Search Results (533)

Background/Objectives: The period between 12 and 16 years of age coincides with peak pubertal change, declining habitual physical activity, and the consolidation of lifelong behavioral patterns, making it a critical window for understanding how fitness develops and how stable (or unstable) it is over time. This review aims to synthesize longitudinal evidence addressing how HRPF changes and tracks in adolescents aged approximately 12 to 16 years, the sex- and maturation-related modifiers of these patterns, the methodological approaches used to assess them, and the secular and behavioral context within which they occur. Methods: A structured narrative review was conducted searching four electronic databases—Google Scholar, PubMed, Web of Science, and Scopus—using terms combining concepts of adolescence, health-related physical fitness, and longitudinal study design published up to April 2026. Reference lists of retrieved systematic reviews and meta-analyses were snowball-searched. Eligible studies employed longitudinal or repeated-measures designs in samples overlapping the 12–16-year age range; no formal risk-of-bias appraisal or quantitative pooling was undertaken, consistent with the narrative-review design. Findings were synthesized narratively by HRPF component and thematic domain. Results: Cardiorespiratory fitness rises through early adolescence before plateauing or declining from approximately age 15 in one longitudinal cohort, more markedly in boys; muscular power and strength diverge increasingly by sex, a pattern consistent with androgen-mediated gains in lean mass in boys, although this mechanism was not directly tested here; flexibility remains the most stable component; and body composition acts as both an outcome and a determinant of other fitness test performance. Within-adolescence tracking is moderate-to-high for most components in the single available 3-year cohort of adolescent girls that reported component-specific tracking coefficients (e.g., lower-limb power β = 0.98, aerobic endurance β = 0.75, trunk muscular endurance β = 0.51), and substantially stronger than tracking from childhood into adolescence. Secular trends indicate population-level fitness has declined in many countries over recent decades, with adolescents showing greater decline than children. Conclusions: Early-to-mid adolescence appears to be a critical and time-limited opportunity to consider for fitness-promoting intervention: fitness rank is still somewhat malleable, but shows progressively stronger tracking with age—a pattern of rank stability that should not itself be read as evidence about responsiveness to intervention. Methodological heterogeneity in test batteries, follow-up duration, and tracking statistics limits direct comparability across studies. Future research should incorporate maturity-status indicators, multi-wave designs, and harmonized assessment protocols. Full article

Multi-decadal trajectories of large arid-zone reservoirs are seldom described by integrated satellite observation. This study characterises the optical and thermal variability of Lake Nasser, Egypt, over 2005–2025. Eight monthly MODIS indicators—NDVI, EVI, NDWI, NDTI, a near-infrared reflectance index, white-sky albedo, and day- and night-time land surface temperature (LST)—together with the derived diurnal temperature range (DTR), were compiled in Google Earth Engine over 186 cells of a 5 km grid and analysed by non-parametric trend, change-point and correlation procedures under false-discovery-rate control, correction for serial correlation, and effective-sample-size significance testing. Because a fixed polygon cannot separate environmental change from shoreline migration, every trend was recomputed on four domains of decreasing shoreline exposure. Three signals survive on all four: night-time LST rises (+0.51 to +0.76 °C decade⁻¹), DTR contracts (−0.83 to −1.95 °C decade⁻¹) and albedo declines (−0.0034 to −0.0193 decade⁻¹). The NDVI, EVI, near-infrared and day-time LST declines that the fixed polygon reports are not reproduced under the control, whereas NDWI declines (−0.048 to −0.077 decade⁻¹) only once it is applied. Change-point tests date a shift in level to 2016–2017, three years before the first filling of the Grand Ethiopian Renaissance Dam. Full article

