Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelado de Intercepción de Dosel× | Modelo de Crecimiento de Cultivos (DSSAT/APSIM)× | |
|---|---|---|
| Campo | Agronomía | Agronomía |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1971–1979 (foundational models; continuous development since) | 1993-2003 |
| Autor original≠ | Multiple contributors (Rutter et al. 1971; Gash 1979 for principal analytical frameworks) | James W. Jones, Gerbrand T. Hoogenboom (DSSAT); Brian A. Keating, Peter S. Carberry (APSIM) |
| Tipo≠ | Process-based hydrological model | Mechanistic crop simulation pipeline |
| Fuente seminal≠ | Rutter, A. J., Kershaw, K. A., Robins, P. C., & Morton, A. J. (1971). A predictive model of rainfall interception in forests. Agricultural Meteorology, 9, 367–384. link ↗ | Jones, J. W., Hoogenboom, G., Porter, C. H., et al. (2003). The DSSAT cropping system model. European Journal of Agronomy, 18(3-4), 235-265. DOI ↗ |
| Alias≠ | interception loss modeling, canopy rainfall partitioning, forest interception modeling, throughfall-stemflow modeling | DSSAT, APSIM, Crop Simulation Model |
| Relacionados≠ | 0 | 3 |
| Resumen≠ | Canopy interception modeling quantifies the fraction of rainfall captured by plant canopies and subsequently evaporated back to the atmosphere before reaching the soil. Applied across agronomy, forestry, and hydrology, it partitions gross precipitation into throughfall, stemflow, and interception loss. By linking vegetation structure — particularly leaf area index and canopy storage capacity — to water balance components, the method informs irrigation scheduling, watershed management, and crop water-use estimation. | Crop growth models are mechanistic simulation systems designed to predict crop development, biomass accumulation, and yield under varying environmental and management conditions. DSSAT (Decision Support System for Agrotechnology Transfer) and APSIM (Agricultural Production Systems Simulator) are the most widely used platforms, developed in the 1990s-2000s to support agronomic decision-making and climate adaptation research. |
| ScholarGateConjunto de datos ↗ |
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