BACKGROUND

Agriculture is by far the largest consumer of water, with about 70% of the diverted water being used in irrigation (UNESCO, 2015). Agriculture is also considered as a key source of diffuse pollution with inefficient practices resulting in high water and nutrient (particularly N and P) surpluses that are transferred to water bodies through diffuse processes (runoff and leaching), promoting eutrophication, with associated biodiversity loss.

Farmers deal with water at the plot and seasonal scale, adopting strategies that best suit their minds, hoping to maximize yields. Farmers’ perception of resulting environmental effects is not always easy as they usually happen further downstream, creating a gap between causes and consequences, and difficulties to Water Agencies that have to manage and protect water resources while considering its availability, multiple uses, and quality.

While the connection between plot and catchment scales is clear, the need to address them using the same tools usually only gets evident when water pollution becomes an issue and/or during periods of scarcity. Detailed information from field plots is scarce, making it difficult to establish a direct link between water quality and specific agricultural practices. This difficulty is enhanced by the time scale of the transport of a pollutant from the agricultural fields down to the water reservoirs where problems are usually detected first. This limitation only further highlights the need for an integrative modeling approach, capable of considering the different spatial and temporal scales occurring in a catchment.

The project combines the most performant monitoring strategies at the plot scale to provide detailed information of water and nutrient flow, and integrates this information at the catchment scale to close the gap between diffuse loads and water quality degradation. The project builds on three basic statements (1) diffuse agriculture pollution is an extra cost for farmers that needs to be minimized; (2) plot scale monitoring can be achieved using low cost sensors and remote sensing; and (3) models are the interdisciplinary tools required to optimise irrigation and fertilization practices and to link spatial and temporal scales.

Using the Integrated Water Resources Management perspective, the project contributes directly to the implementation of the Nitrates Directive and of the Water Framework Directive and indirectly to the implementation of the Wastewater Treatment Directive.