This decade-long surveillance study (2016–2025) investigates the acquisition of multidrug-resistant (MDR) bacteria in South Atlantic cetaceans to evaluate how ecological niches modulate exposure to biological pollution. Analyzing clinical isolates from stranded cetacean carcasses (n = 346), we used Generalized Linear Mixed-Effects Models (GLMMs) to mitigate multi-center analytical biases and compare resistance profiles across coastal and oceanic species. We observed a significant, progressive upward trend in the overall MDR probability over the decade. Although raw MDR was higher in the demersal-feeding Pontoporia blainvillei (58.2%) than in the sympatric, water-column-foraging Sotalia guianensis (22.0%), multivariate modeling revealed that this difference was primarily driven by the geographic stranding location rather than by intrinsic foraging ecology. High gastrointestinal MDR (73.9%) suggests dietary intake as a primary biological gateway. Demographic modeling revealed a significant sex-based association in P. blainvillei, with females facing a higher risk (p = 0.009), although the specific ecological or physiological mechanisms underlying this difference remain unknown. High MDR rates in deep-diving Lagenodelphis hosei (70.8%) and Kogia breviceps (67.9%) suggest that resistant pathogens may reach bathypelagic food webs, potentially via vertical trophic pathways. These findings suggest that spatial environmental contamination, alongside foraging and reproductive ecologies, is a key driver of exposure to the anthropogenic resistome. Because carcass-based sampling inherently targets a diseased or senescent fraction, these high prevalences may overestimate the resistome burden of healthy free-ranging populations. The detection of human pathogens across coastal and offshore habitats indicates persistent deficiencies in terrestrial effluent management, reinforcing cetaceans as One Health sentinels. Full article

Forest fires are among the most critical disturbance agents reshaping Mediterranean ecosystems under accelerating climate change. This study employs a multi-scale remote sensing approach to examine the relationship between post-fire vegetation dynamics and climate variability in high-fire-risk areas of southern İzmir, Türkiye. Burned areas were delineated using the Burned Area Index (BAI) and differenced Normalized Burn Ratio (dNBR) applied to Landsat imagery (1990–2024) and Sentinel-2 imagery (2017–2024). Post-fire vegetation recovery was quantified through the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Vegetation Condition Index (VCI), Leaf Area Index (LAI), and Land Surface Temperature (LST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) products. Climate variables, including soil moisture, precipitation, and maximum, minimum, and mean air temperature, were derived from the TerraClimate dataset. Long-term spatiotemporal trends were assessed using the non-parametric Mann–Kendall (MK) test and Sen’s slope estimator for the 2000–2023 period. Results indicate a statistically significant increase in mean temperature (p < 0.05) and a concurrent decline in soil moisture over the past three decades, consistent with progressive atmospheric aridification. Vegetation indices exhibited marked seasonal asymmetry: significant declines in NDVI, SAVI, and LAI were recorded during summer months, whereas partial recovery was confined to the winter–spring wet season. A pronounced warm-dry shift was identified in the post-2015 period, characterized by positive Land Surface Temperature anomalies and compressed vegetation recovery windows. These findings highlight that increasing thermal stress and diminishing soil moisture collectively constrain post-fire ecosystem resilience in the Mediterranean climatic zone (MCZ). The integrated remote sensing framework developed here provides a robust and transferable basis for fire ecosystem monitoring and the formulation of climate adaptation strategies in fire-prone dryland regions. Full article

Surface solar radiation (SSR) is a fundamental component of the Earth’s energy budget, driving climate dynamics, ecosystem stability, and solar energy potential. By integrating high-quality in situ observations from 87 ground stations with multi-source satellite products (CERES) and reanalysis data, this study systematically quantifies the spatiotemporal evolution and driving mechanisms of SSR across China from 1994 to 2022. Nationally, SSR exhibits a significant brightening trend of 72 MJ m⁻² per decade, despite pronounced regional and seasonal divergence. Annual SSR increases significantly in North, Central, Southwest, and South China—with North China experiencing the fastest growth (160 MJ m⁻² per decade). Strikingly, the Tibetan Plateau exhibits a persistent and significant “dimming” trend (−86 MJ m⁻² per decade). Furthermore, spatial analysis reveals that summer SSR trends show a unique meridional “+ − +” dipole structure that closely resembles the dominant mode of summer precipitation over eastern China. Quantitative attribution analysis indicates that declining aerosol optical depth (AOD) is the primary driver of brightening across most of China, whereas the dimming on the Tibetan Plateau is specifically triggered by increased atmospheric water vapor, cloud cover, and precipitation. These findings underscore that in sensitive high-altitude regions, regional climate dynamics and hydrological feedback can override the radiative effects of anthropogenic aerosol reductions, highlighting the necessity for localized solar resource assessments. Full article

