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At least 559 records · Page 31

Coral Reef Remote Sensing using Simulated VIIRS and LDCM Imagery

The Rapid Prototyping Capability (RPC) node at NASA Stennis Space Center, MS, was used to simulate NASA next-generation sensor imagery over well-known coral reef areas: Looe Key, FL, and Kaneohe Bay, HI. The objective was to assess the degree to which next-generation sensor systems the Visible/Infrared Imager/Radiometer Suite (VIIRS) and the Landsat Data Continuity Mission (LDCM) might provide key input to the National Oceanographic and Atmospheric Administration (NOAA) Integrated Coral Observing Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST). The DST data layers produced from the simulated imagery concerned water quality and benthic classification map layers. The water optical parameters of interest were chlorophyll (Chl) and the absorption coefficient (a). The input imagery used by the RPC for simulation included spaceborne (Hyperion) and airborne (AVIRIS) hyperspectral data. Specific field data to complement and aid in validation of the overflight data was used when available. The results of the experiment show that the next-generation sensor systems are capable of providing valuable data layer resources to NOAA's ICON/CREWS DST.

Estep, Leland↗

Coral Reef Remote Sensing Using Simulated VIIRS and LDCM Imagery

The Rapid Prototyping Capability (RPC) node at NASA Stennis Space Center, MS, was used to simulate NASA next-generation sensor imagery over well-known coral reef areas: Looe Key, FL, and Kaneohe Bay, HI. The objective was to assess the degree to which next-generation sensor systems-the Visible/Infrared Imager/Radiometer Suite (VIIRS) and the Landsat Data Continuity Mission (LDCM)- might provide key input to the National Oceanographic and Atmospheric Administration (NOAA) Integrated Coral Observing Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST). The DST data layers produced from the simulated imagery concerned water quality and benthic classification map layers. The water optical parameters of interest were chlorophyll (Chl) and the absorption coefficient (a). The input imagery used by the RPC for simulation included spaceborne (Hyperion) and airborne (AVIRIS) hyperspectral data. Specific field data to complement and aid in validation of the overflight data was used when available. The results of the experiment show that the next-generation sensor systems are capable of providing valuable data layer resources to NOAA s ICON/CREWS DST.

Estep, Leland↗

2014 ISS Potable Water Characterization and Continuation of the DMSD Chronicle

During 2014 the crews from Expeditions 38-41 were resident on the International Space Station (ISS). In addition to the U.S. potable water reclaimed from humidity condensate and urine, the other water supplies available for their use were Russian potable water reclaimed from condensate and Russian ground-supplied potable water. Beginning in June of 2014, and for the fourth time since 2010, the product water from the U.S. Water Processor Assembly (WPA) experienced a rise in the total organic carbon (TOC) level due to organic contaminants breaking through the water treatment process. Results from ground analyses of ISS archival water samples returned on Soyuz 38 confirmed that dimethylsilanediol (DMSD) was once again the contaminant responsible for the rise. With this confirmation in hand and based upon the low toxicity of DMSD, a waiver was approved to allow the crew to continue to consume the water after the TOC level exceeded the U.S. Segment limit of 3 mg/L. Several weeks after the WPA multifiltration beds were replaced, as anticipated based upon experience from previous rises, the TOC levels returned to below the method detection limit of the onboard TOC analyzer (TOCA). This paper presents and discusses the chemical analysis results for the ISS archival potable water samples returned in 2014 and analyzed by the Johnson Space Center's Toxicology and Environmental Chemistry laboratory. These results showed compliance with ISS potable water quality standards and indicated that the potable water supplies were acceptable for crew consumption. Although DMSD levels were at times elevated they remained well below the 35 mg/L health limit, so continued consumption of the U.S potable water was considered a low risk to crew health and safety. Excellent agreement between inflight and archival sample TOC data confirmed that the TOCA performed optimally and it continued to serve as a vital tool for monitoring organic breakthrough and planning remediation action.

