Sampling frequency, load estimation and the disproportionate effect of storms on solute mass flux in rivers

Riverine discharge (Q) and dissolved concentrations (C) dictate solute mass export from watersheds. Commonly Q is tracked at a much higher frequency than C for most major solutes, leading to the necessity of load estimation algorithms which are often based on sparse data. The result is that the disproportionate effects of short-duration events (e.g., storms) on solute mass fluxes are poorly known. Here we use novel lab-in-the-field instrumentation to compare high temporal-resolution (∼30 min to 7 h) datasets of major ion chemistry collected over a year of continuous monitoring in three watersheds ranging over four orders of magnitude in drainage area. In these diverse settings, we quantify the errors associated with common load estimation algorithms and reduced sampling frequencies. When sample frequencies are coarsened, the mass flux of solutes which are diluted by storm events (i.e., Ca2+, Mg2+, Na+, Cl- and SO42-) are systematically overestimated, while nutrients which become mobilized by these events (K+ and NO3-) are underestimated. This is most pronounced in the largest river, and strongly tied to the increasing likelihood that storm events are missed as sampling frequencies decrease. Coarsening our high-resolution data to monthly sampling frequency yields an average overestimate of 8 % for Na+ and an average underestimate of 32.5 % for K+ across the three watersheds, illustrating clear implications for estuary and coastal water eutrophication, chemical weathering budgets, and agricultural land management practices. SYNOPSIS: A new 'lab-in-the-field' technology produces continuous high-frequency records of the full suite of major ions in rivers. These data highlight the disproportionate effect of large storms on catchment solute exports and the error associated with temporally coarse monitoring.

Bloom-induced internal release controlling phosphorus dynamics in large shallow eutrophic Lake Taihu, China

High phosphorus (P) concentrations are commonly observed in lakes during algal blooms despite massive efforts on external nutrient reduction. However, the knowledge about the relative contribution of internal P loading linked with algal blooms on lake phosphorus (P) dynamics remains limited. To quantify the effect of internal loading on P dynamics, we conducted extensive spatial and multi-frequency nutrient monitoring from 2016 to 2021 in Lake Taihu, a large shallow eutrophic lake in China, and its tributaries (2017-2021). The in-lake P stores (ILSP) and external loading were estimated and then internal P loading was quantified from the mass balance equation. The results showed that the in-lake total P stores (ILSTP) ranged from 398.5 to 1530.2 tons (t), and exhibited a dramatic intra- and inter-annual variability. The annual internal TP loading released from sediment ranged from 1054.3 to 1508.4 t, which was equivalent to 115.6% (TP loading) of the external inputs on average, and responsible for the fluctuations of ILSTP on a weekly scale. High-frequency observations exemplified that ILSTP increased by 136.4% during algal blooms in 2017, while by only 47.2% as a result of external loading after heavy precipitation in 2020. Our study demonstrated that both bloom-induced internal loading and storm-induced external loading are likely to run counter significantly to watershed nutrient reduction efforts in large shallow lakes. More importantly, bloom-induced internal loading is higher than storm-induced external loading over the short term. Given the positive feedback loop between internal P loadings and algal bloom in eutrophic lakes, which explains the significant fluctuation of P concentration while nitrogen concentration decreased. It is emphasized that internal loading and ecosystem restoration are unignorable in shallow lakes, particularly in the algal-dominated region.

Improving accuracy of quantifying nitrate removal performance and enhancing understanding of processes in woodchip bioreactors using high-frequency data

