Using in-situ optical sensors to study dissolved organic carbon dynamics of streams and watersheds: A review

Dissolved organic carbon estimation in lakes: Improving machine learning with data augmentation on fusion of multi-sensor remote sensing observations

This paper presents a novel approach for estimating Dissolved Organic Carbon (DOC) concentrations in lakes considering both carbon sources and sink operators. Despite the critical role of DOC, the combined application of machine learning, as a robust predictor, and remote sensing technology, which reduces costly and time-intensive in-situ sampling, has been underexplored in DOC research. Focusing on lakes over the states of New York, Vermont and Maine (United States, U.S.), this study integrates in-situ DOC measurements with surface reflectance bands obtained from Landsat satellites between 2000 and 2020. Using these bands as inputs of the Random Forest (RF) predictive model, the introduced methodology aims to explore the ability of remote sensing data for large-scale DOC simulation. Initial results indicate low accuracy metrics and significant under-estimation due to the imbalance distribution of DOC samples. Statistical analysis showed that the mean DOC concentration was 5.37±3.37 mg/L (mean±one standard deviation), with peak up to 25 mg/L. A highly skewed distribution of chemical components towards the lower ranges can lead to model misrepresentation of extreme and hazardous events, as they are clouded by unimportant events due to significantly lower occurrence rates. To address this issue, the Synthetic Minority Over-sampling Technique (SMOTE) was applied as a key innovation, generating synthetic samples that enhance RF accuracy and reduce the associated errors. Fusion of in-situ and remote sensing data, combined with machine learning and data augmentation, significantly enhances DOC estimation accuracy, especially in high concentration ranges which are critical for environmental health. With prediction metrics of RMSE = 1.75, MAE = 1.09, and R2 = 0.74, RF-SMOTE significantly improve the metrics obtained from stand-alone RF, particularly in estimating high DOC concentrations. Considering the product spatial resolution of 30 m, the model's output provides potential revenue for global application in lake monitoring, even in remote regions where direct sampling is limited. This novel fusion of remote sensing, machine learning and data augmentation offers valuable insights for water quality management and understanding carbon cycling in aquatic ecosystems.

Meta-Analysis of Optical Surrogates for the Characterization of Dissolved Organic Matter

Optical surrogates, derived from absorbance and fluorescence spectra, are widely used to infer dissolved organic matter (DOM) composition (molecular weight, aromaticity) and genesis (autochthonous vs allochthonous). Despite the broad adoption of optical surrogates, several limitations exist, such as context- and sample-specific factors. These limitations create uncertainty about how compositional interpretations based on optical surrogates are generalized across contexts, specifically if there is duplicative or contradictory information in those interpretations. To explore these limitations, we performed a meta-analysis of optical surrogates for DOM from diverse sources, both from natural systems and after water treatment processes (n = 762). Prior to analysis, data were screened using a newly developed, standardized methodology that applies systematic quality control criteria before reporting surrogates. There was substantial overlap in surrogate values from natural and treated samples, suggesting that the gradients governing the surrogate variability can be generated in both contexts. This overlap provides justification for using optical surrogates originally developed in the context of natural systems to describe DOM changes in engineered systems, although the interpretations may change. Absorbance-based surrogates that describe the amount of spectral tailing (e.g., E2:E3 and S275-295) had a high frequency of strong correlations with one another but not to specific absorbance (SUVA254) or absorbance slope ratio (SR). The fluorescence index (FI) and biological index (β/α) were strongly correlated with one another and to the peak emission wavelength but not to the humification index (HIX). Although SUVA254 and FI have both been correlated to DOM aromaticity in prior research, there was a lack of reciprocity between these optical surrogates across this data set. Additionally, there were patterns of deviations in the wastewater subset, suggesting that effluent organic matter may not follow conventional interpretations, urging caution in the use of optical surrogates to track DOM in water reuse applications. Finally, the meta-analysis highlights that three aspects should be captured when optical spectra are used for DOM interpretation: specific absorbance, absorbance tailing, and the extent of red-shifted fluorescence. We recommend that SUVA254, E2:E3, and FI or β/α be prioritized in future DOM studies to capture these aspects, respectively.

Urban stormwater quality: A review of methods for continuous field monitoring

Urban stormwater is contaminated by a wide range of substances whose concentrations vary greatly between locations, as well as between and during rain events. This literature review evaluates advantages and limitations of current methods for using continuous water quality monitoring for stormwater characterization and control. High-temporal-resolution measurements have been used to improve the understanding of stormwater quality dynamics and pollutant pathways, facilitate the performance evaluation of stormwater control measures and improve operation of the urban drainage system with real-time control. However, most sensors used to study stormwater were developed for either centralized water treatment or natural water contexts and adaptation is necessary. At present, the primary application of interest in stormwater - characterization of pollutant concentrations - can only be achieved through the use of indirect measurements with site-specific relationships of pollutants to basic physical-chemical parameters. In addition, various problems arise in the field context, associated with intermittent or variable flow rates, the accumulation of debris and sediment, adverse conditions for electrical equipment and human factors. Obtaining reliable continuous stormwater quality data requires the adoption of best practices, including the calibration and regular maintenance of sensors, verification of data and accounting for the considerable uncertainties in data; however, the literature review showed that improvement is needed among the scientific community in implementing and documenting these practices.

In Situ Water Quality Monitoring Using an Optical Multiparameter Sensor Probe

Optical methods such as ultraviolet/visible (UV/Vis) and fluorescence spectroscopy are well-established analytical techniques for in situ water quality monitoring. A broad range of bio-logical and chemical contaminants in different concentration ranges can be detected using these methods. The availability of results in real time allows a quick response to water quality changes. The measuring devices are configured as portable multi-parameter probes. However, their specification and data processing typically cannot be changed by users, or only with difficulties. Therefore, we developed a submersible sensor probe, which combines UV/Vis and fluorescence spectroscopy together with a flexible data processing platform. Due to its modular design in the hardware and software, the sensing system can be modified to the specific application. The dimension of the waterproof enclosure with a diameter of 100 mm permits also its application in groundwater monitoring wells. As a light source for fluorescence spectroscopy, we constructed an LED array that can be equipped with four different LEDs. A miniaturized deuterium-tungsten light source (200-1100 nm) was used for UV/Vis spectroscopy. A miniaturized spectrometer with a spectral range between 225 and 1000 nm permits the detection of complete spectra for both methods.