Against the backdrop of accelerating globalization and the reconfiguration of ecological security patterns, border regions—serving as critical carriers of national spatial governance—exhibit pronounced spatial heterogeneity and stage-dependent characteristics in land use evolution that warrant systematic investigation. This study focuses on global border zones to reveal the trends and evolutionary pathways of land use change, thereby providing a scientific basis for border spatial governance. Using the period of 1992–2020, four phases of global land cover data from the European Space Agency (ESA) were employed. Buffer zones of 50 km, 100 km, and 150 km were established along global national boundaries, and the study period was divided into three decadal stages. Border types were classified into terrestrial borders, coastal borders, and island borders. An integrated indicator system was constructed, including the Single Land Use Dynamic Degree (SLUDD), Integrated Land Use Dynamic Degree (ILUDD), and Weighted Composite Transition Intensity. A multi-scale nested analytical framework coupled with transition matrices was applied to assess land use evolution across global, continental, and bilateral national scales. The results indicate the following: (1) Distinct evolutionary pathways exist among border types. Terrestrial borders exhibit a combination of development and ecological restoration, with staged peaks in urban expansion; coastal borders are dominated by a unidirectional conversion from cropland to built-up land; and island borders demonstrate concurrent agricultural decline, ecological recovery, and built-up expansion. (2) From 1992 to 2020, global border land use underwent a transition from high-intensity transformations to low-intensity steady adjustments. Major changes were centered on the expansion of production space, outward diffusion of built-up areas, and vegetation restructuring. High-intensity changes were concentrated near boundary zones and attenuated significantly with increasing buffer distance. (3) At the continental scale, stable hierarchical patterns emerge in terms of change intensity, spatial gradients, and transition structures. Borders in Eurasia and North America show higher activity, Africa exhibits widespread diffusion, and South America and Oceania are characterized by forest boundary reshaping and vegetation adjustments, respectively. (4) Typical border regions can be categorized into three evolutionary types: forest ecological frontiers, agricultural expansion zones, and land–sea composite corridors. Regional trajectories vary significantly, with Southeast Asia transitioning rapidly toward stabilization, West Africa retaining periodic high-intensity disturbances, and South America remaining in a low-intensity adjustment state. This study clarifies the evolutionary patterns and boundary effect ranges of global border land use, providing theoretical support and empirical references for resource allocation and ecological regulation in border regions. It also lays the groundwork for refining border typologies, quantifying driving mechanisms, and developing differentiated cross-border governance strategies. Full article

Amidst the intensification of strategic mineral exploration, the discovery of concealed and deep-seated deposits within covered areas and the peripheries of existing mines has become a critical challenge and a central focus of contemporary research. “Dongchuan-type” (DCT) copper deposits represent a key mineralization style within the SW Yangtze Block. However, significant exploration breakthroughs have stagnated over the past three decades. Consequently, advanced exploration prediction research is urgently required to guide deep-resource evaluation. Using the Shizishan copper deposit in the Yimen area as a representative case, this study applies the theory of “metallogenic geological body prediction” to construct a tripartite model encompassing “metallogenic geological bodies, metallogenic structures and structural planes, and metallogenic characteristic markers”. The Shizishan deposit is classified as a sedimentary-reformed type, characterized by multi-episodic mineralization involving initial sedimentary processes, non-magmatic hydrothermal activity, and subsequent structural-magmatic hydrothermal overprinting. Key metallogenic geological bodies include ore-bearing stratigraphic associations, basin-margin faults, NE-trending fold–fault systems, and deep-seated concealed intrusions. Metallogenic structural planes comprise primary ore-controlling surfaces, secondary fold-related structures, and potential deep-seated magmatic intrusive interfaces. Alteration patterns display a distinct vertical zonation: shallower levels show medium-to-low temperature hydrothermal processes (silicification, carbonatization, sericitization, and chloritization), whereas deeper portions reveal high-temperature magmatic–hydrothermal indicators, specifically skarnization and intense silicification. This study proposes that the integration of “stratigraphy + structures + concealed intrusions” should serve as the primary criterion for target screening in deep exploration. By integrating geophysical and geochemical datasets into this model, three promising exploration targets were delineated within the Yimen area. These findings provide a refined theoretical framework for large-scale prospecting of DCT. Full article

