{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T19:30:51Z","timestamp":1793475051606,"version":"4.5.0"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:00:00Z","timestamp":1790726400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:00:00Z","timestamp":1790726400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Environmental Management"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1007\/s00267-026-02615-w","type":"journal-article","created":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T17:52:22Z","timestamp":1790790742000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Developing an Innovative River Water Quality Index Model for Ecological Risk Assessment in Rivers"],"prefix":"10.1007","volume":"76","author":[{"given":"Pouria","family":"Rafiee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5531-3720","authenticated-orcid":false,"given":"Hossein","family":"Saadati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9245-9796","authenticated-orcid":false,"given":"Ebrahim","family":"Fataei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatemeh","family":"Nasehi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,30]]},"reference":[{"issue":"2","key":"2615_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/s10661-020-8062-3","volume":"192","author":"B Abdi","year":"2020","unstructured":"Abdi B, Bozorg-Haddad O, Lo\u00e1iciga HA (2020) Analysis of the effect of inputs uncertainty on riverine water temperature predictions with a Markov chain Monte Carlo (MCMC) algorithm. Environ Monit Assess 192(2):100. https:\/\/doi.org\/10.1007\/s10661-020-8062-3.","journal-title":"Environ Monit Assess"},{"key":"2615_CR72","doi-asserted-by":"publisher","unstructured":"Aghajanloo K et al. (2022) Evaluation of Karun River Water Quality Based on IRWQI and WAWQI Indicators in Molasani and Ahvaz Stations. Iranian Journal of Soil and Water Research. University of Tehran Press. https:\/\/doi.org\/10.22059\/ijswr.2022.333148.669115.","DOI":"10.22059\/ijswr.2022.333148.669115"},{"key":"2615_CR2","doi-asserted-by":"publisher","first-page":"137","DOI":"10.22034\/HYDRO.2023.57504.1299","volume":"8","author":"M Akbari-Niyari","year":"2023","unstructured":"Akbari-Niyari M, Razavordi-Najjad V, Bahmanesh A, Nikpour M (2023) Simulation of water quality in the Qara Sou River using the QUAL2Kw model. Hydrogeology 8:137\u2013155. https:\/\/doi.org\/10.22034\/HYDRO.2023.57504.1299.","journal-title":"Hydrogeology"},{"key":"2615_CR4","doi-asserted-by":"publisher","unstructured":"Ali SF (2021) Application of CCME water quality index for drinking purpose in Tigris River within Wasit Province, Iraq. Caspian J Environ Sci, https:\/\/doi.org\/10.22124\/CJES.2021.5208","DOI":"10.22124\/CJES.2021.5208"},{"key":"2615_CR61","doi-asserted-by":"crossref","unstructured":"Addressees A, Khan M, Taha ATB, Ali M (2024) Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches. J Water Process Eng, 58:104789.","DOI":"10.1016\/j.jwpe.2024.104789"},{"issue":"1","key":"2615_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.jece.2020.104599","volume":"9","author":"SBHS Asadollah","year":"2021","unstructured":"Asadollah SBHS, Sharafati A, Motta D, Yaseen ZM (2021) River water quality index prediction and uncertainty analysis: A comparative study of machine learning models. J Environ Chem Eng 9(1):104599. https:\/\/doi.org\/10.1016\/j.jece.2020.104599.","journal-title":"J Environ Chem Eng"},{"key":"2615_CR6","unstructured":"Baird RB, Eaton AD, Rice EW (Eds.). (2017) Standard Methods for the Examination of Water and Wastewater (23rd ed.). American Public Health Association, American Water Works Association, Water Environment