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Precipitation-optimised targeting of nitrogen fertilisers in a model maize cropping system

Precipitation-optimised targeting of nitrogen fertilisers in a model maize cropping system
Precipitation-optimised targeting of nitrogen fertilisers in a model maize cropping system
Typically, half of the nitrogen (N) fertiliser applied to agricultural fields is lost to the wider environment. This inefficiency is driven by soil processes such as denitrification, volatilization, surface run-off and leaching. Rainfall plays an important role in regulating these processes, ultimately governing when and where N fertiliser moves in soil and its susceptibility to gaseous loss. The interaction between rainfall, plant N uptake and N losses, however, remains poorly understood. In this study we use numerical modelling to predict the optimal N fertilisation strategy with respect to rainfall patterns and offer mechanistic explanations to the resultant differences in optimal times of fertiliser application.
We developed a modelling framework that describes water and N transport in soil over a growing season and assesses nitrogen use efficiency (NUE) of split fertilisations within the context of different rainfall patterns. We used ninety rainfall patterns to determine their impact on optimal N fertilisation times. We considered the effects of root growth, root N uptake, microbial transformation of N and the effect of soil water saturation and flow on N movement in the soil profile. On average, we show that weather-optimised fertilisation strategies could improve crop N uptake by 20% compared to the mean uptake. In drier years, weather-optimizing N applications improved the efficiency of crop N recovery by 35%. Further analysis shows that maximum plant N uptake is greatest under drier conditions due to reduced leaching, but it is harder to find the maximum due to low N mobility. The model could capture contrasting trends in NUE seen in previous arable cropping field trials. Furthermore, the model predicted that the variability in NUE seen in the field could be associated with precipitation-driven differences in N leaching and mobility. In conclusion, our results show that NUE in cropping systems could be significantly enhanced by synchronising fertiliser timings with both crop N demand and local weather patterns.
Fertiliser optimisation, Greenhouse gases, Nutrient use efficiency, Sustainable agroecosystems, limate modelling
0048-9697
Mckay Fletcher, Daniel
db06e7e0-69af-4fa2-89b3-26f6599e43d4
Ruiz, Siul Aljadi
d79b3b82-7c0d-47cc-9616-11d29e6a41bd
Dias, T.
f1d6edfe-d128-4c37-9312-fafcf81d929c
Chadwick, David
83b1c95b-1b7d-4c6a-bbdf-4e0c2eec3997
Jones, Davey L.
c8e739a8-07d9-4c32-a0d2-e95c7754d168
Roose, Tiina
3581ab5b-71e1-4897-8d88-59f13f3bccfe
Mckay Fletcher, Daniel
db06e7e0-69af-4fa2-89b3-26f6599e43d4
Ruiz, Siul Aljadi
d79b3b82-7c0d-47cc-9616-11d29e6a41bd
Dias, T.
f1d6edfe-d128-4c37-9312-fafcf81d929c
Chadwick, David
83b1c95b-1b7d-4c6a-bbdf-4e0c2eec3997
Jones, Davey L.
c8e739a8-07d9-4c32-a0d2-e95c7754d168
Roose, Tiina
3581ab5b-71e1-4897-8d88-59f13f3bccfe

Mckay Fletcher, Daniel, Ruiz, Siul Aljadi, Dias, T., Chadwick, David, Jones, Davey L. and Roose, Tiina (2021) Precipitation-optimised targeting of nitrogen fertilisers in a model maize cropping system. Science of the Total Environment, 756, [144051]. (doi:10.1016/j.scitotenv.2020.144051).

Record type: Article

Abstract

Typically, half of the nitrogen (N) fertiliser applied to agricultural fields is lost to the wider environment. This inefficiency is driven by soil processes such as denitrification, volatilization, surface run-off and leaching. Rainfall plays an important role in regulating these processes, ultimately governing when and where N fertiliser moves in soil and its susceptibility to gaseous loss. The interaction between rainfall, plant N uptake and N losses, however, remains poorly understood. In this study we use numerical modelling to predict the optimal N fertilisation strategy with respect to rainfall patterns and offer mechanistic explanations to the resultant differences in optimal times of fertiliser application.
We developed a modelling framework that describes water and N transport in soil over a growing season and assesses nitrogen use efficiency (NUE) of split fertilisations within the context of different rainfall patterns. We used ninety rainfall patterns to determine their impact on optimal N fertilisation times. We considered the effects of root growth, root N uptake, microbial transformation of N and the effect of soil water saturation and flow on N movement in the soil profile. On average, we show that weather-optimised fertilisation strategies could improve crop N uptake by 20% compared to the mean uptake. In drier years, weather-optimizing N applications improved the efficiency of crop N recovery by 35%. Further analysis shows that maximum plant N uptake is greatest under drier conditions due to reduced leaching, but it is harder to find the maximum due to low N mobility. The model could capture contrasting trends in NUE seen in previous arable cropping field trials. Furthermore, the model predicted that the variability in NUE seen in the field could be associated with precipitation-driven differences in N leaching and mobility. In conclusion, our results show that NUE in cropping systems could be significantly enhanced by synchronising fertiliser timings with both crop N demand and local weather patterns.

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Accepted/In Press date: 19 November 2020
e-pub ahead of print date: 24 November 2020
Published date: 20 February 2021
Keywords: Fertiliser optimisation, Greenhouse gases, Nutrient use efficiency, Sustainable agroecosystems, limate modelling

Identifiers

Local EPrints ID: 446020
URI: http://eprints.soton.ac.uk/id/eprint/446020
ISSN: 0048-9697
PURE UUID: f5197069-dad6-46a1-88a8-eddf81f30c17
ORCID for Daniel Mckay Fletcher: ORCID iD orcid.org/0000-0001-6569-2931
ORCID for Tiina Roose: ORCID iD orcid.org/0000-0001-8710-1063

Catalogue record

Date deposited: 19 Jan 2021 17:31
Last modified: 26 Nov 2021 05:39

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Contributors

Author: Daniel Mckay Fletcher ORCID iD
Author: T. Dias
Author: David Chadwick
Author: Davey L. Jones
Author: Tiina Roose ORCID iD

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