Predicting water chemistry: comparing modelled and experimental data
What is it about?
Computer models enabling the prediction of the distribution of dissolved metals between different chemical forms in freshwater environments have been available for decades. These models have become important in a large range of academic and regulatory disciplines. This study looks at the performance of the model against experimental data for all aquatic environments. Comparison of the measured and predicted metal forms for the whole data set showed that agreements are best for fresh waters, followed by estuarine and coastal waters, then open-ocean waters. This is likely a reflection of the fact that the model parameters are based on experimental data from terrestrial (soil and river water) organic carbon (degradation material from decay of once living organisms).
Why is it important?
In comparing model predictions with measurements by different analytical techniques, the data suggests that a method called competitive ligand–stripping voltammetry (widely used in chemical oceanography) overestimates metal interaction with organic matter. When this method is excluded there is no overall bias when comparing modelling with experiments. Further work is urgently needed to determine if this is due to analytical error or the failure of the model to represent a pool of natural highly reactive organic matter released by organisms to preferentially get at metal nutrients.
The following have contributed to this page: Anthony Stockdale