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

Wang, Jinyu; Bouchez, Julien; Dolant, Antoine; Floury, Paul; Stumpf, Andrew J.; Bauer, Erin; Keefer, Laura; Gaillardet, Jérôme; Kumar, Praveen; Druhan, Jennifer L.

doi:10.1016/j.scitotenv.2023.167379

Cited by 4 publications

(5 citation statements)

References 79 publications

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“…In particular, the exports of solutes during relatively wet periods of elevated water storage and/or large rain events are fundamentally distinct from those associated with smaller events and dry periods. As a consequence, load estimates focused on event‐based solute export should consider such seasonality, and avoid relying on long‐term average C‐Q patterns (Wang et al., 2024).…”

Section: Discussionmentioning

confidence: 99%

“…The design and analytical performance of the RL are detailed in Floury et al (2017). The utility of such high-frequency RL hydrochemical data sets for solute flux estimates was recently demonstrated by Wang et al (2024), facilitating novel testing of commonly applied load-estimation algorithms (e.g., Cerro et al, 2014;Diamond & Cohen, 2018;Dornblaser & Striegl, 2009;Duan et al, 2012, Park & Engel, 2014Runkel et al, 2004;Moatar et al, 2017;Minaudo et al, 2019;Musolff et al, 2015).…”

Section: The Orgeval River Labmentioning

confidence: 99%

“…To date, a generalized and parsimonious approach to event‐scale C‐Q and storm hydrograph analysis remains to be established. Recent technological advances now offer the possibility for advancement through tracking of C‐Q relationships for a large variety of elements at high frequency and over long timescales through deployment of “lab‐in‐the‐field” devices (Floury et al., 2017; Rode et al., 2016; von Freyberg et al., 2017; Wang et al., 2024). Here we rely on such a device, called the “River Lab” (RL), to measure the full suite of stream major dissolved species at a sub‐hourly frequency (Floury et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

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Linking Dynamic Water Storage and Subsurface Geochemical Structure Using High‐Frequency Concentration‐Discharge Records

Floury,

Bouchez,

Druhan

et al. 2024

Water Resources Research

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Shifts in water fluxes and chemical heterogeneity through catchments combine to dictate stream solute export from the Critical Zone. The ways in which these factors emerge in resultant concentration‐discharge (C‐Q) relationships remain obscure, particularly at the timescale of individual precipitation and discharge events. Here we take advantage of a new high‐frequency, multi‐element and multi‐event stream C‐Q data set. The stream solute concentrations of seven major ions were recorded every 40 min over five flood events spanning one hydrologic year in a French agricultural watershed (Orgeval) using a lab‐in‐the‐field deployment we refer to as a “River Lab.” We focus attention on the recession periods of these events to consider how geochemical heterogeneity within the catchment translates into dynamic stream solute concentrations during shifts in water storage. We first show that for C‐Q relationships resulting from data acquisition over multiple flood events, lumping all trends together can lead to biases in characteristic C‐Q parameters. We then reframe C‐Q relationships using a simple recession curve analysis to consider how hydrological processes produce chemical mixing of distinct solute pools immediately following discharge events. We find three distinct classes of behavior among the major solutes, none of which can be interpreted based on water storage changes alone. The shape of C‐Q relationships for each solute can then be related to their vertical zonation in the subsurface of Orgeval, and to the capacity for subcomponents of these distributions to be readily mobilized during a discharge event.

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Section: Discussionmentioning

confidence: 99%

Section: The Orgeval River Labmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Linking Dynamic Water Storage and Subsurface Geochemical Structure Using High‐Frequency Concentration‐Discharge Records

Floury,

Bouchez,

Druhan

et al. 2024

Water Resources Research

Self Cite

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“…In comparison to research on the effect of sampling frequency that focuses on load calculation [4][5][6][7][8][9], the effects of frequency on regulatory parameters are underrepresented [10][11][12]. Annex V 1.3.4 of the WFD can be considered the benchmark for monitoring frequencies and suggests a sampling frequency for physico-chemical quality elements of 3 months, except for priority substances, which should be sampled on a monthly basis.…”

Section: Introductionmentioning

confidence: 99%

“…This suggests substantially higher required monitoring efforts than the ones envisaged by the WFD. Previous research showed that the required minimum sampling frequency depends on sampling location [12,13], the analyte [9,12], and temporal variability [10,11,14,15]. Skeffington et al (2015) [15] demonstrated the difficulties related to a reliable assessment of the five quality classes with a systematic resampling of a high temporal resolved time series where the results of the monthly sampling showed a high variability of WFD quality classes.…”

Section: Introductionmentioning

confidence: 99%

Can Short-Term Online-Monitoring Improve the Current WFD Water Quality Assessment Regime? Systematic Resampling of High-Resolution Data from Four Saxon Catchments

Benisch,

Helm,

Chang

et al. 2024

Water

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The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of integrated guidance on surface water chemical monitoring (e.g., WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires monthly sampling to assess the chemical quality status of a body of surface water. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data are investigated under different sampling scenarios and compared with current, monthly grab sampling data. About 23 million data points were analyzed for this study. Three chemical parameters (dissolved oxygen, nitrate-nitrogen, and chloride concentration) and discharge data were selected from four catchments of different sizes, ranging from 51,391 km2 to 84 km2 (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper, we propose short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general, we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as a proxy for analyzing event-mobilized pollutants, and (III) investigate the related uncertainties and costs of both sampling methods. Results show that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law, as the probability of catching a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, such as dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, such as nitrogen-nitrate or chloride. The analysis of discharge events as a proxy parameter for event-mobilized pollutants proves that the probability of capturing samples during events is significantly increased by STOM.

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The major element geochemistry of river waters: Fluxes, sources, and controls

Torres

2024

Reference Module in Earth Systems and Environmental Sciences

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

Cited by 4 publications

References 79 publications

Linking Dynamic Water Storage and Subsurface Geochemical Structure Using High‐Frequency Concentration‐Discharge Records

Linking Dynamic Water Storage and Subsurface Geochemical Structure Using High‐Frequency Concentration‐Discharge Records

Can Short-Term Online-Monitoring Improve the Current WFD Water Quality Assessment Regime? Systematic Resampling of High-Resolution Data from Four Saxon Catchments

The major element geochemistry of river waters: Fluxes, sources, and controls

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