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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

WHONDRS Summer 2019 Sampling Campaign: Global River Corridor Surface Water FTICR-MS, NPOC, TN, Anions, Stable Isotopes, Bacterial Abundance, and Dissolved Inorganic Carbon (v8)

The WHONDRS Summer 2019 Sampling (S19S) Campaign collected samples in 97 globally distributed river corridor systems between July and September 2019. Surficial streambed sediments were collected at three locations within each site (upstream, midstream, and downstream). Surface water was collected at the downstream site. This dataset includes a portion of the data types produced from the surface water samples and does not include any results from the sediment. Sediment data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1729719. The S19S campaign was designed with the science community to ask questions associated with links among core/transient metabolomes, microbial metabolism, biogeochemical function, and physical properties of watershed and river corridor systems. This data package was originally published in March 2020. It was updated in October 2020 (v2, new and modified files), July 2021 (v3, new and modified files), January 2023 (v4, new and modified files), February 2023 (v5, new and modified files), August 2023 (v6, new and modified files), July 2025 (v7,new and modified files), and August 2026 (v8, new and modified files). Version 8 includes major restructuring of the files and their formats. See the change history section in readme for more details. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset contains (1) readme, (2) data dictionary, (3) file level metadata, (4) sampling protocol, (5) a data checks report, (6) field metadata, (7) international generic sample number (IGSN) mapping file, (8) joint genome institute (JGI) mapping file, and (9) a folder of sample data. The sample data folder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and FTICR methods, (2) dissolved inorganic carbon (DIC), (3) stable water isotopes (O and H), (4) specific conductivity, (5) total dissolved nitrogen (TN), (6) anions, (7) flow cytometry bacterial abundance data, (8) laboratory methods, and (9) a folder containing unaligned, peak-picked high resolution characterization of dissolved organic matter from sediment via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL, https://www.pnnl.gov/environmental-molecular-sciences-laboratory), and (12) a folder containing processed FTICR-MS data. All files are .msa, .txt, .spx, .xml, .csv, .pdf, .txt, .html, .jpg, or .jpeg.

18-O↗
DOE OSTI2022

Metal fluxes at the sediment–water interface in a free water surface constructed wetland

Metal biogeochemistry in the sediment, water, and the sediment–water interface (SWI) was studied in a free water surface constructed wetland. Concentrations of labile copper (Cu), zinc (Zn), sulfate, chloride, and dissolved organic carbon (DOC) were measured with the diffusive gradients in thin film (DGT) and peeper. A good agreement between peeper- and DGT-measured metals was observed for Cu (regression r 2 = 0.3, 95% CI of the slopes > 0), but not for Zn (95% CI of the slopes overlapped with 0), which was attributed to the different complexed compounds between Cu and Zn in porewater. The depth profile of labile metals in sediment porewater varied with time and was consistent with the solid-phase metal deposition, showing higher concentrations in the surface layer (3 to –3 cm) than in the bottom layer (–4 to –13 cm). The depth-averaged labile Cu and Zn concentrations measured by DGT were 1.0 and 3.1 µg/L, and labile sulfate, chloride, and DOC concentrations measured by peeper were 1.8, 3.6, and 2.1 mg/L, respectively. A sharp decrease in sulfate occurred in September when sulfate concentrations became the lowest among sampling months. This was caused by the seasonal sulfur cycles in the wetland, where the dominant sulfur reaction is sulfate reduction in warm seasons and sulfide oxidation in cold seasons. Different metal-removal mechanisms were observed in the two wetland cells; sulfur dynamics controlled the removal processes in the cell without frequent disturbance but failed to influence metal removal in the cell with frequent disturbance due to the interruption of anoxic layers. The flux ratios that compare labile element concentrations between the water column and the SWI (R-Cu, R-Zn, R-DOC, R-sulfate, and R-chloride) were generated to determine metal diffusive fluxes at the interface. Labile Zn was mostly transported from the water to the SWI during all seasons (R-Zn < 1 for all months except January). Labile Cu moved from the SWI to the water during the warm months (R-Cu < 1), which was explained by the bioturbation-induced transport of organic matter based on the positive correlations between R-Cu and R-DOC. In general, sediment can serve either as a sink or a source depending on the environmental conditions, metal speciation, and presence of living organisms. Here, metal flux at the SWI is a key component in the biogeochemical cycling of a constructed wetland.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