The analysis of beams resting on elastic foundations has attracted significant attention in structural and mechanical engineering due to its extensive applications in different domains. Beams on elastic foundations interact continuously with deformable media. To represent this interaction mathematically, researchers have developed a variety of single-parameter, two-parameter and three-parameter models as well as continuous models. Among the structural elements employed to investigate these models, functionally graded material (FGM) beams have emerged as an attractive platform due to their continuously varying material properties and extensive use in modern engineering applications. Over the past two decades, extensive research has been conducted on the behavior of graded beams resting on elastic foundations using various beam theories, foundation models and analytical as well as numerical solution techniques. The present paper puts forward a detailed review of the existing literature concerning static bending, buckling, free and forced vibration analyses of FG beams supported by elastic foundations. Various material gradation schemes, including power law, exponential, sigmoid, porous and carbon nanotube-reinforced FGMs, are discussed. The review further examines the application of different classical foundation models, such as the Winkler, Pasternak, Kerr and Vlasov models. These classical models may be linear or nonlinear depending on the nature of the foundation medium. A comparative evaluation of the available studies is provided to identify current trends and limitations. Finally, potential future research directions involving multi-physics coupling, advanced foundation modelling, machine-learning-assisted prediction and micro/nanoscale applications are highlighted. The review aims to serve as a valuable reference for researchers and engineers working in the field of FG beams interacting with elastic foundations. Full article

Image steganography is an information-hiding technique, aiming to achieve confidentiality and data privacy while transmitting the data in a digital environment. Over the last two decades, steganography has evolved from classical spatial domain embedding to intelligent and adaptive steganographic systems capable of balancing imperceptibility, embedding capacity, robustness and security. This paper presents a review by categorizing the existing techniques into spatial domain-based, transform domain-based, hybrid and adaptive intelligent techniques. The review follows the PRISMA approach to make the selection process transparent for the inclusion and exclusion of papers in the study. Initially, the reviews include the spatial domain-based methods focusing on higher embedding capacity and simple embedding strategy, followed by transform-domain based techniques, including discrete cosine transform, discrete wavelet transform, and other multi-resolution wavelet transforms aiming to enhance robustness and imperceptibility by embedding the data into frequency coefficients. This paper further explores the methods that combine these techniques with other recent trends to develop adaptive and hybrid techniques. These techniques mainly integrate chaotic theory to enhance the security of secret data before embedding and optimization algorithms such as genetic algorithm, particle swarm optimization, Firefly, etc., for adaptive embedding to achieve an improved tradeoff. Finally, intelligent and adaptive techniques based on deep learning models such as convolutional neural networks, autoencoders, and generative adversarial networks are examined, highlighting their ability to learn intelligent embedding strategies and resist modern steganalysis. A comparative analysis is presented, including the technique, strengths, and limitations, together with the discussion of performance evaluation metrics and vulnerability analysis under image processing attacks. The review highlights the current trends and outlines the future direction to develop next-generation secure image steganographic systems. Full article

Tropical lake ecosystems are vulnerable to degradation due to climate change and anthropogenic pressure. These dual pressures lead to ecological change and alterations in aquatic parameters, including chlorophyll-a (Chl-a). Lake Poso is the third-largest lake in Indonesia; Chl-a variability and phenology in this tropical lake remain understudied due to brief observational records. This study characterizes the spatiotemporal variability and phenology of Chl-a in Lake Poso, Indonesia, over two decades (2003–2025) to establish a multi-decadal baseline and detect early indications of increasing phytoplankton biomass. Chl-a was derived from combined Terra and Aqua MODIS observations processed in Google Earth Engine, followed by trend, phenological, and spatial analyses. Results reveal a significant increase in annual Chl-a and a general upward tendency across the study period. Climatological reconstruction identifies a distinct bimodal phenology, with a primary peak in December and a secondary peak in April. Interannual trends show no significant shift in Start of Season timing; however, primary peak magnitudes tend to increase (+0.079 mg m⁻³ yr⁻¹), largely influenced by extreme episodic anomalies. Spatial analysis reveals heterogeneous increases in Chl-a, particularly in the central and northern zones. These findings suggest a possible early trajectory toward higher phytoplankton biomass and establish the first satellite-derived multi-decadal Chl-a baseline for Lake Poso. Full article

