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

Trade-offs between nitrogen and phosphorus removal with floodplain remediation in agricultural streams

To improve water quality and reduce instream erosion, floodplain remediation along agricultural streams can provide multiple ecosystem services through biogeochemical and fluvial processes. During floodplain inundation, longer water residence time and periodic anoxic conditions can lead to increased nitrogen (N) removal through denitrification but also mobilization of phosphorus (P), impeding overall water quality improvements. To investigate the capacity for N and P processing in remediated streams, we measured potential denitrification and nitrous oxide production and yields together with potential P desorption and P fractions in floodplain and stream sediments in ten catchments in Sweden. Sediment P desorption was measured as equilibrium P concentration, using P isotherm incubations. Denitrification rates were measured with the acetylene inhibition method. Sediment nutrient process rates were combined with hydrochemical monitoring along remediated streams and their paired upstream control reaches of trapezoidal shape to determine the impact of floodplains on water quality. The correlation between floodplain denitrification rates and P desorption (r = 0.53, p = 0.02) revealed a trade-off between soluble reactive P (SRP) and nitrate removal, driven by stream water connectivity to floodplains. Nitrous oxide production was not affected by differences in P processing, but nitrous oxide yields decreased with higher denitrification and P desorption. The release of SRP from floodplains (0.03 ± 0.41 mg P kg-1 day-1) was significantly lower than from trapezoidal stream banks (0.38 ± 0.37 mg P kg-1 day-1), predicted by long-term SRP concentrations in stream water and floodplain inundation frequency. The overall impact of SRP release from floodplains on stream SRP concentrations in remediated reaches was limited. However, the remediated reaches showing increased stream SRP concentrations were also frequently inundated and had higher labile P content and coarse soil texture in floodplain sediments. To fully realize the potential for water quality improvements with constructed floodplains in agricultural streams, the promotion of denitrification through increased inundation should be balanced against the risk of P release from sediments, particularly in streams with high SRP inputs.

Divergent drivers of the spatial variation in greenhouse gas concentrations and fluxes along the Rhine River and the Mittelland Canal in Germany

Lotic ecosystems are sources of greenhouse gases (GHGs) to the atmosphere, but their emissions are uncertain due to longitudinal GHG heterogeneities associated with point source pollution from anthropogenic activities. In this study, we quantified summer concentrations and fluxes of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and dinitrogen (N2), as well as several water quality parameters along the Rhine River and the Mittelland Canal, two critical inland waterways in Germany. Our main objectives were to compare GHG concentrations and fluxes along the two ecosystems and to determine the main driving factors responsible for their longitudinal GHG heterogeneities. The results indicated that the two ecosystems were sources of GHG fluxes to the atmosphere, with the Mittelland Canal being a hotspot for CH4 and N2O fluxes. We also found significant longitudinal GHG flux discontinuities along the mainstems of both ecosystems, which were mainly driven by divergent drivers. Along the Mittelland Canal, peak CO2 and CH4 fluxes coincided with point pollution sources such as a joining river tributary or the presence of harbors, while harbors and in-situ biogeochemical processes such as methanogenesis and respiration mainly explained CH4 and CO2 hotspots along the Rhine River. In contrast to CO2 and CH4 fluxes, N2O longitudinal trends along the two lotic ecosystems were better predicted by in-situ parameters such as chlorophyll-a concentrations and N2 fluxes. Based on a positive relationship with N2 fluxes, we hypothesized that in-situ denitrification was driving N2O hotspots in the Canal, while a negative relationship with N2 in the Rhine River suggested that coupled biological N2 fixation and nitrification accounted for N2O hotspots. These findings stress the need to include N2 flux estimates in GHG studies, as it can potentially improve our understanding of whether nitrogen is fixed through N2 fixation or lost through denitrification.

Recognizing Agricultural Headwaters as Critical Ecosystems

Agricultural headwaters are positioned at the interface between terrestrial and aquatic ecosystems and, therefore, at the margins of scientific disciplines. They are deemed devoid of biodiversity and too polluted by ecologists, overlooked by hydrologists, and are perceived as a nuisance by landowners and water authorities. While agricultural streams are widespread and represent a major habitat in terms of stream length, they remain understudied and thereby undervalued. Agricultural headwater streams are significantly modified and polluted but at the same time are the critical linkages among land, air, and water ecosystems. They exhibit the largest variation in streamflow, water quality, and greenhouse gas emission with cascading effects on the entire stream networks, yet they are underrepresented in monitoring, remediation, and restoration. Therefore, we call for more intense efforts to characterize and understand the inherent variability and sensitivity of these ecosystems to global change drivers through scientific and regulatory monitoring and to improve their ecosystem conditions and functions through purposeful and evidence-based remediation.