Federation"},{"key":"2615_CR7","doi-asserted-by":"publisher","first-page":"2011","DOI":"10.15244\/pjoes\/110526","volume":"29","author":"TD Banda","year":"2020","unstructured":"Banda TD, Kumarasamy MV (2020) Development of Water Quality Indices (WQIs): A Review. Pol J Environ Stud 29:2011\u20132021. https:\/\/doi.org\/10.15244\/pjoes\/110526.","journal-title":"Pol J Environ Stud"},{"key":"2615_CR8","doi-asserted-by":"publisher","unstructured":"Chapman DV (2021) Water quality assessments: a guide to the use of biota, sediments and water in environmental monitoring. CRC Press. https:\/\/doi.org\/10.4324\/9780203476710","DOI":"10.4324\/9780203476710"},{"issue":"1","key":"2615_CR9","doi-asserted-by":"publisher","first-page":"e0340418","DOI":"10.1371\/journal.pone.0340418","volume":"21","author":"R Chi","year":"2026","unstructured":"Chi R, Da Y, Li W, Wen D (2026) Intelligent diagnosis method for river and lake ecosystem health based on improved slime mold algorithm-optimized SVR. PloS ONE 21(1):e0340418. https:\/\/doi.org\/10.1371\/journal.pone.0340418.","journal-title":"PloS ONE"},{"key":"2615_CR74","doi-asserted-by":"publisher","unstructured":"Custodio M et al. (2025) Ecological and human health risk assessment of heavy metals in mining-affected river sediments in the Peruvian Central highlands. Toxics, 13(9):783. https:\/\/doi.org\/10.3390\/toxics13090783.","DOI":"10.3390\/toxics13090783"},{"key":"2615_CR10","doi-asserted-by":"publisher","unstructured":"Das A (2025). Prediction of Urban Surface Water Quality Scenarios Using Water Quality Index (WQI), Multivariate Techniques, and Machine Learning (ML) Models in Water Resources, in Baitarani River Basin, Odisha: Potential Benefits and Associated Challenges. Earth Syst Environ. https:\/\/doi.org\/10.1007\/s41748-025-00623-0","DOI":"10.1007\/s41748-025-00623-0"},{"key":"2615_CR11","doi-asserted-by":"publisher","unstructured":"Das A (2026) Data analytics and integration of CCME-water quality index, water pollution index (WPI), and contamination index (CI) with GIS approach for a better understanding of drinking water quality. In Data Analytics and Remote Sensing-Based Analysis for Sustainable Development (pp. 39\u201363). Cham: Springer Nature Switzerland. https:\/\/doi.org\/10.1007\/978-3-031-98095-4_4","DOI":"10.1007\/978-3-031-98095-4_4"},{"issue":"2","key":"2615_CR13","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1007\/s13201-022-01858-2","volume":"13","author":"AA El-Degwy","year":"2022","unstructured":"El-Degwy AA, Negm NA, El-Tabl AS, Goher ME (2022) Assessment of heavy metal pollution in water and its effect on Nile tilapia (Oreochromis niloticus) in Mediterranean Lakes: a case study at Mariout Lake. Appl Water Sci 13(2):50. https:\/\/doi.org\/10.1007\/s13201-022-01858-2.","journal-title":"Appl Water Sci"},{"key":"2615_CR14","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1016\/j.eti.2018.06.013","volume":"11","author":"SH Ewaid","year":"2018","unstructured":"Ewaid SH, Abed SA, Kadhum SA (2018) Predicting the Tigris River water quality within Baghdad, Iraq by using water quality index and regression analysis. Environ Technol Innov 11:390\u2013398. https:\/\/doi.org\/10.1016\/j.eti.2018.06.013.","journal-title":"Environ Technol Innov"},{"issue":"7","key":"2615_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/s10661-022-10121-9","volume":"194","author":"P Fathi","year":"2022","unstructured":"Fathi P, Ebrahimi Dorche E, Zare Shahraki M, Stribling J, Beyraghdar Kashkooli O, Esmaeili Ofogh A, Bruder A (2022) Revised Iranian Water Quality Index (RIWQI): a tool for the assessment and management of water quality in Iran. Environ Monit Assess 