HUM: A review of hydrochemical analysis using ultraviolet-visible absorption spectroscopy and machine learning

There is a need to develop improved methods for water quality analysis. Traditionally, water quality analysis is performed in a laboratory on discrete samples or in the field with simple sensors, but these methods have inherent limitations. Ultraviolet-visible absorption spectroscopy (UVAS) is a commonly used laboratory technique for water quality analysis and is being applied more broadly in combination with machine learning (ML) to allow for the detection of multiple analytes without sample pretreatments. This methodology (referred to here as Hydrochemical analysis using Ultraviolet-visible absorption spectroscopy and Machine learning; 'HUM') can be applied in the laboratory or in situ while requiring less time, labor, and materials compared to traditional laboratory analysis. HUM has been used for the quantification of a variety of chemicals in a variety of settings, but information is lacking related to instrumental setup, sample requirements, and data analysis procedures. For instance, there is a need to investigate the influence of spectral parameters (e.g., sensitivity, signal-to-noise ratio, and spectral resolution) on measurement error. There is also a lack of research aimed at developing ML algorithms specifically for HUM. Finally, there are emerging concepts such as sensor fusion and model-sensor fusion which have been applied to similar fields but are not common in studies involving HUM. This review suggests the need for further studies to better understand the factors that influence HUM measurement accuracy along with the need for hardware and software developments so that the methodology can ultimately become more robust and standardized. This, in turn, could increase its adoption in both academic and non-academic settings. Once the HUM methodology has matured, it could help to reduce the environmental impacts of society by improving our understanding and management of environmental systems through high-frequency data collection and automated control of water quality in environmentally relevant systems.

Large-stream nitrate retention patterns shift during droughts: Seasonal to sub-daily insights from high-frequency data-model fusion

High-frequency nitrate-N (NO3--N) data are increasingly available, while accurate assessments of in-stream NO3--N retention in large streams and rivers require a better capture of complex river hydrodynamic conditions. This study demonstrates a fusion framework between high-frequency water quality data and hydrological transport models, that (1) captures river hydraulics and their impacts on solute signal propagation through river hydrodynamic modeling, and (2) infers in-stream retention as the differences between conservatively traced and reactively observed NO3--N signals. Using this framework, continuous 15-min estimates of NO3--N retention were derived in a 6th-order reach of the lower Bode River (27.4 km, central Germany), using long-term sensor monitoring data during a period of normal flow from 2015 to 2017 and a period of drought from 2018 to 2020. The unique NO3--N retention estimates, together with metabolic characteristics, revealed insightful seasonal patterns (from high net autotrophic removal in late-spring to lower rates, to net heterotrophic release during autumn) and drought-induced variations of those patterns (reduced levels of net removal and autotrophic nitrate removal largely buffered by heterotrophic release processes, including organic matter mineralization). Four clusters of diel removal patterns were identified, potentially representing changes in dominant NO3--N retention processes according to seasonal and hydrological conditions. For example, dominance of autotrophic NO3--N retention extended more widely across seasons during the drought years. Such cross-scale patterns and changes under droughts are likely co-determined by catchment and river environments (e.g., river primary production, dissolved organic carbon availability and its quality), which resulted in more complex responses to the sequential droughts. Inferences derived from this novel data-model fusion provide new insights into NO3- dynamics and ecosystem function of large streams, as well as their responses to climate variability. Moreover, this framework can be flexibly transferred across sites and scales, thereby complementing high-frequency monitoring to identify in-stream retention processes and to inform river management.

Fluorescent Dissolved Organic Matter Components as Surrogates for Disinfection Byproduct Formation in Drinking Water: A Critical Review

Disinfection byproduct (DBP) formation, prediction, and minimization are critical challenges facing the drinking water treatment industry worldwide where chemical disinfection is required to inactivate pathogenic microorganisms. Fluorescence excitation-emission matrices-parallel factor analysis (EEM-PARAFAC) is used to characterize and quantify fluorescent dissolved organic matter (FDOM) components in aquatic systems and may offer considerable promise as a low-cost optical surrogate for DBP formation in treated drinking waters. However, the global utility of this approach for quantification and prediction of specific DBP classes or species has not been widely explored to date. Hence, this critical review aims to elucidate recurring empirical relationships between common environmental fluorophores (identified by PARAFAC) and DBP concentrations produced during water disinfection. From 45 selected peer-reviewed articles, 218 statistically significant linear relationships (R2 ≥ 0.5) with one or more DBP classes or species were established. Trihalomethanes (THMs) and haloacetic acids (HAAs), as key regulated classes, were extensively investigated and exhibited strong, recurrent relationships with ubiquitous humic/fulvic-like FDOM components, highlighting their potential as surrogates for carbonaceous DBP formation. Conversely, observed relationships between nitrogenous DBP classes, such as haloacetonitriles (HANs), halonitromethanes (HNMs), and N-nitrosamines (NAs), and PARAFAC fluorophores were more ambiguous, but preferential relationships with protein-like components in the case of algal/microbial FDOM sources were noted. This review highlights the challenges of transposing site-specific or FDOM source-specific empirical relationships between PARAFAC component and DBP formation potential to a global model.

Advances in Catchment Science, Hydrochemistry, and Aquatic Ecology Enabled by High-Frequency Water Quality Measurements

High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.

