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- Title
High frequency UV–Vis sensors estimate error in riverine dissolved organic carbon load estimates from grab sampling.
- Authors
Ritson, J. P.; 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
High 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.
- Subjects
UNITED Kingdom; DISSOLVED organic matter; SKEWNESS (Probability theory); DETECTORS; WATER quality monitoring; TIME series analysis; SOIL sampling
- Publication
Environmental Monitoring & Assessment, 2022, Vol 194, Issue 11, p1
- ISSN
0167-6369
- Publication type
Article
- DOI
10.1007/s10661-022-10515-9