Evaluation of Multiple Approaches to Estimate Daily Solar Radiation for Input to Crop Process Models

Daily solar radiation is a critical input for estimating plant growth and development, yet this variable is infrequently measured compared to other climate variables. This study evaluates the sensitivity of simulated maize and soybean production from the CERES-Maize and CROPGRO-Soybean modules of the Decision Support System for Agrotechnology Transfer (DSSAT) to daily solar radiation estimates obtained from traditional (stochastic, empirical, and mechanistic models) and non-traditional (satellite estimation, reanalysis datasets, and regional climate model simulations) approaches, using as an example radiation estimates for Hancock, Wisconsin, USA. When compared to observations, radiation estimates obtained from empirical and mechanistic models and a satellite-based dataset generally had smaller biases than other approaches. Daily solar radiation estimates from a reanalysis dataset and regional climate model simulations overestimate incoming daily solar radiation. When the radiation estimates were used as an input to CERES-Maize, no significant differences were found for maize yield obtained from the different radiation estimates compared to yield from observed radiation, even though differences were found in the daily values of leaf area index, crop evapotranspiration, and crop dry weight (biomass). In contrast, significant differences were found in simulated soybean yield from CROPGRO-Soybean for the majority of the radiation estimates.

Estimation of enteric methane emissions trends (1990–2008) from Manitoba beef cattle using empirical and mechanistic models

Alemu, A. W., Ominski, K. H. and Kebreab, E. 2011. Estimation of enteric methane emissions trends (1990–2008) from Manitoba beef cattle using empirical and mechanistic models. Can. J. Anim. Sci. 91: 305–321. The objective of this study was to estimate and assess trends in enteric methane (CH4) emissions from the Manitoba beef cattle population from the base year of 1990 to 2008 using mathematical models. Two empirical (statistical) models: Intergovernmental Panel on Climate Change (IPCC) Tier 2 and a nonlinear equation (Ellis), and two dynamic mechanistic models: MOLLY (v3) and COWPOLL were used. Beef cattle in Manitoba were categorized in to 29 distinct subcategories based on management practice, physiological status, gender, age and production environment. Data on animal performance, feeding and management practices and feed composition were collected from the literature as well as from provincial and national sources. Estimates of total enteric CH4 production from the Manitoba beef cattle population varied between 0.9 and 2.4 Mt CO2 eq. from 1990 to 2008. Regardless of the type of models used, average CH4 emissions for 2008 were estimated to be 45.2% higher than 1990 levels. More specifically, CH4 emissions tended to increase between 1990 and 1996. Emissions were relatively stable between 1996 and 2002, increased between 2003 and 2005, but declined by 13.2% between 2005 and 2008, following the same trend as that observed in the beef cattle population. Models varied in their estimates of CH4 conversion rate (Ym, percent gross energy intake), emission factor (kg CH4 head−1 yr−1) and CH4 production. Total CH4 production estimates ranged from 1.2 to 2.0 Mt CO2 eq. for IPCC Tier 2, from 0.9 to 1.5 Mt CO2 eq. for Ellis, from 1.3 to 2.1 Mt CO2 eq. for COWPOLL and from 1.5 to 2.4 Mt CO2 eq. for MOLLY. The results indicate that enteric CH4 estimates and emission trends in Manitoba were influenced by the type of model and beef cattle population. As such, it is necessary to use appropriate models for reliable estimates for enteric CH4 inventory. A more robust approach may be to integrate different models by using mechanistic models to estimate regional Ym values, which may then be used as input for the IPCC Tier 2 model.