High frequency UV-Vis sensors estimate error in riverine dissolved organic carbon load estimates from grab sampling

High frequency ultraviolet - visible (UV-VIS) sensors offer a way of improving dissolved organic carbon (DOC) load estimates in rivers as they can be calibrated to DOC concentration. This is an improvement on periodic grab sampling, or the use of pumped sampling systems which store samples in-field before collection. We hypothesised that the move to high frequency measurements would increase the load estimate based on grab sampling due to systemic under-sampling of high flows. To test our hypotheses, we calibrated two sensors in contrasting catchments (Exe and Bow Brook, UK) against weekly grab sampled DOC measurements and then created an hourly time series of DOC for the two sites. Taking this measurement as a 'true' value of DOC load, we simulated 1,000 grab sampling campaigns at weekly, fortnightly and monthly frequency to understand the likely distribution of load and error estimates. We also performed an analysis of daily grab samples collected using a pumped storage sampling system with weekly collection. Our results show that: a) grab sampling systemically underestimates DOC loads and gives positively skewed distributions of results, b) this under-estimation and positive skew decreases with increasing sampling frequency, c) commonly used estimates of error in the load value are also systemically lowered by the oversampling of low, stable flows due to their dependence on the variance in the flow-weighted mean concentration, and d) that pumped storage systems may lead to under-estimation of DOC and over estimation of specific ultra-violet absorbance (SUVA), a proxy for aromaticity, due to biodegradation during storage.

Refining real-time predictions of Vibrio vulnificus concentrations in a tropical urban estuary by incorporating dissolved organic matter dynamics

The south shore of O'ahu, Hawai'i is one of the most visited coastal tourism areas in the United States with some of the highest instances of recreational waterborne disease. A population of the pathogenic bacterium Vibrio vulnificus lives in the estuarine Ala Wai Canal in Honolulu which surrounds the heavily populated tourism center of Waikīkī. We developed a statistical model to predict V. vulnificus dynamics in this system using environmental measurements from moored oceanographic and atmospheric sensors in real time. During a year-long investigation, we analyzed water from 9 sampling events at 3 depths and 8 sites along the canal (n = 213) for 36 biogeochemical variables and V. vulnificus concentration using quantitative polymerase chain reaction (qPCR) of the hemolysin A gene (vvhA). The best multiple linear regression model of V. vulnificus concentration, explaining 80% of variation, included only six predictors: 5-day average rainfall preceding water sampling, daily maximum air temperature, water temperature, nitrate plus nitrite, and two metrics of humic dissolved organic matter (DOM). We show how real-time predictions of V. vulnificus concentration can be made using these models applied to the time series of water quality measurements from the Pacific Islands Ocean Observing System (PacIOOS) as well as the PacIOOS plume model based on the Waikīkī Regional Ocean Modeling System (ROMS) products. These applications highlight the importance of including DOM variables in predictive modeling of V. vulnificus and the influence of rain events in elevating nearshore concentrations of V. vulnificus. Long-term climate model projections of locally downscaled monthly rainfall and air temperature were used to predict an overall increase in V. vulnificus concentration of approximately 2- to 3-fold by 2100. Improving these predictive models of microbial populations is critical for management of waterborne pathogen risk exposure, particularly in the wake of a changing global climate.

Using CDOM spectral shape information to improve the estimation of DOC concentration in inland waters: A case study of Andean Patagonian Lakes

For the last two decades different scientific disciplines have focused on lacustrine dissolved organic matter (DOM) given its importance in the biogeochemistry of carbon and in ecosystem functioning. New satellites supply the appropriate resolutions to evaluate chromophoric dissolved organic matter (CDOM) in inland waters, opening the possibility to estimate DOM at appropriate spatiotemporal scales. This requires, however, a robust relationship between CDOM and dissolved organic carbon (DOC). In this work, we evaluated the use of CDOM as a proxy of DOC in 7 Andean Patagonian lakes. Considering the entire data set, CDOM absorption coefficients (a₃₅₅ and a₄₄₀) were linearly related with DOC. Shallow lakes, however, drove this relationship showing a moderate relationship, whereas, deep lakes with lower colour presented a weaker relationship. Therefore, we assessed the use of CDOM spectral shape information to improve DOC estimates regardless of observed DOM differences due to climatic seasonality and lakes' morphometry. The use of well-known CDOM spectral shape metrics (i.e., S_275-295 and a₂₅₀:a₃₆₅ ratio) significantly improved DOC estimation. Particularly, using a Gaussian decomposition approach we found that much of the variation in the spectral shape, associated with the variability of CDOM:DOC ratio, was explained by differences in two dynamic regions centred at 270 and 320 nm. A strong nonlinear relationship was found between the a₂₇₀:a₃₂₀ ratio and the DOC-specific absorption coefficients a*₃₅₅ and a*₄₄₀. This was translated into a further improvement in DOC estimation yielding the higher R² and lower mean absolute differences (MAPD < 16%), either considering the entire data set or shallow and deep lakes separately. Our results highlight that incorporating the CDOM spectral shape information improves the characterization of the DOC pool of inland waters, which is particularly relevant for remote and/or inaccessible sites and has significant implications for the environmental management, biogeochemical studies and future remote sensing applications.

Land Use Overrides Stream Order and Season in Driving Dissolved Organic Matter Dynamics Throughout the Year in a River Network

Anthropogenic land use has increased nutrient concentrations and altered dissolved organic matter (DOM) character and its bioavailability. Despite widespread recognition that DOM character and its reactivity can vary temporally, the relative influence of land use and stream order on DOM characteristics is poorly understood across seasons and the entire flow regime. We examined DOM character and 28-day bioavailable dissolved organic carbon (BDOC) across a river network to determine the relative roles of land use and stream order in driving variability in DOM character and bioavailability throughout the year. DOM in 1st-order streams was distinct from higher stream orders with lower DOC concentrations, less aromatic (specific ultraviolet absorbance at 254 nm (SUVA₂₅₄)), more autochthonous (fluorescence index), and more recently produced (β/α) DOM. Across all months, variability in DOM character was primarily explained by land use, rather than stream order or season. Land use and stream order explained the most DOM variation in transitional and winter months and the least during dry months. BDOC was greater in watersheds with less aromatic (SUVA₂₅₄) and more recent allochthonous DOM (β/α) and more development and impervious surface. With continued development, the bioavailability of DOM in the smallest and most impacted watersheds is expected to increase.

