Sürdürülebilir Kalkınma Amaçları

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• MakaleYalnız künye2026Scopus SJRQ1/r/munzur/1148
  Hydrogeochemical controls on chromium speciation and potential human health risks in surface waters of an ultramafic mining watershed

  Kutlu, Banu; Baydar, Tarık; Yıldırım, Vesile; Konurhan, Zekeriya

  Accurate assessment of chromium contamination in mining-influenced watersheds requires distinguishing between the environmentally contrasting Cr(III) and Cr(VI) species, yet environmental monitoring and risk assessments still rely predominantly on total chromium concentrations. This study evaluated whether chromium speciation provides additional information beyond operational total chromium for assessing chromium occurrence and potential human health risks in an ultramafic, mining-influenced watershed. Surface-water samples were collected from 28 sampling stations across the Pülümür and Ovacık regions of the Eastern Anatolia Basin (Türkiye) between March 2025 and February 2026. Chromium speciation was determined using species-specific UV–Visible spectrophotometric methods and integrated with hydrochemical characterization, multivariate statistical analyses, mineralogical investigations (XRD, SEM–EDS, and FTIR), and deterministic and empirical-bootstrap human health risk assessments. Operational total chromium, defined as the sum of separately measured Cr(III) and Cr(VI), ranged from below the detection limit to 578.13 µg L−1. For contextual screening, this calculated value exceeded World Health Organization (WHO) drinking-water guideline for total chromium at 14 stations; however, it was not an independently measured total-Cr concentration. The highest Cr(VI) concentration occurred at a localized hotspot, whereas Cr(III) predominated throughout most of the watershed. Nevertheless, Cr(VI)-based screening thresholds were exceeded at multiple stations under the assumed untreated drinking-water ingestion scenario, indicating that operational total chromium alone did not consistently identify the spatial distribution of Cr(VI)-related potential risk. Screening-level hazard quotient (HQ) estimates were higher for children than for adults; however, direct untreated consumption of the sampled surface waters was not verified. Mining-influenced stations generally exhibited higher chromium concentrations, although the relative contributions of geogenic weathering and mining-related mobilization could not be quantitatively apportioned. Overall, chromium speciation provided additional environmentally and toxicologically relevant information beyond operational total chromium for evaluating chromium mobility and screening-level potential human health risks in this ultramafic watershed.

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• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/782
  EBA-Net: A hybrid EfficientNetB3-BiLSTM-Attention model for species-level diatom classification

  Balo Utku, Esen Damla; Kutlu, Banu; Utku, Anil

  Species identification in diatoms is important for assessing water bodies, determining environmental quality, and analyzing biodiversity. Nonetheless, diatom classification has proven difficult due to intra-class variation, interclass similarity, and data imbalance in microscopic images. In this regard, we propose a new deep learning approach for species-level diatom classification. Various deep learning models, including traditional convolutional neural networks or CNNs (ResNet50, DenseNet121), state-of-the-art CNNs (EfficientNetB3, Xception, MobileNetV3), transformer-based architectures (ViT-B16, Swin-Tiny), and our proposed EBA-Net (EfficientNetB3-BiLSTM-Attention Network), were extensively compared under identical experimental settings. The EBA-Net integrates the advantages of convolutional feature extraction, sequence modeling, and an attention mechanism to improve classification accuracy. It first uses the EfficientNetB3 model as the backbone network to obtain higher-level features, followed by a BiLSTM layer to capture dependencies among the extracted features. Then, it applies the attention mechanism to the BiLSTM output to highlight the most informative features. Experimental results showed that the proposed EBA-Net model outperforms other models considered in the study, yielding 95.8% accuracy and 85.1% macro F1-score. In addition, Top-3 (98.9%) and Top-5 (99.6%) accuracies confirmed the efficiency of the proposed model for classifying objects from visually similar classes. An analysis of the model's interpretability was conducted using Gradient-weighted Class Activation Mapping, showing that the proposed model's attention is concentrated on relevant morphological features of diatoms. To the best of our knowledge, the suggested approach achieves state-of-the-art accuracy on the data set of diatoms used.

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• MakaleAçık Erişim2025/r/munzur/6194
  Artificial Intelligence Applications in the Aquaculture Industry: Sustainability, Efficiency and Innovative Solutions

  Kutlu, Banu; Utku, Esen Damla Balo

  Artificial Intelligence (AI) is becoming increasingly important to increase efficiency and sustainability by organizing processes and providing significant improvements in different sectors. AI is reshaping the aquaculture sector. AI is being used to help solve optimization problems in aquaculture, reduce costs, and find sustainable solutions. These scenarios guided the evaluation of the future role of AI in aquaculture and the benefits that AI brings to the aquaculture sector in this study. AI is improving the way fish stocks are monitored, live stocks are assessed, diseases among plants and animals are recognized, water quality is tested, and production lines are controlled. Aquaculture uses AI technologies to help detect diseases early, monitor environmental conditions affecting production, and improve both efficiency and sustainability. In addition, AI is examining and providing solutions to environmental issues such as global warming and water resource management.

