BioIndicators are usually score-based indices built from a tricky protocol. Indicators datasets are often incomplete and heterogeneous time series. Nevertheless, they are necessary tools in order to assess water quality, and to help decision makers. To highlight a water quality evolution, a first operation consists in detecting trends and breaking points on datasets. So, we have chosen to use four different statistical tests specifically adapted to incomplete smallsize datasets. We have focused on a biological indicator, IBGN, because of its robustness and its wide use. It is based on the abundance and the diversity of the benthic invertebrates. The work is applied on 56 datasets located on the Saône catchment (30000 km2 - East of France). Tests results are not always in accordance. Then, we try to find explicative factors that could help us to understand the observed trend and tests disagreements. Several kind of factors can be explored: (i) metrological aspects in relationship with the complex implementation of the protocol and the evolution of monitoring networks; (ii) environmental aspects such as hydrological regime and extreme events (flood, drought); (iii) human pressures aspects (presence of wastewater treatment plant, evolution of land uses at different scales -watershed, riparian area- , restoration actions…). On one hand, we discuss tests results according to the three aspects on some specific cases (i.e. when we can access easily to information). On the second hand, we discuss the importance to conserve and to structure information that usually exists but is located at various operators under different forms (expert knowledge, reports, database…).