Search Results (80)

The Gönen Sub-Basin in Türkiye’s Marmara Region is characterized by intensive agricultural water use and increasing drought pressure. A basin-scale water allocation model developed using the Water Evaluation and Planning (WEAP) system was applied to evaluate sectoral water demands under different drought scenarios. Under existing conditions, approximately 98% of total water demand was satisfied, while irrigation performance declined to 93% under severe drought. Adaptive allocation and crop adjustment scenarios increased irrigation satisfaction to 97% despite reduced water availability. The findings demonstrate that water stress in the basin is predominantly driven by the agricultural sector, and that efficiency-oriented allocation strategies substantially improve system resilience under drought conditions. Full article

In this study, three-dimensional P- and S-wave velocity structures and P- and S-wave velocity ratio variations in the crust and upper mantle beneath the Marmara Region and the Sea of Marmara were modeled using the Poisson tomography method in the field of Seismology. Within this scope, P- and S-wave arrival times from a total of 23,672 earthquakes that occurred in the region between 2011 and 2023 were evaluated, and an inversion procedure based on body-wave arrival times was applied. The obtained results indicate that the northern branch of the North Anatolian Fault Zone is the most active segment among its three main branches. In addition, a low-velocity zone characterized by seismic gap features extending from the southern parts of Marmara toward Istanbul was identified. Within these seismic gap zones, P- and S-wave velocities decrease sharply across regions exhibiting strong velocity gradients. It was determined that this low-velocity structure cuts across the North Anatolian Fault, which branches into three segments within the Sea of Marmara, and continues at depths of approximately 15–25 km. Earthquakes were observed to concentrate particularly in areas with high-velocity ratio variations and within transition zones from low to high values. Due to the complex tectonic and stratigraphic structure of the Marmara Region, these low-velocity seismic gap zones within the crust may be associated with segments capable of generating large earthquakes in the future. Therefore, a detailed investigation of the crustal structure of the region provides important insights for understanding regional earthquake hazards. Full article

This study presents a multi-indicator remote sensing framework for assessing satellite-derived water-quality-related and trophic-state-related dynamics across four freshwater systems in Türkiye Egirdir Lake, Sapanca Lake, Catalan Dam, and Yuvacik Dam between the baseline (2015–2018) and recent (2023–2025) periods. Rather than providing a regulatory or use-specific satellite-based assessment of water-quality-related indicators, the study evaluates optically and thermally detectable surface water indicators derived from Sentinel-2 MSI and Landsat 8/9 imagery processed in Google Earth Engine. The Normalized Difference Chlorophyll Index (NDCI), the Normalized Difference Turbidity Index (NDTI), and land surface temperature (LST, applied to water surfaces) were used to detect change patterns through period-mean difference mapping (Δ-mask) and interannual time series analysis. Results reveal distinct spatial and temporal dynamics broadly consistent with the interplay of climatic, hydrological, and anthropogenic drivers. In the southern Mediterranean systems, positive ΔNDCI anomalies in littoral and inflow zones were associated with increasing summer LST, with Egirdir Lake exhibiting a statistically significant warming trend of +0.170 °C yr⁻¹ (Mann–Kendall τ = 0.53, p = 0.029), interpreted cautiously as a physically plausible signal consistent with regional climate trends, suggesting elevated thermally mediated eutrophication-related optical risk. In the northern Marmara systems, satellite-observed patterns were more strongly associated with anthropogenic nutrient loading and morphological constraints, with turbidity-related optical increases concentrated in western and marginal zones despite relatively stable thermal conditions. As concurrent in situ measurements were unavailable, cross-sensor consistency checks and literature-based benchmarking were applied as alternative validation strategies. Across all four systems, positive ΔNDCI anomalies were systematically concentrated in shallow marginal and inflow zones, while ΔNDTI patterns varied by system, underscoring the role of littoral dynamics as early indicators of optically detectable water-quality deterioration and trophic-state-related change. The proposed framework offers a scalable, cost-effective approach for freshwater quality surveillance in data-scarce environments and provides direct support for integrated water resource management under Türkiye’s National Water Plan (2026–2036). Full article