Straub, John E., II↗

Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales

Previous studies indicate that cyanobacterial harmful algal bloom (cyanoHAB) frequency, extent, and magnitude have increased globally over the past few decades. However, little quantitative capability is available to assess these metrics of cyanoHABs across broad geographic scales and at regular intervals. Here, the spatial extent was quantified from a cyanobacteria algorithm applied to two European Space Agency satellite platforms—the MEdium Resolution Imaging Spectrometer (MERIS) onboard Envisat and the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3. CyanoHAB spatial extent was defined for each geographic area as the percentage of valid satellite pixels that exhibited cyanobacteria above the detection limit of the satellite sensor. This study quantified cyanoHAB spatial extent for over 2,000 large lakes and reservoirs across the contiguous United States (CONUS) during two time periods: 2008–2011 via MERIS and 2017–2020 via OLCI when cloud-, ice-, and snowfree imagery was available. Approximately 56% of resolvable lakes were glaciated, 13% were headwater, isolated, or terminal lakes, and the rest were primarily drainage lakes. Results were summarized at national-, regional-, state-, and lake-scales, where regions were defined as nine climate regions which represent climatically consistent states. As measured by satellite, changes in national cyanoHAB extent did have a strong increase of 6.9% from 2017 to 2020 (|Kendall’s tau (τ)| = 0.56; gamma (γ) = 2.87 years), but had negligible change (|τ| = 0.03) from 2008 to 2011. Two of the nine regions had moderate (0.3 ≤ |τ| < 0.5) increases in spatial extent from 2017 to 2020, and eight of nine regions had negligible (|τ| < 0.2) change from 2008 to 2011. Twelve states had a strong or moderate increase from 2017 to 2020 (|τ| ≥ 0.3), while only one state had a moderate increase and two states had a moderate decrease from 2008 to 2011. A decrease, or no change, in cyanoHAB spatial extent did not indicate a lack of issues related to cyanoHABs. Sensitivity results of randomly omitted daily CONUS scenes confirm that even with reduced data availability during a short four-year temporal assessment, the direction and strength of the changes in spatial extent remained consistent. We present the first set of national maps of lake cyanoHAB spatial extent across CONUS and demonstrate an approach for quantifying past and future changes at multiple spatial scales. Results presented here provide water quality managers information regarding current cyanoHAB spatial extent and quantify rates of change.

Harmful algal blooms↗

Environmental and cost benefits of multi‐purpose buffers in an agricultural watershed for biomass production

Abstract The cost‐benefit of riparian buffers to landowners has not been fully understood despite its ecosystem benefits. This study investigates the environmental and economic value of multi‐purpose buffers for biomass production under alternative land‐management scenarios at the watershed scale. The work incorporates the Soil and Water Assessment Tool with a field‐scale tool, the Agriculture Conservation Practice Framework, and cost‐benefit analysis. Our work took place in the agriculturally dominant Raccoon River watershed (RRW) in Iowa. The cost analysis includes implementing and harvesting the switchgrass buffers, the value of nitrogen and phosphorus fertilizer, and the forgone income of cropland to determine the net return under 12 alternative feedstock scenarios. We estimated that 14 603 Mg of nitrogen and 2563 Mg of phosphorus runoffs can be intercepted by riparian buffers in the RRW, representing a nutrient loss reduction of 11% of nitrogen and 26% of phosphorus. These nutrients are valued at $1.31 million (M) for phosphorus and $1.24 M for nitrogen as fertilizers. The trapped nutrients account for 12% of the riparian buffers’ total cost. We found that net economic returns increase with biomass market price, increase with maintenance fertilizer application, and decrease with the cropland areas that are converted to buffers. Under current land management, a biomass market price at $60 per dry ton of biomass would be economically viable at the sub‐basin level when maintenance fertilizers are applied. At $80 per dry ton, all 108 sub‐basins in the RRW would be profitable up to $517 a year. The results highlight the trade‐offs between water quality and profitability. Published 2021. This article is a U.S. Government work and is inthe public domain in the USA. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗

NEWTS Coal Mine Drainage Dataset from Cravotta Brady (2015)

Data from Cravotta, Brady, "Priority pollutants and associated constituents in untreated and treated discharges from coal mining or processing facilities in Pennsylvania, USA". Applied Geochemistry, 2015. https://doi.org/10.1016/j.apgeochem.2015.03.001 Dataset includes information on water quality composition including inorganic compounds from untreated and treated streams of coal-mine discharge from coal mining and coal processing locations. Data is provided in the original version as well as in a summarized version for easy input into aqueous chemistry modeling software.

