed the morphological characteristics of preferential flow using a staining tracer test in coal mining subsidence areas along the middle reaches of the Yellow River Basin. Characteristic parameters including the dye-stained area ratio, preferential flow ratio, length index, variation coefficient were comparatively evaluated under different initial soil moisture conditions. Results showed that shallow soils exhibited substrate flow, while preferential flow occurred in deeper soil layers below the matrix flow. As initial soil moisture increased, the extent of both substrate flow and preferential flow decreased. The dye-stained area ratio declined with increasing soil depth, and the relationship between dye-stained area and soil layer depth was best described by a cubic function. Higher initial soil moisture reduced maximum infiltration depth and length indices while increasing the coefficient of the stained pattern. Furthermore, a higher of initial soil water content corresponded to a lower preferential flow index. Overall, increased initial soil moisture may reduce the extent of preferential flow and the rapid infiltration of water into soil. These findings provides a basis for further hydrological studies in coal mining subsidence areas in arid and semi-arid regions and offer scientific support for ecological restoration efforts in mining areas. Full article

This review examines South Africa’s escalating flood vulnerability through a synthesis of over 80 peer-reviewed articles, historical records, policy reports, and case studies. Using a PRISMA-guided analysis, the study identifies key climatic drivers, including extreme rainfall from tropical–temperate interactions, cut-off lows, and La Niña conditions that interact with structural weaknesses such as inadequate drainage, poorly maintained stormwater systems, and rapid urban expansion. Apartheid-era spatial planning has further entrenched risk by locating marginalised communities in floodplains. Governance failures like weak disaster risk reduction (DRR) policies, fragmented institutional coordination, and insufficient early warning systems intensify flood vulnerabilities. Catastrophic events in KwaZulu-Natal (KZN) and the Western Cape (WC) illustrate the consequences exemplified by the April 2022 KZN floods alone, which caused over 450 deaths, displaced more than 40,000 people, and generated damages exceeding ZAR 17 billion. Nationally, more than 1500 flood-related fatalities have been documented in the past two decades. Emerging resilience pathways include ecosystem-based adaptation, green infrastructure, participatory governance, integration of Indigenous knowledge, improved hydrological forecasting, and stricter land-use enforcement. These approaches can simultaneously reduce physical risks and address entrenched socio-economic inequalities. However, significant gaps remain in spatial flood modelling, gender-sensitive responses, urban–rural disparities, and policy implementation. The review concludes that South Africa urgently requires integrated, multi-scalar strategies that combine scientific innovation, policy reform, and community-based action. Embedding these insights into disaster management policy and planning is essential to curb escalating losses and build long-term resilience in the face of climate change. Full article

Urbanization is a driving force of landscape transformation. One of the ecosystems most vulnerable to urban expansion processes is montane forests located in high altitude mountainous regions. Despite their significance for biodiversity, regulation of the hydrological cycle, stability, prevention of soil erosion, and potential for organic carbon storage, these forest ecosystems show high vulnerability and risk due to the global urbanization process. We analyzed the potential variations produced by land cover change in some attributes related to soil organic matter in transitional forest fragments due to the expansion of a predominantly urban matrix landscape. We identified and characterized a fragment of a high montane evergreen forest in the Western Cordillera of the Northern Andes located in the urban limits of Quito. Then, we comparatively analyzed the variations in the attributes associated with soil organic carbon: soil organic matter, density, texture, nitrogen, phosphorus, and pH. We also considered the following soil coverages: forest, eucalyptus plantations, and grassland. We viewed the latter two as hinge coverages between forests and urban expansion. Finally, we estimated variations in soil organic carbon stock in the three analyzed coverages. For the montane forest fragment, we identified 253 individuals distributed among 18 species, corresponding to 10 families and 14 genera. We found significant variations in soil attributes associated with organic matter and an estimated 66% reduction in the carbon storage capacity of montane soils when they lose their natural cover and are replaced by Eucalyptus globulus plantations. Urban planning strategies should consider the conservation and restoration of natural and degraded peri-urban areas, ensuring sustainability and utilizing nature-based solutions for global climate change adaptation and mitigation. Peri-urban agroforestry systems represent an opportunity to replace and restore conventional forestry or crop plantation systems in peri-urban areas that affect the structure and function of ecosystems and, therefore, the goods and services derived from them. Full article

