Kalman filtering assimilated machine learning methods significantly improve the prediction performance of water quality parameters by Zhenyu Gao, Guoqiang Wang, Jinyue Chen, Lei Fang, Shilong Ren, A. Yinglan, Shuping Ji, Ruobing Liu, Qiao Wang

“…Our results demonstrated significant improvements in predicting key water quality parameters, including total nitrogen (TN), total phosphorus (TP), and the permanganate index (CODMn), through the integration of KF with four ML models (LSTM, RF, XGBoost, and SVR). …”
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Impact of Land Use on Oceanography Parameters and Quality of Seaweed Kappaphycus alvarezii in Coastal Waters of South Sulawesi, Indonesia by Muhammad Farid Samawi, Mahatma Lanuru, Fajriansyah Nadir, Andi Asriadi Pratama, Indra Kurniawan

“…The quality of seaweed observed was chlorophyll-a, carrageenan content, water content, and ash content in seaweed reared in coastal waters. …”
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An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival by Saima Kanwal, Muhammad Abdullah, Sahil Kumar, Saqib Arshad, Muhammad Shahroz, Dawei Zhang, Dileep Kumar

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Monitoring Stations for Surface Water Quality by Qingren Wang, Yuncong Li, Thomas Obreza, Rafael Munzo-Carpena

“…Specialized probes measure water quality parameters, electronic logging devices record and store data, and automatic samplers capture multiple water samples on either time or flow intervals. …”
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Assessment of groundwater quality for drinking purposes using water quality index in volcanic rock areas of Axum, Northern Ethiopia by Haile Tadelle Abadi, Teka Asresie, Amdom Mihretu, Welday Gebrehiwot

“…However, its quality is increasingly threatened by pollution. This study evaluates the suitability of groundwater for drinking and investigates the hydrogeochemical processes that influence water quality in the volcanic rock-dominated area of Axum, Ethiopia. …”
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Spatiotemporal water quality data reconstruction: A tensor factorization framework by Xuke Wu, Kun Shan, Lan Wang, Jingkai Wang, Mingsheng Shang

“…Automatic high-frequency monitoring (AHFM) of water quality parameters has gained growing attention for managing eutrophic lakes. …”
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Relationship of Chlorophyll a Concentration to Seasonal Water Quality in Lake Manatee, Florida by Craig D. Stanley, R. A. Clarke, Brian L. McNeal, B. W. Macleod

“… The primary objectives of this study were to determine if a significant relationship existed between levels of selected water quality parameters and Chl a concentration in Lake Manatee, and to develop a predictive equation for estimating when water quality conditions were conducive to high Chl a levels. …”
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Helminths of channel catfish (Ictalurus punctatus) from ponds with different water sources by Ricardo Alejandro Pérez-Lizama, Jesús Genaro Sánchez-Martínez, Roberto Pérez-Castañeda

“…ABSTRACT: This study compared water quality and helminth infections in channel catfish across two farms with differing water sources (well vs. river). …”
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Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches by Bing Cheng, Xinyu Liu, Keke Guo, Ahmad Rastegarnia

“…These parameters are directly related to water quality and are influenced by the natural characteristics of the region. …”
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Climate Change Impacts on the Indus River Basin: Hydrology, Water Quality, and Treaty Implications by Muhammad Khizar, Shah Nawaz, Hassan Bashir, Muhammad Aqeel

“…Using field data from the Kunar and Kabul rivers (tributaries of the Indus) and a review of climate impacts, significant regional differences in water quality parameters were noted and climate-induced hazards (e.g. floods, droughts, salinity intrusion, ecosystem stress) outlined. …”
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An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance by Abhijeet Das

“…The geospatial approaches namely, Inverse Distance Weighted (IDW) has been implemented to draw the interpolated maps for different water quality parameters. Water samples were collected from 19 different sites to evaluate 20 water quality indicators during the pre-monsoon (PRM) season. …”
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Integrated evaluation of groundwater hydrochemistry using multivariate statistics and irrigation-based water quality indices by Raisul Islam, Vinod Kumar Kushwah, Nakul Gupta, Ashish Kumar, Rajesh Goyal, Parveen Berwal, Faisal M. Alfaisal, Ali Majdi, Osamah J. Al-sareji, Majed Alsubih

