Dataset related to article "New composite physico-chemical indicators constructed by Bayesian inference for water quality monitoring"

These dataset are associated with the paper being submitted entitled: New composite physico-chemical indicators constructed by Bayesian inference for water quality monitoring. Data collection covered an 8-year period divided into two sets of years: 2002 to 2006 and 2014 to 2016. All data were acquired from several comparable scientific studies using the same methods (AFNOR,1997). Imputation of missing data was performed to complete this dataset using the non-parametric "missForest" algorithm for mixed-type data. Physico-chemical parameters were extracted from publications (Gnohossou, 2006; Odountan et al., 2019, Zandagba et al., 2016a, 2016b). 17 variables were measured: water temperature, transparency, turbidity, conductivity, salinity, pH, dissolved oxygen (DO), BOD, COD, Kjeldahl nitrogen (TKN), ammonium , nitrates , nitrites , dry organic matter (DM) content, orthophosphates, total phosphorus (TP), suspended solids (SS). The geographical distribution of the sampling points is made to cover the whole Nokoué lagoon complex. A total of 20 sampling points were surveyed. The parameters were measured according to the four seasons of the year and/or at the succession of high water, low water, high water, and low water-stretch transitions. Nine driving forces described as factors likely to induce pressures were retained to explain the physico-chemical characteristics of the Nokoué and complete this data set.  The data resulting from the land use maps and relative to the distances between the considered stations and the tributaries can be improved in the future (Lead to other versions of this data set). As natural forcing variables, we have the sampling years, the seasons (SWS: short wet season or flood period; SDS: short dry season; LWS: long wet season; LDS: long dry season), the average monthly water level (MAWL) and the average wind speed (AWS), which is important in the context of Nokoué...