Clair SI, Bratsman S, Merritt M, Norris AJ, Carling GT, Hansen N, St. Clair SB, Abbott BW. Megafire affects stream sediment flux and dissolved organic matter reactivity, but land use dominates nutrient dynamics in semiarid watersheds

Climate change is causing larger wildfires and more extreme precipitation events in many regions. As these ecological disturbances increasingly coincide, they alter lateral fluxes of sediment, organic matter, and nutrients. Here, we report the stream chemistry response of watersheds in a semiarid region of Utah (USA) that were affected by a megafire followed by an extreme precipitation event in October 2018. We analyzed daily to hourly water samples at 10 stream locations from before the storm event until three weeks after its conclusion for suspended sediment, solute and nutrient concentrations, water isotopes, and dissolved organic matter concentration, optical properties, and reactivity. The megafire caused a ~2,000-fold increase in sediment flux and a ~6,000-fold increase in particulate carbon and nitrogen flux over the course of the storm. Unexpectedly, dissolved organic carbon (DOC) concentration was 2.1-fold higher in burned watersheds, despite the decreased organic matter from the fire. DOC from burned watersheds was 1.3-fold more biodegradable and 2.0-fold more photodegradable than in unburned watersheds based on 28-day dark and light incubations. Regardless of burn status, nutrient concentrations were higher in watersheds with greater urban and agricultural land use. Likewise, human land use had a greater effect than megafire on apparent hydrological residence time, with rapid stormwater signals in urban and agricultural areas but a gradual stormwater pulse in areas without direct human influence. These findings highlight how megafires and intense rainfall increase short-term particulate flux and alter organic matter concentration and characteristics. However, in contrast with previous research, which has largely focused on burned-unburned comparisons in pristine watersheds, we found that direct human influence exerted a primary control on nutrient status. Reducing anthropogenic nutrient sources could therefore increase socioecological resilience of surface water networks to changing wildfire regimes.

Adaptive monitoring approach to assess dissolved organic matter dynamics during rainfall events

Rainfall events induce water quality transformation in river systems influenced by the watershed land use and hydrology dynamics. In this context, an adaptive monitoring approach (AMA) is used to assess non-point sources (NPS) of pollution events, through dissolved organic matter (DOM) contribution. The case study is a monitoring site in a semi-urban watershed characterized by NPS contribution. An integrated quali-quantitative method for DOM based on dissolved organic carbon (DOC) content, spectroscopic techniques of excitation-emission fluorescence (EEF), and UV-visible absorbance is proposed. The results indicate a mix of allochthonous and autochthonous DOM characteristics from NPS sources associated to vegetation area influence (A₂₈₅/DOC of 15.43 L (g cm)^-1 and SUVA₂₅₄ of 2.11 L (mg m)^-1). The EEF signals showed more humic-like than protein-like characteristics with peaks A and C (approximately 5.72 r.u.) more intense than peaks B, T₁, and T₂ (approximately 4.33 r.u.), indicating NPS from the soil leachate. The absorbance ratio values indicate a mix of organic compounds with greater proportion of refractory characteristics with high aromaticity and molecular weight (approximately A₃₀₀/A₄₀₀ of 4.15 and A₂₅₀/A₃₆₅ of 4.48), associated with the surface wash-off of accumulated residual and subsurface soil erosion, which contribute to complex organic matter structures. The fluorescence indexes, overall, indicated allochthonous sources with intermediate humic characteristics (FI ≈ 1.43, BIX ≈ 0.65, and HIX ≈ 7.98). The proposed integrated optical property strategy represents an opportunity for better understanding of DOM dynamic assessment for identifying potential mitigation techniques for organic pollution control and improving water quality conditions.

Chromophoric dissolved organic matter in inland waters: Present knowledge and future challenges

Chromophoric dissolved organic matter (CDOM) plays an important role in the biogeochemical cycle and energy flow of aquatic ecosystems. Thus, systematic and comprehensive understanding of CDOM dynamics is critically important for aquatic ecosystem management. CDOM spans multiple study fields, including analytical chemistry, biogeochemistry, water color remote sensing, and global environmental change. Here, we thoroughly summarize the progresses of recent studies focusing on the characterization, distribution, sources, composition, and fate of CDOM in inland waters. Characterization methods, remote sensing estimation, and biogeochemistry cycle processes were the hotspots of CDOM studies. Specifically, optical, isotope, and mass spectrometric techniques have been widely used to characterize CDOM abundance, composition, and sources. Remote sensing is an effective tool to map CDOM distribution with high temporal and spatial resolutions. CDOM dynamics are mainly determined by watershed-related processes, including rainfall discharge, groundwater, wastewater discharges/effluents, and biogeochemical cycling occurring in soil and water bodies. We highlight the underlying mechanisms of the photochemical degradation and microbial decomposition of CDOM, and emphasize that photochemical and microbial processes of CDOM in inland waters accelerate nutrient cycling and regeneration in the water column and also exacerbate global warming by releasing greenhouse gases. Future study directions to improve the understanding of CDOM dynamics in inland waters are proposed. This review provides an interdisciplinary view and new insights on CDOM dynamics in inland waters.