Racing pigeons (Columba livia domestica) have been selectively bred for centuries for superior flight capacity. Yet, the quantitative structure of flight performance traits and the extent to which sex influences these parameters remain poorly characterized, particularly in Turkish populations. This study aimed to evaluate flight performance in racing pigeons raised in the South Marmara region of Türkiye using three key kinematic traits (flight duration, speed, and distance) and to explore the multivariate structure and individual variation of these parameters through an integrative machine learning framework. Data were compiled from 166 individually registered pigeons (77 females, 89 males), totaling 781 race records used for pattern analysis. A composite Flight Performance Score (FPS) was constructed using min–max normalized component variables, and its internal consistency was assessed via Cronbach’s alpha and principal component analysis. Univariate comparisons revealed no statistically significant sex-related differences in any of the three flight parameters (p > 0.05 for all traits). Principal component analysis confirmed substantial overlap between male and female individuals in multivariate trait space, and Random Forest classification failed to discriminate between sexes above chance level (accuracy = 0.490; ROC-AUC = 0.500), collectively indicating that sex is not a dominant determinant of flight performance in this population. Internal consistency analysis revealed that flight duration, speed, and distance are functionally independent dimensions (Cronbach’s α = 0.135; r = −0.749 between duration and speed), with PCA of the FPS component variables indicating an effectively two-dimensional variance structure (PC1: 60.1%; PC2: 39.7%). Pattern analysis of race records identified four biologically distinct flight performance profiles, characterized by differential trade-offs among flight duration, speed, and distance, suggesting that individual-level performance strategy, rather than sex, is the primary axis of variation in this dataset. These findings challenge common breeder assumptions about sex-based differences in performance and highlight the multidimensional, individual-specific nature of flight performance in racing pigeons. Full article

Determining the relative impacts of climate variability and human activities on vegetation dynamics remains a central theme in paleoecological research. In climate transition zones like the southeastern Marmara region, isopollen maps are important because they allow for the evaluation of spatially diverse pollen records within an integrated regional framework. The aim of this study is to present a spatially holistic reconstruction of Late Holocene vegetation change in the southern Marmara region using isopollen maps based on fossil pollen records obtained from Manyas, Iznik and Sapanca lakes. Isopollen maps were created for five time periods, approximately 2600, 2000, 1250, 800 and 400 yr BP, representing major climatic and historical phases of the Late Holocene, and the spatial distribution patterns of the major tree and herbaceous taxa were reconstructed. The results demonstrate the presence of a continuous west–east variability in the region’s vegetation structure, reflecting the transition between Mediterranean and Black Sea climate regimes. However, the temporal variation patterns show that vegetation responses cannot always be directly explained by climatic phases. In particular, Artemisia highlights the persistence and local expansion of open-area vegetation, reaching approximately 24% of the study area to the present day. Given the region’s long history of settlement, these findings indicate that vegetation dynamics during the Late Holocene were shaped by the combined effects of climatic changes, local environmental conditions and human activities. Therefore, the study emphasizes the importance of spatially integrated approaches in paleoecological reconstructions. Full article

Hydrogen (H₂) is regarded as a promising option for sustainable energy systems; however, its large-scale use in electricity supply remains limited. This study develops a stochastic network optimization model to examine the applicability of H₂-based electricity generation. The proposed Hydrogen Supply Chain (HSC) model evaluates cost and emission performance under uncertainty by considering disaster conditions, transmission losses, depreciation, and the time value of money. The Marmara Region of Türkiye is divided into 24 grid nodes, and a single-period model for 2023 is solved using Mixed-Integer Linear Programming (MILP). The HSC is allowed to meet 10–40% of electricity demand and to replace collapsed grid lines by supplying critical public centers (CPCs) during disasters. The results show that the HSC can meet 24.82% of demand, although at costs approximately 3.9 times higher than power grid (PG) electricity, while producing 3.44 MtCO₂/year compared to 65.96 MtCO₂/year from the PG. The model is then extended to a multi-period structure (2023–2053) and solved by Variable Neighborhood Search (VNS). Over time, H₂ costs decline, and their share rises from 19% to 35%, while electricity costs decrease from 408 USD/MWh to 170 USD/MWh. These findings suggest that H₂-based electricity supply can support long-term sustainability and resilience objectives in regional energy planning. Full article