WHONDRS Surface Water Geochemistry and Organic Matter Characterization Data from Streams Distributed across Latin America

This dataset supports a broader study examining global transferability of stream biogeochemistry and was generated in collaboration with the MicroSudAqua (µSudAqua) network (https://microsudaqua.netlify.app/en/). The dataset provides surface water geochemistry (dissolved organic carbon, total dissolved nitrogen, cations) and organic matter characterization (FTICR-MS) from streams in Argentina, Brazil, Chile, and Colombia. Samples were collected across stream orders (1st to 6th order) within five basins. Related data were collected and will be published separately in collaboration with the µSudAqua network. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos; (2) a folder of surface water sample data, (3) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data; (4) file-level metadata; (5) data dictionary; (6) field metadata; (7) readme; (8) international generic sample number (IGSN) mapping file; and (9) field protocol. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total dissolved nitrogen data and averages; (3) anions and averages; (4) methods codes; (5) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4.

Anions↗
DOE OSTI2023

WHONDRS Surface Water Dissolved Organic Carbon and FTICR-MS across Glacial Features in Svalbard 2022

This dataset supports a broader study examining climatic forcing of terrestrial greenhouse gas emission through permafrost and glaciers in Svalbard. The dataset provides geochemistry and organic matter characterization data generated from surface water collected from 11 sites across central Svalbard. Data were also collected in 2021 and can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1888571. Additional related data were collected and will be published separately in collaboration with Yde and Kleber.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC; measured as non-purgeable organic carbon; NPOC); (5) surface water sampling protocol; (6) readme; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; (9) a folder of field photos; and (10) folder of high resolution characterization of organic matter via 7 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Water-Surface Drag Coating: A New Route Toward High-Quality Conjugated Small-Molecule Thin Films with Enhanced Charge Transport Properties

Electronic properties of organic semiconductor (OSC) thin films are largely determined by their morphologies and crystallinities. However, solution-processed conjugated small-molecule OSC thin films usually exhibit abundant grain boundaries and impure grain orientations because of complex fluid dynamics during solution coating. Here, a novel methodology, water-surface drag coating, is demonstrated to fabricate high-quality OSC thin films with greatly enhanced charge transport properties. This method utilizes the water surface to alter the evaporation dynamics of solution to enlarge the grain size, and a unique drag-coating process to achieve the unidirectional growth of organic crystals. Furthermore, using 2,8-difluoro-5,11-bis(triethylsilylethynyl)anthradithiophene (Dif-TES-ADT) as an example, thin films with millimeter-sized single-crystal domains and pure crystallographic orientations are achieved, revealing a significant enhancement (4.7 times) of carrier mobility. More importantly, the resulting film can be directly transferred onto any desired flexible substrates, and flexible transistors based on the Dif-TES-ADT thin films show a mobility as high as 16.1 cm 2 V -1 s -1 , which represents the highest mobility value for the flexible transistors reported thus far. The method is general for the growth of various high-quality OSC thin films, thus opening up opportunities for high-performance organic flexible electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

WHONDRS Surface Water Dissolved Organic Carbon and FTICR-MS across Stream Orders in Four United States Watersheds in 2019 and 2020 (v3)

This dataset supports the broader Watershed Rules of Life (WROL) study examining spatial and temporal biogeochemical and microbial relationships across the Connecticut River, Deschutes River, Gunnison River, and Willamette River watersheds. The dataset provides geochemistry and organic matter characterization data generated from surface water collected from August 2019 to September 2020 in Colorado, Connecticut, Oregon, and Vermont. Related data were collected and will be published separately in collaboration with P. A. Raymond and B. C. Crump as part of WROL. This dataset is comprised of one folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (6) surface water sampling protocol; (7) methods codes; (8) international generic sample number (IGSN) mapping file; and (9) a folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. This data package was originally published in October 2022. It was updated in July 2023 (v2) and again in November 2023 (v3). See the change history section in the readme for more details.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

