Simulation of long-term soil redistribution by tillage using a cellular automata model

被引:12
|
作者
Vanwalleghem, T. [1 ]
Jimenez-Hornero, F. J. [2 ]
Giraldez, J. V. [1 ]
Laguna, A. [3 ]
机构
[1] Univ Cordoba, Dept Agron, E-14071 Cordoba, Spain
[2] Univ Cordoba, Dept Graph Engn & Geomat, E-14071 Cordoba, Spain
[3] Univ Cordoba, Dept Appl Phys, E-14071 Cordoba, Spain
关键词
soil erosion; tillage translocation; Cs-137; cellular automata; sensitivity analysis; EROSION RATES; SOUTHWESTERN ONTARIO; AGRICULTURAL LAND; SPATIAL VARIATION; FIELD EXPERIMENTS; DEBRIS FLOWS; LAVA FLOWS; TRANSLOCATION; WATER; LANDSCAPES;
D O I
10.1002/esp.1923
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
The process of tillage translocation is well studied and can be described adequately by different existing models. Nevertheless, in complex environments with numerous obstacles, such as olive orchards, the application of conventional tillage erosion models is not straightforward. However, such obstacles have important effects on the spatial pattern of soil redistribution and on resulting soil properties. Cellular automata could provide a valuable alternative here. This study aims at developing a cellular automata model for tillage translocation (CATT) that can take into account such obstacles, exploring its possibilities and limitations. Firstly, model outcome was tested on a traditional field with rolling topography, for which caesium-137 (Cs-137) inventories are available. The observed spatial soil redistribution patterns could be adequately represented by the CATT model. Secondly, a global sensitivity analysis was performed to explore the effect of input parameter uncertainty on several selected model outputs. The variance-based extended Fourier Amplitude Sensitivity Test (FAST) method was used to determine first- and total-order sensitivity indices. Tillage depth was identified as the input parameter that determined most of the output variance, followed respectively by tillage direction and speed. The high difference between the total- and first-order sensitivity indices indicated that, in spite of the simple model structure, the model behaves non-linearly with respect to some of the model output variables. Higher order interactions were especially important for determining the proportion of eroding and deposition cells. Finally, simulations were performed to analyse the model behaviour in complex landscapes, applying it to a field with protruding obstacles (representing olive trees). The model adequately represented some morphological features observed in actual olive orchards, such as mounds around the olive trees. The results show that cellular automata are an appropriate tool to describe long-term tillage soil redistribution. Copyright (C) 2010 John Wiley & Sons, Ltd.
引用
收藏
页码:761 / 770
页数:10
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