Stream Dissolved Organic Matter in Permafrost Regions Shows Surprising Compositional Similarities but Negative Priming and Nutrient Effects

Permafrost degradation is delivering bioavailable dissolved organic matter (DOM) and inorganic nutrients to surface water networks. While these permafrost subsidies represent a small portion of total fluvial DOM and nutrient fluxes, they could influence food webs and net ecosystem carbon balance via priming or nutrient effects that destabilize background DOM. We investigated how addition of biolabile carbon (acetate) and inorganic nutrients (nitrogen and phosphorus) affected DOM decomposition with 28-day incubations. We incubated late-summer stream water from 23 locations nested in seven northern or high-altitude regions in Asia, Europe, and North America. DOM loss ranged from 3% to 52%, showing a variety of longitudinal patterns within stream networks. DOM optical properties varied widely, but DOM showed compositional similarity based on Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) analysis. Addition of acetate and nutrients decreased bulk DOM mineralization (i.e., negative priming), with more negative effects on biodegradable DOM but neutral or positive effects on stable DOM. Unexpectedly, acetate and nutrients triggered breakdown of colored DOM (CDOM), with median decreases of 1.6% in the control and 22% in the amended treatment. Additionally, the uptake of added acetate was strongly limited by nutrient availability across sites. These findings suggest that biolabile DOM and nutrients released from degrading permafrost may decrease background DOM mineralization but alter stoichiometry and light conditions in receiving waterbodies. We conclude that priming and nutrient effects are coupled in northern aquatic ecosystems and that quantifying two-way interactions between DOM properties and environmental conditions could resolve conflicting observations about the drivers of DOM in permafrost zone waterways.

A Semi-Analytical Optical Remote Sensing Model to Estimate Suspended Sediment and Dissolved Organic Carbon in Tropical Coastal Waters Influenced by Peatland-Draining River Discharges off Sarawak, Borneo

Coastal water quality degradation is a global challenge. Marine pollution due to suspended sediments and dissolved matter impacts water colour, biogeochemistry, benthic habitats and eventually human populations that depend on marine resources. In Sarawak (Malaysian Borneo), peatland-draining river discharges containing suspended sediments and dissolved organic carbon influence coastal water quality at multiple locations along the coast. Optical remote sensing is an effective tool to monitor coastal waters over large areas and across remote geographic locations. However, the lack of regional optical measurements and inversion models limits the use of remote sensing observations for water quality monitoring in Sarawak. To overcome this limitation, we have (1) compiled a regional spectral optical library for Sarawak coastal waters, (2) developed a new semi-analytical remote sensing model to estimate suspended sediment and dissolved organic carbon in coastal waters, and (3) demonstrated the application of our remote sensing inversion model on satellite data over Sarawak. Bio-optical data analysis revealed that there is a clear spatial variability in the inherent optical properties of particulate and dissolved matter in Sarawak. Our optical inversion model coupled with the Sarawak spectral optical library performed well in retrieving suspended sediment (bias = 3% and MAE = 5%) and dissolved organic carbon (bias = 3% and MAE = 8%) concentrations. Demonstration products using MODIS Aqua data clearly showed the influence of large rivers such as the Rajang and Lupar in discharging suspended sediments and dissolved organic carbon into coastal waters. The bio-optical parameterisation, optical model, and remote sensing inversion approach detailed here can now help improve monitoring and management of coastal water quality in Sarawak.

Estimation of Water Quality Parameters with High-Frequency Sensors Data in a Large and Deep Reservoir

High-frequency sensors can monitor water quality with high temporal resolution and without environmental influence. However, sensors for detecting key water quality parameters, such as total nitrogen(TN), total phosphorus(TP), and other water environmental parameters, are either not yet available or have attracted limited usage. By using a large number of high-frequency sensor and manual monitoring data, this study establishes regression equations that measure high-frequency sensor and key water quality parameters through multiple regression analysis. Results show that a high-frequency sensor can quickly and accurately estimate dynamic key water quality parameters by evaluating seven water quality parameters. An evaluation of the flux of four chemical parameters further proves that the multi-parameter sensor can efficiently estimate the key water quality parameters. However, due to the different optical properties and ecological bases of these parameters, the high-frequency sensor shows a better prediction performance for chemical parameters than for physical and biological parameters. Nevertheless, these results indicate that combining high-frequency sensor monitoring with regression equations can provide real-time and accurate water quality information that can meet the needs in water environment management and realize early warning functions.

High Anthropogenic Organic Matter Inputs during a Festival Increase River Heterotrophy and Refractory Carbon Load

Streams and rivers metabolize dissolved organic matter (DOM). Although most DOM compounds originate from natural sources, recreational use of rivers increasingly introduces chemically distinct anthropogenic DOM. So far, the ecological impact of this DOM source is not well understood. Here, we show that a large music festival held adjacent to the Traisen River in Austria increased the river's dissolved organic carbon (DOC) concentration from 1.6 to 2.1 mg L^-1 and stream ecosystem respiration from -3.2 to -4.5 mg L^-1. The DOC increase was not detected by sensors continuously logging absorbance spectra, thereby challenging their applicability for monitoring. However, the fluorescence intensity doubled during the festival. Using parallel factor analysis, we were able to assign the increase in fluorescence intensity to the chemically stable UV-B filter phenylbenzimidazole sulfonic acid, indicating organic compounds in sunscreen and other personal care products as sources of elevated DOC. This observation was confirmed by liquid chromatography coupled with mass spectrometry. The elevated respiration is probably fueled by anthropogenic DOM contained in beer and/or urine. We conclude that intense recreational use of running waters transiently increases the anthropogenic DOM load into stream ecosystems and alters the fluvial metabolism. We further propose that chemically distinct, manmade DOM extends the natural range of DOM decomposition rates in fluvial ecosystems.