Anions↗
DOE OSTI2026

WHONDRS River Corridor Surface Water Metabolites and Geochemistry from Global Sites

This dataset supports a broader study examining the character of organic matter that may be delivered to subsurface sediments via hydrologic exchange. To implement the global survey, free stream sampling kits were provided to interested volunteers throughout the world. Samples were collected with minimal constraints in terms of location, but following strict protocols, and shipped for metabolomic analysis via Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). In addition, basic geochemistry analyses (e.g., dissolved organic matter concentration) were conducted, standardized photos of each field system were taken, and extensive metadata were captured. Sampling began in 2018 and is ongoing as of 2025. This dataset is comprised of one folders of field photos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; and (7) a subfolder with sample data. The sample data subfolder contains (1) surface water dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) methods codes; (3) surface water FTICR methods; and (4) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains three subfolders, one containing the.xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, or .png. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.

Biogeochemistry↗
DOE OSTI2025

The Risk Assessment Information System Compendium of Ecological Screening Benchmarks for Chemicals and Radionuclides (2025) (Volume V – Chemicals for Surface Water: General)

Volume V presents the chemical benchmarks for surface water: general. The benchmarks here are applicable to both fresh water and marine or where no differentiation was made by the source. These values are not repeated in the fresh water and marine categories. Likewise, values listed in the fresh water and marine categories are not repeated in the generic categories. Consult Volume I for information on the sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Temporal Study 2022-2024: Sample-Based Surface Water Dissolved Inorganic Carbon, Dissolved Organic Carbon, Total Nitrogen, Stable Isotopes, and Total Suspended Solids from across Multiple Watersheds in the Yakima River Basin, Washington, USA

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry data generated from samples collected at bi-weekly or monthly intervals at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sensor data from 2022-2024 will be published separately. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) dissolved inorganic carbon (DIC) and averages; (6) dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC) and averages; (7) total dissolved nitrogen (TN) and averages; (8) total suspended solids (TSS); (9) stable isotopes; (10) surface water sampling protocol; (11) sensor protocol; (12) methods codes; and (13) international generic sample number (IGSN) mapping file. All files are .csv or .pdf. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. For data and scripts associated with "Shifts in rain-snow partitioning drive faster water transit times in the US Pacific Northwest" (Butler et al., 2026), go to https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3025481

18-O↗
DOE OSTI2023

Distribution of Antibiotic Resistance in a Mixed-Use Watershed and the Impact of Wastewater Treatment Plants on Antibiotic Resistance in Surface Water

The aquatic environment has been recognized as a source of antibiotic resistance (AR) that factors into the One Health approach to combat AR. To provide much needed data on AR in the environment, a comprehensive survey of antibiotic-resistant bacteria (ARB), antibiotic resistance genes (ARGs), and antibiotic residues was conducted in a mixed-use watershed and wastewater treatment plants (WWTPs) within the watershed to evaluate these contaminants in surface water. A culture-based approach was used to determine prevalence and diversity of ARB in surface water. Low levels of AR Salmonella (9.6%) and Escherichia coli (6.5%) were detected, while all Enterococcus were resistant to at least one tested antibiotic. Fewer than 20% of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae (17.3%) and carbapenem-resistant Enterobacteriaceae (CRE) (7.7%) were recovered. Six ARGs were detected using qPCR, primarily the erythromycin-resistance gene, ermB. Of the 26 antibiotics measured, almost all water samples (98.7%) had detectable levels of antibiotics. Analysis of wastewater samples from three WWTPs showed that WWTPs did not completely remove AR contaminants. ARGs and antibiotics were detected in all the WWTP effluent discharges, indicating that WWTPs are the source of AR contaminants in receiving water. However, no significant difference in ARGs and antibiotics between the upstream and downstream water suggests that there are other sources of AR contamination. The widespread occurrence and abundance of medically important antibiotics, bacteria resistant to antibiotics used for human and veterinary purposes, and the genes associated with resistance to these antibiotics, may potentially pose risks to the local populations exposed to these water sources.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Ebullition dominates methane fluxes from the water surface across different ecohydrological patches in a temperate freshwater marsh at the end of the growing season

