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(Type ML2x, Delta-T Devices, Cambridge, UK) that were calibrated for the soil and inserted into the surface at each point. In total, measurements were made at 52 different times. Soil water content was compared to other properties that were anticipated to influence water transport and storage. At least 3 times during the growing season the following measurements were made in situ. Shear strength was measured with a hand-held shear vane tester (Geonor H-60, Norway). Water repellency was estimated with the water drop penetration time (WDPT) test, by measuring the time taken for a 0.5 mm 3 drop of water to enter the soil. A longer time indicates greater water repellency. Hydraulic conductivity was measured using a Mini-disk Infiltrometer (Decagon devices, USA) at a suction value of 0.5 cm. Once each year, in July or August, the vegetation coverage was analyzed using a non-destructive method based on Braun-Blanquet (1964). Abovegro<strong>und</strong> biomass was sampled on 0.25 m x 0.25 m plots by cutting plant at 10 mm height, including the standing dead material. At the first sampling time in 2004, 0-4 cm depth samples were taken for soil organic carbon determined in duplicate by dry combustion on a Vario Max CNS elemental analyzer (Elementar Analysensysteme GmbH, Hanau), and soil texture with the pipette method. Intact soil cores, 56 mm diameter x 40 mm heigh were taken for bulk density and water retention. The cores were dried to pF 1.8 (field capacity) on a sand table and 4.2 (wilting point) on a pressure plate to describe water retention. The main mean characteristics (100 points) for each plot are described in Table 1. A terrain elevation model was derived from Real Time Kinematic dGPS (RTK-GPS) measurements with a lateral resolution of 2 m and vertical resolution of 0.1 m. Using this information, topographical variables such as slope, aspect, curvature, and upslope contribution area were computed using ArcGIS (Johnston, et al., 2001). A wetness index, which is a surrogate for lateral subsurface flow process, was also derived. This index was defined as ln(α/tanβ), where α is the upslope contribution area and β is the local slope angle (Gómez-Plaza, et al., 2001). 44
Chapter 3 Spatio-temporal variability of soil moisture in grazed steppe areas investigated by geostatistics 2.2. Data analysis All measured variables were analyzed with descriptive statistics and geostatistics. Correlations were tested using Pearson’s correlation coefficient. Prior to calculating spatial variation, data were tested for normal distribution with a Kolmogorov-Smirnov test. By removing one or two outliers (m±3s method) and data transformations (Ln, Cos and Tan), a normal distribution was obtained for each variable. For each plot and sampling time, the mean soil water content of all 100 points was used to delineate a soil moisture class. Three classes were defined as wet (>20%), medium (10-20%) and dry (
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SCHRIFTENREIHE Institut für Pflanz
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Aus dem Institut für Pflanzenernä
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I Table of contents I Table of cont
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controlling soil moisture are of pa
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Zusammenfassung Überweidung wird a
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Page 25 and 26: Chapter 1 Introduction water in spr
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Page 101 and 102: Soil water content (%) 40 30 20 10
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Chapter 5 Modeling Grazing Effects
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Chapter 6 Modeling of Coupled Water
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Chapter 7 General discussion and co
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References Chapter 7 General discus
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8. ACKNOWLEDGMENTS Firstly I would
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Curriculum Vitae M.Sc. Ying Zhao Of
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Schriftenreihe des Instituts Neuere
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