High frequency fluorescence monitoring reveals new insights into organic matter dynamics of an urban river, Birmingham, UK

Natural organic matter (NOM) is fundamental to many biogeochemical processes in river ecosystems. Currently, however, we have limited knowledge of NOM dynamics across the spectrum of flow conditions as previous studies have focused largely on storm events. Field deployable fluorescence technology offers new opportunities to explore both stochastic and predictable diel NOM dynamics at finer time-steps and for longer periods than was hitherto possible, thus yielding new insight into NOM sources, processing, and pathways. Hourly fluorescence data (humic-like fluorescence [Peak C] and tryptophan-like fluorescence [Peak T]) and a suite of hydro-climatological variables were collected from an urban river (Birmingham, UK). We explored monthly concentration-discharge (C-Q) patterns using segmented regression and assessed hysteretic and flushing behaviour for Peak C, T and turbidity to infer source zone activation. Diel patterns were assessed during low flow periods. Wavelet analysis identified strong diurnal variations in Peak C with early morning peaks while no diel dynamics were apparent for Peak T. Using generalised linear modelling relationships between Peak C periodicity and both solar radiation and time since previous storm/scouring event were identified. Breakpoints and positive slopes for C-Q relationship highlighted chemodynamic behaviour for NOM over most of the monitoring period, with Peak T mobilised more relative to Peak C during high Q. Hysteresis patterns were highly variable but flushing behaviour of Peak T and C suggested exhaustion of humic compounds during long duration events and following successive rainfall events. Peak T flushing was correlated with Q magnitude highlighting the potential for combined sewer overflows to act as important NOM sources despite significant dilution potential. This research highlights the potential of real-time, field deployable fluorescence spectroscopy as a viable method for providing insight into diel and transport driven NOM dynamics.

Methodology for selection of optical parameters as wastewater effluent organic matter surrogates

Absorbance- and fluorescence-based optical parameters are commonly used as surrogates in engineered systems, but there is no systematic approach for selecting robust parameters. This study develops a methodology that is applied to a case study of differentiating wastewater effluent organic matter from naturally-derived organic matter. The methodology defines criteria to identify optical parameters that could detect statistically significant compositional differences in organic matter, independent of organic matter concentration, and measure fluorescence-based parameters with low susceptibility to inner filter effects. The criteria were applied to 26 parameters that were measured for 11 pairs of source water and conventionally-treated wastewater samples collected from sites with varied spatial and temporal conditions. Only two parameters, apparent fluorescence quantum yield measured at excitation 370 nm and fluorescence peak ratio A:T, met the criteria across all sites. These results demonstrate and encourage an objective and robust process for selecting optical surrogates for organic matter characterization.

Diurnal Patterns in Solute Concentrations Measured with In Situ UV-Vis Sensors: Natural Fluctuations or Artefacts?

In situ spectrophotometers measuring in the UV-visible spectrum are increasingly used to collect high-resolution data on stream water quality. This provides the opportunity to investigate short-term solute dynamics, including diurnal cycling. This study reports unusual changes in diurnal patterns observed when such sensors were deployed in four tropical headwater streams in Kenya. The analysis of a 5-year dataset revealed sensor-specific diurnal patterns in nitrate and dissolved organic carbon concentrations and different patterns measured by different sensors when installed at the same site. To verify these patterns, a second mobile sensor was installed at three sites for more than 3 weeks. Agreement between the measurements performed by these sensors was higher for dissolved organic carbon (r > 0.98) than for nitrate (r = 0.43–0.81) at all sites. Higher concentrations and larger amplitudes generally led to higher agreement between patterns measured by the two sensors. However, changing the position or level of shading of the mobile sensor resulted in inconsistent changes in the patterns. The results of this study show that diurnal patterns measured with UV-Vis spectrophotometers should be interpreted with caution. Further work is required to understand how these measurements are influenced by environmental conditions and sensor-specific properties.

Strengths of correlations with formation of chlorination disinfection byproducts: effects of predictor type and other factors

Measurements of the UV-Vis absorbance (Abs) and intensity of fluorescence emission (Fluor), as well as of concentrations of total or dissolved organic carbon (OC) in aqueous samples are commonly used to estimate the potential for disinfection byproducts (DBPs) formation during water chlorination. In this work, based on 574 linear associations collected from 70 experimental research papers published over the period of 1997-2019, the strengths of the correlations of Abs, Fluor, and OC with DBPs concentrations are compared. The correlations were expressed as approximately normally distributed Z-scores using Fisher variance-stabilizing transformation. The effects of specific prediction method, chlorination agent, water source, and DBPs type, with consideration of possible effects due to the presence of bromide, are examined against Z-scores by ANOVA, testing main effects and some variables interactions. The performed analysis is a first attempt to expose differences and patterns in correlation strengths associated with DBPs formation, based on systematically covered broad existing literature. Abs and OC concentration of water samples tend to demonstrate the strongest correlations with DBPs formation as compared with specific UV absorbance (SUVA) or intensity of fluorescence emission. Correlations of DBPs formation during chloramination demonstrated weaker strengths as compared with other chlorination agents, suggesting more caution in predicting DBPs concentrations, based on simple descriptors such as Abs, OC, and Fluor. In a series of different water types, the correlations with DBPs formation are expected to be enhanced, when wastewater is chlorinated. Non-fluorescent matter may be an important contributor to DBPs formation during water chlorination. When fluorescence intensity is considered as a predicting tool, choosing humic-like rather than proteinaceous fluorescence may enhance the strengths of the correlations with DBPs formation. Different performances of Abs, OC, and Fluor in correlating with DBPs formation may be beneficial for their concurrent use helping to optimize removal of different DBPs precursors.