194(7):504. https:\/\/doi.org\/10.1007\/s10661-022-10121-9.","journal-title":"Environ Monit Assess"},{"issue":"2","key":"2615_CR16","doi-asserted-by":"publisher","first-page":"289","DOI":"10.3390\/w15020289","volume":"15","author":"A Gaagai","year":"2023","unstructured":"Gaagai A, Aouissi HA, Bencedira S, Hinge GA (2023) Application of Water Quality Indices, Machine Learning Approaches, and GIS to Identify Groundwater Quality for Irrigation Purposes: A Case Study of Sahara Aquifer, Doucen Plain, Algeria. Water Water 15(2):289. https:\/\/doi.org\/10.3390\/w15020289.","journal-title":"Water Water"},{"key":"2615_CR17","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1080\/01621459.1990.10476213","volume":"85","author":"AE Gelfand","year":"1990","unstructured":"Gelfand AE, Smith AF (1990) Sampling-based approaches to calculating marginal densities. J Am Stat Assoc 85:398\u2013409.","journal-title":"J Am Stat Assoc"},{"key":"2615_CR18","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1214\/ss\/1177011136","volume":"7","author":"A Gelman","year":"1992","unstructured":"Gelman A, Rubin DB (1992) Inference from iterative simulation using multiple sequences. Stat Sci 7:457\u2013472.","journal-title":"Stat Sci"},{"key":"2615_CR19","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1080\/02664769300000058","volume":"20","author":"S Geman","year":"1993","unstructured":"Geman S, Geman D (1993) Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. J Appl Stat 20:25\u201362.","journal-title":"J Appl Stat"},{"key":"2615_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoinf.2021.101299","volume":"63","author":"S Gupta","year":"2021","unstructured":"Gupta S, Gupta SK (2021a) A critical review on water quality index tool: Genesis, evolution and future directions. Ecol Inform 63: 101299. https:\/\/doi.org\/10.1016\/j.ecoinf.2021.101299.","journal-title":"Ecol Inform"},{"issue":"21","key":"2615_CR22","doi-asserted-by":"publisher","first-page":"27033","DOI":"10.1007\/s11356-021-12501-z","volume":"28","author":"S Gupta","year":"2021","unstructured":"Gupta S, Gupta SK (2021b) Development and evaluation of an innovative Enhanced River Pollution Index model for holistic monitoring and management of river water quality. Environ Sci Pollut Res 28(21):27033\u201327046. https:\/\/doi.org\/10.1007\/s11356-021-12501-z.","journal-title":"Environ Sci Pollut Res"},{"key":"2615_CR71","doi-asserted-by":"publisher","unstructured":"Hajiradkouchak E et al. (2024). Water quality assessment of Qarasu River using IRWQIsc index. J Eng Geol 18(3):365\u2013381. https:\/\/doi.org\/10.22034\/JEG.2024.18.3.1019932","DOI":"10.22034\/JEG.2024.18.3.1019932"},{"issue":"8","key":"2615_CR23","doi-asserted-by":"publisher","first-page":"975","DOI":"10.1016\/0043-1354(80)90143-8","volume":"14","author":"L Hakanson","year":"1980","unstructured":"Hakanson L (1980) An ecological risk index for aquatic pollution control. A sedimentological approach. Water Res 14(8):975\u20131001.","journal-title":"Water Res"},{"key":"2615_CR65","doi-asserted-by":"crossref","unstructured":"Hastings WK (1970) Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57(1):97\u2013109","DOI":"10.1093\/biomet\/57.1.97"},{"key":"2615_CR68","doi-asserted-by":"publisher","unstructured":"Hridoy MAAM et al., (2025) Advanced machine learning models for accurate water quality classification and WQI prediction: Implications for aquatic disease risk management. Sci Total Environ 1008:180965. https:\/\/doi.org\/10.1016\/j.scitotenv.2025.180965.","DOI":"10.1016\/j.scitotenv.2025.180965"},{"issue":"1","key":"2615_CR25","doi-asserted-by":"publisher","first-page":"355","DOI":"10.3390\/app16010355","volume":"16","author":"H