Environmental Monitoring and Assessment最新文献

{"title":"Identification of particulate matter (PM₁₀ and PM_2.5) sources using bivariate polar plots and k-means clustering in a South American megacity: Metropolitan Area of Lima-Callao, Peru.","authors":"José Abel Espinoza-Guillen, Marleni Beatriz Alderete-Malpartida, Franchesco David Roncal-Romero, Joycy Claudia Vilcanqui-Sarmiento","doi":"10.1007/s10661-025-13696-1","DOIUrl":"https://doi.org/10.1007/s10661-025-13696-1","url":null,"abstract":"<p><p>The identification of different air pollution sources is essential to effectively control atmospheric pollution, particularly in megacities of emerging countries with rapid economic development, such as the Metropolitan Area of Lima-Callao (MALC). The objective of this research was to identify the main sources of particulate matter pollution by applying bivariate polar plots and the k-means clustering algorithm. These statistical techniques were applied to hourly in situ data of four variables collected over a 5-year period (2015-2019) by the Automatic Air Quality Monitoring Network of the MALC: wind direction, wind speed, PM₁₀, and PM_2.5 concentrations. Average PM₁₀ concentrations ranged from 34 μg m^-3 (CDM station) to 126.7 μg m^-3 (VMT station), while average PM_2.5 concentrations ranged from 16.8 μg m^-3 (CDM station) to 41.2 μg m^-3 (ATE station). The diurnal variation of PM presented two peaks, one in the morning (from 0800 to 1000 h) and the other at night (from 1900 to 2300 h), with the highest concentrations of PM₁₀ recorded at the ATE (0800 h: 155.8 μg m^-3) and VMT (2100 h: 154.6 μg m^-3) stations, and PM_2.5 at the ATE station (0800 h: 60.3 μg m^-3 and 2300 h: 37.5 μg m^-3). The results showed that the contributions of PM₁₀ are directly related to emissions from industrial activities, automotive fleet, construction, demolition, wind erosion, and the suspension and resuspension of particulates from unpaved roads. Meanwhile, high concentrations of PM_2.5 are mainly attributed to vehicle exhaust emissions, industrial emissions, secondary particulate formation, and drag by the action of the winds. The major source of particulate matter contamination is the vehicle fleet, and within this, automobiles, station wagons, combi vans, and 2 and 3-wheel motorcycles are those that have the greatest contribution. These results were supported by non-parametric statistical tests such as Kruskal-Wallis and Mann-Whitney U and validated by the conditional bivariate probability function. The findings of this work may help to implement pollution prevention and control strategies in the future within this South American megacity.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 3","pages":"226"},"PeriodicalIF":2.9,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fast, in situ, and eco-friendly determination of Mn in plant leaves using portable X-ray fluorescence spectrometry for agricultural and environmental applications.","authors":"Marcela Vieira da Costa, Guilherme Lopes, Luiz Roberto Guimarães Guilherme, Fábio Aurélio Dias Martins, Kellen Nara Silva, Leônidas Canuto Dos Santos, Marco Aurélio Carbone Carneiro, Mariene Helena Duarte, Bruno Teixeira Ribeiro","doi":"10.1007/s10661-025-13692-5","DOIUrl":"https://doi.org/10.1007/s10661-025-13692-5","url":null,"abstract":"<p><p>The portable X-ray fluorescence (pXRF) spectrometry has been very useful for the characterization of different earth materials, and its application for foliar analysis is really promising. The performance of pXRF for foliar analysis depends on several factors such as concentration of the elements, fluorescence yield which is influenced by atomic number, spectral interference, and water content. Mn is one of the elements that present a prominent fluorescence peak. In this sense, it was hypothesized that pXRF can directly determine the Mn concentration on foliar samples, even when used on intact leaves (fresh or dry) being a useful tool for agronomic and environmental purposes. Thus, the objective was to assess the performance of a pXRF to determine Mn concentration in two different foliar datasets from Brazil/South America and Mali/Africa. In the Brazilian dataset, leaves from eight crops (common bean, castor plant, coffee, eucalyptus, guava tree, maize, mango, and soybean) were scanned via pXRF at the following conditions: intact and fresh leaves, intact and dry leaves, and powdered samples). In the Malian dataset, powdered samples from cotton and maize were analyzed via pXRF. For comparison, Mn concentration was also determined after