Understanding spatial variability in crop yields across fields is critical for developing precision agricultural strategies that optimize productivity while reducing negative environmental impacts. This variability often arises from a complex interplay of topographic features, soil characteristics, and hydrological conditions. This study investigates the influence of hydro-topographic factors on corn and soybean yield variability from 2016 to 2023 at the well-managed experimental sites in Beltsville, Maryland. A high-resolution surface digital elevation model (DEM) and subsurface DEM derived from ground-penetrating radar (GPR) were used to quantify topographic factors (elevation, slope, and aspect) and hydrological factors (surface flow accumulation, depth from the surface to the subsurface-restricting layer, and distance from each crop pixel to the nearest subsurface flow pathway). Topographic variables alone explained yield variation, with a relative root mean square error (RRMSE) of 23.7% (r² = 0.38). Adding hydrological variables reduced the error to 15.3% (r² = 0.73), and further combining with remote sensing data improved the explanatory power to an RRMSE of 10.0% (r² = 0.87). Notably, even without subsurface data, incorporating surface-derived flow accumulation reduced the RRMSE to 18.4% (r² = 0.62), which is especially important for large-scale cropland applications where subsurface data are often unavailable. Annual spatial yield variation maps were generated using hydro-topographic variables, enabling the identification of long-term persistent yield regions (LTRs), which served as stable references to reduce spatial anomalies and enhance model robustness. In addition, by combining remote sensing data with interannual meteorological variables, prediction models were evaluated with and without hydro-topographic inputs. The inclusion of hydro-topographic variables improved spatial characterization and enhanced prediction accuracy, reducing error by an average of 4.5% across multiple model combinations. These findings highlight the critical role of hydro-topography in explaining spatial yield variation for corn and soybean and support the development of precise, site-specific management strategies to enhance productivity and resource efficiency. Full article

This study assesses the impact of climate change and glacier retreat on river runoff in the high-altitude Terek River Basin using the physically based ECOMAG hydrological model. Sensitivity experiments examined the influence of glaciation, precipitation, and air temperature on runoff variability. Results indicate that glacier retreat primarily affects streamflow in upper reaches during peak melt (July–October), while precipitation changes influence both annual runoff and peak flows (May–October). Rising temperatures shift snowmelt to earlier periods, increasing runoff in spring and autumn but reducing it in summer. The increase in autumn runoff is also due to the shift between solid and liquid precipitation, as warmer temperatures cause more precipitation to fall as rain, rather than snow. Scenario-based modeling incorporated projected glacier area changes (GloGEMflow-DD) and regional climate data (CORDEX) under RCP2.6 and RCP8.5 scenarios. Simulated runoff changes by the end of the 21st century (2070–2099) compared to the historical period (1977–2005) ranged from −2% to +5% under RCP2.6 and from −8% to +14% under RCP8.5. Analysis of runoff components (snowmelt, rainfall, and glacier melt) revealed that changes in river flow are largely determined by the elevation of snow and glacier accumulation zones and the rate of their degradation. The projected trends are consistent with current observations and emphasize the need for adaptive water resource management and risk mitigation strategies in glacier-fed catchments under climate change. Full article

Excessive nitrogen export from lowland polders is a key contributor to cultural eutrophication in downstream aquatic ecosystems. This study investigated the spatiotemporal characteristics, migration pathways, and sources of nitrogen pollution in a typical polder system. Eight surface water sampling campaigns were conducted at 13 sites in Quyuan Polder, Dongting Lake, from 2022 to 2023, combining ArcGIS spatial analysis, multivariate statistics, and dual-isotope (δ¹⁵N-NO⁻), δ¹⁸O-NO₃⁻) techniques. Nitrate and ammonium nitrogen dominated the nitrogen pool, accounting for ~76% of total nitrogen. Concentrations were higher in the dry season (2.48 mg/L) than in the wet season (1.89 mg/L) and differed significantly among hydrological periods (p < 0.05). Within the polder, total nitrogen and ammonium nitrogen were elevated, whereas nitrate nitrogen was higher at the outlet, reflecting distinct nitrogen profiles along the hydrological gradient. Nitrogen transport patterns were largely consistent with flow direction, driven by both upstream inputs and in situ generation. Isotopic signatures indicated that nitrate originated mainly from ammonium fertilizer and soil nitrogen, with contributions from manure and sewage. These findings enhance understanding of nitrogen dynamics in lowland catchments and provide a scientific basis for targeted pollution control in polder waters. Full article

Modern artificial intelligence methods are increasingly applied in hydrology, particularly for forecasting water inflow into reservoirs. However, their limited interpretability constrains practical deployment in critical water resource management systems. Explainable AI offers solutions aimed at increasing the transparency of models, which makes the topic relevant in the context of developing sustainable and trusted AI systems in hydrology. Articles published in leading scientific journals in recent years were selected for the review. The selection criteria were the application of XAI methods in hydrological forecasting problems and the presence of a quantitative assessment of interpretability. The main attention is paid to approaches combining LSTM, GRU, CNN, and ensembles with XAI methods such as SHAP, LIME, Grad-CAM, and ICE. The results of the review show that XAI mechanisms increase confidence in AI forecasts, identify important meteorological features, and allow analyzing parameter interactions. However, there is a lack of standardization of interpretation, especially in problems with high-dimensional input data. The review emphasizes the need to develop robust, unified XAI approaches that can be integrated into next-generation hydrological models. Full article

