An explicit and computationally efficient method to initialise first-order-based soil organic matter models-The Geometric Series Solution (GSS)

H. Wong*, J. Hillier, D. B. Clark, J. Smith, P. Smith

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper derives an algebraic solution (the Geometric Series Solution: GSS) to replace iterative runs of soil organic matter (SOM) models for initialisation of SOM pools. The method requires steady-state/long-term-average series of plant input and soil climate driving data. It calculates the values of SOM pools as if SUM models are iterated for a large number of cycles. The method has a high computational efficiency because it is an explicit solution to the calculations used to initialise the model and so requires a single iteration of the SOM model. Under the premise that the iterative pool inputs can be derived analytically, the GSS equations are applicable for other first-order-based SOM models. To illustrate applicability the method is applied to the coupled JULES-ECOSSE model. (c) 2013 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)48-53
Number of pages6
JournalEcological Modelling
Volume267
Early online date26 Aug 2013
DOIs
Publication statusPublished - 10 Oct 2013

Keywords

  • algebraic method
  • model initialisation
  • soil organic matter (SOM)
  • spin-up
  • The ECOSSE model
  • The JULES model
  • carbon
  • equilibrium
  • nitrogen
  • pools

Cite this

An explicit and computationally efficient method to initialise first-order-based soil organic matter models-The Geometric Series Solution (GSS). / Wong, H.; Hillier, J.; Clark, D. B.; Smith, J.; Smith, P.

In: Ecological Modelling, Vol. 267, 10.10.2013, p. 48-53.

Research output: Contribution to journalArticle

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AU - Smith, J.

AU - Smith, P.

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N2 - This paper derives an algebraic solution (the Geometric Series Solution: GSS) to replace iterative runs of soil organic matter (SOM) models for initialisation of SOM pools. The method requires steady-state/long-term-average series of plant input and soil climate driving data. It calculates the values of SOM pools as if SUM models are iterated for a large number of cycles. The method has a high computational efficiency because it is an explicit solution to the calculations used to initialise the model and so requires a single iteration of the SOM model. Under the premise that the iterative pool inputs can be derived analytically, the GSS equations are applicable for other first-order-based SOM models. To illustrate applicability the method is applied to the coupled JULES-ECOSSE model. (c) 2013 Elsevier B.V. All rights reserved.

AB - This paper derives an algebraic solution (the Geometric Series Solution: GSS) to replace iterative runs of soil organic matter (SOM) models for initialisation of SOM pools. The method requires steady-state/long-term-average series of plant input and soil climate driving data. It calculates the values of SOM pools as if SUM models are iterated for a large number of cycles. The method has a high computational efficiency because it is an explicit solution to the calculations used to initialise the model and so requires a single iteration of the SOM model. Under the premise that the iterative pool inputs can be derived analytically, the GSS equations are applicable for other first-order-based SOM models. To illustrate applicability the method is applied to the coupled JULES-ECOSSE model. (c) 2013 Elsevier B.V. All rights reserved.

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KW - model initialisation

KW - soil organic matter (SOM)

KW - spin-up

KW - The ECOSSE model

KW - The JULES model

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KW - equilibrium

KW - nitrogen

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