Comparison of site sensitivity of crop models using spatially variable field data from Precision Agriculture

Site conditions and soil properties have a strong influence on impacts of climate change on crop production. Vulnerability of crop production to changing climate conditions is highly determined by the ability of the site to buffer periods of adverse climatic situations like water scarcity or excessive rainfall.  Therefore, the capability of models to reflect crop responses and water and nutrient dynamics under different site conditions is essential to assess climate impact even on a regional scale. To test and improve sensitivity of models to various site properties such as soil variability and hydrological boundary conditions, spatial variable data sets from precision farming of two fields in Germany and Italy were provided to modellers. For the German 20 ha field soil and management data for 60 grid points for 3 years (2 years wheat, 1 year triticale) were provided. For the Italian field (12 ha) information for 100 grid points were available for three growing seasons of durum wheat. Modellers were asked to run their models using a) the model specific procedure to estimate soil hydraulic properties from texture using their standard procedure and use in step b) fixed values for field capacity and wilting point derived from soil taxonomy. Only the phenology and crop yield of one grid point provided for a basic calibration. In step c) information for all grid points of the first year (yield, soil water and mineral N content for Germany, yield, biomass and LAI for Italy) were provided. First results of five out of twelve participating models are compared against measured state variables analysing their site specific response and consistency across crop and soil variables.(Main text to be published in a peer-reviewed journal

Comparison of site sensitivity of crop models using spatially variable field data from Precision Agriculture

Site conditions and soil properties have a strong influence on impacts of climate change on crop production. Vulnerability of crop production to changing climate conditions is highly determined by the ability of the site to buffer periods of adverse climatic situations like water scarcity or excessive rainfall.  Therefore, the capability of models to reflect crop responses and water and nutrient dynamics under different site conditions is essential to assess climate impact even on a regional scale. To test and improve sensitivity of models to various site properties such as soil variability and hydrological boundary conditions, spatial variable data sets from precision farming of two fields in Germany and Italy were provided to modellers. For the German 20 ha field soil and management data for 60 grid points for 3 years (2 years wheat, 1 year triticale) were provided. For the Italian field (12 ha) information for 100 grid points were available for three growing seasons of durum wheat. Modellers were asked to run their models using a) the model specific procedure to estimate soil hydraulic properties from texture using their standard procedure and use in step b) fixed values for field capacity and wilting point derived from soil taxonomy. Only the phenology and crop yield of one grid point provided for a basic calibration. In step c) information for all grid points of the first year (yield, soil water and mineral N content for Germany, yield, biomass and LAI for Italy) were provided. First results of five out of twelve participating models are compared against measured state variables analysing their site specific response and consistency across crop and soil variables.(Main text to be published in a peer-reviewed journal

The chaos in calibrating crop models

Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of system models and has an important impact on simulated values. Here we propose and illustrate a novel method of developing guidelines for calibration of system models. Our example is calibration of the phenology component of crop models. The approach is based on a multi-model study, where all teams are provided with the same data and asked to return simulations for the same conditions. All teams are asked to document in detail their calibration approach, including choices with respect to criteria for best parameters, choice of parameters to estimate and software. Based on an analysis of the advantages and disadvantages of the various choices, we propose calibration recommendations that cover a comprehensive list of decisions and that are based on actual practices.HighlightsWe propose a new approach to deriving calibration recommendations for system modelsApproach is based on analyzing calibration in multi-model simulation exercisesResulting recommendations are holistic and anchored in actual practiceWe apply the approach to calibration of crop models used to simulate phenologyRecommendations concern: objective function, parameters to estimate, software usedCompeting Interest StatementThe authors have declared no competing interest

Validation of regionalized soil information of forest soils by examining site specific growth performance of Scots pine in Brandenburg

Für die Inventurpunkte der zweiten Bundeswaldinventur (BWI2) im Land Brandenburg liegen umfangreiche Bodenund Standortsinformationen vor, die zum einen direkt aus der Bodenzustandserhebung (BZE) stammen und zum anderen mit Hilfe eines ausgewählten Regionalisierungsansatzes generiert wurden. Es erfolgt eine Verknüpfung der Bestandes- und Bodendaten und eine stichprobenbezogene Modellierung der Standorts-Leistungs-Beziehung für die Baumart Kiefer unter Berücksichtigung des Bestandesalters. Die in unterschiedlichen Teilkollektiven ermittelten Regressionsmodelle liefern bei einem R2-Wert von 0,56 identische Einflussgrößen (Nährkraft, Verdunstung) und vergleichbare Parameterkoeffizienten für die Zielgröße der absoluten Höhenbonität. Im Hinblick auf die Bonitäts-Alters-Beziehung ergibt sich aufgrund allgemein verbesserter Standortsbedingungen ein Vorteil der Jungbestände gegenüber den Altbeständen. Dieser Effekt ist umso stärker, je geringer die Stammnährkraft an einem Standort ist.Extensive soil and site information exist for the inventory plots of the national forest inventory (2002) in the federal state of Brandenburg. That information originates firstly from the forest soil condition inventory (BZE) and, secondly, from a determined regionalization approach. After connection of soil and stock data at the inventory plots, sample related regression models allow the definition of site related growth of Scots pine in consideration of stock age and, hence, a validation of regionalized soil information. The regression models perform with a similar R2-value of 0.56 and define identical impact variables (nutritional state, evapotranspiration) and coefficients estimation the stand top height. Regarding the relation between stock age and growth performance of Scots pine, the impact of anthropogenic caused site improvement becomes visible, as young stocks show better performance than old ones. This advantage increases with decreasing nutrient state