Woodchip bioreactors have gained popularity in many countries as a conservation practice for reducing nitrate load to freshwater. However, current methods for assessing their performance may be inadequate when nitrate removal rates (RR) are determined from low-frequency (e.g., weekly) concurrent sampling at the inlet and outlet. We hypothesised that high-frequency monitoring data at multiple locations can help improve the accuracy of quantifying nitrate removal performance, enhance the understanding of processes occurring within a bioreactor, and therefore improve the design practice for bioreactors. Accordingly, the objectives of this study were to compare RRs calculated using high- and low-frequency sampling and assess the spatiotemporal variability of the nitrate removal within a bioreactor to unravel the processes occurring within a bioreactor. For two drainage seasons, we monitored nitrate concentrations at 21 locations on an hourly or two-hourly basis within a pilot-scale woodchip bioreactor in Tatuanui, New Zealand. A novel method was developed to account for the variable lag time between entry and exit of a parcel of sampled drainage water. Our results showed that this method not only enabled lag time to be accounted for but also helped quantify volumetric inefficiencies (e.g., dead zone) within the bioreactor. The average RR calculated using this method was significantly higher than the average RR calculated using conventional low-frequency methods. The average RRs of each of the quarter sections within the bioreactor were found to be different. 1-D transport modelling confirmed the effect of nitrate loading on the removal process as nitrate reduction followed Michaelis-Menten (MM) kinetics. These results demonstrate that high-frequency temporal and spatial monitoring of nitrate concentrations in the field allows improved description of bioreactor performance and better understanding of processes occurring within woodchip bioreactors. Thus, insights gained from this study can be used to optimise the design of future field bioreactors.

Ultra-low Esfenvalerate concentrations increase biomass and may reduce competitiveness of Daphnia magna populations

Aquatic communities are frequently exposed to pesticides at sublethal concentrations, known to affect fitness parameters such as feeding, reproduction and population growth. Beside adverse effects, beneficial responses to toxicants at low concentrations may also occur. Positive effects, however, are thought to involve trade-offs. To identify such trade-offs, we quantified the population level effects on Daphnia magna during population carrying capacity in laboratory nanocosms after exposure to a single pulse of the pyrethroid insecticide esfenvalerate, including ultra-low concentrations ≤¹/₃₀ EC₅₀. Population abundance and biomass were monitored 3 times per week for 3 months using a non-invasive imaging technique. High concentrations ≥¹/₁₀ EC₅₀ resulted in reduced fitness endpoints. In contrast, ultra-low concentrations in the range of 0.01 μg/L significantly increased the population abundance of small (+160 %), medium (+130 %) and large organisms (+340 %) and their combined biomass (+200 %) during the 2 months after exposure. During the first five days after exposure to 0.01 μg/L and 0.03 μg/L esfenvalerate, population biomass increased by 0.1 mg/day while staying constant in the controls. While high control mortality makes firm conclusions about population responses of D. magna to esfenvalerate difficult, we hypothesize that population increases at ultra-low concentrations may be due to a hormetic response, where reduced intraspecific competitiveness is the trade-off that enables this response.

Wind drives fast changes of light climate in a large, shallow re-established lake

With ever greater frequency, wetlands and shallow lakes that had been diverted for agriculture are being re-established to reduce nutrient loss and greenhouse gas emission, as well as to increase biodiversity. Here, we investigate drivers of water column light attenuation (K_d) at multiple time scales and locations in Lake Fil, Denmark, during the first five years after its re-establishment in 2012. We found that K_d was generally high (overall mean: 3.4 m^-1), with resuspended sediment particles and colored dissolved organic matter being the main contributors. Using daily time series of light attenuation recorded at four stations, we used a generalized additive model to analyze the influence of wind speed and direction on K_d. This model explained a high proportion of the variation (R² = 0.62, RMSE = 0.74 m^-1, and MAE = 0.55 m^-1) and showed that higher wind speed increased K_d on the same day and, with smaller influence, on the next day. Furthermore, we found a significant influence of wind direction and an interaction between wind speed and wind direction, a combination that suggests that short-term variations in light climate depends on the interplay between wind direction and sources of particles. Wind from non-prevailing directions thus influence K_d more, as it can activate previously deposited particles. The maximum colonization depths of submerged vegetation occurred at ~2-6% of sub-surface light from 2014 to 2016 and peaked at 1.2 m in 2016. The fast, day-to-day variation of K_d in Lake Fil reveals the importance of wind on light climate and in turn biological elements such as phytoplankton and submerged macrophyte development in shallow lakes. The implications are essential for the prior planning and management of future lake re-establishment.

