title: Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data.
abstract: The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulation models provide excellent instruments for researchers to gain more 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 assessment was conducted by testing six detailed state-of-the-art models 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 the models: 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.
authors.affiliation: Alterra, P.O. Box 47, 6700 AA Wageningen, The Netherlands. Electronic address: piet.groenendijk@wur.nl.
authors.forename: Piet
authors.initials: P
authors.lastname: Groenendijk
authors.affiliation: Alterra, P.O. Box 47, 6700 AA Wageningen, The Netherlands.
authors.forename: Marius
authors.initials: M
authors.lastname: Heinen
authors.affiliation: Joanneum Research, Forschungsgesellschaft mbH, Leonhardstraße 59, 8010 Graz, Austria.
authors.forename: Gernot
authors.initials: G
authors.lastname: Klammler
authors.affiliation: Joanneum Research, Forschungsgesellschaft mbH, Leonhardstraße 59, 8010 Graz, Austria.
authors.forename: Johann
authors.initials: J
authors.lastname: Fank
authors.affiliation: Joanneum Research, Forschungsgesellschaft mbH, Leonhardstraße 59, 8010 Graz, Austria.
authors.forename: Hans
authors.initials: H
authors.lastname: Kupfersberger
authors.affiliation: Democritus University of Thrace, Department of Environmental Engineering, Vas. Sofias 12, Xanthi 67100, Greece.
authors.forename: Vassilios
authors.initials: V
authors.lastname: Pisinaras
authors.affiliation: Democritus University of Thrace, Department of Environmental Engineering, Vas. Sofias 12, Xanthi 67100, Greece.
authors.forename: Alexandra
authors.initials: A
authors.lastname: Gemitzi
authors.affiliation: Institute of Environmental Engineering, ETH Zurich, Wolfgang-Pauli-Str. 15, CH-8093 Zurich, Switzerland.
authors.forename: Salvador
authors.initials: S
authors.lastname: Peña-Haro
authors.affiliation: Universitat Politècnica de València, Department of Hydraulic Engineering and Environment, Camino de Vera, 46022 Valencia, Valencia, Spain.
authors.forename: Alberto
authors.initials: A
authors.lastname: García-Prats
authors.affiliation: Universitat Politècnica de València, Research Institute of Water and Environmental Engineering (IIAMA), Camino de Vera, 46022 Valencia, Valencia, Spain.
authors.forename: Manuel
authors.initials: M
authors.lastname: Pulido-Velazquez
authors.affiliation: University of Milan, Department of Agricultural and Environmental Science, Via G. Celoria 2, 20133 Milan, Italy.
authors.forename: Alessia
authors.initials: A
authors.lastname: Perego
authors.affiliation: University of Milan, Department of Agricultural and Environmental Science, Via G. Celoria 2, 20133 Milan, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Acutis
authors.affiliation: Università Cattolica del Sacro Cuore, sede di Piacenza, Via Emilia Parmense, 84 29100 Piacenza, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Trevisan
mesh_terms: D000383:Agriculture; D001317:Austria; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods*; D005308:Fertilizers / Q000032:analysis* / Q000706:statistics & numerical data; D060587:Groundwater / Q000737:chemistry; D008956:Models, Chemical; D009566:Nitrates / Q000032:analysis*; D009584:Nitrogen / Q000032:analysis; D012987:Soil / Q000737:chemistry*; D012989:Soil Pollutants / Q000032:analysis*
chemical_list: D005308:Fertilizers; D009566:Nitrates; D012987:Soil; D012989:Soil Pollutants; D009584:Nitrogen
keywords: Lysimeter; Model comparison; Nitrate leaching; Performance assessment; Predictive power; Simulation model