The initial seconds after an earthquake are critical for rapid magnitude estimation to support real-time early warning. This study evaluates the determination of P-wave moment magnitude (M_wp) using strong-motion records from the 23 April 2025 Marmara Sea earthquake. High-quality accelerometric data from the Turkish National Strong Motion Network were analysed to extract early P-wave features within the first 3 s after P-wave onset. Results show significant rupture-directivity effects, whereby stations located approximately along the fault strike and rupture-propagation direction recorded larger ground-motion amplitudes and higher station-based Mwp estimates than stations located near nodal directions. The mean M_wp was 6.5 ± 0.2, consistent with the Global Centroid Moment Tensor (GCMT) moment magnitude estimate. Magnitude estimation was achievable within 8–20 s of P-wave arrival, confirming the method’s real-time applicability. Our findings demonstrate that strong-motion P-wave analysis can provide rapid and reliable magnitude estimates suitable for earthquake early warning, tsunami warning, and rapid-response applications. In the Marmara Sea region, where tsunami arrival times may be on the order of 20–30 min and critical infrastructure is concentrated in densely populated coastal areas, rapid determination of magnitude within seconds of earthquake initiation can provide valuable information for emergency management and hazard mitigation decisions. Full article

The Marmara region of Türkiye, situated along the North Anatolian Fault Zone (NAFZ), constitutes one of the most seismically active and densely monitored zones globally. Given the region’s high vulnerability and the catastrophic impacts of historical events—notably the 1999 İzmit and 2023 Kahramanmara¸s sequences—there is a critical need for advanced seismic hazard risk assessment (SHRA) methods that move beyond static models. This review examines the paradigm shift from traditional geophysics to big data seismology, characterized by the “Five Vs”: volume, velocity, variety, veracity, and value. Critically, we distinguish between two fundamentally different problems: Earthquake Early Warning (EEW), which operates on sub-second timescales after rupture initiation, and probabilistic earthquake forecasting, which operates on timescales of years to decades. The study discusses how cloud-native platforms such as Azure Databricks, combined with data pipelines using Apache Kafka (version 3.5.1) and Apache Spark (version 4.1.2), enable the real-time processing of petabyte-scale seismic sensor streams. Key technological tools, including Physics-Informed Neural Networks (PINNs) and deep learning models such as PhaseNet, are analyzed for their demonstrated ability to enhance EEW systems through sub-second phase picking and automated event detection. Seismic tomography is also undergoing AI-enabled transformation, yielding higher-resolution subsurface imaging. We present statistical validation metrics and uncertainty quantification methods essential for credible hazard assessment. By addressing computational bottlenecks through hybrid computing architectures and edge computing, this framework aims to improve the warning lead time for Istanbul’s critical infrastructure. This work provides a structured roadmap for bridging the gap between traditional seismic data analysis and operational predictive analytics in the Marmara region. Full article

Traditional wooden granaries in rural Türkiye are disappearing at an accelerating rate due to agricultural abandonment, rural depopulation, and the absence of systematic documentation and conservation frameworks. In the Sındırgı district of Balıkesir, one of the richest concentrations of vernacular granary architecture in the Marmara Region, these structures remain largely unprotected and unstudied within a sustainable design framework, constituting an urgent conservation challenge. This study aims to assess the current preservation status of Sındırgı granaries, classify their typological diversity, and evaluate their sustainability performance against a defined set of ecological design criteria. A mixed methods approach was employed, combining a systematic literature review with extensive fieldwork across 33 neighborhoods. In total, 1411 granaries were identified and grouped into five typologies: evli, Simav, kabak, sandık, and üstü örtülü sandık. These typologies were systematically compared to five parameters: spatial distribution across neighborhoods, plan and section geometry, construction system and structural elements, material selection and condition, and preservation status. This comparison revealed that typological variation is not incidental but directly reflects differences in land ownership, agricultural production capacity, topography, and distance from the district center. Representative examples from each typology were documented through onsite measurements, photogrammetry, technical drawings, and interviews with local craftsmen. The sustainability performance of the granaries was then assessed across seven ecological design criteria: spatial organization, building form design, structural element design, material use and conservation, design with nature, urban design area planning, and nature interaction. The findings demonstrate that the long-term durability of these structures depends on an interrelated system of climate-responsive design decisions rather than any single factor. The study concludes by proposing a holistic conservation model comprising typology-based inventory, roof water moisture-focused intervention, periodic monitoring, and transmission of vernacular building knowledge, a framework applicable to comparable rural granary heritage across the region. Full article