In situ fluorescence measurements of dissolved organic matter: A review

There is a need for an inexpensive, reliable and fast monitoring tool to detect contaminants in a short time, for quick mitigation of pollution sources and site remediation, and for characterization of natural dissolved organic matter (DOM). Fluorescence spectroscopy has proven to be an excellent technique in quantifying aquatic DOM, from autochthonous, allochthonous or anthropogenic sources. This paper reviews the advances in in situ fluorescence measurements of DOM and pollutants in various water environments. Studies have demonstrated, using high temporal-frequency DOM fluorescence data, that marine autochthonous production of DOM is highly complex and that the allochthonous input of DOM from freshwater to marine water can be predicted. Furthermore, river measurement studies found a delayed fluorescence response of DOM following precipitation compared to turbidity and discharge, with various lags, depending on season, site and input of dissolved organic carbon (DOC) concentration. In addition, research has shown that blue light fluorescence (λ_emission = 430-500 nm) can be a good proxy for DOC, in environments with terrestrial inputs, and ultraviolet fluorescence (λ_emission = UVA-320-400 nm) for biochemical oxygen demand, and also E. coli in environments with sanitation issues. The correction of raw fluorescence data improves the relationship between fluorescence intensity and these parameters. This review also presents the specific steps and parameters that must be considered before and during in situ fluorescence measurement session for a harmonized qualitative and quantitative protocol. Finally, the strengths and weaknesses of the research on in situ fluorescence are identified.

Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes

PURPOSE

This review of sediment source fingerprinting assesses the current state-of-the-art, remaining challenges and emerging themes. It combines inputs from international scientists either with track records in the approach or with expertise relevant to progressing the science.

METHODS

Web of Science and Google Scholar were used to review published papers spanning the period 2013-2019, inclusive, to confirm publication trends in quantities of papers by study area country and the types of tracers used. The most recent (2018-2019, inclusive) papers were also benchmarked using a methodological decision-tree published in 2017.

SCOPE

Areas requiring further research and international consensus on methodological detail are reviewed, and these comprise spatial variability in tracers and corresponding sampling implications for end-members, temporal variability in tracers and sampling implications for end-members and target sediment, tracer conservation and knowledge-based pre-selection, the physico-chemical basis for source discrimination and dissemination of fingerprinting results to stakeholders. Emerging themes are also discussed: novel tracers, concentration-dependence for biomarkers, combining sediment fingerprinting and age-dating, applications to sediment-bound pollutants, incorporation of supportive spatial information to augment discrimination and modelling, aeolian sediment source fingerprinting, integration with process-based models and development of open-access software tools for data processing.

CONCLUSIONS

The popularity of sediment source fingerprinting continues on an upward trend globally, but with this growth comes issues surrounding lack of standardisation and procedural diversity. Nonetheless, the last 2 years have also evidenced growing uptake of critical requirements for robust applications and this review is intended to signpost investigators, both old and new, towards these benchmarks and remaining research challenges for, and emerging options for different applications of, the fingerprinting approach.

Chlorophyll-a, dissolved organic carbon, turbidity and other variables of ecological importance in river basins in southern Ontario and British Columbia, Canada

Optical sensing of chlorophyll-a (chl-a), turbidity, and fluorescent dissolved organic matter (fDOM) is often used to characterize the quality of water. There are many site-specific factors and environmental conditions that can affect optically sensed readings; notwithstanding the comparative implication of different procedures used to measure these properties in the laboratory. In this study, we measured these water quality properties using standard laboratory methods, and in the field using optical sensors (sonde-based) at water quality monitoring sites located in four watersheds in Canada. The overall objective of this work was to explore the relationships among sonde-based and standard laboratory measurements of the aforementioned water properties, and evaluate associations among these eco-hydrological properties and land use, environmental, and ancillary water quality variables such as dissolved organic carbon (DOC) and total suspended solids (TSS). Differences among sonde versus laboratory relationships for chl-a suggest such relationships are impacted by laboratory methods and/or site specific conditions. Data mining analysis indicated that interactive site-specific factors predominately impacting chl-a values across sites were specific conductivity and turbidity (variables with positive global associations with chl-a). The overall linear regression predicting DOC from fDOM was relatively strong (R² = 0.77). However, slope differences in the watershed-specific models suggest laboratory DOC versus fDOM relationships could be impacted by unknown localized water quality properties affecting fDOM readings, and/or the different standard laboratory methods used to estimate DOC. Artificial neural network analyses (ANN) indicated that higher relative chl-a concentrations were associated with low to no tree cover around sample sites and higher daily rainfall in the watersheds examined. Response surfaces derived from ANN indicated that chl-a concentrations were higher where combined agricultural and urban land uses were relatively higher.

Analysis of the Mixing Processes in a Shallow Subtropical Reservoir and Their Effects on Dissolved Organic Matter

A good understanding of the physical processes of lakes or reservoirs, especially of those providing drinking water to residents, plays a vital role in water management. In this study, the water circulation and mixing processes occurring in the shallow, subtropical Tingalpa Reservoir in Australia have been investigated. Bathymetrical, meteorological, chemical and physical data collected from field measurements, laboratory analysis of water sampling and an in-situ Vertical Profile System (VPS) were analysed. Based on the high-frequency VPS dataset, a 1D model was developed to provide information for vertical transport and mixing processes. The results show that persistent high air temperature and stable reservoir water depth lead to a prolonged thermal stratification. Analysis indicates that heavy rainfalls have a significant impact on water quality when the dam level is low. The peak value of Dissolved Organic Carbon (DOC) concentration occurred in the wet season, while the specific UV absorbance (SUVA) value decreased when solar radiation increased from spring to summer. The study aims to provide a comprehensive approach for understanding and modelling the water mixing processes in similar lakes with high-frequency data from VPS’s or other monitoring systems.

