Conceptual development of a harmonised method for tracking change and evaluating policy in the agri-environment: The Agri-environmental Footprint Index

An aggregated farm-level index, the Agri-environmental Footprint Index (AFI), based on multiple criteria methods and representing a harmonised approach to evaluation of EU agri-environmental schemes is described. The Index uses a common framework for the design and evaluation of policy that can be customised to locally relevant agri-environmental issues and circumstances. Evaluation can be strictly policy-focused, or broader and more holistic in that context-relevant assessment criteria that are not necessarily considered in the evaluated policy can nevertheless be incorporated. The Index structure is flexible, and can respond to diverse local needs. The process of Index construction is interactive, engaging farmers and other relevant stakeholders in a transparent decision-making process that can ensure acceptance of the outcome, help to forge an improved understanding of local agri-environmental priorities and potentially increase awareness of the critical role of farmers in environmental management. The structure of the AFI facilitates post-evaluation analysis of relative performance in different dimensions of the agri-environment, permitting identification of current strengths and weaknesses, and enabling future improvement in policy design. Quantification of the environmental impact of agriculture beyond the stated aims of policy using an ‘unweighted’ form of the AFI has potential as the basis of an ongoing system of environmental audit within a specified agricultural context.     

Analysing Seasonal Differences between a Soil Water Balance Model and in Situ Soil Moisture Measurementsat Nine Locations Across Europe

We compared soil moisture from the soil water balance model for European Water Accounting (swbEWA) with in situ observations from nine locations in three European climatic zones (continental, Mediterranean and maritime temperate), for different periods between 2003 and 2011. Despite the simplicity of the swbEWA model, the patterns of temporal changes in soil moisture content are well represented at all locations. Annual averages show that the model overestimates the soil moisture content, and that overestimations are the smallest when measurements are obtained from more than one depth. These results suggest that the relationship between simulated and observed soil moisture also depends on the number of measurements and the depth over which they are taken. In the continental climate, where snow cover and frozen soil influence soil moisture, we observe higher root mean square error values in winter months. However, in the Mediterranean and maritime temperate climates, we do not observe clear common seasonal patterns in the soil moisture profile, which makes it difficult to relate the model’s accuracy to climate. With the percentage of correctness and probability of detection measures, we tested the model performance in simulating dry versus non-dry events. The percentage of the correctly classified dry and non-dry events is higher than 84 % at all locations, whereas the probability to detect dry events is significantly lower, exceeding 50 % at only four out of nine stations. The frequency distribution of consecutive days with dry soil (CDDS) confirms the model performance: higher number of short dry periods (with less than 20 days of soil moisture near wilting point) are reproduced and observed in continental climates, whereas long dry periods (longer than 50 days) are noted in the Mediterranean climate. Overall, the statistical measures suggest that the model produces the highest accuracy in summer months at the stations in continental climates, whereas in the Mediterranean climate, the accuracy is slightly higher in the colder seasons.