Assessing temporal representativeness of water quality monitoring data

Abstract

The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.

Calibration of in situ chlorophyll fluorometers for organic matter

“…In the clearwater lakes, predictability stayed lower than in humic lakes, likely due to interfering factors other than organic matter. It has been shown that in one of the clear water lakes, Lake Vesijärvi, Chl fluorescence is influenced by the high amount of cyanobacteria, and therefore the calibration of the Chl fluorometer with microscopic counts of cyanobacteria biomass was found effective for increasing the accuracy of Chl fluorometer results (compared to Chl a alone extracted in the laboratory, (Anttila et al, 2012). In this study, we did not study algal pigment abundance or algal community composition.…”

Variação nictemeral de qualidade da água em rios urbanos: implicações no monitoramento

“…Logo, quanto mais esta relação se afasta da unidade pior é a estimativa da variância total dos dados. Este estudo foi baseado no trabalho de Antilla et al (2012), o qual, através de um conjunto grande de dados Observa-se que a maioria dos parâmetros analíticos (Tabela 2) apresenta variância de coletas individuais acima da variância obtida a partir de um conjunto maior de dados. Esse fato sugere que a representatividade de amostragens únicas pode prejudicar a avaliação estatística dos parâmetros de qualidade da água.…”

Spatial statistics of hydrography and water chemistry in a eutrophic boreal lake based on sounding and water samples

“…In modeling the lake ecosystem, it is crucial that spatial variability is accounted for, especially in the period of stratification (Göransson et al 2004), although shortage of proper field data often limits the validation. Besides, sampling interval is another issue, which has to be taken into consideration in lake monitoring (see, e.g., Anttila et al 2012;Van de Bogert et al 2007).…”