e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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.

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Title

Advances in validating SALTIRSOIL at plot scale: First results

en
Abstract

SALTIRSOIL (SALTS in IRrigated SOILs) is a model for the medium to long term simulation of soil salinity in irrigated, well-drained lands. Once the algorithms were verified, the objective of our study was to validate SALTIRSOIL under one of several water quality and management scenarios in Mediterranean agriculture. Because drip and surface are the most common irrigation systems in irrigated agriculture in Valencia (Spain), the validation was performed with climate, soil, irrigation water (composition and management) and crop (species and management) information from an experimental plot surface irrigated with well water and planted with watermelon that has been monitored since the late spring of 2007. To carry out the validation, first we performed a global sensitivity analysis (GSA). Second, we compared simulated soil saturation extract composition against measured data. According to the GSA, SALTIRSOIL calculations of soil salinity seem to be most affected by climate (rainfall and evapotranspiration) with 60% of explained soil salinity variance, water salinity with 26% of explained variance, and then irrigation with 4%. According to the closeness of the first comparisons between predictions and measurements, SALTIRSOIL does not seem to be affected by any systematic error, and as a consequence, neither inclusion of new parameters nor calibration of the others already included would be needed at least for surface irrigation. The validation of SALTIRSOIL continues under other water quality and irrigation management scenarios. (C) 2011 Elsevier Ltd. All rights reserved.

en
Year
2012
en
Country
  • ES
Organization
  • Univ_Valencia_UV (ES)
  • IVIA_Valencian_Inst_Agr_Res (ES)
Data keywords
  • agricultural model
en
Agriculture keywords
  • agriculture
en
Data topic
  • modeling
en
SO
JOURNAL OF ENVIRONMENTAL MANAGEMENT
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
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    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.