Aqueous Chemistry↗

Environmental outcomes of the US Renewable Fuel Standard

Biofuels are included in many proposed strategies to reduce anthropogenic greenhouse gas emissions and limit the magnitude of global warming. The US Renewable Fuel Standard is the world’s largest existing biofuel program, yet despite its prominence, there has been limited empirical assessment of the program’s environmental outcomes. Even without considering likely international land use effects, we find that the production of corn-based ethanol in the United States has failed to meet the policy’s own greenhouse gas emissions targets and negatively affected water quality, the area of land used for conservation, and other ecosystem processes. Our findings suggest that profound advances in technology and policy are still needed to achieve the intended environmental benefits of biofuel production and use.

54 ENVIRONMENTAL SCIENCES↗

Lessons Learned in the Development of Industry Guidance - 20279

The availability of industry guidance on different aspects of waste management forms a valuable reference for waste practitioners. The guidance typically details the principles, processes and practices that should be consulted during each stage of the relevant activities. It also includes relevant regulatory and international requirements, appropriate case studies and examples of best practices to illustrate technical concepts and make the information available to the reader in an accessible manner. Over recent years Wood have developed (or are developing) a number of industry guidance documents on a range of topics including Solid Waste Characterization, Routine Water Quality Monitoring on Nuclear Sites: Pipeline Characterization: Determining Background Radioactivity for Land Quality Assessment: Interim Storage and Aqueous Waste Management. This talk provides an overview of lessons learned along the way including: - the importance of stakeholder engagement through the process: - how to identify 'good practice'; - the importance of iterative development; and - the selection of illustrative and informative case studies. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Propagation of the 2014–2016 Northeast Pacific Marine Heatwave Through the Salish Sea

Effects and impacts of the Northeast Pacific marine heatwave of 2014–2016 on the inner coastal estuarine waters of the Salish Sea were examined using a combination of monitoring data and an established three-dimensional hydrodynamic and biogeochemical model of the region. The anomalous high temperatures reached the U.S. Pacific Northwest continental shelf toward the end of 2014 and primarily entered the Salish Sea waters through an existing strong estuarine exchange. Elevated temperatures up to + 2.3°C were observed at the monitoring stations throughout 2015 and 2016 relative to 2013 before dissipating in 2017. The hydrodynamic and biogeochemical responses to this circulating high-temperature event were examined using the Salish Sea Model over a 5-year window from 2013 to 2017. Responses of conventional water-quality indicator variables, such as temperature and salinity, nutrients and phytoplankton, zooplankton, dissolved oxygen, and pH, were evaluated relative to a baseline without the marine heatwave forcing. The simulation results relative to 2014 show an increase in biological activity (+14%, and 6% Δ phytoplankton biomass, respectively) during the peak heatwave year 2015 and 2016 propagating toward higher zooplankton biomass (+14%, +18% Δ mesozooplankton biomass). However, sensitivity tests show that this increase was a direct result of higher freshwater and associated nutrient loads accompanied by stronger estuarine exchange with the Pacific Ocean rather than warming due to the heatwave. Strong vertical circulation and mixing provided mitigation with only ≈+0.6°C domain-wide annual average temperature increase within Salish Sea, and served as a physical buffer to keep waters cooler relative to the continental shelf during the marine heatwave.

54 ENVIRONMENTAL SCIENCES↗

Satellite Ocean Colour: Current Status and Future Perspective

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided.

