Is soil variation random?

被引:120
|
作者
Webster, R [1 ]
机构
[1] Rothamsted Expt Stn, Harpenden AL5 2JQ, Herts, England
关键词
soil; spatial variation; geostatistics; chaos; random processes; stationarity;
D O I
10.1016/S0016-7061(00)00036-7
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
A typical geostatistical analysis of soil data proceeds on the assumption that the properties of interest are the outcomes of random processes. Is the assumption reasonable? Many factors have contributed to the soil as we see it, both in the parent material and during its formation. Each has a physical cause, each must obey the laws of physics, and each is in principle deterministic except at the sub-atomic level. The outcome must therefore be deterministic. Yet such is the complexity of the factors in combination, their variation over the time, and the incompleteness of our knowledge, that the outcome, the soil, appears to us as if it were random. Only when we see the results of man's activities, such as the division of the land into fields, the imposition of irrigation, and ditches for drainage, do we recognize organized control. Clearly, the soil is not random, but except in the latter instances we an unlikely to go far wrong if we assume that it is. A second assumption underlying many geostatistical analyses is that of stationarity. We might ask if this holds. In the real world, we have ever only one realization of the random process in a particular region, and so the question has no answer. We can look to see whether regional averages are the same when we move from region to region. This means treating data from different regions as if they were different realizations of the same generating process. We should therefore change our question to 'is a stationary model of the soil realistic?' We can then examine the reality against the assumptions of our model. The soil is neither random nor stationary, but our models of it may be one or other or both. We should therefore ask whether our models are reasonable in the circumstances and whether they are profitable in leading to accurate predictions. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:149 / 163
页数:15
相关论文
共 50 条
  • [41] Stochastic simulation: Modeling random or actual variation
    Oderwald, RG
    PROCEEDINGS OF THE 1996 SOCIETY OF AMERICAN FORESTERS CONVENTION: DIVERSE FORESTS, ABUNDANT OPPORTUNITIES, AND EVOLVING REALITIES, 1996, : 67 - 72
  • [42] Epialleles - a source of random variation in times of stress
    Finnegan, EJ
    CURRENT OPINION IN PLANT BIOLOGY, 2002, 5 (02) : 101 - 106
  • [43] RANDOM OFFSPRING MORTALITY AND VARIATION IN PARENTAL FITNESS
    CABANA, G
    KRAMER, DL
    EVOLUTION, 1991, 45 (01) : 228 - 234
  • [44] Random sources for beams with azimuthal intensity variation
    Wang, Fei
    Korotkova, Olga
    OPTICS LETTERS, 2016, 41 (03) : 516 - 519
  • [45] Random variation and systematic biases in probability estimation
    Howe, Rita
    Costello, Fintan
    COGNITIVE PSYCHOLOGY, 2020, 123
  • [46] On the variation of the f-inequality of a random variable
    Cascos-Fernández, I
    López-Díaz, M
    Gil-Alvarez, MA
    SOFT METHODS IN PROBABILITY, STATISTICS AND DATA ANALYSIS, 2002, : 98 - 104
  • [47] NETWORK OPTIMIZATION BY RANDOM VARIATION OF COMPONENT VALUES
    KJELLSTR.G
    ERICSSON TECHNICS, 1969, 25 (03): : 133 - &
  • [48] SIMPLE TEST FOR HETEROSCEDASTICITY AND RANDOM COEFFICIENT VARIATION
    BREUSCH, TS
    PAGAN, AR
    ECONOMETRICA, 1979, 47 (05) : 1287 - 1294
  • [49] CHARACTERISTICS WITH DISCRETE VARIATION - INDEPENDENT RANDOM VARIABLE
    SANDU, G
    DRAGANESCU, C
    REVISTA DE CRESTEREA ANIMALELOR, 1976, 26 (09): : 45 - 46
  • [50] A simple method for measuring the random variation of an interferometer
    Picart, P
    Mercier, R
    Lamare, M
    Breteau, JM
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2001, 12 (08) : 1311 - 1317