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  AtıfOpenAlex5

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• MakaleAçık Erişim2025/r/munzur/6146
  Enhancing water quality prediction with artificial intelligence: A hybrid convlstm model for spatio-temporal analysis

  Utku, Anıl; Kutlu, Banu; Utku, Esen Damla Balo

  Water quality plays a vital role in public health, environmental sustainability and ecosystem balance. However, industrialization, urbanization, and agricultural activities cause water pollution to increase, threatening both human health and aquatic ecosystems. Traditional water quality monitoring methods are usually time-consuming, costly, and require manual intervention. Therefore, developing automatic, data-driven, and high-accuracy prediction models is crucial for sustainable water management. This study created a hybrid ConvLSTM model to increase prediction accuracy. The created model was comparatively analyzed with RF, SVR, XGBoost, MLP, CNN, and LSTM. The dataset used includes historical measurement values of chemical pollutants. Input data includes geographical coordinates of sample points, chemical parameter type, and compliance with regulatory standards. Experimental results show that ConvLSTM provides the lowest prediction errors by learning spatial and temporal dependencies and reaches the highest accuracy rate with 0.994 R2 compared to other models.

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• MakaleAçık Erişim2025/r/munzur/6011
  The Health Effects of Fluoride and Nitrate in Drinking Water in Tunceli (Türkiye)

  Kutlu, Banu; Çetindağ, Serdar

  Fluoride (F⁻) and nitrate (NO₃⁻) are common inorganic constituents of drinking water and can cause significant public health effects when present at inadequate or excessive concentrations. This study determines the levels of fluoride and nitrate in drinking water collected from 18 stations across Tunceli Province, Türkiye, during 2021, and evaluates the non-carcinogenic health risks for four age groups (infants, children, adolescents, and adults). Fluoride and nitrate concentrations were measured using spectrophotometric methods and Estimated Daily Intake (EDI) and Hazard Quotient (HQ) values were calculated. Fluoride concentrations ranged from 0.06 to 0.31 mg L⁻¹ and were below the WHO guideline value, with all HQ values <1. Nitrate concentrations varied more widely (0.45–64.38 mg L⁻¹), and exceedances of WHO limits were recorded at several rural stations. Infants and children exhibited HQ>1 values, indicating potential health risks associated with nitrate exposure. The findings highlight spatial heterogeneity in water quality across Tunceli and emphasize the need for age-specific monitoring programs and improved groundwater protection strategies.

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  AtıfOpenAlex1

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• MakaleYalnız künye2025Scopus SJRQ3/r/munzur/1887
  Assessments of heavy metal contaminations of surface water and sediment of Pülümür Stream (Türkiye)

  Kutlu, Banu; Çevik, Fatma; Çetindağ, Serdar

  The primary considerations within aquatic ecosystems are water and sediment quality, rendering it imperative to assess their concentrations, pollution levels, origins, and ecological hazards. In this study, heavy metal concentrations in surface waters and sediments of the Pülümür Stream were investigated to assess the level, distribution, source of pollution and the associated human risks. Water and sediment samples from the river were collected monthly from February 2021 to January 2022 and examined using the Inductively Coupled Plasma Mass Spectrometry (ICP– MS) technique. Metal concentrations in the sediment followed a decreasing or derivative sequence of Fe > Al > Mn > Ni > Cr > Zn > Cu > Pb > As >Cd > Hg. The ecological indices of the stream water have low degrees of contamination by heavy metals. Igeo and EF showed that most of the sites are moderately to highly polluted due to Ni, and Cr, while PLI and PERI showed a progressive deterioration of the environment at site 9. Moreover, the modified hazard quotient (mHQ) indicates low ecological risk for Cu, Pb, Zn, Cd, Hg metals, while Ni, As and Cr reach high pollution at sediment sites. Pearson correlation analysis revealed that the presence of Zn, Cu, Pb, Hg, and Mn metals in the sediment analysis has a lithogenic source, and As, Ni, Cd, and Cr accumulate due to human activities, mainly domestic and agricultural irrigation wastes and mining wastes, all of which affect the aquatic environment. According to this study, more attention should be paid to the comprehensive monitoring of metals in the water and sediment for both aquatic biota and human risk of the Pülümür River.

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  AtıfScopus6·WoS5·OpenAlex5

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• MakaleYalnız künye2024/r/munzur/6247
  Şerefiye (Zara-Sivas) Barajının Su Kalitesi İndekslerine Göre Değerlendirilmesi

  Mutlu, Ekrem; Kutlu, Banu

  Sivas ili Şerefiye Baraj gölünün su kalitesinin belirlenmesi üzerine yapılmış olan bu çalışma; Ocak 2014 ile Aralık 2014 tarihleri arasında 3 istasyondan aylık olarak toplanan numuneler üzerinde gerçekleştirilmiştir. 25 değişkenin incelendiği analizlerde su kalitesi, Dünya Sağlık Örgütü içme suyu standartları, su kalite indeksi (WQI), sodyum absorbsiyon oranı (SAR), sodyum yüzdesi, geçirgenlik indeksi (PI), magnezyum indeksi, sulama indeksi ve Türkiye Cumhuriyeti Yüzey Suyu Kalitesi Yönetmeliği (SWQR) Orman ve Su İşleri Daire Başkanlığı değerlerine göre belirlenmiştir. Barajdaki su kalite indeksinin ortalama değeri 46,82, sulama suyu değerleri ortalama 3,90 olarak bulunmuştur. Burada elde edilen sonuçlar Şerefiye Barajı'nın su kalite indeksi ve sulama suyu kalitesi açısından "çok iyi" sınıfta olduğunu göstermiştir.