Using dissolved organic matter fluorescence to identify the provenance of nutrients in a lowland catchment; the River Thames, England

Catchment based solutions are being sought to mitigate water quality pressures and achieve multiple benefits but their success depends on a sound understanding of catchment functioning. Novel approaches to monitoring and data analysis are urgently needed. In this paper we explore the potential of river water fluorescence at the catchment scale in understanding nutrient concentrations, sources and pathways. Data were collected from across the River Thames basin from January 2012 to March 2015. Analysing emission excitation matrices (EEMs) using both PARAFAC and optimal area averaging produced consistent results for humic-like component 1 and tryptophan-like component 4 in the absence of a subset of samples that exhibited an unusual peak; illustrating the importance of inspecting the entire EEM before using peak averaging methods. Strong relationships between fluorescence components and dissolved organic carbon (DOC), soluble reactive phosphorus (SRP), and ammonium clearly demonstrated its potential, in this study basin, as a field based surrogate for nutrients. Analysing relationships between fluorescence, catchment characteristics and boron from across the basin enabled new insights into the provenance of nutrients. These include evidence for diffuse sources of DOC from near surface hydrological pathways (i.e. soil horizons); point source inputs of nutrients from sewage effluent discharges; and diffuse contributions of nutrients from agriculture and/or sewage (e.g. septic tanks). The information gained by broad scale catchment wide monitoring of fluorescence could support catchment managers in (a) prioritising subcatchments for nutrient mitigation; (b) providing information on relative nutrient source contributions; and (c) providing evidence of the effectiveness of investment in pollution mitigation measures. The collection of high resolution fluorescence data at the catchment scale and, in particular, over shorter event timescales would complement broad scale assessments by enhancing our hydro-biogeochemical process understanding.

Online fluorescence spectroscopy for the real-time evaluation of the microbial quality of drinking water

We assessed the utility of online fluorescence spectroscopy for the real-time evaluation of the microbial quality of untreated drinking water. Online fluorimeters were installed on the raw water intake at four groundwater-derived UK public water supplies alongside existing turbidity sensors that are used to forewarn of the presence of microbial contamination in the water industry. The fluorimeters targeted fluorescent dissolved organic matter (DOM) peaks at excitation/emission wavelengths of 280/365 nm (tryptophan-like fluorescence, TLF) and 280/450 nm (humic-like fluorescence, HLF). Discrete samples were collected for Escherichia coli, total bacterial cell counts by flow cytometry, and laboratory-based fluorescence and absorbance. Both TLF and HLF were strongly correlated with E. coli (ρ = 0.71-0.77) and total bacterial cell concentrations (ρ = 0.73-0.76), whereas the correlations between turbidity and E. coli (ρ = 0.48) and total bacterial cell counts (ρ = 0.40) were much weaker. No clear TLF peak was observed at the sites and all apparent TLF was considered to be optical bleed-through from the neighbouring HLF peak. Therefore, a HLF fluorimeter alone would be sufficient to evaluate the microbial water quality at these sources. Fluorescent DOM was also influenced by site operations such as pump start-up and the precipitation of cations on the sensor windows. Online fluorescent DOM sensors are a better indicator of the microbial quality of untreated drinking water than turbidity and they have wide-ranging potential applications within the water industry.

Examining Natural Attenuation and Acute Toxicity of Petroleum-Derived Dissolved Organic Matter with Optical Spectroscopy

Groundwater samples containing petroleum-derived dissolved organic matter (DOM_HC) originating from the north oil body within the National Crude Oil Spill Fate and Natural Attenuation Research Site near Bemidji, MN, USA were analyzed by optical spectroscopic techniques (i.e., absorbance and fluorescence) to assess relationships that can be used to examine natural attenuation and toxicity of DOM_HC in contaminated groundwater. A strong correlation between the concentration of dissolved organic carbon (DOC) and absorbance at 254 nm ( a₂₅₄) along a transect of the DOM_HC plume indicates that a₂₅₄ can be used to quantitatively assess natural attenuation of DOM_HC. Fluorescence components, identified by parallel factor (PARAFAC) analysis, show that the composition of the DOM_HC beneath and adjacent to the oil body is dominated by aliphatic, low O/C compounds ("protein-like" fluorescence) and that the composition gradually evolves to aromatic, high O/C compounds ("humic-/fulvic-like" fluorescence) as a function of distance downgradient from the oil body. Finally, a direct, positive correlation between optical properties and Microtox acute toxicity assays demonstrates the utility of these combined techniques in assessing the spatial and temporal natural attenuation and toxicity of the DOM_HC in petroleum-impacted groundwater systems.

Trends and seasonality of river nutrients in agricultural catchments: 18years of weekly citizen science in France

Agriculture and urbanization have disturbed three-quarters of global ice-free land surface, delivering huge amounts of nitrogen and phosphorus to freshwater ecosystems. These excess nutrients degrade habitat and threaten human food and water security at a global scale. Because most catchments are either currently subjected to, or recovering from anthropogenic nutrient loading, understanding the short- and long-term responses of river nutrients to changes in land use is essential for effective management. We analyzed a never-published, 18-year time series of anthropogenic (NO₃^- and PO₄^3-) and naturally derived (dissolved silica) riverine nutrients in 13 catchments recovering from agricultural pollution in western France. In a citizen science initiative, high-school students sampled catchments weekly, which ranged from 26 to 1489km². Nutrient concentrations decreased substantially over the period of record (19 to 50% for NO₃^- and 14 to 80% for PO₄^3-), attributable to regional, national, and international investment and regulation, which started immediately prior to monitoring. For the majority of catchments, water quality during the summer low-flow period improved faster than during winter high-flow conditions, and annual minimum concentrations improved relatively faster than annual maximum concentrations. These patterns suggest that water-quality improvements were primarily due to elimination of discrete nutrient sources with seasonally-constant discharge (e.g. human and livestock wastewater), agreeing with available land-use and municipal records. Surprisingly, long-term nutrient decreases were not accompanied by changes in nutrient seasonality in most catchments, attributable to persistent, diffuse nutrient stocks. Despite decreases, nutrient concentrations in almost all catchments remained well above eutrophication thresholds, and because additional improvements will depend on decreasing diffuse nutrient sources, future gains may be much slower than initial rate of recovery. These findings demonstrate the value of citizen science initiatives in quantifying long-term and seasonal consequences of changes in land management, which are necessary to identify sustainable limits and predict recovery timeframes.