The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Pollutant routing modeling in agricultural watersheds requires both an accurate hydrological modeling and a water quality monitoring network that captures all the significant sources of variability. However, the latter is often lacking in many areas and the use of complex models usually involves too many parameters, which increases the model uncertainty and makes it impractical to apply. This work proposes a simple parametric approach to model pollutant transfer from soil to runoff and its routing throughout the watershed, based on a GIS physically based hydrological model, and applies it to herbicide routing in two agricultural watersheds in southern Spain. The results show the good performance of this mixed approach to simulate the herbicide daily loads at a control point located upstream a reservoir in the first watershed, where specific sampling work was done to monitor herbicide concentration, with a global error around 11% on a daily basis and 6% for the whole study period (a hydrological year). The applicability of the model under the usually available datasets was confirmed from the results in the second watershed, with higher surface and where no specific sampling was performed and just monthly public dataset were used. The distributed character of the model allows the mapping of the contribution to the pollutant loads within the watershed, and made it possible to identify the most active areas in herbicide transfer to runoff, where mitigation actions should be concentrated. The model constitutes a useful basis to develop further tools for assessing soil and crop management practices in relation to water quality issues.
Inappropriate format for Document type, expected simple value but got array, please use list format