Published in

American Geophysical Union, Earth Interactions, 12(16), p. 1-15, 2012

DOI: 10.1175/2012ei000452.1

Links

Tools

Export citation

Search in Google Scholar

Evaluation of a Dynamic Agroecosystem Model (Agro-IBIS) for Soybean in Southern Brazil

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Orange circle
Published version: archiving restricted
Data provided by SHERPA/RoMEO

Abstract

Abstract With the growing demands for food and biofuel, new technologies and crop management systems are being used to increase productivity and minimize land-use impacts. In this context, estimates of productivity and the impacts of agriculture management practices are becoming increasingly important. Numerical models that describe the soil–surface–atmosphere interactions for natural and agricultural ecosystems are important tools to explore the impacts of these agronomical technologies and their environmental impacts. However, these models need to be validated by considering the different soil and environmental conditions before they can be widely applied. The process-based terrestrial agricultural version of the Integrated Biosphere Simulator (IBIS) model (Agro-IBIS) has only been calibrated and validated for North American sites. Here, the authors validate the Agro-IBIS results for an experimental soybean site in southern Brazil. At this site, soybean was grown under two different management systems: no tillage (NT) and conventional tillage (CT). The model results were evaluated against micrometeorological, soil condition, and biomass observations made during the soybean growing season. The leaf area index (LAI) was underestimated, approaching the values obtained in the CT crop system, with higher error in the leaf senescence period. The model shows higher skill for daily averages and the diurnal cycle of the energy balance components in the period of high LAI. The soil temperature and moisture were robustly simulated, although the latter is best correlated with the observations made at the CT field. The ecosystem respiration is highly underestimated, causing an overestimation of the cumulative net ecosystem exchange (NEE), particularly at the end of the crop cycle.