nitro-perchloric digestion followed by quantification via inductively coupled plasma optical emission spectroscopy (ICP-OES). After descriptive statistics, linear regressions were performed for all sample preparation conditions in both datasets, using Mn concentrations obtained through pXRF and the acid digestion method. The data quality level of all linear regressions was considered quantitative with high R (0.93 to 0.98) and R² (0.87 to 0.96) values. The direct analysis of Mn via pXRF on intact and fresh leaves yielded R of 0.93, R² of 0.87, and a low relative standard deviation (< 10%). The manufactured pXRF calibration used in this work allowed an accurate direct Mn determination in plant leaves. Considering the importance of Mn as a plant micronutrient and its potential toxicity depending on soil redox conditions, the fast, in situ, non-destructive, and eco-friendly determination via pXRF has a tremendous agronomic and environmental application worldwide.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 3","pages":"227"},"PeriodicalIF":2.9,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heavy metals pollution in riverine sediments: Distribution, source, and environmental implications.","authors":"Kifayatullah Khan, Muhammad Younas, Muhammad Yaseen, Hassan Sher, Afsheen Maryam, Sobhy M Ibrahim, Adnan Adnan, Ahmad Ali, Muhammad Fawad, Akhtar Zeb Khan, Nasrullah Khan, Izaz Ali Shah","doi":"10.1007/s10661-025-13623-4","DOIUrl":"https://doi.org/10.1007/s10661-025-13623-4","url":null,"abstract":"<p><p>This research reports heavy metal pollution in riverine sediments from River Kabul, Pakistan, which could endanger human health and ecology via the food web. The results revealed a substantial special variation in the average contents (mg/kg) of chromium (Cr), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd), mercury (Hg), lead (Pb), iron (Fe), and aluminum (Al) in riverine sediments, in the order of Fe (20,234.51) > Al (17,550.86) > Mn (375.45) > Zn (149.08) > Ni (89.11) > Cr (83.36) > Pb (45.29) > Cu (19.86) > Cd (7.48) > Co (6.28) > Hg (0.81). Among the heavy metals, Cd exhibited the highest degree of pollution along the river, followed by Hg > Ni > Zn > Pb > Al > Cr > Mn > Fe > Cu > Co. The overall contamination factor (CF) values for the sum of heavy metals were highest at monitoring site S-9, followed by S-8 > S-10 > S-6 > S-5 > S-7 > S-1 > S-4 > S-12 > S-3 > S-2 > S-1 with pollution load index (PLI) > 1, whereas the geo-accumulation index (Igeo) values of Cd and Hg fluctuated between Levels 3, 4, and 6, suggesting moderate to extreme pollution in the river. The correlation statistics determined the fate and distribution of heavy metals by establishing significant positive correlations between the specific metals of bounded sediments. The cluster analysis separates the correlated metals into Groups A and B, and Groups 1 and 2. While the principal component analysis evaluates the qualitative behavior of clustering by discerning industrial, agrochemicals, mining, and domestic wastewater discharges, leakages of lubricants along with multiple geogenic inputs, erosion of mafic and ultramafic rocks, and minimal atmospheric deposition are all potential sources of Cr, Mn, Co, Ni, Cu, Zn, Cd, Hg, Pb, Fe, and Al contamination. In terms of risk, the contaminations of Mn, Co, Cu, Zn, and Pb in riverine sediments were 85, 100, 100, 17, and 11%, respectively, representing a rare biological influence because their value is less than their corresponding threshold effect concentrations (TECs), whereas the levels of Mn, Ni, Cd, and Hg were above their probable effect concentrations (PECs) of 100, 100, 81, and 52%, respectively, representing prominent adverse biological influence. Based on consensus-based TECs and PECs, the contamination levels of Cr, Mn, Zn, Cd, Hg, and Pb were 100, 85, 83, 19, 48, and 90%, respectively, indicating occasionally exhibited adverse biological effects on the riverine population. Besides, the overall potential ecological risk index (PERI) of Cd and Hg, in particular, exhibited the maximum pollution level ( <math><msubsup><mi>E</mi> <mrow><mtext>r</mtext></mrow> <mtext>i</mtext></msubsup> </math> ≥ 320), suggesting a very high potential ecological risk in the drainage that requires special attention from pollution control authorities.