ocean colour↗

Advances in Resin Management Using 3R-Scan - 20154

The most important factor underlying optimal waste management is developing a clear picture of the radioactivity content of the waste and its impact on waste disposal cost. For over 35 years since the publishing of 10CFR61, waste characterization has relied on sampling the final waste product after formation. In the days following 10CFR61, the cost of final disposal was marginal with only a small impact on the overall costs. Constraints were added by provisions of the Low Level Waste Policy Act of 1985 leading to increasingly limited access to those disposal sites that remained available. In addition, Nuclear Regulatory Commission (NRC) pressure promoting waste volume reduction led to disposal costs inevitably rising. Despite this, characterization practices in monitoring of waste generation for activity content still center on the same dated processes. This results in a disposal classification on the basis of endpoint sampling without consideration of the homogeneity of the waste mixture. It can also disregard consideration of the representativeness of the single or small sample base. As a minimum effort, a formalized sampling program of a fixed grouping of waste streams can be implemented that could account for more than 95% of all of the activity carried in solid waste products. The sample results for each radionuclide could then be trended as time passes to develop reasonable scaling factors for difficult to measure radionuclides. This process, identified in NRC guidance, has been rigorously followed by a relatively small number of facilities. The trended scaling factors serve to improve accuracy by identifying anomalous results that could otherwise go undetected. Direct monitoring of the accumulation of activity in process streams generating solid radwaste, including demineralizers and filter streams, is a more precise approach. Nearly all of these streams are monitored by plant chemistry on a regular schedule to maintain water quality. This paper discusses viable options for developing the basis for characterization through process monitoring of the accumulation of activity at the point of generation. Special focus is on resin bed tracking and how process knowledge of these streams can be brought together to form a consistent and precise solid waste radioactivity inventory. Some of the specific points covered in this paper include the merger of the fission product release computer program, 3R-STAT, with the radwaste sample analysis computer program, SCAN4 to create 3R-SCAN, the importance of individual waste stream influences on the overall source term, and the use of historic sample data to develop scaling factors using an automated process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗

Oregon Coast Range Ecological Conservation: Mapping Recent Logging Within Drinking Watersheds of Oregon’s Coastal Range to Support Future Resource Management Policies

Logging operations are widespread across the Oregon Coast Range and conventional logging practices pose a risk of contamination to surface water quality. The NASA DEVELOP Oregon Coast Ecological Conservation team partnered with nonprofit Oregon Wild to quantify the extent of clearcutting and commercial thinning in 80 Coast Range drinking watersheds between 2000 and 2022. This project used all available Landsat data from 1997 through June 2023 in Google Earth Engine. Sensors used include Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, and Landsat 9 Operational Land Imager-2. The Continuous Change Detection and Classification (CCDC) algorithm was used with Landsat observations to identify clearcutting patches. Percent change in summer median Landsat Normalized Difference Vegetation Index (NDVI) images were used to identify areas of forest disturbance including commercial thinning. The team concluded that logging, including both clearcutting and commercial thinning, impacted 31% of forested area in drinking watersheds and the intensity of logging remained consistent from year to year. Clearcutting occurred primarily on private land while commercial thinning occurred primarily on state and federal lands. This study showed that CCDC effectively identifies clearcutting, and percent change in NDVI successfully identifies disturbances including commercial thinning. Key constraints included the lack of field validation data and the inability to attribute disturbances to logging with certainty. Ultimately, this study identified the drinking watersheds and communities most likely to be impacted by logging activity. These results can inform legislation aimed at balancing the commercial and environmental benefits of forestlands.

Logging↗

International Space Station Potable Water Characterization for 2013

In this post-construction, operational phase of International Space Station (ISS) with an ever-increasing emphasis on its use as a test-bed for future exploration missions, the ISS crews continue to rely on water reclamation systems for the majority of their water needs. The onboard water supplies include US Segment potable water from humidity condensate and urine, Russian Segment potable water from condensate, and ground-supplied potable water, as reserve. In 2013, the cargo returned on the Soyuz 32-35 flights included archival potable water samples collected from Expeditions 34-37. The Water and Food Analytical Laboratory at the NASA Johnson Space Center continued its long-standing role of performing chemical analyses on ISS return water samples to verify compliance with potable water quality specifications. This paper presents and discusses the analytical results for potable water samples returned from Expeditions 34-37, including a comparison to ISS quality standards. During the summer of 2013, the U.S. Segment potable water experienced an anticipated temporary rise and fall in total organic carbon (TOC) content, as the result of organic contamination breaking through the water system's treatment process. Analytical results for the Expedition 36 archival samples returned on Soyuz 34 confirmed that dimethylsilanediol was once again the responsible contaminant, just as it was for comparable TOC rises in 2010 and 2012. Discussion herein includes the use of the in-flight Total Organic Carbon Analyzer (TOCA) as a key monitoring tool for tracking these TOC rises and scheduling appropriate remediation action.