“…Fifteen different hydro chemical parameters selected for analysis, they are pH, total dissolved solids (TDS), electrical conductivity (EC), Total Hardness (TH), Mg2+, Cl−, Ca2+, Na+, K+, NO3 −, SO4 2−, PO4 3−, F−, CO3 2−, and HCO3 − In the present research various approaches such as Multivariate statistical techniques (MSTs), Arithmetic water quality index (WQI), sodium absorption ratio (SAR), permeability index (PI), sodium percentage (Na%), US salinity, were examined. …”
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Evaluating Groundwater Quality to Determine the Feasibility of Modern Irrigation Techniques (Case Study: Bam-Narmashir Plain) by Hadi Dehghan, Maryam Safavi, Somayeh Galdavi, Mohammad Naderianfar

“…In this study, the groundwater quality parameters of the region were obtained from 55 wells, and the Langiller index was calculated. …”
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Analysis of Illegal Gold Mining (PETI) Impact on The Environment with TDS, TSS, Mercury and Cyanide Parameters in Water and Sediment of Cikaniki River by Awang Silvan Erusani, Nurmaya Arofah*, Sofatunida Sofatunida, Talitha Hasna Fauzi, Muhammad Andi Jabbar

“…This research was conducted at the location of post Illegal gold mining (PETI), although PETI activities have been disciplined, but based on the characteristics of mercury which is difficult to dissolve in water, easily binds to suspended solids and easily deposited to the bottom of the waters, can pollute river sediments. …”
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Comparative analysis of machine learning models for predicting river water quality: a case study of the Zayandeh Rood River by Elham Fazel Najafabadi, Paria Shojaei, Mojgan Askarizadeh

“…This study evaluated five machine learning models, i.e., Lasso Regression, Random Forest (RF), Gradient Boosting (GB), XGBoost, and Support Vector Machine (SVM) for predicting four water quality parameters—EC (Electrical Conductivity), TDS (Total Dissolved Solids), Sodium Adsorption Ratio (SAR), and TH (Total Hardness)—using data collected over a 31-year period from eight monitoring stations along the Zayandeh Rood River, a vital water source for drinking, agriculture, and industry in the arid region of central Iran. …”
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Real-time monitoring of water quality dynamics using low-cost sensor networks in Lagos lagoon by Idowu Ayisat Aneyo, Mumin Olatunji Oladipo, Funmilayo Victoria Doherty, Julius Osato Ehigie, Adebayo Fasasi Adebari, Abdulwakeel Oluwatobi Atoyebi, Peter Ozomata Balogun, Ambrose Obinna Ikpele

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Adaptive biases-incorporated latent factorization of tensors for predicting missing data in water quality monitoring networks by Xuke Wu, Xuke Wu, Lan Wang, Lan Wang, Miao Ge, Miao Ge, Jing Jiang, Jing Jiang, Yu Cai, Bing Yang, Bing Yang

“…Real-time monitoring of key water quality parameters is essential for the scientific management and effective maintenance of aquatic ecosystems. …”
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Substituting photoautotrophic with heterotrophic Chlorella species for water quality regulation and microbial community modification in Litopenaeus vannamei pond culture by Chu-er Song, Zhen Meng, Bangyin Zhang, Lin Yang, Xiaoxuan Sun, Zheng Zhang, Xiaojin Song

“…Regular sampling was performed on water and L. vannamei individuals from both sets of ponds to evaluate water nutrient parameters, bacterial community composition, and growth parameters correspondingly. …”
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Applicability of the series resistance model in predicting the permeability of coated papers to oxygen and water vapor: importance of data quality and associated metadata by Allison Vercasson, Sébastien Gaucel, Nathalie Gontard, Hélène Angellier-Coussy, Valérie Guillard

“…This quality index highlighted that most permeation parameter data from the literature (∼58 %) were not reusable due to the lack of associated metadata. …”
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Spatial and temporal distribution of potentially toxic elements and human health risk assessment in the gold mining area of Santa Rosa, Southern Ecuador by Cindy Goyburo-Chávez, Karla Villamar-Marazita, Cristhian Aguilar-Aguilar, Ana Gonzalez-Valoys, Samantha Jiménez-Oyola

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