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 3","pages":"225"},"PeriodicalIF":2.9,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geo-environmental GIS modeling to predict flood hazard in heavy rainfall eastern Himalaya region: a precautionary measure towards disaster risk reduction.","authors":"Pradeep Kumar Rawat, Khrieketouno Belho, Mohan Singh Rawat","doi":"10.1007/s10661-025-13652-z","DOIUrl":"https://doi.org/10.1007/s10661-025-13652-z","url":null,"abstract":"<p><p>The Eastern Himalaya region is highly susceptible to flood and other hydrological hazards due to frizzle geophysical setup, reshaping geomorphology, and heavy annual rainfall (1600-3200 mm). Despite that, anthropogenic activities have been enhancing this susceptibility which increases the intensity and impact of floods in terms of economic loss, human loss, and environmental degradation. Addressing this environmental problem, a geospatial technology-based case study of the Kohima district, Nagaland state (India), a part of the eastern Himalaya is presented here. Various experiential models are available for computing flood hazards; however, the geospatial technique-based analytic hierarchy process (AHP) method was applied in this study due to its robustness and high accuracy level. AHP integrates reclassified GIS layers of hazard-triggering factors and sub-factors by assigning relative weights 1-9 based on their corresponding impacts on flood occurrence. Overlay operation of reclassified GIS layer (causative factors and sub-factors) in ArcMap 10.8 software generated flood spatial variability map which shows four zones, namely low, moderate, high, and very high hazard zones, covers 23%, 35%, 28%, and 14% proportion of total area (978.96 km²), respectively. The study poses a serious concern for the study area as most of the densely populated urban centers fall into moderate to very high flood hazard zones including the state capital city Kohima. So, to avert a worse flood disaster, a flood hazard zone study is the need of the hour. The present study can be used as a decision support system (DSS) for flood disaster risk reduction, infrastructural development, and land use planning in Kohima district.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 2","pages":"220"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid constructed wetlands for tertiary treatment of poultry slaughter wastewater to meet quality standards of discharge and reuse: a full-scale case study in Vietnam.","authors":"Hung Viet Dang, Huy Quoc Lam, Linh My Nguyen","doi":"10.1007/s10661-025-13624-3","DOIUrl":"https://doi.org/10.1007/s10661-025-13624-3","url":null,"abstract":"<p><p>The construction and operation of a small-scale hybrid constructed wetland (HCW) system for tertiary wastewater treatment was presented. The HCW system includes a vertical sub-surface flow CW (VFCW), a horizontal sub-surface flow CW (HFCW), and a free water surface flow CW (FWSCW). Operated in series, it had a total area of 150 m². It received 7.5 m³day of secondary effluent wastewater from the existing treatment system of a poultry slaughter enterprise at the production capacity of 500 ducks per day in an on-site experiment of 12 months. The results showed that the removal efficiencies of biological oxygen demand (BOD₅), chemical oxygen demand (COD), total suspended solids (TSS), ammonia nitrogen (NH₄⁺-N), nitrate nitrogen (NO₃^--N), total nitrogen (TN), orthophosphate (PO₄^3--P), total phosphorus (TP), Escherichia coli (E. coli), and total coliforms (T. coli) reached average values of 76.2, 78.7, 77.1, 83.9, 86.3, 84.9, 72.3, 73.9, 98.9, and 96.4%, respectively, while the effluent concentrations of the study system complied with the most difficult limits not only for discharge into the receiving water source but also for reusing wastewater to water plants. The function made by various configurations such as a VFCW, a HFCW, and a FWSCW placed sequentially in the HCW system proved crucial to treat wastewater and make it reusable.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 2","pages":"222"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-assisted prediction of engineered carbon systems' capacity to treat textile dyeing wastewater via adsorption technology.","authors":"Om Kulkarni, Priya Dongare, Bhavana Shanmughan, Amrita Nighojkar, Shilpa Pandey, Balasubramanian Kandasubramanian","doi":"10.1007/s10661-025-13664-9","DOIUrl":"https://doi.org/10.1007/s10661-025-13664-9","url":null,"abstract":"<p><p>Dyes are widely used in industries like printing, cosmetics, paper, leather processing, textiles, and manufacturing to add color to products. However, improper disposal of dyes into wastewater has raised major concerns due to their harmful effects on plants, animals, and humans. Using engineered carbon systems (ECSs) to treat dye-contaminated wastewater has shown promise for sustainable waste management. Dye adsorption on ECSs is a complex, non-linear process, making it essential to understand ECSs' dye removal capabilities through a modeling framework that includes experimental and environmental factors. To support this, a database of ECSs used in dye removal from textile wastewater was compiled. Twelve machine learning models, including XGBoost, Light Gradient Boost, Random Forest, Gradient Boost, CatBoost, AdaBoost, Decision Tree, Artificial Neural Network, K-Nearest Neighbor, Support Vector Machine, Huber, and Ridge Regressor, were applied to analyze ECSs' dye removal potential. Out of all the models, XGBoost exhibited the highest coefficient of determination (R²) of 0.986 during the training and 0.978 during testing, alongside the lowest prediction error (MSE) of 0.01 and 0.136 in the training phase and testing phase. The quantity of ECS, concentration of dye (C_o), and pH of wastewater highly influenced the adsorption process. The optimization results indicated the highest affinity of direct, reactive, and dispersed dyes towards ECSs in the acidic solution. In contrast, the maximum adsorption of Basic and VAT dye on ECSs was found in the alkaline solution. The partial dependence analysis provided valuable insights into the interaction between ECS dose and water matrix parameters that can lead to efficient extraction of dyes from aqueous matrices.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 2","pages":"223"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Citizen science to promote a nature-based solution: barriers and lessons learned from a vegetated vermifilter implementation experience in a Chilean community.","authors":"Mariela A Yevenes, Alan S Kolok, Ana Araneda","doi":"10.1007/s10661-025-13628-z","DOIUrl":"https://doi.org/10.1007/s10661-025-13628-z","url":null,"abstract":"<p><p>Nature-based solutions (NBSs) offer environmentally rational, socially acceptable, and economically viable alternatives for solving diverse water issues. Therefore, the involvement of local communities is crucial, as their participation in developing shared knowledgewithin their territories is essential for building and sustaining resilient ecosystems. This study highlights a co-created, nature-based initiative that led to the construction of a vegetated vermifilter for greywater reuse and monitoring in a small community at the Nonguén School Community, located in the Biobío region, central Chile. The project was initiated in 2019, but not completed until 2022 due to the COVID-19 pandemic. The vermifilter was based on green filters and was used to recover white greywater (dishwater and handwash water) for irrigation use. The circular biofilter, built by the community and directly connected to the kitchen, consisted of four distinct layers: rock, sand, topsoil, and sawdust. It also included populations of earthworms and wetland plants, all primarily collected by the community. Water analysis (i.e., pH, temperature, BOD₅, TSS, nitrate, phosphate, turbidity, dissolved oxygen, and total and fecal coliforms) demonstrated a moderate effectiveness during a measured period in 2022. We highlight and discuss the fundamental role of the participation of the local community in the whole co-work process and key lessons and barriers to further optimize a vermifilter design.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 2","pages":"221"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of electrocoagulation and solar energy for sustainable wastewater treatment: a thermodynamic and life cycle assessment study.","authors":"Afşın Yusuf Çetinkaya","doi":"10.1007/s10661-025-13662-x","DOIUrl":"https://doi.org/10.1007/s10661-025-13662-x","url":null,"abstract":"<p><p>This study presents an innovative approach to sustainable wastewater treatment by integrating electrocoagulation (EC) with solar energy and biogas. The research evaluates the performance of an EC reactor in terms of chemical oxygen demand (COD) removal efficiency under varying current densities, demonstrating enhanced COD removal rates with increased current densities, achieving up to 95.3% at 1500 A/m². Life cycle assessment (LCA) is employed to compare the environmental impacts of different energy sources for powering the EC system. The findings indicate that biogas derived from domestic waste offers a lower environmental impact compared to natural gas, coal, hydro, solar, and wind. The study further explores the potential of solar energy in Turkey, particularly in Istanbul, where high solar radiation could be harnessed. However, the efficiency of photovoltaic (PV) panels is affected by temperature, with an observed efficiency decrease of approximately 0.5% per degree Celsius increase in temperature. Effective cooling strategies are thus essential for optimizing PV performance. The integration of EC with solar energy, powered by biogas, not only enhances wastewater treatment efficiency but also contributes to reduced greenhouse gas emissions and energy costs. This combined approach presents a viable solution for both domestic and industrial wastewater treatment, especially in remote or off-grid areas.