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
This paper addresses the impact of climate change on the volume of inflow to a reservoir and the volume of downstream water demand by considering three climate change scenarios in an East Azerbaijan river basin. The HadCM3 model was used to estimate possible scenarios of temperature and rainfall for the period 2026-2039 under an emission scenario (A2). A hydrological model (IHACRES) was first calibrated for the basin; and then, a monthly time series of future temperatures and rainfall were entered into IHACRES. In addition, a 14-year time series of monthly runoff was simulated for 2026-2039. Modeling results indicated that the average long-term annual runoff volume decreased by 0.7% relative to the base period (1987-2000). However, by assuming a nonchanging cultivation area, the average long-term annual water demand volume for crops increased by 16%. Both simulation and optimization models of reservoir operation were used. The simulation of reservoir performance in the delivery of water demand was implemented according to the standard operating policy (SOP) and by using the water evaluation and planning (WEAP) model. The three aforementioned climate change scenarios were then introduced to the WEAP, and the reservoir performance indexes (reliability, vulnerability, and resiliency) were calculated. Results showed that indexes would change in the future relative to the base. Next, for the optimal operation of the reservoir with a water supply for agricultural and environmental purposes, the minimization of total squared deficiencies in the allocation to these purposes was determined for each month and climate change scenario by the using LINGO Version 11.0 software [nonlinear programming (NLP)] algorithm. Results showed that the indexes would change. DOI: 10.1061/(ASCE)IR.1943-4774.0000496. (C) 2013 American Society of Civil Engineers.
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