The aim of this project is to further develop the e-infrastructure for crop system modelling and crop yield forecast by contributing to relevant global initiatives such as the Agricultural Model Intercomparison Project (AgMIP) and the Global Yield Gap Atlas (GYGA).
In these projects through model intercomparison, model application, data base development, data schematization and rich client interface development, relevant steps in IT will be made to realize an advanced e-infrastructure for crop growth modelling and forecasting supported by a global community.
A generic data model STAC has been developed to store agronomy related data in a very generic, powerful yet simple way. Loading and storage of public weather data has been implemented and is used to generate crop model (WOFOST) input weather files. A start has been made to store and open in-situ data collected in within the GEO-GLAM initiative.
The Global Yield Gap Atlas portal and web map viewer was designed and constructed (www.yieldgap.org) giving access to underpinning data, methodology and protocols and yield gap data for cereals at different spatial levels.
ESG participated in the inter-comparison of crop models around grain maize. A large number of base, scenario and sensitivity runs were conducted for 4 different sites (USA, Tanzania, France, Brazil) to explore the behaviour of WOFOST under different scenarios of temperature and rainfall.
A generic data schema for crop experiment data in food security research
In: Proceedings of the sixth biannial meeting of the International Environmental Modelling and Software Society. - Leipzig - ISBN 9788890357428 - p. 2447 - 2454.
A regional implementation of WOFOST for calculating yield gaps of autumn-sown wheat across the European Union
A regional implementation of WOFOST for calculating yield gaps of winter wheat across the European Union
Field Crops Research 143 (2013). - ISSN 0378-4290 - p. 130 - 142.
Climate Zonations As Extrapolation Domains for Yield Gap Assessments
Crop modelling for integrated assessment of risk to food production from climate change
Environmental Modelling & Software 72 (2015). - ISSN 1364-8152 - p. 287 - 303.
Global yield gap atlas to identify options for sustainable intensification
How do various maize crop models vary in their responses to climate change factors?
Global Change Biology 20 (2014)7. - ISSN 1354-1013 - p. 2301 - 2320.
Open data at Wageningen UR and its cooperation with international partners: From institutional to operational to future-oriented
Putting it all together: Functionality of the Global Yield Gap Atlas Website
Soil Data for Yield Gap Assessment and Soil Suitability Index for Sustainable Intensification