Mining the sequential patterns of water quality preceding the biological status of waterbodies - Corinne Grac (Elsevier, 2021)
We have implemented a specific data mining process to explore the relationship between biological indices and physico-chemical pressures in rivers. Data were collected in the framework of the French National monitoring network set up to assess the ecological status of rivers under the European Water Framework Directive (WFD). Chemical parameters and biological indices were collected regularly from 1.781 locations in metropolitan France from 2007 to 2013. The sequential pattern mining process generates closed partially ordered patterns representing a succession of physico-chemical events that precede a given biological index in a given status, validated using a subset of data. This paper focuses on the patterns and their occurrence. We showed that biological statuses depend on these temporal successions of alterations and not only on the last alterations. The physico-chemical statuses of water bodies usually appeared to be higher than their biological statuses, suggesting synergism between toxicants and/or an additive impact of other stressors related to hydromorphology or hydrology. Patterns found in the highest biological status for the biological indices based on macroinvertebrates, diatoms, macrophytes or fish, were characterised by the constancy of a high physico-chemical status over time. By contrast, before indices based on macroinvertebrates and macrophytes, two types of patterns were observed for bad biological status: (1) a chronic multi-pressure pattern, in which pressure categories such as nitrates, pesticides and other organic hydrocarbons, in moderate, poor or bad status, repeated themselves several times over time, or (2) a single occurrence of a degraded pressure category, such as one moderate nitrogen, excluding nitrate, or one poor oxidizable organic matter, among other pressure categories in good status. Extracting such patterns is a promising solution both to disentangle the effects of the different stressors on water quality, and to identify the key temporal sequences among them in a context of multi-stress conditions, which is a challenge currently facing the WFD.