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A Sensitivity Analysis of the SPACSYS Model

Author

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  • Yan Shan

    (Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UK
    State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling 712100, China
    College of Resources and Environment, Northwest A & F University, Yangling 712100, China
    Current address: Shandong Institute of Sericulture, Yantai 264002, China.)

  • Mingbin Huang

    (State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling 712100, China
    Center for Excellence in Quaternary Science and Global Change, Chinese Academy of Sciences, Xi’an 710061, China)

  • Paul Harris

    (Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UK)

  • Lianhai Wu

    (Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UK)

Abstract

A sensitivity analysis is critical for determining the relative importance of model parameters to their influence on the simulated outputs from a process-based model. In this study, a sensitivity analysis for the SPACSYS model, first published in Ecological Modelling (Wu, et al., 2007), was conducted with respect to changes in 61 input parameters and their influence on 27 output variables. Parameter sensitivity was conducted in a ‘one at a time’ manner and objectively assessed through a single statistical diagnostic (normalized root mean square deviation) which ranked parameters according to their influence of each output variable in turn. A winter wheat field experiment provided the case study data. Two sets of weather elements to represent different climatic conditions and four different soil types were specified, where results indicated little influence on these specifications for the identification of the most sensitive parameters. Soil conditions and management were found to affect the ranking of parameter sensitivities more strongly than weather conditions for the selected outputs. Parameters related to drainage were strongly influential for simulations of soil water dynamics, yield and biomass of wheat, runoff, and leaching from soil during individual and consecutive growing years. Wheat yield and biomass simulations were sensitive to the ‘ammonium immobilised fraction’ parameter that related to soil mineralization and immobilisation. Simulations of CO 2 release from the soil and soil nutrient pool changes were most sensitive to external nutrient inputs and the process of denitrification, mineralization, and decomposition. This study provides important evidence of which SPACSYS parameters require the most care in their specification. Moving forward, this evidence can help direct efficient sampling and lab analyses for increased accuracy of such parameters. Results provide a useful reference for model users on which parameters are most influential for different simulation goals, which in turn provides better informed decision making for farmers and government policy alike.

Suggested Citation

  • Yan Shan & Mingbin Huang & Paul Harris & Lianhai Wu, 2021. "A Sensitivity Analysis of the SPACSYS Model," Agriculture, MDPI, vol. 11(7), pages 1-30, July.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:7:p:624-:d:587931
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    References listed on IDEAS

    as
    1. Wu, L. & McGechan, M.B. & McRoberts, N. & Baddeley, J.A. & Watson, C.A., 2007. "SPACSYS: Integration of a 3D root architecture component to carbon, nitrogen and water cycling—Model description," Ecological Modelling, Elsevier, vol. 200(3), pages 343-359.
    2. Wu, Renye & Lawes, Roger & Oliver, Yvette & Fletcher, Andrew & Chen, Chao, 2019. "How well do we need to estimate plant-available water capacity to simulate water-limited yield potential?," Agricultural Water Management, Elsevier, vol. 212(C), pages 441-447.
    3. Jouni, Hamidreza Javani & Liaghat, Abdolmajid & Hassanoghli, Alireza & Henk, Ritzema, 2018. "Managing controlled drainage in irrigated farmers’ fields: A case study in the Moghan plain, Iran," Agricultural Water Management, Elsevier, vol. 208(C), pages 393-405.
    4. Zhao, Gang & Bryan, Brett A. & Song, Xiaodong, 2014. "Sensitivity and uncertainty analysis of the APSIM-wheat model: Interactions between cultivar, environmental, and management parameters," Ecological Modelling, Elsevier, vol. 279(C), pages 1-11.
    5. Kathryn G Link & Michael T Stobb & Jorge Di Paola & Keith B Neeves & Aaron L Fogelson & Suzanne S Sindi & Karin Leiderman, 2018. "A local and global sensitivity analysis of a mathematical model of coagulation and platelet deposition under flow," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-38, July.
    6. Kang, Shaozhong & Zhang, Lu & Liang, Yinli & Hu, Xiaotao & Cai, Huanjie & Gu, Binjie, 2002. "Effects of limited irrigation on yield and water use efficiency of winter wheat in the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 55(3), pages 203-216, June.
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    2. Wang, Yuehua & Wang, Zhongwu & Wu, Lianhai & Li, Haigang & Li, Jiangwen & Zhu, Aimin & Jin, Yuxi & Han, Guodong, 2024. "Effects of grazing and climate change on aboveground standing biomass and sheep live weight changes in the desert steppe in Inner Mongolia, China," Agricultural Systems, Elsevier, vol. 217(C).
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    4. Chuang Liu & Huiyi Yang & Kate Gongadze & Paul Harris & Mingbin Huang & Lianhai Wu, 2022. "Climate Change Impacts on Crop Yield of Winter Wheat ( Triticum aestivum ) and Maize ( Zea mays ) and Soil Organic Carbon Stocks in Northern China," Agriculture, MDPI, vol. 12(5), pages 1-12, April.

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