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Connecting crop models with highly resolved sensor observations to improve site-specific fertilisation

Published online by Cambridge University Press:  01 June 2017

E. Wallor ,
K.C. Kersebaum ,
K. Lorenz  and
R. Gebbers
E. Wallor*
Affiliation:
Leibniz Centre for Agricultural Landscape Research (ZALF), Institute of Landscape System Analysis, Müncheberg, Germany
K.C. Kersebaum
Affiliation:
Leibniz Centre for Agricultural Landscape Research (ZALF), Institute of Landscape System Analysis, Müncheberg, Germany
K. Lorenz
Affiliation:
Regional Farmers Association Brandenburg, Teltow, Germany
R. Gebbers
Affiliation:
Leibniz Institute for Agricultural Engineering and Bioeconomy, Department of Engineering for Crop Production, Potsdam, Germany
*
† Email: evelyn.wallor@zalf.de
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Abstract

High spatial variability of soil properties restricts the benefits of process-oriented modelling for management recommendations on field scale due to rare information about the soil inventory and its distribution. Geo-electrical mapping provides with a certain spatial pattern, but results are influenced by various factors. The model HERMES was applied to 60 of altogether 80 soil sampling points of a well-documented field in North-Rhine Westphalia characterised by a wide range of soil texture. Validation of HERMES resulted in satisfactory root mean square errors (RMSE) for yield (0.76 t ha-1), water (34.70 mm) and nitrogen in soil (51.44 kg ha-1) over the whole simulation period. At the same field, values of conducted electrical conductivity (ECa) mapping ranged from 20 to 90 mS m-1 and have been assigned to the soil sampling points to proof statistical relations. Clay and sand contents of three soil layers were highly correlated with measured ECa values. Derived regression models show R2 values between 0.73 and 0.89. The subsequent calculation of soil texture at points of ECa mapping produced an improved resolution of this key value to initialize model simulation.

Keywords

soil variabilitysoil sensingprocess modelssite-specific management
Type
Spatial Crop Models
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 689 - 693
Copyright
© The Animal Consortium 2017 

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