4.6 Article

Controls of surface soil moisture spatial patterns and their temporal stability in a semi-arid steppe

Journal

HYDROLOGICAL PROCESSES
Volume 24, Issue 18, Pages 2507-2519

Publisher

WILEY-BLACKWELL
DOI: 10.1002/hyp.7665

Keywords

time stability; soil moisture; controlling factor; sampling strategy; grazing

Funding

  1. German Research Council (DFG) [DFG RU 536 MAGIM, Ho 911/35]

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Temporal stability of soil moisture spatial patterns has important implications for optimal soil and water management and effective field monitoring. The aim of this study was to investigate the temporal stability of soil moisture spatial patterns over four plots of 105 m x 135 m in grid size with different grazing intensities in a semi-arid steppe in China. We also examined whether a time-stable location can be identified from causative factors (i. e. soil, vegetation, and topography). At each plot, surface soil moisture (0-6 cm) was measured about biweekly from 2004 to 2006 using 100 points in each grid. Possible controls of soil moisture, including soil texture, organic carbon, bulk density, vegetation coverage, and topographic indices, were determined at the same grid points. The results showed that the spatial patterns of soil moisture were considerably stable over the 3-y monitoring period. Soil moisture under wet conditions (averaged volumetric moisture contents > 20%) was more stable than that under dry ((theta) over bar (j),(t) < 10%) or moist (<(theta)over bar>(j),(t) = 10-20%) conditions. The best representative point for the whole field identified in each plot was accurate in representing the field mean moisture over time (R(2) >= 0.97; p < 0.0001). The degree of temporal persistence varied with grazing intensity, which was partly related to grazing-induced differences in soil and vegetation properties. The correlation analysis showed that soil properties, and to a lesser extent vegetation and topographic properties, were important in controlling the temporal stability of soil moisture spatial patterns in this relatively flat grassland. Response surface regression analysis was used to quantitatively identify representative monitoring locations a priori from available soil-plant parameters. This allows appropriate selection of monitoring locations and enhances efficiency in managing soil and water resources in semi-arid environments. Copyright (C) 2010 John Wiley & Sons, Ltd.

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