Comparison of plant proximal sensing approaches for nitrogen supply detection in crops

Nondestructive proximal sensors can be an efficient source of information of N status in crops for localized and rapid adjustment of fertilization applications. The aim of this study was to compare two transmittance/reflectance-based sensors (SPAD, ASD) and a florescence-based sensor (Multiplex) in their ability to measure N content in corn (Zea mays L.), spring and winter barley (Hordeum vulgare L.), and rye (Secale cereale L.), both at the leaf and canopy level. Measurements of leaves and canopies from six fertilization field trials in 2019 and 2020 were analyzed to establish relationships between sensor information and laboratory-determined N content in crops. Analyses included linear regression for single sensor variables and machine learning for multivariate approaches, to assess the relative accuracy of the proximal sensors to measure N. The ASD is time-intensive and requires post hoc analyses of the spectra. However, the spectral outputs of this device were clearly correlated with the N status of leaves and canopies. At the leaf level, SPAD showed higher accuracy than any of the single Multiplex variables to predict plant N. Multiplex performance could be improved by combining three of its variables. At the canopy level, interpolated SPAD values and the best-performing Multiplex variables showed similar accuracy. It could be concluded that the relationship sensor-N status is species specific. Despite the high standard deviation recorded in some raw Multiplex variable, the derived indices showed a comparable low standard deviation. At both, leaf and canopy levels an integrated sensor solution would combine the multidimensionality of Multiplex and ASD, and the accuracy and practicality of SPAD

A comprehensive data set demonstrating the spatial variability of soil properties and crop growth conditions at field scale

A four-year (1999-2002) multivariable data set for one specific agricultural used field located in North Rhine-Westphalia is documented in detailed. The data set focusses on the small-scale heterogeneity of soil properties varying in the spatial and temporal dimension. Initial soil sampling was conducted at altogether 80 sampling points arranged in a regular and a nested grid along the 20 ha large field. Information about the soil inventory (soil texture, soil organic carbon) exists for three subsequent soil layers to a total depth of 90 cm and for every sampling point. Subsequently, the same points and layers were examined for the soil variables soil moisture and soil nitrogen biannually. Additional information about crop rotation, tillage, site-specific fertilization, yield performance and weather complete the data set was that used for model inter-comparison within the crop modelling part (CropM) of the international FACCE JPI MACSUR2 project

Estimating the contribution of crop residues to soil organic carbon conservation

Crop residues contribute to the maintenance of soil organic carbon (SOC) stores, a key component of soil fertility and soil-based climate change mitigation strategies, such as the ‘4 per 1000’ initiative. Residues are also in demand in sectors coupled to crop production, such as the supply chain of livestock and bioenergy production. Ongoing debate revolves around balancing these competing uses, but science-based assessments of the long-term sustainability of residue exploitation are rare. This work uses biophysical simulation modelling to explore the likely response of SOC to different management strategies, using the land area of North Rhine-Westphalia (Germany) as a case study. Four strategies are tested: zero, one third and 100% removal of cereal residues, plus an approach proposed by the State farm advisory service. Simulations are carried out for the period 1971–2050 and 19 crop rotations coincident with land use throughout the study area. Uncertainty associated with the modelled SOC changes is explored by sampling values of relevant parameters for SOC turnover and running an ensemble of model configurations. Simulated SOC is used to trace time-dependent response functions following a change in residue management under different soil textures, initial SOC levels and crop rotations. Results highlight a general exponential decrease in SOC, with relative changes in 2050 distributed between +10% and −40% with respect to a reference period. SOC loss can be buffered or offset by returning all crop residues to the soil. Under such management, an SOC increase can be achieved on clayey soils characterized by a low initial SOC. Under moderate crop residue removal, positive SOC trends are limited to a few crop rotations. In this context, 4 per 1000 increase rate in SOC appears largely out of reach through residue management, calling for additional measures to meet the targets of land-based mitigation of anthropogenic emissions

Long Range and High-Speed Personal Laser Scanning (PLS) and Simultaneous Localization and Mapping (SLAM) Technology in Roundwood Measurement

1041011033German Federal Ministry of Food and Agriculture (BMEL