Measurements of the spatial heterogeneity of methane fluxes in wetlands are critical to better understand and predict methane emissions at the ecosystem scale. However, the within-wetland spatial heterogeneity of fluxes is rarely assessed. Here, we use a spatially balanced rapid chamber-based survey of methane at different ecohydrological patches within a temperate freshwater marsh. We measured fluxes exclusively from the water surface without including vegetation. We further used the data from chamber measurements to partition diffusive and ebullitive fluxes. Three ecohydrological patches were distinguishable in the marsh, defined by the type and presence/absence of vegetation. Here, these patches were emergent vegetation, floating-leaved, and open water. Net methane fluxes from the water surface (diffusion plus ebullition) in emergent vegetation patches were larger than in the floating-leaved vegetation and open water patches (p < 0.05). Diffusive fluxes, representing a sizable smaller fraction of net fluxes, were larger in vegetated than in unvegetated patches (p < 0.05), while ebullitive fluxes mirrored the magnitude and differences observed in the net fluxes.Moreover, pooled net and ebullitive fluxes across patches (but not diffusive fluxes) were negatively correlated with water levels, the primary variable affecting patch distribution. Altogether, our results indicate that the differences among ecohydrological patches are driven by ebullition, ultimately highlighting challenges faced by scientists and practitioners in the field and modelers seeking to improve the predictability and resolution of wetland biogeochemical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization of Surface Water Dynamics within Fourmile Branch and its Linkages with Groundwater and I-129 Geochemistry

This research work has been supported by the DOE-FIU Science & Technology Workforce Development Initiative, an innovative program developed by the U.S. Department of Energy’s Environmental Management (DOE-EM) and Florida International University’s Applied Research Center (FIU-ARC). During the summer of 2021, DOE Fellow intern, Stevens Charles, spent 10 weeks doing a summer internship at Lawrence Berkley National Laboratory (LBNL) under the supervision and guidance of Dr. Haruko Wainwright from LBNL and Dr. Hansell GonzalezRaymat from Savannah River National Laboratory (SRNL). The intern’s project was initiated on June 1, 2020, and continued through August 6, 2020, with the objective of characterizing the surface water dynamics in the F-Area of Savannah River Site (SRS) and analyzing the surface water dynamics to find any linkages with groundwater and Iodine-129(I-129) geochemistry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”

Surface water and pore water samples were collected at five sites along a shoreline transect of the Columbia River, southeastern WA, USA in 2017. This dataset is comprised of (1) high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) and (2) a metadata csv file. The FTICR-MS files are .xml, and the data package includes instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user’s specific needs. The data are associated with the publication “Using community assembly metrics from metacommunity ecology to understand environmental metabolomes” that will be published in Nature Communications (Danczak et al.). The study aimed to investigate gaps in understanding the spatiotemporal organization of environmental metabolomes to improve the ability to predict ecosystem function. Associated sequencing data will be published via NCBI. The access information for NCBI and the publication DOI will be added to this abstract when they are available. Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Biogeochemistry of upland to wetland soils, sediments, and surface waters across Mid-Atlantic and Great Lakes coastal interfaces

Transferable and mechanistic understanding of cross-scale interactions is necessary to predict how coastal systems respond to global change. Cohesive datasets across geographically distributed sites can be used to examine how transferable a mechanistic understanding of coastal ecosystem control points is. To address the above research objectives, data were collected by the EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Consortium – a regionally distributed network of researchers that collaborated on experimental design, methodology, collection, analysis, and publication. The EXCHANGE Consortium collected samples from 52 coastal terrestrial-aquatic interfaces (TAIs) during Fall of 2021. At each TAI, samples collected include soils from across a transverse elevation gradient (i.e., coastal upland forest, transitional forest, and wetland soils), surface waters, and nearshore sediments across research sites in the Great Lakes and Mid-Atlantic regions (Chesapeake and Delaware Bays) of the continental USA. The first campaign measures surface water quality parameters, bulk geochemical parameters on water, soil, and sediment samples, and physicochemical parameters of sediment and soil.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

machine learning (ML)↗