Sensitivity Analysis of Soil Parameters in Crop Model Supported with High-Throughput Computing
| Autor: | Anna Petrovskaia, Polina Tregubova, Sergey A. Matveev, Ivan V. Oseledets, Maria Pukalchik, Artyom Nikitin, Mikhail Gasanov |
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| Rok vydání: | 2020 |
| Předmět: |
Topsoil
010504 meteorology & atmospheric sciences biology Crop yield fungi food and beverages Sampling (statistics) Sobol sequence 04 agricultural and veterinary sciences Agricultural engineering biology.organism_classification 01 natural sciences Crop 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Sugar beet High-throughput computing Sensitivity (control systems) 0105 earth and related environmental sciences Mathematics |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030504359 ICCS (7) |
| Popis: | Uncertainty of input parameters in crop models and high costs of their experimental evaluation provide an exciting opportunity for sensitivity analysis, which allows identifying the most significant parameters for different crops. In this research, we perform a sensitivity analysis of soil parameters which play an essential role in plant growth for the MONICA agro-ecosystem model. We utilize Sobol’ sensitivity indices to estimate the importance of main soil parameters for several crop cultures (soybeans, sugar beet and spring barley). High-throughput computing allows us to speed up the computations by more than thirty times and increase the number of sampling points significantly. We identify soil indicators that play an essential role in crop yield productivity and show that their influence is the highest in the topsoil layer. |
| Databáze: | OpenAIRE |
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