Skip to main content
Research article - Peer-reviewed, 2020

Simulation of spatial variability in crop leaf area index and yield using agroecosystem modeling and geophysics-based quantitative soil information

Brogi, C.; Huisman, J. A.; Herbst, M.; Weihermüller, L.; Klosterhalfen, Anne; Montzka, C.; Reichenau, T. G.; Vereecken, H.

Abstract

Agroecosystem models that simulate crop growth as a function of weather conditions and soil characteristics are among the most promising tools for improving crop yield and achieving more sustainable agricultural production systems. This study aims at using spatially distributed crop growth simulations to investigate how field-scale patterns in soil properties obtained using geophysical mapping affect the spatial variability of soil water content dynamics and growth of crops at the square kilometer scale. For this, a geophysics-based soil map was intersected with land use information. Soil hydraulic parameters were calculated using pedotransfer functions. Simulations of soil water content dynamics performed with the agroecosystem model AgroC were compared with soil water content measured at two locations, resulting in RMSE of 0.032 and of 0.056 cm(3) cm(-3), respectively. The AgroC model was then used to simulate the growth of sugar beet (Beta vulgaris L.), silage maize (Zea mays L.), potato (Solanum tuberosum L.), winter wheat (Triticum aestivum L.), winter barley (Hordeum vulgare L.), and winter rapeseed (Brassica napus L.) in the 1- by 1-km study area. It was found that the simulated leaf area index (LAI) was affected by the magnitude of simulated water stress, which was a function of both the crop type and soil characteristics. Simulated LAI was generally consistent with the observed LAI calculated from normalized difference vegetation index (LAI(NDVI)) obtained from RapidEye satellite data. Finally, maps of simulated agricultural yield were produced for four crops, and it was found that simulated yield matched well with actual harvest data and literature values. Therefore, it was concluded that the information obtained from geophysics-based soil mapping was valuable for practical agricultural applications.

Keywords

DM; dry matter; EMI; electromagnetic induction; FVC; fractional vegetation cover; LAI; leaf area index; NDVI; normalized difference vegetation index; PTF; pedotransfer function

Published in

Vadose Zone Journal
2020, volume: 19, number: 1, article number: e20009

Authors' information

Brogi, C.
Jülich Research Centre
Huisman, J. A.
Jülich Research Centre
Herbst, M.
Jülich Research Centre
Weihermüller, L.
Jülich Research Centre
Klosterhalfen, Anne
Swedish University of Agricultural Sciences, Department of Forest Ecology and Management
Montzka, C.
Jülich Research Centre
Reichenau, T. G.
University of Cologne
Vereecken, H.
Jülich Research Centre

Sustainable Development Goals

SDG12 Ensure sustainable consumption and production patterns

UKÄ Subject classification

Environmental Sciences
Geophysics
Soil Science

Publication Identifiers

DOI: https://doi.org/10.1002/vzj2.20009

URI (permanent link to this page)

https://res.slu.se/id/publ/106148