Keywords

database, crop models, climate change, Gibberella zeae, model coupling

Location

Session H5: Systems Modeling and Climate Change: A Systematic Methodology for Disentangling Elements of Vulnerability, Adaptation and Adaptive Capacity

Start Date

16-6-2014 10:40 AM

End Date

16-6-2014 12:00 PM

Description

This paper describes a practical, integrated, web-based and user friendly analysis tool for crop model users that provides quality control of input data, tracks user selections in model parameterization, and enables visual analysis of model outcomes using a single graphical user interface. This allows the user to undertake numerous steps in crop modeling and analysis in a seamless and integrated environment. The analysis and visualization components of the system were enabled utilizing R (pl/r) and the robustness of the underlying data structures and coupling point between crop and disease models were achieved through use of PostgreSQL database management system. The approach was tested to investigate changes in: 1) wheat yield between current climate and plausible future climate in the southern part of Brazil; and 2) climate-related risks such as Fusarium Head Blight (FHB), an important fungal disease that impacts wheat grain yield and quality. The integrative modeling framework (IMF) greatly enabled the assessment of impacts of climate variability/change on wheat. Application results found that wheat yields might benefit from higher rainfall in the projected climate scenario. In contrast, increase of FHB severity should contribute to reduced grain quality.

 
Jun 16th, 10:40 AM Jun 16th, 12:00 PM

An integrative modeling framework to evaluate wheat production systems: Fusarium head blight

Session H5: Systems Modeling and Climate Change: A Systematic Methodology for Disentangling Elements of Vulnerability, Adaptation and Adaptive Capacity

This paper describes a practical, integrated, web-based and user friendly analysis tool for crop model users that provides quality control of input data, tracks user selections in model parameterization, and enables visual analysis of model outcomes using a single graphical user interface. This allows the user to undertake numerous steps in crop modeling and analysis in a seamless and integrated environment. The analysis and visualization components of the system were enabled utilizing R (pl/r) and the robustness of the underlying data structures and coupling point between crop and disease models were achieved through use of PostgreSQL database management system. The approach was tested to investigate changes in: 1) wheat yield between current climate and plausible future climate in the southern part of Brazil; and 2) climate-related risks such as Fusarium Head Blight (FHB), an important fungal disease that impacts wheat grain yield and quality. The integrative modeling framework (IMF) greatly enabled the assessment of impacts of climate variability/change on wheat. Application results found that wheat yields might benefit from higher rainfall in the projected climate scenario. In contrast, increase of FHB severity should contribute to reduced grain quality.