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 2","pages":"224"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wastewater quality prediction based on channel attention and TCN-BiGRU model.","authors":"Jianbo Yuan, Yongjian Li","doi":"10.1007/s10661-025-13627-0","DOIUrl":"https://doi.org/10.1007/s10661-025-13627-0","url":null,"abstract":"<p><p>Water quality prediction is crucial for water resource management, as accurate forecasting can help identify potential issues in advance and provide a scientific basis for sustainable management. To predict key water quality indicators, including chemical oxygen demand (COD), suspended solids (SS), total phosphorus (TP), pH, total nitrogen (TN), and ammonia nitrogen (NH₃-N), we propose a novel model, CA-TCN-BiGRU, which combines channel attention mechanisms with temporal convolutional networks (TCN) and bidirectional gated recurrent units (BiGRU). The model, which uses a multi-input multi-output (MIMO) architecture, is capable of simultaneously predicting multiple water quality indicators. It is trained and tested using data from a wastewater treatment plant in Huizhou, China. This study investigates the impact of data preprocessing and the channel attention mechanism on model performance and compares the predictive capabilities of various deep learning models. The results demonstrate that data preprocessing significantly improves prediction accuracy, while the channel attention mechanism enhances the model's focus on key features. The CA-TCN-BiGRU model outperforms others in predicting multiple water quality indicators, particularly for COD, TP, and SS, where MAE and RMSE decrease by approximately 23% and 26%, respectively, and R2 improves by 5.85%. Moreover, the model shows strong robustness and real-time performance across different wastewater treatment plants, making it suitable for short-term (1-3 days) water quality prediction. The study concludes that the CA-TCN-BiGRU model not only achieves high accuracy but also offers low computational overhead and fast inference speed, making it an ideal solution for real-time water quality monitoring.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 2","pages":"219"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A decade-long spatial analysis of opportunistic rice cultivation in a water-stressed agricultural landscape.","authors":"Mahboob Karimi, Mozhgan Ahmadi Nadoushan, Elham Chavoshi","doi":"10.1007/s10661-025-13656-9","DOIUrl":"https://doi.org/10.1007/s10661-025-13656-9","url":null,"abstract":"<p><p>Rice cultivation is a highly criticized sector of agriculture in Iran. Despite the intensifying drought conditions, Central Iranian farmers continue to prioritize rice cultivation due to its substantial economic benefits, affecting the structure and configuration of irrigated agricultural landscapes. In a river catchment, we mapped rice fields over a 10-year period (2014-2023) using Landsat-8 OLI images, with mapping accuracy metrics showing kappa coefficients above 81.75 and overall accuracy above 92.78. Spatial analysis of the layers revealed the following: (1) an inconsistent pattern of rice cultivation over the study period, with more than 51% of the total agricultural area experiencing rice cultivation only once; (2) a contiguous area of high suitability for opportunistic rice cultivation along the main river of the region based on frequency hotspot analysis; and (3) years with larger rice cultivation resulted in more fragmented rice landscapes due to the incentive to cultivate smaller, scattered plots in newly accessible areas. Our results demonstrate that increased water availability does not necessarily translate to improved landscape structure; as rice cultivation expands, the landscape becomes more fragmented.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 2","pages":"216"},"PeriodicalIF":2.9,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}