Karahan","year":"2025","unstructured":"Karahan H, Alkaya D (2025) Integrating SVR Optimization and Machine Learning-Based Feature Importance for TBM Penetration Rate Prediction. Appl Sci 16(1):355. https:\/\/doi.org\/10.3390\/app16010355.","journal-title":"Appl Sci"},{"issue":"3","key":"2615_CR26","doi-asserted-by":"publisher","first-page":"274","DOI":"10.22034\/jewe.2020.238090.1381","volume":"6","author":"R Kkhalili","year":"2020","unstructured":"Kkhalili R, Parvinnia M, Zali A (2020) Water quality assessment of Garmarood River using the national sanitation foundation water quality index (NSFWQI), river pollution index (RPI) and weighted arithmetic water quality index (WAWQI). Environ Water Eng 6(3):274\u2013284. https:\/\/doi.org\/10.22034\/jewe.2020.238090.1381.","journal-title":"Environ Water Eng"},{"key":"2615_CR62","doi-asserted-by":"crossref","unstructured":"Kuhn M, Johnson K (2013) Factors that can affect model performance. In Applied predictive modeling (pp. 521\u2013546). New York, NY: Springer New York.","DOI":"10.1007\/978-1-4614-6849-3_20"},{"key":"2615_CR59","doi-asserted-by":"crossref","unstructured":"Kumar M, Patel AK, Singh A (2022) Anthropogenic dominance on geogenic arsenic problem of the groundwater in the Ganga-Brahmaputra floodplain: A paradox of origin and mobilization. Sci Total Environ 807, 151461.\u200f","DOI":"10.1016\/j.scitotenv.2021.151461"},{"key":"2615_CR60","doi-asserted-by":"crossref","unstructured":"Li H, Chen S, Ma T, Ruan X (2022) The quantification of the influencing factors for spatial and temporal variations in surface water quality in recent ten years of the Huaihe River Basin, China. Environ Sci Pollut Res 29(29):44490\u201344503.","DOI":"10.1007\/s11356-021-18282-9"},{"issue":"1","key":"2615_CR27","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1007\/s13201-024-02341-w","volume":"15","author":"M Latif","year":"2025","unstructured":"Latif M, Nasim I, Ahmad M, Nawaz R, Tahir A, Irshad MA, Al-Mutairi AA, Irfan A, Al-Hussain SA, Zaki MEA (2025) Human health risk assessment of drinking water using heavy metal pollution index: a GIS-based investigation in mega city. Appl Water Sci 15(1):12. https:\/\/doi.org\/10.1007\/s13201-024-02341-w.","journal-title":"Appl Water Sci"},{"issue":"9","key":"2615_CR29","doi-asserted-by":"publisher","first-page":"1736","DOI":"10.3390\/w15091736","volume":"15","author":"DK Lukhabi","year":"2023","unstructured":"Lukhabi DK, Mensah PK, Asare NK, Pulumuka-Kamanga T, Ouma KO (2023) Adapted Water Quality Indices: Limitations and Potential for Water Quality Monitoring in Africa. Water 15(9):1736. https:\/\/doi.org\/10.3390\/w15091736.","journal-title":"Water"},{"key":"2615_CR30","doi-asserted-by":"publisher","DOI":"10.34133\/olar.0050","volume":"3","author":"Z Lv","year":"2024","unstructured":"Lv Z, Ran X, Liu J, Feng Y, Zhong X, Jiao N (2024) Effectiveness of chemical oxygen demand as an indicator of organic pollution in aquatic environments. Ocean-Land-Atmosphere Res 3:0050. https:\/\/doi.org\/10.34133\/olar.0050.","journal-title":"Ocean-Land-Atmosphere Res"},{"issue":"1","key":"2615_CR31","first-page":"99","volume":"12","author":"F Mahrooyan","year":"2021","unstructured":"Mahrooyan F, Taghavi L, Sarai Tabrizi M, Babazadeh H (2021) Water quality assessment of Qazvin River using NSFWQI Index for water quality classification. J Wetl Ecobiol 12(1):99\u2013112. http:\/\/jweb.ahvaz.iau.ir\/article-1-855-en.html.","journal-title":"J Wetl Ecobiol"},{"key":"2615_CR73","doi-asserted-by":"publisher","unstructured":"Mohammadi J et al. (2023) Investigation and determination of land use effects on surface water quality in semi-arid areas: Case study on Qarasu River in Iran. Anthropogenic