Challenges in the Interpretation of River Water Quality Time Series
Per Stålnacke, Eva Skarbøvik
Bioforsk, Aas, Norway

It is essential for managers and scientists alike that the water quality status in rivers can be assessed with appropriate accuracy and precision. Quantifying the development of water quality over time is also essential, e.g. in order to detect the time needed for a river system to respond to changes in emissions. Such information is needed to allow environmental authorities and decision and policy makers to establish realistic environmental goals, as well as to assess whether or not the goals have been met. Water quality is normally monitored by regular spot samples (e.g. fortnightly or monthly), despite the common knowledge that water quality often varies substantially during short time intervals. Moreover, it is known that the water quality could be heavily influenced by the temporal variability in water discharge. This poses problems in determining the pollution loads and trends over time. Another problem is related to changes in laboratory techniques over time, including changes in levels of detection (LoD-values).

In this presentation, the focus will be on the challenges related to the interpretation of water quality time series. More specifically we will focus on the following three aspects:

1) the importance of sampling frequencies for trend detection and pollution load estimates,

2) the effects of changed LoD values over time

3) means and methods to account for the hydrological effects on water quality variability

The latter will include considerations around load estimation methods, sampling techniques and flow-normalization for trend detection.

Examples from Norway and rivers in Europe will be given.

Keywords: Time series; Hydrology; Water quality

Biography: Per Stålnacke is a senior researcher at Bioforsk (Norwegian Institute for Agricultural and Environmental Research). He is head of department 'Water quality and hydrology). His primary research field in statistics is on time series analysis