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

Author:

Ritson J. P.ORCID,Kennedy-Blundell O.,Croft J.,Templeton M. R.,Hawkins C. E.,Clark J. M.,Evans M. G.,Brazier R. E.,Smith D.,Graham N. J. D.

Abstract

AbstractHigh 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.

Funder

Engineering and Physical Sciences Research Council

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine

Reference31 articles.

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