Book/Dissertation / PhD Thesis

FZJ-2020-04774

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Geophysics-based soil mapping for improved modelling of spatial variability in crop growth and yield

Brogi, C. (Corresponding author)FZJ*

2020
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag Jülich
ISBN: 978-3-95806-510-9

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Please use a persistent id in citations: http://hdl.handle.net/2128/26357

Abstract: Water shortage is one of the predominant factors that can directly or indirectly cause a reduction in crop yield and thus poses a severe threat to sustainable crop production. It is therefore critical to improve the sustainability of current agricultural management practices and develop new strategies that will allow the establishment of more sustainable agricultural production systems that can meet present and future food demand. The use of agro-ecosystem models to simulate crop growth for given environmental conditions, and the use of detailed information on soil heterogeneity beyond the field scale are among the most promising tools for achieving this goal. Soil properties are a key control for water and nutrient availability and are therefore co-responsible for yield gaps and harvest failures. A detailed representation of the spatial variability of soil is consequently essential for establishing relevant spatially distributed agro-ecosystem simulations of crop performance in response to water stress. Unfortunately, a detailed soil representation is costly to obtain, and generally cannot be substituted by the use of existing general-purpose soil maps that lack the necessary level of detail. Recently, improvements in digital soil mapping have been made using non-invasive geophysical methods such as electromagnetic induction (EMI) that provide fast and costeffective mapping of relevant soil information. It is however still challenging to derive information relevant for agricultural management from large geophysical datasets and their added value for agricultural applications has not been fully investigated yet, especially for the analysis of patterns in crop performance. This thesis aims at investigating and quantifying the added value of detailed soil information obtained using large-scale geophysical mapping for the simulation and prediction of the spatial variability of crop growth and yield obtained with agro-ecosystem modelling. [...]

Note: Universität Stuttgart, Diss., 2019

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Contributing Institute(s):

1. Agrosphäre (IBG-3)

Research Program(s):

1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2020

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Database coverage:
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