This study estimates daily nitrogen dioxide (NO₂) concentrations at ground level across the Marmara Region of Türkiye at 0.01° resolution. The framework integrates Sentinel-5P (S5P) TROPOspheric Monitoring Instrument (TROPOMI) and GEOS Composition Forecast (GEOS-CF) tropospheric NO₂ vertical column density (VCD) data with meteorological, topographic, land-use, socioeconomic, and temporal features through four tree-based ensemble algorithms trained on 74 ground station observations. Under a temporal split (2019–2022 training, 2023 validation, 2024 testing), S5P-Categorical Boosting (CatBoost) achieved the best performance (Pearson correlation coefficient (R) = 0.706, R² = 0.498, root mean square error (RMSE) = 14.31 µg/m³). Random splitting inflated R by +0.168 due to temporal autocorrelation, while leave-one-station-out and leave-one-province-out cross-validation reduced R to ~0.50 by removing spatial dependence, together revealing the combined effect of temporal and spatial autocorrelation. SHapley Additive exPlanations (SHAP) analysis identified TROPOMI NO₂ VCD, population density, road length, and nighttime light as dominant predictors; population density was the top predictor in the GEOS-CF model, followed by VCD. Concentration maps for 2024 showed that 95.9% of the region’s 26.74 million inhabitants were exposed above the WHO annual air quality guideline of 10 µg/m³, with a population-weighted mean of 21.08 µg/m³. Full article

Background: Hypertension remains the single most important modifiable risk factor for cardiovascular disease, stroke, and premature mortality worldwide. Despite major pharmacological advances, awareness, treatment, and control rates remain globally inadequate, particularly in low- and middle-income settings. Türkiye occupies a unique epidemiological position at the intersection of European and Asian cardiovascular risk patterns, with national surveys documenting a stable hypertension prevalence of approximately 30% but persistent deficits in disease control. Methods: This cross-sectional study was conducted on World Hypertension Day (17 May 2025) across nine provinces in Türkiye representing five geographic regions (Marmara, Aegean, Mediterranean, Black Sea, and Southeastern Anatolia). A total of 1967 adult volunteers were enrolled. Blood pressure was measured following standardized protocols and classified per ESH 2023 guidelines. A structured questionnaire captured sociodemographic data, lifestyle factors, medication adherence, and hypertension-related awareness. Results: The median participant age was 51 years; 55.4% were female. Screening-detected hypertension (BP ≥ 140/90 mmHg) was identified in 26.6% and above-optimal blood pressure in 41.6%. A prior hypertension diagnosis was reported by 35.1%. Among the 1277 participants without a known diagnosis, 51.1% had above-optimal or hypertension-range blood pressure readings, including 11.6% with screening-detected hypertension-range blood pressure. Independent predictors in multivariate analysis included age (OR = 1.048), male sex (OR = 1.528), BMI (OR = 1.096), and alcohol consumption (OR = 1.536); regular exercise was protective (OR = 0.796). Among known hypertensive patients, only 50% monitored blood pressure regularly, 30% skipped doses, and awareness of renal (40.4%) and visual (30.6%) complications was notably low. Conclusions: This large multi-center screening study reveals a substantial proportion of previously undetected hypertension-range blood pressure readings and persistent management gaps in a volunteer-based Turkish community sample. The observed screening rate below national prevalence averages likely reflects a healthy volunteer effect inherent to this study design. World Hypertension Day offers an effective framework for simultaneous multi-center screening. Targeted interventions should address non-cardiovascular complication awareness, sodium intake, and medication adherence. Full article

Marine mucilage events are intensifying in semi-enclosed seas under accelerating climate- and nutrient-driven pressures, yet their ecosystem-level consequences for aquaculture-linked coastal habitats remain insufficiently documented. This study provides an integrated spatiotemporal assessment of water quality, phytoplankton community structure, and biometric responses of Mytilus galloprovincialis during and after the 2025 mucilage outbreak in the Gulf of Erdek (Sea of Marmara, Türkiye). Mucilage accumulation was associated with sharp increases in turbidity, total suspended solids, and particulate organic matter, alongside declines in dissolved oxygen and pH. Phytoplankton assemblages exhibited marked seasonal restructuring: the mucilage period was characterized by the coexistence of mucilage-forming taxa, non-toxic bloomers, and multiple harmful algal bloom (HAB) groups, including DSP- and ASP-related species, whereas post-mucilage conditions were dominated by non-toxic diatoms with substantially reduced HAB representation. The dinoflagellate species representing the May period in terms of abundance were Noctiluca scintillans and Prorocentrum micans; the diatom species were Chaetoceros radiatus, Cylindrotheca closterium, Pseudo-nitzschia pseudodelicatissima, and Thalassiosira rotula; and the coccolithophore was Phaeocystis pouchetii. Mussel biometric analyses revealed biometric indices and condition values markedly below regional historical baselines during the mucilage event, alongside reduced meat yield, followed by pronounced compensatory growth during the post-mucilage period. Our findings demonstrate that mucilage acts as both a physical and biological stressor, driving short-term ecological shifts in phytoplankton diversity and imposing substantial but reversible physiological impacts on mussel stocks. These results underscore the need for continuous biodiversity monitoring frameworks that integrate mucilage dynamics, HAB occurrence, and aquaculture resilience in regions vulnerable to climate-enhanced organic aggregate formation. Full article

