River monitoring plays a pivotal role in evaluating urban water quality status, detecting pollution events and their potential sources, and guiding the development of effective intervention strategies. In complex river networks, water quality degradation can stem from urban factors, such as inadequate sewer system management or runoff from contaminated surfaces during rainfall, as well as from external inputs linked to agricultural or industrial activities in surrounding areas. Accurately identifying the primary drivers of water quality deterioration is essential for designing targeted action plans and predicting their effectiveness. Although sporadic water sampling or visible indicators, such as foul odors during low-flow periods, can reveal quality impairment, more detailed information is required to differentiate pollution sources, thus, to implement appropriate restoration and mitigation measures. This study presents a monitoring system designed and tested to distinguish pollutants originating from urbanized areas from those associated with external activities (e.g., agriculture, industry), addressing the common challenge of prioritizing interventions for urban river improvement. The Sile River and the city of Treviso (Italy) were selected as a case study to validate the system and monitoring approach. Developed between 2021 and 2023, the system is characterized by six stations equipped with radar sensors for continuous water level and velocity measurements, three of which also feature multiparametric probes and refrigerated samplers. Two additional portable samplers allow for flexible sampling at other relevant locations. Both high-frequency (grab samples) and low-frequency (daily composite samples) monitoring strategies were implemented. Since 2023, the system collects data on the urban area’s impact during both dry and wet weather conditions and identifies temporal behaviour of physical and chemical species, providing a comprehensive overview of the Sile River’s current status. Data analysis developed through correlation, multilinear regression, principal component analysis, and load balance methods reveals which water quality parameters serve as indicators of specific pollution origins, ultimately supporting targeted improvement actions. Escherichia coli and Ptot resulted to be primarily associated with urban activities and indicative of sewer system contributions in both downtown and surrounding areas, whereas NO₃-N reflected agricultural inputs. Insights gained during the first two years of monitoring confirm the system’s effectiveness in assessing urban river quality and distinguishing between urban and agricultural contributions. Furthermore, the findings inform the design of monitoring programs for similar urban river contexts. After two years of operation, the study summarizes the strengths and limitations of the implemented system and evaluates its applicability to other case studies.
Mazzarotto et al. (Wed,) studied this question.