Groenendijk, P.; Heinen, M.; Klammler, G.; Fank, J.; Kupfersberger, H.; Pisinaras, V.; Gemitzi, A.... (2014). Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data. Science of the Total Environment. 499:463-480. https://doi.org/10.1016/j.scitotenv.2014.07.002
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/61621
Título:
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Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data
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Autor:
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Groenendijk, P.
Heinen, M.
Klammler, G.
Fank, J.
Kupfersberger, H.
Pisinaras, V.
Gemitzi, A.
Peña Haro, Salvador
García Prats, Alberto
Pulido-Velazquez, M.
Perego, A.
Acutis, M.
Trevisan, M
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Entidad UPV:
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Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient
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Fecha difusión:
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Resumen:
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[EN] The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulationmodels provide excellent instruments for researchers to gainmore insight into relevant ...[+]
[EN] The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulationmodels provide excellent instruments for researchers to gainmore insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessmentwas conducted by testing six detailed state-of-the-artmodels for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of themodels: 1) a blind test for 2005 2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009 2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement,model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates.
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Palabras clave:
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Lysimeter
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Model comparison
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Nitrate leaching
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Performance assessment
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Predictive power
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Simulation model
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Derechos de uso:
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Reserva de todos los derechos
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Fuente:
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Science of the Total Environment. (issn:
0048-9697
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DOI:
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10.1016/j.scitotenv.2014.07.002
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Editorial:
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Elsevier
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Versión del editor:
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http://dx.doi.org/10.1016/j.scitotenv.2014.07.002
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Código del Proyecto:
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info:eu-repo/grantAgreement/EC/FP7/226536/EU/Groundwater and dependent Ecosystems: NEw Scientific basIS on climate change and land-use impacts for the update of the EU Groundwater Directive/
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Agradecimientos:
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This research was made possible by the GENESIS project of the EU 7th Framework Programme (Project No. 226536; FP7-ENV-2008-1). We are grateful for the experimental data provided by Joanneum Raum (Graz, Austria). The modelling ...[+]
This research was made possible by the GENESIS project of the EU 7th Framework Programme (Project No. 226536; FP7-ENV-2008-1). We are grateful for the experimental data provided by Joanneum Raum (Graz, Austria). The modelling team of Democritus University of Thrace would like to thank Per-Erik Jansson (Royal Institute of Technology, Stockholm, Sweden) for his valuable help during the application of Coup Model.
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Tipo:
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Artículo
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