Continuous high-frequency pesticide monitoring to observe the unexpected and the overlooked

Synthetic Plant Protection Products (PPPs) are a key element for a large part of today's global food systems. However, the transport of PPPs and their transformation products (TPs) to water bodies has serious negative effects on aquatic ecosystems. Small streams in agricultural catchments may experience pronounced concentration peaks given the proximity to fields and poor dilution capacity. Traditional sampling approaches often prevent a comprehensive understanding of PPPs and TPs concentration patterns being limited by trade-offs between temporal resolution and duration of the observation period. These limitations result in a knowledge gap for accurate ecotoxicological risk assessment and the achievement of optimal monitoring strategies for risk mitigation. We present here high-frequency PPPs and TPs concentration time-series measured with the autonomous MS²Field platform that combines continuous sampling and on-site measurements with a high-resolution mass spectrometer, which allows for overcoming temporal trade-offs. In a small agricultural catchment, we continuously measured 60 compounds at 20 minutes resolution for 41 days during the growing season. This observation period included 8 large and 15 small rain events and provided 2560 concentration values per compound. To identify similarities and differences among the compound-specific concentration time-series, we analysed the entire dataset with positive matrix factorisation. Six factors sufficiently captured the overall complexity in concentration dynamics. While one factor reflected dilution during rainfall, five factors identified PPPs groups that seemed to share a common history of recent applications. The investigation per event of the concentration time-series revealed a surprising complexity of dynamic patterns; physico-chemical properties of the compounds did not influence the (dis)similarity of chemographs. Some PPPs concentration peaks led while others lagged by several hours the water level peaks during large events. During small events, water level peaks always preceded concentration peaks, which were generally only observed when the water levels had almost receded to pre-event levels. Thus, monitoring schemes relying on rainfall or water level as proxies for triggering sampling may lead to systematic biases. The high temporal resolution revealed that the Swiss national monitoring integrating over 3.5 days underestimated critical concentration peaks by a factor of eight to more than 32, captured 3 out of 11 exceedances of legal acute quality standards (the relevant values in the Swiss Water Protection Law) and recorded 1 out of 9 exceedances of regulatory acceptable concentrations (the relevant values for the PPPs registration process). MS²Field allowed for observing unexpected and overlooked pesticide dynamics with consequences for further research but also for monitoring. The large variability in timing of concentration peaks relative to water level calls for more in-depth analyses regarding the respective transport mechanisms. To perform these analyses, spatially distributed sampling and time-series of geo-referenced PPPs application data are needed.

High-frequency monitoring reveals how hydrochemistry and dissolved carbon respond to rainstorms at a karstic critical zone, Southwestern China

Hydrochemical behavior and dissolved carbon dynamics are highly-sensitive to hydrological variations in the monsoon-influenced karstic critical zone which has high chemical weathering rates and experiences strong anthropogenic impact. Continuous high-frequency monitoring in the spring outlet of a karstic catchment in Southwestern China revealed that most hydrochemical variables changed distinctively in response to hydrologic variations, influenced by mixing of different sources and miscellaneous biogeochemical processes. Na⁺, K⁺ and SO₄^2- varied significantly with hydrology, showing weak chemostatic behavior controlled by dilution. The flushing effect and random behavior of NO₃^- and Cl^- likely reflect agricultural inputs from high throughflow. Soil CO₂ in infiltrated water supports carbonate weathering, enabling DIC (dissolved inorganic carbon) and weathering products (e.g., Ca²⁺ and Mg²⁺) to maintain chemostatic behavior. Biogenic DIC exhibited a stronger chemostatic response than carbonate sources and was the foremost control in DIC behavior. Carbon exchange between DIC and DOC (dissolved organic carbon) did not significantly influence DIC concentration and δ¹³C due to very low DOC concentration. More DOC was exported by flushing from increasing discharge. Hysteretic analysis indicated that the transport processes were controlled by proximal sources mixing and diverse mobilization in various periods responding to rainstorms. NO₃^- and Cl^- presented different hysteresis behavior as sourced from agricultural activities. DOC increased on the hydrograph rising limb and was controlled by a transport-limited regime. However, the hysteresis behavior of most weathering products and DIC were regulated by a process-limited regime in the karstic critical zone. Overall, biogeochemical processes, hydrogeological properties, storm intensity/magnitude and the timing of storms (antecedent conditions) are main factors influencing the response of hydrochemical variables and dissolved carbon to storm events.