Estimating the impacts of climate change on streamflow in the Xiaoxingkai Lake Basin is vital for ensuring sustainable water resource management and transboundary cooperation across the entire Xingkai Lake Basin, a transboundary lake system shared between China and Russia. In this study, 11 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways (SSP245 and SSP585) were used to drive the Soil and Water Assessment Tool Plus (SWAT+) model. Streamflow projections were made for two future periods: the 2040s (2021–2060) and the 2080s (2061–2100). To correct for systematic biases in the GCM outputs, we applied the Delta Change method, which significantly reduced root mean square error (RMSE) in both precipitation and temperature by 3–35%, thereby improving the accuracy of SWAT+ simulations. To better capture inter-model variability and enhance the robustness of streamflow projections, we used the Bayesian Model Averaging (BMA) technique to generate a weighted ensemble, which outperformed the simple arithmetic mean by reducing uncertainty across models. Our results indicated that under SSP245, greater increases were projected in annual streamflow as well as in wet and normal-flow seasons (e.g., streamflow in normal-flow season in the 2080s increased by 13.0% under SSP245, compared to 7.0% under SSP585). However, SSP585 produced a much larger relative amplification in the dry season, with percentage changes relative to the historical baseline reaching up to +171.7% in the 2080s, although the corresponding absolute increases remained limited due to the low baseline flow. These findings quantify climate-driven hydrological changes in a cool temperate lake basin by integrating climate projections, hydrological modeling, and ensemble techniques, and highlight their implications for understanding hydrological sustainability under future climate scenarios, providing a critical scientific foundation for developing adaptive, cross-border water management strategies, and for further studies on water resource resilience in transboundary basins. Full article

This study aims to analyse the effect of partially clogged inlets on the behaviour of urban drainage systems at the city scale, particularly regarding intercepted volumes and flood depths. The main challenges were to represent the inlet network in detail at a rather large scale and to avoid the effect of sewer network surcharging on the draining capacity of inlets. This goal has been achieved through a 1D/2D coupled hydraulic model of the whole urban drainage system in La Almunia de Doña Godina (Zaragoza, Spain). The model focuses on the interaction between grated drain inlets and the sewer network under partial clogging conditions. The model is fed with data obtained on field surveys. These surveys identified 948 inlets, classified into 43 types based on geometry and grouped into 7 categories for modelling purposes. Clogging patterns were derived from field observations or estimated using progressive clogging trends. The hydrological model combines a semi-distributed approach for micro-catchments (buildings and courtyards) and a distributed “rain-on-grid” approach for public spaces (streets, squares). The model assesses the impact of inlet clogging on network performance and surface flooding during four rainfall scenarios. Results include inlet interception volumes, flooded surface areas, and flow hydrographs intercepted by single inlets. Specifically, the reduction in intercepted volume ranged from approximately 7% under a mild inlet clogging condition to nearly 50% under severe clogging conditions. Also, the model results show the significant influence of the 2D mesh detail on flood depths. For instance, a mesh with high resolution and break lines representing streets curbs showed a 38% increase in urban areas with flood depths above 1 cm compared to a scenario with a lower-resolution 2D mesh and no curbs. The findings highlight how inlet clogging significantly affects the efficiency of urban drainage systems and increases the surface flood hazard. Further novelties of this work are the extent of the analysis (city scale) and the approach to improve the 2D mesh to assess flood depth. Full article

Riverbank erosion poses a significant threat to livelihoods and infrastructure in the Vietnamese Mekong Delta (VMD), necessitating innovative and sustainable solutions. This study explores the use of old tyres as a material for embankment construction to stabilize riverbanks, combining physical reinforcement with bioengineering techniques. A pilot project was conducted in Dinh My commune, An Giang Province, where an embankment was constructed using old tyres, geotextile, riprap, and vegetation. Field measurements using the Leica TS02 Plus Total Station and Finite Element Method (FEM) modeling were employed to assess the embankment’s performance. Results indicate that the embankment effectively stabilized the riverbank, with a maximum displacement of 18 mm observed after one year. The FEM predictions closely aligned with the measured data, achieving an accuracy of 68% or higher, validating the model’s accuracy. The integration of vegetation further enhanced stability, demonstrating the potential of this approach as a sustainable and cost-effective solution for riverbank protection. This study highlights the dual benefits of erosion control and waste management, offering a replicable strategy for addressing riverbank erosion across deltaic and lowland regions. The pilot offers a scalable model for climate-resilient infrastructure in deltaic regions globally, linking erosion control with circular economy strategies. Full article