Pattern analysis of Australia soil profiles for plant available water capacity

被引:6
作者
Gladish, Daniel W. [1 ]
He, Di [2 ]
Wang, Enli [2 ]
机构
[1] CSIRO Data61, 41 Boggo Rd, Dutton Pk, Qld, Australia
[2] CSIRO Agr & Food, Cluniess Ross St, Black Mt, ACT, Australia
关键词
Typical soil profiles; Shape analysis; Pattern analysis; APSIM; Soil-crop modelling; HOLDING CAPACITY; FARMING SYSTEMS; YIELD; WHEAT; FIELD; IMPACT; APSIM; MODEL; VARIABILITY; PREDICTION;
D O I
10.1016/j.geoderma.2021.114977
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Plant available water capacity (PAWC), defined as the amount of water held in the soil between the drained upper limit (DUL) and crop lower limit (CLL), is a major determinant for crop yield in dryland cropping areas. However, measured soil profile data quantifying the physical soil parameters that determine PAWC are limited. Choosing a 'representative' soil profile in order to parameterise a deterministic model is often subjective and may not be appropriate, leading to biased conclusions. To help support these deterministic crop modelling studies, we analysed soil profile data in Australia available in the APSoil database; a database of field and laboratory measured physical soil properties used to parameterise the Agricultural Production Systems sIMulator (APSIM) model. Specifically, we developed typical soil pattern profiles utilizing wheat for CLL using statistical shape analysis and cluster analysis. Our method allows modellers to reduce the number of soil profile parameter choices using a statistically sound basis. We implement our method by grouping the APSoil soil profiles into five clusters, whereby each cluster is represented by a more general soil profile. The representative soil profiles reflect impact of the soil texture on PAWC. The five clusters and representative soil profiles can then be used in future modelling studies to investigate the impact of soil variation on systems performance. In turn, soil scientists will have a plausible and quantifiable collection of soil profiles to choose from for future studies.
引用
收藏
页数:12
相关论文
共 60 条
  • [11] Estivill-Castro Vladimir, 2002, ACM SIGKDD explorations newsletter, V4, P65, DOI 10.1145/568574.568575
  • [12] Inverse meta-modelling to estimate soil available water capacity at high spatial resolution across a farm
    Florin, M. J.
    McBratney, A. B.
    Whelan, B. M.
    Minasny, B.
    [J]. PRECISION AGRICULTURE, 2011, 12 (03) : 421 - 438
  • [13] FORGY EW, 1965, BIOMETRICS, V21, P768
  • [14] Friedman J., 2001, Springer Series in Statistics: The Elements of Statistical Learning Data Mining, Inference, and Prediction, V1
  • [15] Digital soil mapping of available water content using proximal and remotely sensed data
    Gooley, L.
    Huang, J.
    Page, D.
    Triantafilis, J.
    [J]. SOIL USE AND MANAGEMENT, 2014, 30 (01) : 139 - 151
  • [16] Hartigan J. A., 1979, Applied Statistics, V28, P100, DOI 10.2307/2346830
  • [17] Predicting plant available water holding capacity of soils from crop yield
    He, Di
    Oliver, Yvette
    Wang, Enli
    [J]. PLANT AND SOIL, 2021, 459 (1-2) : 315 - 328
  • [18] On the relation between soil water holding capacity and dryland crop productivity
    He, Di
    Wang, Enli
    [J]. GEODERMA, 2019, 353 : 11 - 24
  • [19] Uncertainty in canola phenology modelling induced by cultivar parameterization and its impact on simulated yield
    He, Di
    Wang, Enli
    Wang, Jing
    Lilley, Julianne
    Luo, Zhongkui
    Pan, Xuebiao
    Pan, Zhihua
    Yang, Ning
    [J]. AGRICULTURAL AND FOREST METEOROLOGY, 2017, 232 : 163 - 175
  • [20] Simulation of environmental and genotypic variations of final leaf number and anthesis date for wheat
    He, Jianqiang
    Le Gouis, Jacques
    Stratonovitch, Pierre
    Allard, Vincent
    Gaju, Oorbessy
    Heumez, Emmanuel
    Orford, Simon
    Griffiths, Simon
    Snape, John W.
    Foulkes, M. John
    Semenov, Mikhail A.
    Martre, Pierre
    [J]. EUROPEAN JOURNAL OF AGRONOMY, 2012, 42 : 22 - 33