Abstract
A six-year (1993-1998) multivariable data set for a four-plot intensive crop rotation (sugar beet - winter wheat - winter barley - winter rye - catch crop) located at Leibniz Centre for Agricultural Landscape Research (ZALF) Experimental Station, Muncheberg, Germany, is documented in detail. The experiment targets crop response to water supply on sandy soils (Eutric Cambisol), applying rain-fed and irrigated treatments. Weather as well as soil and crop processes were intensively monitored and management actions were consistently recorded. The data set contains coherent data for soil (water, nitrogen contents), crop (ontogenesis, plant, tiller and ear numbers, above-ground and root biomasses, yield, carbon and nitrogen content in biomass and their fractions, sugar content in beet), weather (all standard meteorological variables) and management (soil tillage, sowing, fertilisation, irrigation, harvest). In addition, observation methods are briefly described. The data set is available via the Open Research Data Portal at ZALF Muncheberg and is published under doi:10.4228/ZALF.1992.271. The data set was used for model intercomparison within the crop modelling part (CropM) of the international FACCE MACSUR project. Data access via DOI 10.4228/ZALF.1992.271.
Highlights
At present, land use and climate changes act continuously on agricultural landscapes
It is impossible to perform scenario simulations for arable land without well-parameterised agro-ecosystem models; in turn, good model parameterisation is only possible on the basis of coherent data sets generated from well-designed field or climate chamber experiments
The experiment is targeted towards the production of coherent data sets for agro-ecosystem model parameterisation and validation, which represent different management intensities and inter-annual variations in crop rotations under rain-fed and irrigated conditions
Summary
Land use and climate changes act continuously on agricultural landscapes. A wide variety of these models exist, such as APSIM (Holzworth et al 2015), STICS (Brisson et al, 2003), Daisy (Hansen et al, 2001), CROPSYST (Stöckle et al, 2003) and DSSAT (Jones et al, 2003) Such models require a wide base of experimental data for model parameterisation and model evaluation, including soil, crop, weather/climate and management data (Kersebaum et al 2015). It is impossible to perform scenario simulations for arable land without well-parameterised agro-ecosystem models; in turn, good model parameterisation is only possible on the basis of coherent data sets generated from well-designed field or climate chamber experiments. The experiment is targeted towards the production of coherent data sets for agro-ecosystem model parameterisation and validation, which represent different management intensities and inter-annual variations in crop rotations under rain-fed and irrigated conditions. The data set is one of five currently being used within a pan-European study (Kollas et al, 2015), a joint activity within the crop modelling part of the European JPI FACCE knowledge hub MACSUR: https://www.faccejpi.com/FACCE-Joint-activities/FACCE-MACSUR
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