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
Spatially distributed assessment of short- and long-term impacts of multiple best management practices in agricultural watersheds
Best management practices (BMPs) are a critical tool for preventing or mitigating the degradation of water quality caused by soil erosion. However, currently available assessment models are primarily designed for use over and, therefore, are only valid over these particular spatial and temporal scales. This study investigates the feasibility of combining three models that were designed for use at different spatial scale into a single assessment toot that allows for more detailed, spatially-explicit assessment of BMPs over both short (four to eight years) and longer (100 year) time scale. The three models evaluated were: 1) the Water Erosion Prediction Project (WEPP) model for hillslope and small watershed Up to 260, ha (642 ac); 2) the Geospatial interface for WEPP (GeoWEPP), which utilizes geographic information system (GIS) or precision farming datasets of topography, soils, and landuse to automatically derive WEPP model input; and 3) a linked GeoWEPP-SWAT model, which injected WEPP model output as point sources into the Soil and Water Assessment Toot (SWAT). The linked GeoWEPP-SWAT model provides a mechanism for applying the WEPP model to larger watershed scales beyond the validity of its channel routing algorithms. This paper summarizes the challenges, validity, and opportunities of this modeling approach for BMP assessment in large watersheds.
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