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  AtıfOpenAlex4·TR Dizin5

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• MakaleAçık Erişim2023Scopus SJRQ4/r/munzur/2653
  The Assessment of Health Risk from Heavy Metals with Water Indices for Irrigation and the Portability of Munzur Stream: A Case Study of the Ovaclk Area (Ramsar Site), Türkiye

  Kutlu, Banu; Sarlgül, Ali

  Surface water samples from the area of Munzur Stream in Türkiye (a Ramsar site) were evaluated for their suitability for irrigation and drinking purposes using different water quality indices. The human health risks were assessed as well. The study was conducted over a period of 24 months from January 2019 to December 2021 by taking samples from nine stations every month in order to determine the water quality of Munzur Stream, located in Tunceli. According to the results, Munzur Stream is in good condition in terms of the quality of drinking water and irrigation water. The concentrations of heavy metals such as Cu, Ni, Fe and Hg were high, though the water quality parameter according to Türkiye Ministry of Forestry and Water Affairs Surface Water Quality Regulations (TSWQR) was significantly lower than the permitted limits. In Munzur Stream, the irrigation water for all stations was reported to be excellent, good and suitable in terms of SAR, Na% and MH, respectively. The principal component analysis data formed the four principal components, explaining 98.22% of the total variance. The sources of pollution in this area include the rock types of the basin, soil erosion, domestic waste water discharge and agricultural flow of inorganic fertilisers.

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  AtıfWoS1·OpenAlex3

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• MakaleYayıncıda açık erişim2023Scopus SJRQ3/r/munzur/2393
  Contamination and Ecological Risk Assessment of Heavy Metals in Surface Sediments of the Munzur Stream, Turkey

  Kutlu, Banu

  The aim of the present study is to determine the heavy metal concentrations in the surface sediment between 2019-2020 in Munzur Stream,Turkey. The impact of pollution level in the study area was evaluated by geoaccumulation index (Igeo), Contamination Factor (CF), enrichment factor (EF), pollution ecological risk (PER) index, and pollution load index (PLI). The average amount of heavy metals detected in sediment in the study in mg/kg was, in descending order, Fe>Al>Mn>Ni>Cr>Zn >Cu>Pb>Cd>Hg. The data evaluated by several statistical methods indicated that the metals with a positive relationship between them in the Pearson correlation analysis and the elements of the same factor in the factor analysis were mostly the same. The comparison of the results with the sediment quality criteria showed that only the mean value of Mn and Ni exceeded the values of PEL. Heavy metal levels in Munzur Stream sediment exposed to domestic and agricultural wastes, agricultural fertilizers and pesticides, and mines were not high enough to pose a threat to aquatic life.

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  AtıfScopus9·WoS8·OpenAlex11

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• MakaleYalnız künye2023Scopus SJRQ2/r/munzur/1904
  Microplastic pollution in two remote rivers of Türkiye

  Gündoğdu, Sedat; Kutlu, Banu; Özcan, Tahir; Büyükdeveci, Ferhat; Blettler, Martin C. M.

  Microplastic pollution in aquatic ecosystems presents an emerging environmental threat that can have adverse effects on ecology, endanger aquatic species, and result in economic damage. Despite the numerous studies reporting the presence of microplastics in marine environments, research into their presence in freshwater systems or inland waters remains limited. This study aimed to assess the level of microplastic pollution transported by the Munzur and Pülümür Rivers and some small rivers that flow into the Uzunçayır dam lake, which is the confluence of the Munzur and Pülümür Rivers in Türkiye. Samples were collected from 23 stations, with the concentration of microplastics ranging from 0.01 MP/m3 at P-4 station to 28.21 MP/m3 at P-10, a station located near a city. Microplastics comprise four types: fiber, film, fragment, and glitter. The average size of microplastics was 1.46 ± 0.05 mm, with the average size of fibers, films, fragments, and glitter-type microplastics being 1.58 ± 0.07 mm, 1.23 ± 0.10 mm, 1.21 ± 0.11 mm, and 0.78 ± 0.16 mm, respectively. The most frequent polymers were polyethylene (31.8%), polystyrene (21.1%), and polypropylene (10.5%). Despite being considered remote and less populated rivers compared to other river systems in Türkiye, all sampling sites showed varying concentrations of microplastics.

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  AtıfScopus34·OpenAlex37

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