Pollution, 7(2). https:\/\/doi.org\/10.57647\/j.jap.2023.0702.19.","DOI":"10.57647\/j.jap.2023.0702.19"},{"key":"2615_CR36","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.22108\/GEP.2022.133344.1516","volume":"21","author":"N Metropolis","year":"1953","unstructured":"Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21:1087\u20131092. https:\/\/doi.org\/10.22108\/GEP.2022.133344.1516.","journal-title":"J Chem Phys"},{"key":"2615_CR37","unstructured":"Mohammadpour-Khalilabad A, Fataei E (2014) Assessment of environmental pollution sources in the Sabalan Dam watershed of Ardabil Proceedings of the Second National Conference on Agricultural Engineering and Management, Environment, and Sustainable Natural Resources"},{"key":"2615_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.jwpe.2024.105695","volume":"64","author":"JCY Ngu","year":"2024","unstructured":"Ngu JCY, Yeo WS, Chan MK, Nandong J (2024) Least squares support vector regression-based modeling of ammonia oxidation using immobilized nanoFeCu. J Water Process Eng 64:105695. https:\/\/doi.org\/10.1016\/j.jwpe.2024.105695.","journal-title":"J Water Process Eng"},{"key":"2615_CR39","unstructured":"Parivesh B, Nagar EA (2020) Central pollution control board. Central Pollut. Control Board, New Delhi, India, Tech. Rep, 20\u201321. https:\/\/dghindia.gov.in\/assets\/downloads\/687a44d57baeecpcb.pdf"},{"key":"2615_CR63","doi-asserted-by":"crossref","unstructured":"Palab\u0131y\u0131k S, Akkan T (2024) Evaluation of water quality based on artificial intelligence: performance of multilayer perceptron neural networks and multiple linear regression versus water quality indexes. Environ Dev Sustain.","DOI":"10.1007\/s10668-024-05075-6"},{"key":"2615_CR66","doi-asserted-by":"publisher","unstructured":"Rafiee G et al. (2023) Assessing water quality indices and autopurification capacity of Balighli-Chai and Ghare-Sou Rivers using QUAL2Kw model. Environ. Water Eng., 9(3):335\u2013351. https:\/\/doi.org\/10.22034\/jewe.2022.336023.1756","DOI":"10.22034\/jewe.2022.336023.1756"},{"key":"2615_CR41","doi-asserted-by":"publisher","unstructured":"Relji\u0107 M, Romi\u0107 M, Romi\u0107 D, Gilja G, Mornar V, Ondrasek G, Bubalo Kova\u010di\u0107 M, Zovko M. (2023) Advanced Continuous Monitoring System\u2014Tools for Water Resource Management and Decision Support System in Salt Affected Delta. Agriculture, 13(2). https:\/\/doi.org\/10.3390\/agriculture13020369","DOI":"10.3390\/agriculture13020369"},{"key":"2615_CR42","doi-asserted-by":"publisher","unstructured":"Roshani-Sefidkouhi M, Mortezazadeh F, Eslamifar M, Babanezhad E, Sheikhi M, Gholami-Borujeni F (2025) Water quality assessment using IRWQIsc and NSFWQI water quality indicators; A case study: Talar River (Iran). Heliyon, 11(2). https:\/\/doi.org\/10.1016\/j.heliyon.2025.e41812","DOI":"10.1016\/j.heliyon.2025.e41812"},{"key":"2615_CR43","doi-asserted-by":"publisher","unstructured":"Rusydi AF (2018) Correlation between conductivity and total dissolved solid in various type of water: A review. In IOP conference series: earth and environmental science (Vol. 118, 012019). IOP publishing. https:\/\/doi.org\/10.1088\/1755-1315\/118\/1\/012019","DOI":"10.1088\/1755-1315\/118\/1\/012019"},{"issue":"6","key":"2615_CR44","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1080\/20421338.2019.1692460","volume":"12","author":"MM Sahoo","year":"2020","unstructured":"Sahoo MM, Patra KC (2020) River water quality modelling and simulation based on Markov Chain Monte Carlo computation and Bayesian inference model. Afr J Sci, Technol Innov Dev 12(6):771\u2013785. https:\/\/doi.org\/10.1080\/20421338.2019.1692460.","journal-title":"Afr