Understanding impacts of environment-related payments on farm level production and economy through integrated spatial modelling

The EU Water Framework Directives (WFD) sets to achieve a ‘good’ surface water quality status, while the practical means to achieve this target is in hands of the individual member states though application of Agri-Environmental Schemes and their specific protective measures. In its EU withdrawal agreement, the United Kingdom has decided to retain the European water regulatory framework. In Scotland, almost 30% of watercourses are expected to be of lower than ‘good’ ecological status in 2021, and thus require attention of policymakers. Scotland’s River Basin Management Plans (RBMPs) set out a range of actions to address the issues with regional water quality. The farmers’ capacity to meet its obligations are, in turn, supported by the adoption of the Agri-Environment Climate Scheme (AECS). Nitrogen is one of the main water pollutants emitted by agricultural practices of farms, and thus it is of crucial importance to determine the most cost-effective ways to reduce nitrogen pollution bellow the target levels. This study aims to adapt the SMILE spatial microsimulation model to run farm-level scenario analysis of a set of specific measures aimed at reducing disperse nitrogen loads. The scenario results are compared against a baseline simulation, that represents the current state of all the farms. The resulting net change in total nitrogen emitted, and the change in farm gross margins is used to calculate the individual marginal abatement costs of the farms with a specific geographic reference on the level of electoral districts. The context, in which the abatement costs vary does not only change the absolute values of the costs, but also their relative ranks, and thus the appropriateness of given measures under the circumstances. In order to describe the main determinants of variation in abatement costs, they are analysed in context of geographically varying environmental conditions, water quality metrics and farm characteristics, followed by an analysis of variation within and between electoral districts. These assessments will then drive a discussion on appropriateness of specifically targeted policies, in contrast of undifferentiated, one-size-fits-all schemes. Furthermore, the targeting of policies will also be assessed based on the results of spatial analysis of variation to determine, whether policies targeted on farm specific characteristics, or those targeted geographically, would achieve the targets with higher efficiency. The empirically surveyed farmers’ attitudes to given measures, and thus the likelihood to adopt them with also be included in the final analysis of scenario results.