Biological-based techniques for real-time water-quality studies: Assessment of non-invasive (swimming consistency and respiration) and toxicity (antioxidants) biomarkers of zebrafish

Swimming consistency and respiration of fish are recognized as the non-invasive stress biomarkers. Their alterations could directly indicate the presence of pollutants in the water ecosystem. Since these biomarkers are a routine process for fish, it is difficult to monitor their activity manually. For this reason, experts employ engineering technologies to create sensors that can monitor the regular activities of fish. Knowing the importance of these non-invasive stress biomarkers, we developed online biological behavior monitoring system-OBBMS and online biological respiratory response monitoring system-OBRRMS to monitor real-time swimming consistency and respiratory response of fish, respectively. We continuously monitored the swimming consistency and respiration (OCR, CER and RQ) of zebrafish (control and atrazine-treatments) for 7 days using our homemade real-time biological response monitoring systems. Furthermore, we analyzed oxidative stress indicators (SOD, CAT and POD) within the vital tissues (gills, brain and muscle) of zebrafish during stipulated sampling periods. The differences in the swimming consistency and respiratory rate of zebrafish between the control and atrazine treatments could be precisely differentiated on the real-time datasets of OBBMS and OBRRMS. The zebrafish exposed to atrazine toxin showed a concentration-dependent effect (hypoactivity). The OCR and CER were increased in the atrazine treated zebrafish. Both Treatment I and II received a negative response for RQ. Atrazine toxicity let to a rise in the levels of SOD, CAT and POD in the vital tissues of zebrafish. The continuous acquisition of fish signals is achieved which is one of the main merits of our OBBMS and OBRRMS. Additionally, no special data processing was done, the real-time data sets were directly used on statistical tools and the differences between the factors (groups, photoperiods, exposure periods and their interactions) were identified precisely. Hence, our OBBMS and OBRRMS could be a promising tool for biological response-based real-time water quality monitoring studies.

Routine stream monitoring data enables the unravelling of hydrological pathways and transfers of agricultural contaminants through catchments

Catchment-scale understanding of water and contaminant fluxes through all pathways is essential to address land use and climate change impacts on freshwater. However, few options exist to obtain this understanding for the many catchments worldwide for which streamflow and low-frequency water chemistry, but little other data exists. We applied the Bayesian chemistry-assisted hydrograph separation and load partitioning model (BACH) to 47 catchments with widely differing characteristics. As BACH relies on concentration differences between pathways, chemodynamic behaviour of a water constituent indicates its likely suitability as tracer. Typical tracers (e.g. silica, chloride) were unavailable, but Electrical Conductivity and a few monitored nutrients proved chemodynamic in most catchments. Using one of two tracer combinations (Total Nitrogen + Electrical Conductivity, Total Nitrogen + Total Phosphorus) allowed in 85 % of the catchments to estimate streamflow contributions by near-surface (NS), shallow groundwater (SGW), and deep groundwater (DGW) pathways and pathway-specific tracer concentrations and yields with acceptable confidence. In 46 catchments, at least two pathways contributed ≥20 % of the streamflow, and all three ≥20 % in 12 catchments, cautioning against the notion of a single 'dominant' pathway. In contrast to hydrometric hydrograph separation, BACH allows differentiation between 'young' (NS + SGW) and 'old' (DGW) water, which is crucial for the understanding of pollution in catchments with strong temporal gradients in land use intensity. Consistent with generally increasing land use intensity, and groundwater denitrification occurring in some catchments, Total Nitrogen (TN) concentrations were in most catchments higher in NS and SGW compared to DGW. In most catchments, the greatest fraction of the TN yield was conveyed by SGW (≈ 40-90 %). Exceptions were wet and hilly catchments under bush, where the NS transferred most of the very low yields, and three young volcanic catchments where the DGW transferred the majority of the yield due to particularly high DGW flow contributions.

Internet of Things and citizen science as alternative water quality monitoring approaches and the importance of effective water quality communication

The increasing demand for water and worsening climate change place significant pressure on this vital resource, making its preservation a global priority. Water quality monitoring programs are essential for effectively managing this resource. Current programs rely on traditional monitoring approaches, leading to limitations such as low spatiotemporal resolution and high operational costs. Despite the adoption of novel monitoring approaches that enable better data resolution, the public's comprehension of water quality matters remains low, primarily due to communication process deficiencies. This study explores the advantages and challenges of using Internet of Things (IoT) and citizen science as alternative monitoring approaches, emphasizing the need for enhancing public communication of water quality data. Through a systematic review of studies implemented on-field, we identify and propose strategies to address five key challenges that IoT and citizen science monitoring approaches must overcome to mature into robust sources of water quality information. Additionally, we highlight three fundamental problems affecting the water quality communication process and outline strategies to convey this topic effectively to the public.