Benchmarking inference methods for water quality monitoring and status classification

River water quality monitoring at limited temporal resolution can lead to imprecise and inaccurate classification of physicochemical status due to sampling error. Bayesian inference allows for the quantification of this uncertainty, which can assist decision-making. However, implicit assumptions of Bayesian methods can cause further uncertainty in the uncertainty quantification, so-called second-order uncertainty. In this study, and for the first time, we rigorously assessed this second-order uncertainty for inference of common water quality statistics (mean and 95th percentile) based on sub-sampling high-frequency (hourly) total reactive phosphorus (TRP) concentration data from three watersheds. The statistics were inferred with the low-resolution sub-samples using the Bayesian lognormal distribution and bootstrap, frequentist t test, and face-value approach and were compared with those of the high-frequency data as benchmarks. The t test exhibited a high risk of bias in estimating the water quality statistics of interest and corresponding physicochemical status (up to 99% of sub-samples). The Bayesian lognormal model provided a good fit to the high-frequency TRP concentration data and the least biased classification of physicochemical status (< 5% of sub-samples). Our results suggest wide applicability of Bayesian inference for water quality status classification, a new approach for regulatory practice that provides uncertainty information about water quality monitoring and regulatory classification with reduced bias compared to frequentist approaches. Furthermore, the study elucidates sizeable second-order uncertainty due to the choice of statistical model, which could be quantified based on the high-frequency data.

Autotrophic nitrate uptake in river networks: A modeling approach using continuous high-frequency data

High-frequency sensor measurements enable calculation of continuous autotrophic nitrate uptake rate based on its intrinsic relationship with gross primary production (GPP). The spatiotemporally available data offer prospects to advance process understandings across scales. We used continuous 15-min data (2011-2015) from a forest upstream reach and an agricultural downstream reach of the Selke River, Germany. Based on the high-frequency data, we developed a parsimonious approach for regionalizing the autotrophic uptake rate, considering effects of global radiation and riparian shading. For networked modeling, we integrated this approach into the fully distributed mesoscale hydrological nitrate model (mHM-Nitrate). Daily GPP-based uptake rate calculations showed distinct seasonal patterns and ranges in the agricultural and forest streams (mean values were 80.9 and 15.5 mgNm^-2d^-1, respectively). Validation in the two streams showed acceptable performance (R² = 0.47 and 0.45, respectively) and spatial transferability of the regionalization approach, given its parsimony. Networked modeling results showed high spatiotemporal variability in nitrate transport and uptake throughout the river network. The magnitude of gross uptake increased, whereas uptake efficiency decreased significantly along stream order. Longitudinal analysis in the main stem of the Selke River revealed that riparian shading and inter-annual hydrochemical variations strongly influenced daily dynamics of the uptake efficiency. This study provides a parsimonious and transferable procedure for regionalizing in-stream autotrophic nitrate uptake based on high-frequency data at reach scale. Integrating this approach in the mHM-Nitrate model allows detailed nitrate transport and in-stream uptake processes to be investigated throughout river networks.

The concentration-discharge slope as a tool for water quality management

Recent technological breakthroughs of optical sensors and analysers have enabled matching the water quality measurement interval to the time scales of stream flow changes and led to an improved understanding of spatially and temporally heterogeneous sources and delivery pathways for many solutes and particulates. This new ability to match the chemograph with the hydrograph has promoted renewed interest in the concentration-discharge (c-q) relationship and its value in characterizing catchment storage, time lags and legacy effects for both weathering products and anthropogenic pollutants. In this paper we evaluated the stream c-q relationships for a number of water quality determinands (phosphorus, suspended sediments, nitrogen) in intensively managed agricultural catchments based on both high-frequency (sub-hourly) and long-term low-frequency (fortnightly-monthly) routine monitoring data. We used resampled high-frequency data to test the uncertainty in water quality parameters (e.g. mean, 95th percentile and load) derived from low-frequency sub-datasets. We showed that the uncertainty in water quality parameters increases with reduced sampling frequency as a function of the c-q slope. We also showed that different sources and delivery pathways control c-q relationship for different solutes and particulates. Secondly, we evaluated the variation in c-q slopes derived from the long-term low-frequency data for different determinands and catchments and showed strong chemostatic behaviour for phosphorus and nitrogen due to saturation and agricultural legacy effects. The c-q slope analysis can provide an effective tool to evaluate the current monitoring networks and the effectiveness of water management interventions. This research highlights how improved understanding of solute and particulate dynamics obtained with optical sensors and analysers can be used to understand patterns in long-term water quality time series, reduce the uncertainty in the monitoring data and to manage eutrophication in agricultural catchments.