The Tuzla Submarine Landslide represents one of the most significant mass-wasting features associated with the active North Anatolian Fault Zone (NAFZ). The failure surface geometry and sediment stratigraphy indicate the presence of a mechanically weak, saturated layer that may become unstable under strong seismic loading. This study presents a comprehensive geotechnical evaluation of the Tuzla Submarine Landslide. Based on regional sediment properties, the landslide was characterized and modeled with an estimated volume of 0.015 km³ and an average slope angle of 14°. The submarine landslide potential was investigated through re-analysis of seismic, geotechnical, and bathymetric datasets. Finite Element Method (FEM) simulations were conducted to model the seismic slope failure. Based on these analyses, the seismic slope displacements, stress distributions, and equivalent plastic strains were identified. The estimated landslide displacements under varying seismic acceleration scenarios corresponding to three major earthquakes ranged between 2.38 m and 4.12 m, depending on the triggering ground motion and slope stability conditions. These findings highlight that reactivation of the Tuzla submarine landslide, potentially triggered by a future large earthquake along the NAFZ, could pose a moderate landslide hazard to the coastal settlements bordering the Marmara Sea. Full article

This study provides a model-based exploratory assessment of the economic impact attributable to coccidiosis within the Turkish broiler sector. Primary data were obtained from 117 commercial enterprises (total capacity: 1,666,000 broilers) across the Mediterranean, Marmara, and Central Anatolia regions during the 2024 production cycle. Epidemiological analysis estimated a disease prevalence of 13% within the sampled population. The economic impact was evaluated using a stochastic modeling framework informed by Monte Carlo simulation and integrated with the Delphi method. Total national financial losses in Türkiye were estimated to reach a mean of $15.1 million in the most likely scenario (with a probabilistic range extending from $3.3 million under optimistic assumptions to $46.3 million under pessimistic conditions). The model-estimated average financial burden per animal was approximately $0.41 (representing an estimated $2.06 per clinically infected bird). Notably, projections suggest that roughly 62% of this economic impact could be attributed to subclinical factors, characterized by a modeled 5% (150 g) reduction in live weight and an estimated 8% (274 g) increase in feed consumption due to impaired Feed Conversion Ratio. The mortality rate within the modeled scenarios was calibrated at 8%. These findings suggest a substantial potential economic burden on the poultry industry. The analysis indicates that the majority of financial losses may stem from subclinical performance declines—specifically, impaired Feed Conversion Ratio and reduced growth—rather than acute mortality. These projections emphasize the urgent need for enhanced preventative strategies and subclinical monitoring to mitigate the estimated economic impact in Türkiye. Full article

Increasing agricultural productivity is vital for global food security, but it poses significant risks to aquatic ecosystems through diffuse pollution. As Türkiye aims to harmonise its agricultural policies with the European Green Deal, quantifying agricultural non-point-source pollution (ANPSP) is essential for sustainable water management. This study evaluates ANPSP loads, including Total Nitrogen (TN), Total Phosphorus (TP), Chemical Oxygen Demand (COD), and Ammonia Nitrogen (NH₃-N), originating from cereal production, fertiliser application, and livestock farming across Türkiye from 2015 to 2024. By employing activity data and pollution load coefficients, the spatiotemporal dynamics of ANPSP were analysed at both national and regional levels. The results demonstrate that cereal production is the predominant source of nutrient loading (60.5% TN, 64.9% TP), whereas livestock activities account for 52.2% of the COD load. Fertiliser use contributed 23.0% and 20.6% to TN and TP loads, respectively. The Marmara, Aegean, and Central Anatolia regions were identified as high-intensity pollution hotspots. These findings provide a robust baseline for developing region-specific mitigation strategies, such as precision fertilisation and circular waste-to-energy systems, to support Türkiye’s transition toward a Zero-Pollution and sustainable agricultural future. Full article