J Sci, Technol Innov Dev"},{"issue":"5","key":"2615_CR45","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s13201-024-02135-0","volume":"14","author":"B Sharma","year":"2024","unstructured":"Sharma B, Goel NK (2024) Streamflow prediction using support vector regression machine learning model for Tehri Dam. Appl Water Sci 14(5):99. https:\/\/doi.org\/10.1007\/s13201-024-02135-0.","journal-title":"Appl Water Sci"},{"key":"2615_CR64","doi-asserted-by":"crossref","unstructured":"Shi P, Yang T, Yong B, Xu CY, Li Z, Wang X, Zhou X (2023) Some statistical inferences of parameter in MCMC approach and the application in uncertainty analysis of hydrological simulation. J. Hydrol. 617:128767.","DOI":"10.1016\/j.jhydrol.2022.128767"},{"key":"2615_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2022.157389","volume":"846","author":"Y Tian","year":"2022","unstructured":"Tian Y, Wen Z, Cheng M, Xu M (2022) Evaluating the water quality characteristics and tracing the pollutant sources in the Yellow River Basin, China. Sci Total Environ 846:157389. https:\/\/doi.org\/10.1016\/j.scitotenv.2022.157389.","journal-title":"Sci Total Environ"},{"key":"2615_CR48","doi-asserted-by":"publisher","unstructured":"Tiwari D, Kumar R, Yadav M, Kumar Singh S (2024) Holistic Analysis of Ganga Basin Water Quality: A Statistical Approach with WQI, HMCI, HMQI, and HRI Indices. https:\/\/doi.org\/10.1039\/D4RA06144F","DOI":"10.1039\/D4RA06144F"},{"key":"2615_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2020.107218","volume":"122","author":"MG Uddin","year":"2021","unstructured":"Uddin MG, Nash S, Olbert AI (2021) A review of water quality index models and their use for assessing surface water quality. Ecol Indic 122:107218. https:\/\/doi.org\/10.1016\/j.ecolind.2020.107218.","journal-title":"Ecol Indic"},{"key":"2615_CR50","doi-asserted-by":"publisher","first-page":"808","DOI":"10.1016\/j.psep.2022.11.073","volume":"169","author":"MG Uddin","year":"2023","unstructured":"Uddin et al. (2023) Performance analysis of the water quality index model for predicting water state using machine learning techniques. Process Saf Environ Prot 169:808\u2013828. https:\/\/doi.org\/10.1016\/j.psep.2022.11.073.","journal-title":"Process Saf Environ Prot"},{"issue":"1","key":"2615_CR51","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s13201-019-0893-0","volume":"9","author":"RK Verma","year":"2019","unstructured":"Verma RK, Murthy S, Tiwary RK, Verma S (2019) Development of simplified WQIs for assessment of spatial and temporal variations of surface water quality in upper Damodar river basin, eastern India. Appl Water Sci 9(1):21. https:\/\/doi.org\/10.1007\/s13201-019-0893-0.","journal-title":"Appl Water Sci"},{"key":"2615_CR69","doi-asserted-by":"publisher","unstructured":"Wang B, Wang Y, Wang S (2021) Improved water pollution index for determining spatiotemporal water quality dynamics: Case study in the Erdao Songhua River Basin, China. Ecol Indic 129:107931. https:\/\/doi.org\/10.1016\/j.ecolind.2021.107931","DOI":"10.1016\/j.ecolind.2021.107931"},{"issue":"18","key":"2615_CR52","doi-asserted-by":"publisher","first-page":"2701","DOI":"10.3390\/w16182701","volume":"16","author":"Y Wang","year":"2024","unstructured":"Wang Y, Li M, Zhao J, Yang J\u2019e (2024) Evaluation of River Health and Human Well-Being in the Heihe River Basin Using the SMI-P Method: A Case Study of the Zhangye City. Water 16(18):2701. https:\/\/doi.org\/10.3390\/w16182701.","journal-title":"Water"},{"issue":"7","key":"2615_CR53","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1007\/s11783-023-1688-y","volume":"17","author":"Z Wang","year":"2023","unstructured":"Wang Z, Wang