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Abstract

The deterioration of superficial water quality is a relevant issue as regards water management. However, most European rivers still not achieved the qualitative standards defined by the Water Framework Directive (WFD). Also, river ecological status is defined on the basis of monitoring data, which are in most of the cases available only along main watercourses and appear erratic in time and space. Given the goals of the WFD, a short-cut methodology to perform a semi-quantitative assessment of water pressures on rivers starting from easily accessible data is proposed. The methodology presents a procedure for: (1) identifying river segment exposed to pollution spills with a raster-based hydrological approach; (2) defining a Biochemical Quality Index (BQI) for each exposed river segment and a procedure for its spatial allocation. A validity check is performed comparing the BQI with monitoring data. Results shows that the BQI is well reflected in the monitoring values, faithfully reproducing the increasing and decreasing trend of biochemical pressures along the river. The BQI is used as a reliable proxy variable to represent the anthropogenic pressures that impacts on superficial water bodies. Thus, its suitability within a machine learning algorithm trained starting from easily available input data (e.g., climatic and hydrological variables, anthropic pressures, water management techniques, etc.) to predict the ecological status of rivers is also investigated. Based on the findings of this study, the proposed methodology can represent a valued tool to sustain decision-making processes and predictive studies in areas with no, or poor, monitoring data.