Straub, John E. II↗

International Space Station Potable Water Characterization for 2013

In this post-construction, operational phase of International Space Station (ISS) with an ever-increasing emphasis on its use as a test-bed for future exploration missions, the ISS crews continue to rely on water reclamation systems for the majority of their water needs. The onboard water supplies include U.S. Segment potable water from humidity condensate and urine, Russian Segment potable water from condensate, and ground-supplied potable water, as reserve. In 2013, the cargo returned on the Soyuz 32-35 flights included archival potable water samples collected from Expeditions 34-37. The former Water and Food Analytical Laboratory (now Toxicology and Evironmental Chemistry Laboratory) at the NASA Johnson Space Center continued its long-standing role of performing chemical analyses on ISS return water samples to verify compliance with potable water quality specifications. This paper presents and discusses the analytical results for potable water samples returned from Expeditions 34-37, including a comparison to ISS quality standards. During the summer of 2013, the U.S. Segment potable water experienced a third temporary rise and fall in total organic carbon (TOC) content, as the result of organic contamination breaking through the water system's treatment process. Analytical results for the Expedition 36 archival samples returned on Soyuz 34 confirmed that dimethylsilanediol was once again the responsible contaminant, just as it was for the previous comparable TOC rises in 2010 and 2012. Discussion herein includes the use of the in-flight total organic carbon analyzer (TOCA) as a key monitoring tool for tracking these TOC rises and scheduling appropriate remediation.

Straub, John E., II↗

Chlorophyll- a dynamics in the lower Amazon River: insights from in situ and hyperspectral remote sensing using OCI-PACE

Chlorophyll-a concentration (Chla) is a key indicator of phytoplankton biomass and aquatic trophic status. However, satellite-derived Chla in sediment-rich waters, such as those found in the Lower Amazon River, remains challenging. The present study characterizes in situ Chla levels and their relationships with geographic, physical, and biogeochemical parameters in the Lower Amazon. Data collected between 2014 and 2017 across four hydrological seasons included measurements of Chla, remote sensing reflectance, and water quality parameters such as total suspended sediment, conductivity, water surface temperature, dissolved oxygen, pH, dissolved organic carbon and coloured dissolved organic matter. An empirical model was developed to estimate Chla using simulated hyperspectral bands from NASA’s PACE mission, achieving high performance (R 2 = 0.76; RMSE = 0.11 μg·L −1 ). Red bands proved particularly effective for Chla retrieval, while the addition of ultraviolet bands further enhanced model accuracy. The application of the developed model to satellite imagery yielded results consistent with in situ observations for the same hydrologic season. Seasonal variation and geographic location were major factors influencing Chla dynamics. This study provides a novel contribution to Chla estimation in optically complex, highly turbid waters and highlights the potential of the PACE mission to enhance global aquatic ecosystem monitoring. In conclusion, by offering freely available hyperspectral data with high radiometric resolution, PACE represents a significant advancement in the realm of remote sensing of aquatic environments.

Amazon River↗

Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.

54 ENVIRONMENTAL SCIENCES↗

Mercury Accumulation in a Stream Ecosystem: Linking Labile Mercury in Sediment Porewaters to Bioaccumulative Mercury in Trophic Webs

Mercury (Hg) deposition and accumulation in the abiotic and biotic environments of a stream ecosystem were studied. This study aimed to link labile Hg in porewater to bioaccumulative Hg in biota. Sediment cores, porewaters, and biota were sampled from four sites along the Fourmile Branch (SC, USA) and measured for total Hg (THg) and methyl-Hg (MHg) concentrations. Water quality parameters were also measured at the sediment–water interface (SWI) to model the Hg speciation. In general, Hg concentrations in porewaters and bulk sediment were relatively high, and most of the sediment Hg was in the solid phase as non-labile species. Surface sediment presented higher Hg concentrations than the medium and bottom layers. Mercury methylation and MHg production in the sediment was primarily influenced by sulfate levels, since positive correlations were observed between sulfate and Hg in the porewaters. The majority of Hg species at the SWI were in non-labile form, and the dominant labile Hg species was complexed with dissolved organic carbon. MHg concentrations in the aquatic food web biomagnified with trophic levels (biofilm, invertebrates, and fish), increasing by 3.31 times per trophic level. Based on the derived data, a modified MHg magnification model was established to estimate the Hg bioaccumulation at any trophic level using Hg concentrations in the abiotic environment (i.e., porewater).

54 ENVIRONMENTAL SCIENCES↗