Implementation of an active ‘bryomonitoring’ network for chemical status and temporal trend assessment under the Water Framework Directive in the Chiampo Valley's tannery district (NE Italy)

2013 ◽  
Vol 114 ◽  
pp. 303-315 ◽  
Author(s):  
Mattia Cesa ◽  
Andrea Baldisseri ◽  
Giovanni Bertolini ◽  
Ezio Dainese ◽  
Monia Dal Col ◽  
...  
2015 ◽  
Vol 19 (5) ◽  
pp. 2491-2504 ◽  
Author(s):  
R. A. Skeffington ◽  
S. J. Halliday ◽  
A. J. Wade ◽  
M. J. Bowes ◽  
M. Loewenthal

Abstract. The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High-frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to three or four of the WFD classes with 95% confidence, due to random sampling effects, whereas with weekly sampling this was one or two classes for the same cases. In the most extreme case, the same water body could have been assigned to any of the five WFD quality classes. Weekly sampling considerably reduces the uncertainties compared to monthly sampling. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Low-frequency measurements will generally be unsuitable for assessing standards expressed as high percentiles. Confining sampling to the working week compared to all 7 days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.


2015 ◽  
Vol 12 (1) ◽  
pp. 1279-1309
Author(s):  
R. A. Skeffington ◽  
S. J. Halliday ◽  
A. J. Wade ◽  
M. J. Bowes ◽  
M. Loewenthal

Abstract. The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to one of 3 or 4 WFD classes with 95% confidence, whereas with weekly sampling this was 1 or 2 classes for the same cases. In the most extreme case, random sampling effects could result in the same water body being assigned to any of the 5 WFD quality classes. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Confining sampling to the working week compared to all seven days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.


Author(s):  
María Jesús Belzunce-Segarra ◽  
Natalia Montero ◽  
José Germán Rodríguez ◽  
Iratxe Menchaca ◽  
Javier Franco ◽  
...  

2020 ◽  
Vol 114 (3) ◽  
pp. e24-e25
Author(s):  
Nahid Punjani ◽  
Omar Al Hussein Alawamlh ◽  
Soo Jeong Kim ◽  
Carolyn A. Salter ◽  
Gal Wald ◽  
...  

2009 ◽  
Vol 58 (9) ◽  
pp. 1389-1400 ◽  
Author(s):  
Itziar Tueros ◽  
Ángel Borja ◽  
Joana Larreta ◽  
J. Germán Rodríguez ◽  
Victoriano Valencia ◽  
...  

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