Abu Dhabi Sabkha, located along the southern margin of the Arabian Gulf, is among the most scientifically significant arid coastal systems on Earth. Submitted by the United Arab Emirates to the UNESCO World Heritage Tentative List in 2018 under natural heritage criterion (viii), the site is currently the only documented coastal sabkha where all four diagnostic sedimentary layers, lagoon mud, microbial mat, gypsum mud, and anhydrite nodules, co-occur within a single coastal setting, south of Al Dhabaya and Abu Al Abyadh Islands. This review evaluates Abu Dhabi Sabkha as a geological heritage system by synthesizing its formation processes, UNESCO significance, complete sabkha sequence, microbial and evaporite processes, climatic setting, environmental sensitivity, and conservation requirements. The site operates under a hyper-arid climatic regime with a documented warming trend of +0.43 °C per decade over 1981–2025 (NASA POWER MERRA-2), confirming that the evaporative processes sustaining its geological record are intensifying. Microbial mats facilitate dolomite mineralization via Extracellular Polymeric Substances at a scale unmatched elsewhere in the Arabian Gulf, while gypsum mud and anhydrite nodules record advanced supratidal evaporitic development. Comparative analysis with sabkha systems in Qatar, Kuwait, Saudi Arabia, and Oman confirms that no other regional coastal sabkha preserves equivalent stratigraphic completeness within a single, actively forming setting. The site faces mounting pressures from urban expansion, coastal reclamation, off-road vehicle movement, groundwater modification, and the increasing frequency of extreme rainfall events, all of which can permanently damage fragile surface structures and microbial systems. Sustainable conservation requires protection zoning, controlled access, multi-scale satellite and drone monitoring, groundwater tracking, and integration into coastal planning frameworks. Abu Dhabi Sabkha should be recognized not as marginal saline terrain, but as a globally important geoheritage system whose scientific value depends on the active preservation of biological, chemical, and physical processes operating together within an irreplaceable coastal setting. Full article

Understanding long-term changes in agricultural landscapes is essential for assessing the sustainability of land-use systems and guiding agro-environmental policy. This study analyzes three decades of landscape simplification and natural habitat complexity (1990–2018) across three spatial scales—Europe, Spain, and Extremadura—using CORINE Land Cover data and generalized additive models (GAMs). Four agricultural systems were examined: total agriculture, vineyards, olive groves, and rice fields. For each year and region, 1000 randomly selected 1 km buffers were used to quantify the proportions of focal crops and natural habitat as indicators of landscape simplification and complexity, respectively. Results showed that landscape simplification was widespread and statistically significant across most agricultural systems, particularly in Spanish vineyards (p = 3.02 × 10⁻⁵) and rice fields (p = 3.74 × 10⁻⁵). Temporal analyses indicated declining simplification trends in Europe and Spain (approximately −1.5%), whereas Extremadura exhibited increasing simplification (+1.5%) and a decline in landscape complexity after 2006. Landscape complexity showed fewer significant trends, with Europe and Spain displaying slight increases over time, whereas Extremadura shifted from initial complexity gains to a decline after 2006, indicating pressures from irrigation expansion and crop intensification. Overall, the results reveal marked spatial differences in agricultural landscape trajectories, demonstrating how intensification processes depend on crop type, regional context, and policy frameworks. This multi-scale analysis provides a quantitative basis for designing land-use policies that preserve ecological connectivity, promote diversification, and strengthen the long-term sustainability of agricultural landscapes. Full article

