Simplifying Sirius: sensitivity analysis and development of a meta-model for wheat yield prediction

被引:50
|
作者
Brooks, RJ
Semenov, MA [1 ]
Jamieson, PD
机构
[1] Univ Bristol, Dept Agr Sci, IACR Long Ashton Res Stn, Bristol BS41 9AF, Avon, England
[2] Univ Lancaster, Sch Management, Dept Management Sci, Lancaster LA1 4YX, England
[3] New Zealand Inst Crop & Food Res Ltd, Christchurch, New Zealand
基金
英国生物技术与生命科学研究理事会;
关键词
crop model; model simplification; meta-model; mathematical modelling; computer simulation;
D O I
10.1016/S1161-0301(00)00089-7
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
A sensitivity analysis and analysis of the structure of the Sirius wheat model has resulted in the development of a simpler meta-model, which produced very similar yield predictions to Sirius of potential and water-limited yields at two locations in the UK, Rothamsted and Edinburgh. This greatly increases the understanding of the nature and consequences of the relationships implicit within Sirius. The analysis showed that the response of wheat crops to climate could be explained using a few simple relationships. The meta-model aggregates the three main Sirius components, the calculation of leaf area index, the soil water balance model and the evapotranspiration calculations. into simpler equations. This results in a requirement for calibration of fewer model parameters and means that weather variables can be provided on a monthly rather than a daily lime-step, because the meta-model can use cumulative values of weather variables. Consequently the meta-model is a valuable tool for regional impact assessments when detailed input data are usually not available. Because the meta-model was developed from the analysis of Sirius, rather than from statistical fitting of yield to weather data, it should perform well for other locations in Great Britain and with different management scenarios. (C) 2001 Elsevier Science B,V. All rights reserved.
引用
收藏
页码:43 / 60
页数:18
相关论文
共 50 条
  • [41] Identification of species traits enhancing yield in wheat-faba bean intercropping: development and sensitivity analysis of a minimalist mixture model
    H. N. C. Berghuijs
    Z. Wang
    T. J. Stomph
    M. Weih
    W. Van der Werf
    G. Vico
    Plant and Soil, 2020, 455 : 203 - 226
  • [42] Identification of species traits enhancing yield in wheat-faba bean intercropping: development and sensitivity analysis of a minimalist mixture model
    Berghuijs, H. N. C.
    Wang, Z.
    Stomph, T. J.
    Weih, M.
    Van der Werf, W.
    Vico, G.
    PLANT AND SOIL, 2020, 455 (1-2) : 203 - 226
  • [43] Development of a robust ensemble meta-model for prediction of salinity time series under uncertainty (case study: Talar aquifer)
    Ranjbar, Ali
    Cherubini, Claudia
    HELIYON, 2020, 6 (12)
  • [44] An efficient SRAM yield analysis method based on scaled-sigma adaptive importance sampling with meta-model accelerated
    Pang, Liang
    Wang, Ziqi
    Shi, Rui
    Yao, Mengyun
    Shi, Xiao
    Yan, Hao
    Shi, Longxin
    INTEGRATION-THE VLSI JOURNAL, 2023, 89 : 155 - 167
  • [45] Combining lightweight wheat spikes detecting model and offline Android software development for in-field wheat yield prediction
    Chen J.
    Li Q.
    Tan Q.
    Gui S.
    Wang X.
    Yi F.
    Jiang D.
    Zhou J.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2021, 37 (19): : 156 - 164
  • [46] Applicability evaluation of CERES-Wheat model and yield prediction of winter wheat
    Wang W.
    Huang Y.
    Huang W.
    Li C.
    Wang X.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2010, 26 (03): : 233 - 237
  • [47] Interval prediction of the fatigue crack cycle using evidence theory and the Kriging meta-model
    Dong Soo Kim
    Jongsoo Lee
    International Journal of Precision Engineering and Manufacturing, 2015, 16 : 2315 - 2320
  • [48] Interval prediction of the fatigue crack cycle using evidence theory and the Kriging meta-model
    Kim, Dong Soo
    Lee, Jongsoo
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2015, 16 (11) : 2315 - 2320
  • [49] GLOBAL SENSITIVITY ANALYSIS OF WINTER WHEAT YIELD AND PROCESS-BASED VARIABLE WITH AQUACROP MODEL
    Xing, Huimin
    Xu, Xingang
    Yang, Fuqin
    Feng, Haikuan
    Yang, Guijin
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 5929 - 5932
  • [50] A meta-model for the analysis and design of organizations in multi-agent systems
    Ferber, J
    Gutknecht, O
    INTERNATIONAL CONFERENCE ON MULTI-AGENT SYSTEMS, PROCEEDINGS, 1998, : 128 - 135