Characterisation of a major phytoplankton bloom in the River Thames (UK) using flow cytometry and high performance liquid chromatography

Recent river studies have observed rapid phytoplankton dynamics, driven by diurnal cycling and short-term responses to storm events, highlighting the need to adopt new high-frequency characterisation methods to understand these complex ecological systems. This study utilised two such analytical methods; pigment analysis by high performance liquid chromatography (HPLC) and cell counting by flow cytometry (FCM), alongside traditional chlorophyll spectrophotometry and light microscopy screening, to characterise the major phytoplankton bloom of 2015 in the River Thames, UK. All analytical techniques observed a rapid increase in chlorophyll a concentration and cell abundances from March to early June, caused primarily by a diatom bloom. Light microscopy identified a shift from pennate to centric diatoms during this period. The initial diatom bloom coincided with increased HPLC peridinin concentrations, indicating the presence of dinoflagellates which were likely to be consuming the diatom population. The diatom bloom declined rapidly in early June, coinciding with a storm event. There were low chlorophyll a concentrations (by both HPLC and spectrophotometric methods) throughout July and August, implying low biomass and phytoplankton activity. However, FCM revealed high abundances of pico-chlorophytes and cyanobacteria through July and August, showing that phytoplankton communities remain active and abundant throughout the summer period. In combination, these techniques are able to simultaneously characterise a wider range of phytoplankton groups, with greater certainty, and provide improved understanding of phytoplankton functioning (e.g. production of UV inhibiting pigments by cyanobacteria in response to high light levels) and ecological status (through examination of pigment degradation products). Combined HPLC and FCM analyses offer rapid and cost-effective characterisation of phytoplankton communities at appropriate timescales. This will allow a more-targeted use of light microscopy to capture phytoplankton peaks or to investigate periods of rapid community succession. This will lead to greater system understanding of phytoplankton succession in response to biogeochemical drivers.

Dynamic behaviour of trace metals in the Deûle River impacted by recurrent polluted sediment resuspensions: from diel to seasonal evolutions

An automatic trace metal monitoring station (ATMS) have been implemented in the river bank of the Deûle canal in the city of Auby (northern France), in the vicinity of metallurgical industries that have heavily polluted sediments, in Cd, Pb and Zn. Additionally, the fluvial traffic in this river is intense and surface sediments are resuspended several times per day. This paper is the following part of that published recently (Superville et al., 2014) in this journal. The main purpose of this paper is to present new information on diel and seasonal variations of trace metals in the Deûle River and highlight the potential role of sediments in the contamination of the water column. To this end, Cd, Zn and Pb were monitored at a high frequency (~1h(-1)) by voltammetry, distinguishing an electrolabile and an acid-leachable fraction. Our measurements revealed that (i) acid-leachable Cd is mainly bound to light particles such as clays and carbonates and its daily behaviour does not really depend on the intensity of sediment remobilisation process; (ii) acid-leachable Pb and Zn exhibit some seasonal variations which are explained here, suggesting they should at least partly depend on the ageing of hydrous ferric oxides in the sediments; (iii) in spring, the electrolability of Zn increases in agreement with the biological activity that may break some strong association between Zn and ligands and/or particles (e.g., organic matter, hydrous ferric oxides, etc.). This trend is observed for electrolabile Pb later in summer, but on a smaller scale since this metal is generally more strongly scavenged and less labile than Zn; and (iv) electrolabile Mn concentrations increase during the day due to desorption process of resuspended sediment particles in the water.