The global prevalence of lung diseases has risen markedly over the past three decades, driven by factors such as population growth, harmful environmental exposures, and increased life expectancy. Epidemiological studies have highlighted not only the growing burden of chronic respiratory disorders but also the trend toward earlier onset across age groups. Early detection and timely treatment of these conditions are essential to improving long-term clinical outcomes and reducing premature mortality. Chest radiography (X-ray) remains the most widely used and cost-effective initial diagnostic tool for respiratory diseases. However, the reliable identification of multiple thoracic abnormalities, such as cardiomegaly, emphysema, hernia, infiltration, mass, nodules, atelectasis, pneumothorax, pleural thickening, pneumonia, fibrosis, consolidation, effusion and edema, poses challenges even for experienced radiologists. Recent advances in deep learning, particularly convolutional neural networks, have improved medical image analysis and classification. In this study, we propose DualPool-DenseNet121, a modified DenseNet121 architecture combining global average and global max pooling, for multi-label classification of thoracic abnormalities on the NIH ChestX-ray14 dataset. Following removal of “No Finding” cases, our analysis used 51,759 pathological radiographs from 14,402 patients, annotated for fourteen pathological conditions, partitioned patient-wise into training, validation, and test sets with verified zero patient overlap. The pipeline incorporates standardized preprocessing, offline augmentation of under-represented classes, staged transfer learning, and per-class decision thresholds selected on the validation set. Model performance was evaluated using per-class AUC together with threshold-based clinical metrics. The proposed model achieved a macro-averaged AUC of 0.803 and a micro-averaged AUC of 0.831 on the held-out test set. Zero-shot external validation on the CheXpert validation set reached a macro-averaged AUC of 0.806 across the five overlapping pathologies with sufficient positive cases. Grad-CAM visualizations indicated that, in correctly classified cases, the model frequently attended to anatomically relevant regions. These results suggest that the proposed approach provides a reliable and reproducible retrospective benchmark for multi-label thoracic abnormality classification. External validation and expert radiological assessment are required before any clinical application can be considered. Full article

Urban Heat Island (UHI) effects are increasingly affecting Mediterranean coastal cities, where climate change, urbanization, and seasonal tourism intensify thermal stress and environmental vulnerability. In this context, climate-oriented planning and green infrastructure are recognized as key strategies for urban adaptation. This study investigates the spatiotemporal evolution of Land Surface Temperature (LST) and vegetation cover in the coastal municipality of Lignano Sabbiadoro (northeastern Italy) through the analysis of Landsat imagery acquired between 1984 and 2023. Summer LST and Normalized Difference Vegetation Index (NDVI) maps were derived from June–August observations and used to assess long-term thermal dynamics, vegetation patterns, and Urban Heat Island development. Meteorological data indicate a significant increase in mean annual air temperature, with a warming trend of approximately 0.57 °C per decade between 1984 and 2023. Correspondingly, Landsat-derived LST maps reveal a marked intensification of summer surface temperatures, with mean summer LST increasing from 32.16 °C in 1984–1993 to a peak of 35.91 °C in 2004–2013, followed by a slight decrease to 35.77 °C during 2014–2023. During the same period, the proportion of municipal surfaces characterized by temperatures above 35 °C increased from 10.7% to more than 60%, while cooler areas (<30 °C) declined from 17.7% to 2.3%. The comparison between LST and NDVI patterns revealed a persistent inverse relationship between vegetation cover and surface temperature, with coastal pinewoods, green spaces, and water bodies consistently exhibiting lower thermal values than densely urbanized sectors. A key methodological contribution of the study is the operational integration of satellite-derived thermal remote sensing into the Green Plan of Lignano Sabbiadoro. LST mapping was used to identify priority areas for climate adaptation measures, including ecological corridors, wooded landscape connections, urban green corridors, and depaving interventions. The results demonstrate how multi-temporal thermal analysis can support evidence-based planning by linking climate assessment with the spatial prioritization and design of green infrastructure strategies. The proposed workflow provides a transferable framework for integrating remote sensing into climate-informed planning processes in Mediterranean coastal cities and other urban contexts increasingly exposed to heat-related risks. Full article

Satellite altimetry has become an important tool for monitoring inland water dynamics and has been widely used for water-level retrieval, hydrological simulation, and flood–drought risk assessment. To review research progress and development trends over the past three decades, this study combines bibliometric analysis with a traditional review approach. A total of 4764 publications indexed in the Web of Science Core Collection from 1991 to 2025 were analyzed. Using VOSviewer_1.6.20 and CiteSpace_6.4, we constructed knowledge maps of publication trends, disciplinary intersections, author collaboration, keyword clustering, and burst evolution. Representative studies were further synthesized qualitatively. The results show that remote sensing, geology, and imaging science form the core disciplinary framework of this field. Research hotspots have shifted from single water-level observation to multi-parameter retrieval and integration with hydrological models. New missions, including Surface Water and Ocean Topography (SWOT) and Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), have improved spatial resolution and coverage, accelerating the development of this field. However, agricultural water management and the integration of artificial intelligence with hydrological models remain limited. Key challenges include monitoring small and complex water bodies, multi-source data fusion, uncertainty quantification, physics-informed artificial intelligence, and operational applications. Full article