Multivariate statistical analyses for water and sediment quality index development: A study of susceptibility in an urban river

In this study, multivariate statistical analyses were performed to develop water and sediment quality indexes, allowing us (i) to select with reliability the most appropriate chemical variables for the evaluation of river quality susceptibility; (ii) to weight the influence of each variable based on monitored data; (iii) to consider possible synergism or antagonism derived from the combined effect of several pollutants; and (iv) to express the quality as a deviation from selected site-specific reference conditions. For the establishment of these threshold/maximum values, combining two biological indicators related to denitrifying bacteria in sediments turned out to be applicable to ensure compliance with the European water quality standard. The joint implementation of water and sediment quality indexes assisted us in the rapid detection of the deleterious effect of different anthropogenic contamination sources, as well as the influence of hydrological regime seasonality on river quality. In addition, metal-dependent water quality appeared to be coupled to sediment dynamics, since they were preferentially adsorbed onto sediments during low flow seasons, whereas there was potential for metal mobilization to water during sediment resuspension in high flow seasons. Therefore, an annual determination of sediment quality index was also recommended as suitable tool for prospective monitoring water quality, identifying those sites which could deserve special attention during certain periods, and planning future strategies for river quality improvement. However, two limitations were found: (1) sediment was not appropriate for water physicochemical quality early monitoring due to organic matter and nutrient continuous transformation; and (2) a multimetric index did not provide a concise and definitive quality information, thus a new tool for combining with quality index was proposed for specifically evaluate the water and sediment quality by identifying pollutant/s of concern at each location. (C) 2019 Elsevier B.V. All rights reserved.