Integrated continuous water quality monitoring for the LOIS river syndromme

Evans, James George; Wass, P.D.; Hodgson, P.

doi:10.1016/s0048-9697(96)05387-9

Cited by 30 publications

(23 citation statements)

References 2 publications

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“…Data based on sampling are affected by errors in capturing a volume of flow without altering its composition of dissolved and suspended substances (Wass and Leeks, 1999). The errors associated with automatic sampling systems may be greater in this respect compared with manual samples, as these rely on sufficient suction and prior flushing and are confounded by clogging, biofouling and, for particles and particulate-bound substances, preferential sampling effects (Evans et al, 1997;Jordan et al, 2005). For SS concentrations, for example, sampler effects may introduce a relative error as large as 36% (Figure 3a).…”

Section: Typical Resultsmentioning

confidence: 99%

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

McMillan

Krueger

Freer

2012

Hydrological Processes

414

366

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This review and commentary sets out the need for authoritative and concise information on the expected error distributions and magnitudes in observational data. We discuss the necessary components of a benchmark of dominant data uncertainties and the recent developments in hydrology which increase the need for such guidance. We initiate the creation of a catalogue of accessible information on characteristics of data uncertainty for the key hydrological variables of rainfall, river discharge and water quality (suspended solids, phosphorus and nitrogen). This includes demonstration of how uncertainties can be quantified, summarizing current knowledge and the standard quantitative results available. In particular, synthesis of results from multiple studies allows conclusions to be drawn on factors which control the magnitude of data uncertainty and hence improves provision of prior guidance on those uncertainties. Rainfall uncertainties were found to be driven by spatial scale, whereas river discharge uncertainty was dominated by flow condition and gauging method. Water quality variables presented a more complex picture with many component errors. For all variables, it was easy to find examples where relative error magnitudes exceeded 40%. We consider how data uncertainties impact on the interpretation of catchment dynamics, model regionalization and model evaluation. In closing the review, we make recommendations for future research priorities in quantifying data uncertainty and highlight the need for an improved ‘culture of engagement’ with observational uncertainties. Copyright © 2012 John Wiley & Sons, Ltd.

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Section: Typical Resultsmentioning

confidence: 99%

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

McMillan

Krueger

Freer

2012

Hydrological Processes

414

366

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“…Automatic water samplers can be linked to continuous stage or turbidity loggers and programmed to sample at different frequencies according to changing river flow or turbidity conditions (Evans et al, 1997). Successful automated sampling for P monitoring has been reported (e.g.…”

Section: Sampling : Collecting a Representative Samplementioning

confidence: 99%

Review of robust measurement of phosphorus in river water: sampling, storage, fractionation and sensitivity

Jarvie

Withers

Neal

2002

Hydrol. Earth Syst. Sci.

181

164

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This paper reviews current knowledge on sampling, storage and analysis of phosphorus (P) in river waters. Potential sensitivity of rivers with different physical, chemical and biological characteristics (trophic status, turbidity, flow regime, matrix chemistry) is examined in terms of errors associated with sampling, sample preparation, storage, contamination, interference and analytical errors. Key issues identified include:The need to tailor analytical reagents and concentrations to take into account the characteristics of the sample matrix. The effects of matrix interference on the colorimetric analysis. The influence of variable rates of phospho-molybdenum blue colour formation. The differing responses of river waters to physical and chemical conditions of storage. The higher sensitivities of samples with low P concentrations to storage and analytical errors.Given high variability of river water characteristics in space and time, no single standardised methodology for sampling, storage and analysis of P in rivers can be offered. 'Good Practice' guidelines are suggested, which recommend that protocols for sampling, storage and analysis of river water for P is based on thorough site-specific method testing and assessment of P stability on storage. For wider sampling programmes at the regional/national scale where intensive site-specific method and stability testing are not feasible, 'Precautionary Practice' guidelines are suggested. The study highlights key areas requiring further investigation for improving methodological rigour.

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“…These continuous series result in a more representative image of the water quality. In the second place, they can mean a solid basis to develop a more scientific approach on the sampling strategy and the needed amount of additional samples and the required chemical analyses (Beck et al, 1998;D'heygere et al, in preparation;Evans et al, 1997). Continuous measurements can also allow for detecting sudden changes in rivers, for example due to accidental discharges.…”

Section: Discussionmentioning

confidence: 99%

Application of Automated Measurement Stations for Continuous Water Quality Monitoring of the Dender River in Flanders, Belgium

Vandenberghe

Goethals

Griensven

et al. 2005

Environ Monit Assess

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During the summer of 1999, two automated water quality measurement stations were installed along the Dender river in Belgium. The variables dissolved oxygen, temperature, conductivity, pH, rain-intensity, flow and solar radiation were measured continuously. In this paper these on-line measurement series are presented and interpreted using also additional measurements and ecological expert-knowledge. The purpose was to demonstrate the variability in time and space of the aquatic processes and the consequences of conducting and interpreting discrete measurements for river quality assessment and management. The large fluctuations of the data illustrated the importance of continuous measurements for the complete description and modelling of the biological processes in the river.

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Integrated continuous water quality monitoring for the LOIS river syndromme

Cited by 30 publications

References 2 publications

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

Review of robust measurement of phosphorus in river water: sampling, storage, fractionation and sensitivity

Application of Automated Measurement Stations for Continuous Water Quality Monitoring of the Dender River in Flanders, Belgium

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