Monitoring to detect changes in water quality to meet policy objectives

Detecting change in water quality is key to providing evidence of progress towards meeting water quality objectives. A key measure for detecting change is statistical power. Here we calculate statistical power for all regularly (monthly) monitored streams in New Zealand to test the effectiveness of monitoring for policy that aims to decrease contaminant (phosphorus and nitrogen species, E. coli and visual clarity) concentrations to threshold levels in 5 or 20 years. While > 95% of all monitored sites had sufficient power and samples to detect change in nutrients and clarity over 20 years, on average, sampling frequency would have to double to detect changes in E. coli. Furthermore, to detect changes in 5 years, sampling for clarity, dissolved reactive phosphorus and E. coli would have to increase up to fivefold. The cost of sampling was predicted to increase 5.3 and 4.1 times for 5 and 20 years, respectively. A national model of statistical power was used to demonstrate that a similar number of samples (and cost) would be required for any new monitoring sites. Our work suggests that demonstrating the outcomes of implementing policy for water quality improvement may not occur without a step change in investment into monitoring systems. Emerging sampling technologies have potential to reduce the cost, but existing monitoring networks may also have to be rationalised to provide evidence that water quality is meeting objectives. Our study has important implications for investment decisions involving balancing the need for intensively sampled sites where changes in water quality occur rapidly versus other sites which provide long-term time series.

IR-based device to acquire real-time online heart ECG signals of fish (Cyprinus carpio) to evaluate the water quality

Water quality monitoring is a challenging task due to continuous pollution. The rapid development of engineering technologies has paved the way for the development of efficient and convenient computer-based online continuous water-quality assessment techniques. Techniques based on biological-responses are gaining attention, worldwide. Different biosensors have been developed in recent years to monitor real-time biological responses to evaluate water-quality. The survival and function of various organs of the organism depends on the cardiac system. Alterations in the cardiac system could signify the occurrence/initiation of stress in the organism. We developed a real-time online cardiac function assessment system-OCFAS to acquire fish ECG-signals. We obtained P-wave, R-wave, T-wave, PR-intervals, QT-intervals and QRS-complex continuously, which did not affect the normal activities of carp. We exposed Cyprinus carpio to different concentrations (National Environmental Quality Standards) of ammonia for 48 h. Our OCFAS has precisely acquired the required ECG-signals. A real-time dataset reveals sensitivity to ammonia in carp ECG-indexes. Compared with the control group the P-wave, R-wave and T-wave were weaker in ammonia-treated groups. In contrast, the PR-intervals, QT-intervals and QRS-complex were prolonged in the ammonia-treatment groups. The self-organizing map signifies that the PR-intervals, the QRS-complex and the QT-intervals are consistent with environmental stress. Linear regression analysis also quantitatively signifies that the PR interval has the highest R2 value and the lowest SSE-value, followed by the QRS complex and the QT interval. A concentration-related effect was observed in the ammonia treated groups. The integrated biomarker response (IBRv2) index was used to determine the overall stress of ammonia on carp heart ECG-indexes. IBRv2 also supports the real-time response of carp to ammonia stress. Ammonia levels in the aquaculture and water environment require special attention to avoid its adverse effects on the health of aquatic biota. Our study emphasizes the importance of online real-time fish ECG for water-quality assessment.

Glacial Erosion Drives High Summer Mercury Exports from the Yukon River, Canada

Mercury concentrations and yields in the Yukon River are the highest of the world's six largest panarctic drainages. Permafrost thaw has been implicated as the main driver of these high values. Alternative sources include mercury released from glacial melt and erosion, atmospheric mercury pollution, or surface mining. To determine the summer source and speciation of mercury across the Yukon River basin within Canada, we sampled water from 12 tributaries and the mainstem during July 2021. The total (unfiltered) mercury concentration in the glacier-fed White River was 57 ng/L, >10 times higher than all other sampled tributaries. The White River's high total mercury concentrations were driven by suspended sediment and persisted ∼300 km downstream of glacierized headwaters. Total mercury concentrations were lowest (typically <2 ng/L) in tributaries downstream of still-water landscape features (e.g., lakes and settling ponds), suggesting these features are effective sinks for sediment-bound mercury. Low total mercury concentrations (∼2 ng/L) were also observed in five tributaries across diverse thawing permafrost landscapes. These results suggest that glacial erosion and meltwater transport, not permafrost, drive enhanced exports of mercury with suspended sediment. Mercury exports may decline as glacial watersheds pass peak water. Other factors, including mercury released from permafrost thaw, are minor components at present.

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.