Max Eysholdt

Many countries in the EU fail to protect their waters adequately from nitrogen and phosphorus inputs (European Environment Agency. 2024), often originating from agricultural sources (Sutton 2011). Germany was found guilty by the European Court of Justice for insufficient implementation of the EU Nitrates Directive, for protection of waters from nutrient pollution from agriculture (European Court of Justice 2018). In response, Germany introduced a monitoring system for assessing the impact of the recently updated application ordinance, which implements the EU Nitrates Directive. This monitoring creates time series of pollution-related spatial indicators ranging from land use to modelled nutrient budgets. Input data on land use sources the Integrated Administration and Control System. The results are used by German authorities for reporting to the EU as well as national and regional water protection policy.We present the technical concept, infrastructure and workflows established for this data-intensive, long-term project and discuss challenges and limitations when operating in the science-policy nexus. We aim to share good practices in modularization, automation, and reproducibility, and discuss strategies for efficient maintenance of scientific software development in context of long-term, policy-relevant monitoring projects.Our system is designed to handle heterogeneous data with different levels of data protection requirements related to General Data Protection Regulation (GDPR). A modular structure was chosen to enhance usability and maintenance. Reproducibility is ensured through version-controlled, script-based software development. For efficiency, consistency and the streamlining of workflows reporting is automated and an ever-growing set of user-faced functions is bundled into a package. To ensure the possibility of advances in data preparation and modelling, a submission-based approach was chosen, recalculating all indicator times series each reporting year. This requires robust data management, reproducibility, and resilient workflows to accommodate evolving input data.We still face challenges in handling Open Science principles, political stakeholder interests as well as GDPR. Similarly, scientific advances lead to updated results which may conflict with the need for clear and unambiguous outcomes of the authorities. Regular deadlines and stakeholder needs resulted in an organically grown code base, and sometimes cause neglection of quality checks and unit testing. Additionally, interaction between reproducible, script-based solutions and “traditional” workflows based on Microsoft Word are inefficient. The changing structure of the yearly gathered data hinders automatization of data processing. Due to this and the annual advances in the processing of the input data, maintaining the database is also challenging. This we would like to share and discuss with other teams facing similar problemOur system is tailored to handle heterogeneous and sensitive data of different sources producing reliable results and accommodating advances in data preparation and modelling in the long run. However, navigating technical limitations, good scientific practice and policymakers’ interests is challenging for us.LiteratureEuropean Court of Justice (2018). European Commission against Federal Republic of Germany. Infringement Proceedings ‐ Directive 91/676/EEC.European Environment Agency. (2024). Europe's state of water 2024: the need for improved water resilience. Publications Office.Sutton, Mark A. (Ed.) (2011). The European nitrogen assessment. Sources, effects and policy perspectives. Cambridge 2011.

Water pollution with nitrogen (N) from agriculture constitutes a persisting environmental problem in intensive farming regions worldwide. Understanding the spatio-temporal interconnection between agricultural N emissions and N inputs to water bodies is key to evaluating and improving existing mitigation policies. Nitrogen flux models are an indispensable tool for addressing these complex research questions in the land use–water nexus, requiring adequate data on agricultural N surpluses. However, high-resolution farm management data are not readily available to the scientific community. We develop a municipality-level agricultural N budget model for Germany based on farm-level administration data from the Integrated Administration and Control System (IACS) and regional expert knowledge. We estimate a total agricultural N surplus of 58 kg N ha⁻¹ of utilised agricultural area as the three-year average for 2014–2016. About 90% of municipalities exhibit N surpluses between 21 and 99 kg N ha⁻¹. Evaluation with collected farm accountancy data revealed a good fit of the modelled (with observed) mineral N quantities applied. Our results highlight the potential of farm-level data for N flux models. Due to the ubiquitous reporting of land use and farming structures in the IACS, our approach can be adapted in other countries of the EU to serve as a harmonised backbone of monitoring and policy impact assessments.

For the first time, the AGRUM model consortium—consisting of the agro-economic model RAUMIS, the water balance model mGROWA, the hydrological nutrient transport models DENUZ, WeKu and MEPhos, and the urban emission model MONERIS—was jointly set up throughout Germany (357,000 km²). This provided a nationwide consistent nutrient model to capture the current status of N and P inputs to surface waters from diffuse sources and urban areas. Diffuse nutrient emissions were quantified in high spatial resolution for the input pathways’ groundwater, drainage runoff, and natural interflow (100 m × 100 m), as well as for water erosion and wash-off (25 m × 25 m). The sum of diffuse nutrient inputs to surface waters is about 385,000 metric tons N/yr and ca. 11,530 metric tons P/yr. Urban emissions were quantified either as point source inputs (wastewater treatment plants, industrial direct dischargers) or at municipality scale for different collection and treatment systems, e.g., rainwater sewers or decentralized treatment plants, and sum up to ca. 95,000 t N/yr and 7500 t P/yr. As modelled, total N and P inputs into surface waters correspond well with observed N and P loads in rivers. The model results represent valuable information for water managers, being responsible for the preparation of management plans for the third management cycle of the EC Water Framework Directive spanning from 2021 to 2027.

This article presents a mixed-methods research protocol suitable for studying everyday mobility and its effects on life chances for a wide range of populations. We argue that it can address, among other issues, two important methodological challenges in the study of mobility: addressing pre-reflexivity and habits, as well as differentiating between voluntary and forced movements. The research protocol combines a problem-centered interview, two weeks of GPS tracking, and a subsequent mobility interview. It has been shaped by its application to more than 60 socially disadvantaged residents of rural peripheries as part of an international research project. It contributes to existing qualitative methods of spatial analysis because its design incorporates not only theoretical considerations but also insights of real-world application from conducting it in varied contexts and with different populations, which are typically underrepresented in more elaborate research designs. Nevertheless, due to its thematic openness, the design is not only interesting for mobility research, but also for other research focusing on spatial phenomena at the individual level. We provide a detailed account of the method’s implementation, contextualize it in relation to previous approaches, and discuss the analytical potential of the data obtained. We suggest that by triangulating movement data with interview data, perceptions and meanings of everyday mobility can be uncovered that would otherwise remain at a pre-reflexive level.