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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Expert knowledge based modeling for integrated water resources planning and management in the Zayandehrud River Basin


This study highlights the need for water resource planning and management using expert knowledge to model known extreme hydrologic variability in complex hydrologic systems with lack of data. The Zayandehrud River Basin in Iran is used as an example of complex water system; this study provides a comprehensive description of the basin, including its water demands (municipal, agricultural, industrial and environmental) and water supply resources (rivers, inter-basin water transfer and aquifers). The objective of this study is to evaluate near future conditions of the basin (from Oct./2015 to Sep./2019) considering the current water management policies and climate change conditions, referred as Baseline scenario. A planning model for the Zayandehrud basin was built to evaluate the Baseline scenario, the period of hydrologic analysis is 21 years, (from Oct./1991 to Sep./2011); it was calibrated for 17 years and validated for 4 years using a Historic scenario that considered historic water supply, infrastructure and hydrologic conditions. Because the Zayandehrud model is a planning model and not a hydrologic model (rainfall runoff model), an Adaptive Network-based Fuzzy Inference System (ANFIS) is used to generate synthetic natural flows considering temperature and precipitation as inputs. This model is an expert knowledge and data based model which has the benefits of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS). Outputs of the ANFIS model were compared to the Historic scenario results and are used in the Baseline scenario. Three metrics are used to evaluate the goodness of fit of the ANFIS model. Water supply results of the Baseline scenario are analyzed using five performance criteria: time-based and volumetric reliability, resilience, vulnerability and maximum deficit. One index, the Water Resources Sustainability Index is used to summarize the performance criteria results and to facilitate comparison among trade-offs. Results for the Baseline scenario show that water demands will be supplied at the cost of depletion of surface and groundwater resource, making this scenario undesirable, unsustainable and with the potential of irreversible negative impact in water sources. Hence, the current water management policy is not viable; there is a need for additional water management policies that reduce water demand through improving irrigation efficiency and reduction of groundwater extraction for sustainable water resources management in the Zayandehrud basin. (C) 2015 Elsevier B.V. All rights reserved.

  • IR
  • US
  • Univ_Calif_Davis (US)
  • Isfahan_Univ_Technol (IR)
Data keywords
  • knowledge
  • knowledge based
Agriculture keywords
  • agriculture
Data topic
  • modeling
  • semantics
Document type

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

Institutions 10 co-publis
  • Univ_Calif_Davis (US)
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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.