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Resumen
Biophysical simulation models can help to satisfactorily estimate the crop performance for grain production, their stability across years and their impact on components of hydrological balance in diverse areas once those models have been calibrated and validated with field data. The Inner Argentinian Pampas (IAP) region is very susceptible to both frequent flooding and random droughts due to flat landscape, sub-humid to semi-arid climate, coarse- textured [ver mas...]
dc.contributor.authorVidela Mensegue, Horacio Rogelio
dc.contributor.authorCaviglia, Octavio
dc.contributor.authorDegioanni, Américo José
dc.contributor.authorMarcos, J.
dc.contributor.authorBonadeo, E.
dc.date.accessioned2021-03-09T14:55:13Z
dc.date.available2021-03-09T14:55:13Z
dc.date.issued2021-02
dc.identifier.issn0168-1699
dc.identifier.otherhttps://doi.org/10.1016/j.compag.2020.105892
dc.identifier.urihttp://hdl.handle.net/20.500.12123/8851
dc.identifier.urihttps://www.sciencedirect.com/science/article/abs/pii/S0168169920330970
dc.description.abstractBiophysical simulation models can help to satisfactorily estimate the crop performance for grain production, their stability across years and their impact on components of hydrological balance in diverse areas once those models have been calibrated and validated with field data. The Inner Argentinian Pampas (IAP) region is very susceptible to both frequent flooding and random droughts due to flat landscape, sub-humid to semi-arid climate, coarse- textured soils and shallow water tables. The Soil Water Balance (SWB) model appears to be suitable for the IAP region since it includes most of the necessary requirements for the particular conditions of such an environment. The objectives of this study were: i) to identify the most sensitive crop parameters of the SWB model for a satisfactory estimation of aerial biomass, grain yield and crop evapotranspiration in the IAP region; ii) to parameterise and calibrate the SWB model for simulation of aerial biomass, grain yield and crop evapotranspiration of wheat (Triticum aestivum L.), soybean [Glycine max L. (Merr.)] and maize (Zea mays L.); iii) to validate the SWB model using an independent dataset over a wide area in the IAP region. We used data from 9 field experiments for calibration and from 116 field experiments for validation. The most critical parameters, as indicated by a sensitivity analysis, were biomass-transpiration coefficient (Kb), radiation use efficiency (e), and extinction coefficient (k), suggesting that they should be locally obtained before promoting the use of the SWB model in a given region. The SWB model, after calibration, was able to accurately estimate crop aerial biomass (d = 0.97–0.99, GSD = 9.5–23.9% and RMSE = 786–2,438 kg ha−1), grain yield (d = 0.95–0.96, GSD = 4.5–10.7% and RMSE = 357–637 kg ha−1), crop evapotranspiration (d = 0.97–0.99; GSD = 8.1–16.1%, RMSE = 17–51 mm) and soil water content (d = 0.87–0.96, GSD = 11.2–15.5% and RMSE = 9.6–13.2 mm). The robustness to estimate water balance, aerial biomass and grain yield fluctuations for wheat, soybean, and maize across different soil textures and rainfall variability reflects the potential of SWB model as a valuable tool to face the main challenges of the agricultural systems in our region.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.relationinfo:eu-repograntAgreement/INTA/2019-PE-E1-I011-001/2019-PE-E1-I011-001/AR./Intensificacion Sustentable de la Agricultura en la Region Pampeanaes_AR
dc.relationinfo:eu-repograntAgreement/INTA/2019-PE-E2-I041-001/2019-PE-E2-I041-001/AR./Aportes para la gestión integrada de los recursos hídricos (GIRH) en cuencas del Sistema Agroalimentario Argentinoes_AR
dc.relationinfo:eu-repograntAgreement/INTA/2019-PE-E2-I042-001/2019-PE-E2-I042-001/AR./Uso y gestión eficiente del Agua en Sistemas de Secanoes_AR
dc.relationinfo:eu-repograntAgreement/INTA/2019-PD-E2-I044-001/2019-PD-E2-I044-001/AR./Interacción de agroecosistemas y napas freáticas: innovaciones tecnológicas y organizacionales para su manejo a diferentes escalas.es_AR
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.sourceComputers and Electronics in Agriculture 181 : 105892 (February 2021)es_AR
dc.subjectUso del Aguaes_AR
dc.subjectWater Useeng
dc.subjectBalance Hídrico del Sueloes_AR
dc.subjectSoil Water Balanceeng
dc.subjectModeloses_AR
dc.subjectModelseng
dc.subjectCultivoses_AR
dc.subjectCropseng
dc.subject.otherRegión Pampeanaes_AR
dc.titleCalibration and validation of soil water balance (SWB) model in the Inner Argentinian Pampases_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.description.filFil: Videla Mensegue, Horacio Rogelio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Laboulaye; Argentinaes_AR
dc.description.filFil: Caviglia, Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentinaes_AR
dc.description.filFil: Degioanni, Américo José. Universidad Nacional Río Cuarto, Facultad de Agronomía y Veterinaria. Departamento de Ecología Agraria; Argentinaes_AR
dc.description.filFil: Marcos, J. Investigador jubilado; Argentinaes_AR
dc.description.filFil: Bonadeo, E. Universidad Nacional Río Cuarto, Facultad de Agronomía y Veterinaria. Departamento de Ecología Agraria; Argentinaes_AR
dc.subtypecientifico


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