Q, Wu T (2023) A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM. Front Environ Sci Eng 17(7):88. https:\/\/doi.org\/10.1007\/s11783-023-1688-y.","journal-title":"Front Environ Sci Eng"},{"key":"2615_CR67","unstructured":"World Health Organization (2022) WHO European conference on tackling noncommunicable diseases through digital solutions, 14\u201315 December 2021, Moscow. Good practice examples: European Response to Noncommunicable Diseases 4.0: 10 years following the Moscow Declaration viewed through the lens of the European Programme of Work (No. WHO\/EURO: 2022-4573-44336-62640). World Health Organization. Regional Office for Europe.\u200f"},{"key":"2615_CR54","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2022.108561","volume":"135","author":"H Xu","year":"2022","unstructured":"Xu H, Gao Q, Yuan B (2022) Analysis and identification of pollution sources of comprehensive river water quality: Evidence from two river basins in China. Ecol Indic 135:108561. https:\/\/doi.org\/10.1016\/j.ecolind.2022.108561.","journal-title":"Ecol Indic"},{"issue":"2","key":"2615_CR55","doi-asserted-by":"publisher","first-page":"559","DOI":"10.3390\/su16020559","volume":"16","author":"K Yao","year":"2024","unstructured":"Yao K, Chen Y, Li Y, Zhang X, Zhu B, Gao Z, Lin F, Hu Y (2024) Water quality prediction of small-micro water body based on the intelligent-algorithm-optimized support vector machine regression method and unmanned aerial vehicles multispectral data. Sustainability 16(2):559. https:\/\/doi.org\/10.3390\/su16020559.","journal-title":"Sustainability"},{"issue":"4","key":"2615_CR56","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1007\/s43452-025-01251-1","volume":"25","author":"L Yu","year":"2025","unstructured":"Yu L, Wang C-Q, Liu C-K (2025) Phosphogypsum composite cement-based permeable bricks: optimization of mix design, performance evaluation, and environmental impact. Arch Civ Mech Eng 25(4):197. https:\/\/doi.org\/10.1007\/s43452-025-01251-1.","journal-title":"Arch Civ Mech Eng"},{"key":"2615_CR70","doi-asserted-by":"crossref","unstructured":"Yu et al. (2024) Enhancing long-term river water quality prediction: construction and validation of an improved hybrid model. Process Saf Environ Prot 186:388\u2013398.","DOI":"10.1016\/j.psep.2024.03.090"},{"key":"2615_CR58","doi-asserted-by":"publisher","unstructured":"Zhang P, Yang M, Lan J, Huang Y, Zhang J, Huang S, Yang Y, Ru J. (2023) Water Quality Degradation Due to Heavy Metal Contamination: Health Impacts and Eco-Friendly Approaches for Heavy Metal Remediation. Toxics, 11(10). https:\/\/doi.org\/10.3390\/toxics11100828","DOI":"10.3390\/toxics11100828"}],"container-title":["Environmental Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00267-026-02615-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00267-026-02615-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00267-026-02615-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T18:30:24Z","timestamp":1793471424000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00267-026-02615-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,30]]},"references-count":62,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2026,10]]}},"alternative-id":["2615"],"URL":"https:\/\/doi.org\/10.1007\/s00267-026-02615-w","relation":{},"ISSN":["0364-152X","1432-1009"],"issn-type":[{"value":"0364-152X","type":"print"},{"value":"1432-1009","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,30]]},"assertion":[{"value":"27 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 August 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 September 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"333"}}