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[Validation of the ALMANAC model with different spatial scale].
Yun Xie1, Kiniry James, Baoyuan Liu
1Department of Resource and Environmental Sciences, Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education of China, Beijing Normal University, Beijing 100875, China. xieyun@bnu.edu.cn
Ying Yong Sheng Tai Xue Bao = the Journal of Applied Ecology
|December 6, 2003
Summary
The ALMANAC model accurately simulates maize and sorghum yields at both plot and county scales, even under drought conditions. This validation extends its use for agricultural predictions in similar climates.
Area of Science:
- Agricultural modeling
- Agronomy
- Climate impact assessment
Context:
- Crop simulation models are crucial for agricultural planning and yield prediction.
- Validating models like ALMANAC under diverse conditions, including drought, is essential for reliable forecasting.
- Texas experienced drought-stressed periods, providing a critical test case for the ALMANAC model.
Purpose:
- To validate the Agricultural Multipurpose Applications (ALMANAC) model's performance in simulating maize and sorghum yields.
- To assess the model's accuracy across different spatial scales (plot vs. county) and climatic conditions.
- To determine the ALMANAC model's suitability for long-term yield prediction and its applicability in similar climatic regions.
Summary:
- The ALMANAC model was validated using data from Texas, including a drought year and a 1989-1998 period, across multiple sites and counties for maize and sorghum.
- The model demonstrated comparable accuracy in simulating yields at both plot and county levels, with mean errors of 8.9% for sorghum and 9.4% for maize at field scale, and 2.6% for maize and -0.6% for sorghum at county level.
- ALMANAC successfully simulated single-year yields under water-limited conditions and showed low coefficient of variation for long-term predictions, indicating its robustness.
Impact:
- The study provides validated soil, weather, and crop parameter datasets that can guide the application of the ALMANAC model in similar agricultural and climatic settings.
- The findings support the use of the ALMANAC model for more accurate agricultural yield forecasting, particularly in regions prone to water-limited conditions.
- This research enhances the utility of crop simulation models for farmers and researchers, aiding in better agricultural management decisions and risk assessment.