Winter oilseed rape (OSR) demands high levels of N fertilizer, often exceeding 200 kg N ha -1 . Large amounts of residual soil mineral nitrogen (SMN) after harvest are regularly observed, and therefore N leaching during the percolation period over winter is increased. In this study agronomic strategies (fertilization level, crop rotation, tillage intensity) to control nitrate leaching after OSR were investigated by combining field measurements (soil mineral nitrogen, soil water content, crop N uptake) of a 2-year trial and another 5-year field trial with simulation modeling. The crop-soil model uses a daily time step and was built from existing and partly refined submodels for soil water dynamics, mineralization processes, and N uptake. It was used to reproduce the complex processes of the N dynamics and to calculate N concentration in the leachate and total volume of percolation water. Some parameters values were thereby newly identified based on the agreement between measured data and model results. Although SMN in the 60-90 cm layer was overestimated, the model could reproduce the measured data with an acceptable degree of accuracy. Overfertilization of OSR increased N leaching and therefore the precise calculation of N fertilizer doses is a first step towards prevent N leaching. Compared to ploughing, minimum tillage decreased N leaching when winter wheat was grown as the subsequent crop. Volunteer OSR and Phacelia tanacetifolia were grown as catch crops after OSR harvest. N leaching could be decreased especially when Phacelia was grown, but nitrate concentrations in the drainage water were higher and exceeded the European Union (EU) threshold for drinking water when volunteer OSR was grown. The results of this study provide strong evidence that reduced tillage or growing of noncruciferous catch crops decrease N leaching and may be used as an agricultural measure to prevent N pollution.

Abstract:Crop system models are generally parametrized with daily air temperatures recorded at 1.5 or 2 m height. These data are not able to represent temperatures at the canopy level, which control crop growth, and the impact of heat stress on crop yield, which are modified by canopy characteristics and plant physiological processes Since such data are often not available and current simulation approaches are complex and/or based on unrealistic assumptions, new methods for integrating canopy temperatures in the framework of crop system models are needed. Based on a forward stepwise-based model selection procedure and quantile regression analyses, we developed empirical regression models to predict winter wheat canopy temperatures obtained from thermal infrared observations performed during four growing seasons for three irrigation levels. We used daily meteorological variables and the daily output data of a crop system model as covariates. The standard cross validation revealed a root mean square error (RMSE) of~0.8˝C, 1.5-2˝C and 0.8-1.2˝C for estimating mean, maximum and minimum canopy temperature, respectively. Canopy temperature of both water-deficit and fully irrigated wheat plots significantly differed from air temperature. We suggest using locally calibrated empirical regression models of canopy temperature as a simple approach for including potentially amplifying or mitigating microclimatic effects on plant response to temperature stress in crop system models.

We investigated the leaf : stem partitioning of winter wheat (Triticum aestivum L. varieties 'Dekan' and 'Batis') with and without drought influence. Irrigated and drought-stressed winter wheat, grown in a rainout shelter in 2009/10 and 2013/14, were sampled during shoot elongation phase at the experimental Farm Hohenschulen located in Northern Germany. The data set contains leaf (DM L ) and stem dry masses (DM S ), as well as measured water contents for several soil layers. A reduced relative dry matter allocation to leaves was observed under drought stress. Our results clearly show that, if simulated leaf : stem partitioning is not sensitive to drought, this will cause a positive bias in simulated leaf and a negative bias in simulated stem dry matter under water-limited conditions. This is in accordance with previous studies which revealed that crop simulators often overestimate the impact of drought on light-use efficiency, whereas the consequences on leaf area development are underestimated. However, the drought stress-induced shift in leaf : stem partitioning is yet not considered by most common wheat crop simulators. Our aim was to fill the gap in simulation of drought stress implications on leaf area development. A simple allometric model for leaf : stem partitioning (InðDM S Þ ¼ g Á InðDM L Þ þ h) was parameterized. Starting from the allometric leaf : stem relationship observed under optimum water supply, a correction term was introduced, which allows to adapt the partitioning to drought stress conditions. The lg-transformed root-weighted soil water potential in the rooting zone (lgw root , lg(hPa)), calculated as a function of measured water contents and simulated root distribution, was used as a drought stress indicator. The linear correction term assumes an increase of the stem fraction, proportional to the difference between lgw root and a drought stress threshold (pF crit , lg(hPa)). The analysis revealed that the shift in allometric partitioning towards stem fraction starts with lgw root greater than 1.92 [lg (hPa)]. The slope of the relative increase of dry matter allocated to the stem fraction was determined with 0.26 [lg(hPa) À1 ]. Both parameters of the correction term were found to be highly significant. Implications for crop modelling are discussed.

An accurate estimation of stomatal resistance (r S ) also under drought stress conditions is of pivotal importance for any process-based prediction of transpiration and the energy budget of real crop canopies and quantification of drought stress. A new model for r S was developed and parameterized for winter wheat using data from field experiments accounting for the influences of net radiation (R Net ), air temperature (T Air ) and vapour pressure deficit of the atmosphere (VPD) interacting with an average water potential in the rooted soil (w RootedSoil ). r S is simulated with a limiting factor approach as maximum of the metabolic (related to photosynthesis) and hydraulic (related to drought stress) acting influences assuming that, if drought stress occurs, it will dominate stomatal control: r S = max (r S (T Air ), r S (R Net ), r S (VPD, w RootedSoil )). This transitional approach is suited to reproduce measured daily time courses of r S with a varying accuracy for the single measurement dates but performed satisfactorily for the whole data set (r 2 = 0.63, RMSE = 59 s m À1 , EF = 0.60). This new semi-empiric approach calculates r S directly from external environmental conditions. Therefore, it can be easily implemented in existing model frameworks as link between operational crop growth models that use the concept of radiation use efficiency instead of mechanistic photosynthesis modelling and soil-vegetation-atmosphere transport models.

No abstract