Anthropogenic litter, plastic in particular, is an emerging ecological hazard. To effectively prevent, mitigate and reduce litter in river systems, accurate monitoring of litter in the Dutch rivers is necessary. Inspired by the OSPAR Guideline for monitoring marine litter on the beaches in the OSPAR maritime area, a riverbank litter monitoring protocol (River-OSPAR) was developed by Stichting De Noordzee. In this report, we present an evaluation of the River-OSPAR method in. We compared the River-OSPAR protocol with the original Beach-OSPAR protocol, as well as other methods for riverbank litter monitoring. Subsequently, we present the results of a data analysis based on the two years of available observations (2017 – 2019) at in total 211 unique measurement locations. We explored the variation of space and time, as well as the composition, sources and transport mechanisms. Finally, we discuss the learnings from monitoring efforts focusing on litter in other components of the river system, and potential use of additional data to study sources and pathways of litter in Dutch Rivers. The strengths of the River-OSPAR include the extensive geographical coverage and detailed item categorization. These data allow for detailed hotspot analysis along the rivers Meuse and Waal. Both incidental and consistent hotspots were found. Incidental peaks may be related to increased input or accumulation at that location. Consistent hotspots were found to be located close to urban areas with direct access to the river, such as the cities of Nijmegen, Roermond and Maastricht. The detailed data on occurrence of specific items allowed for a correlation analysis to determine the sources of each item. Recommendations for improvement of the method and dataset include (1) increased temporal resolution, (2) additional reference measurements, and (3) inclusion of item mass statistics. The limited temporal extent of the data causes some uncertainty. Tentative conclusions on the spatial variation and seasonality can only be supported through expansion of the dataset in time. Increasing the measurement frequency from two to four times per year will also increase the possible analysis, specifically with regard to exploring the relation between litter density and hydrometeorological conditions. Additional reference measurements will shed light on the volunteer bias. It was found that volunteers generally observe less items than the reference measurements. It is recommended to plan reference measurements at the exact same locations to determine the bias. Finally, inclusion of mass statistics will allow expressing the litter density in terms of mass rather than items. Mass can in turn be related to production, consumption and waste handling data. Furthermore, this can help optimizing strategies to mitigate and remove litter from river systems. Additional recommendations include the application of new technology for data collection and management, and observing other components of the river system. New technological advances include the development of camera-based automated litter monitoring systems, UAVs and mobile applications. Cameras can be used for permanent monitoring of litter at specific locations. UAVs on the other hand can be used for quick scans of large areas, or follow-up monitoring of hotspots from the River-OSPAR observations. To facilitate better recording of raw data, it is recommended to use mobile apps for data collection. As samples need to be sorted in over 100 categories, apps with smart indexing may faster data collection. Also, raw data can easier be quality checked. The current monitoring effort mainly focusses on riverbank litter. A large share of litter however is mobile as floating litter. Several citizen science methods exist for rapid monitoring of floating litter in rivers. We recommend to expand the country-wide monitoring effort with floating litter observations from bridges. They can either be implemented in the current monitoring effort, or be organized as stand-alone observations with higher temporal frequency. The current River-OSPAR method has provided an unprecedented data with high spatial frequency and detailed item categorization. These insights already provide valuable insights that can support decision-making in litter prevention, mitigation and reduction strategies. Several aspects can be considered to further improve the protocol, which may help answering the questions that remain open to date.