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mechanisms of environmental changes in response to grazing, which is the basis for making a more sustainable land management. 140 Although a large amount of data is required for this kind of analysis we consider it is a prerequisite when matter fluxes on a regional scale are investigated. Spatio-temporal distribution of water-related variables is valuable information not only for deriving a conceptual <strong>und</strong>erstanding of landscape fluxes but also for the spatial discretization and parameter estimation in the modeled domain. For instance, the analysis of correlation length is very useful to determine appropriate model element sizes, and to extrapolate and upscale processes with the aid of physically-based hydrological models from plot (e.g. Hydrus-1D) to catena (e.g. Hydrus-2D) and finally to a regional scale (e.g. SWAT) (Western et al. 1999). Currently, the estimation of water fluxes at different spatial scales remains a challenging task in hydrology. Indeed, the scale of the hydrological measurement technique is generally much smaller than the scale at which the predictions are required. The knowledge of scaling (regionalization, transferability and upscaling) is therefore needed to estimate water fluxes at large scales based on a series of local measurements. We expect that further studies will have to concentrate on questions like what size model elements should have at different spatial scales. In addition, except for the spatial dependence of water-related variables aforementioned, time stability analysis of soil moisture is also important. In fact, due to the high costs of long-term soil moisture monitoring, it is rare that the monitoring sites are uniformly distributed in the entire studied area (Gomez-Plaza et al., 2000; Martinez-Fernandez and Ceballos, 2005; Lin, 2006). Consequently, selected monitoring sites may not represent the true field mean water content. In addition, in the study of hydraulic model, normally the observation or modeled points are selected without the prior analysis so that representative of the selected points is also uncertain. To account for this uncertainty, we combined the temporal stability concept with a hydraulic model (HYDRUS-1D) applied in the derived time stability point (TSP). Helpfully, we proofed it to be a suitable method to reduce the sampling number of soil
Chapter 7 General discussion and conclusions moisture. Conversely, our monitoring position can be considered as kind of location that can represent the field mean moisture content (i.e. representative position) since it also matched with measured water content in TSP. From this aspect, we set up a bridge connected the representative of monitoring and field mean value in term of temporal stability concept. Grazing effects on soil properties and functions (Chapters 2, 3 and 5) Grazing has an influence on soil hydraulic, thermal and mechanical properties and functions, predominantly in the upper layers (10-15 cm). Furthermore, those properties are interlinked with each other. For instance, the mechanical results revealed that grazing increased the precompression stress on the grazed sites (Krümmelbein et al., 2006), and further increased bulk density accompanied with changes in soil structure as indicated by Peth and Horn (2006). The structural change due to grazing is also reflected by a decrease of Ks, total- and macro- pore volume and an increase of meso-pore volume. This is in agreement with Villamil et al. (2001), who proofed a change of water retention characteristics by grazing in Argentina. Furthermore, grazing decreased hydraulic conductivity because of animals trampling as indicated by Wang and Ripley (1997). Therefore, we considered that heavy grazing particularly deteriorated soil physical and hydraulic properties, while moderate to light grazing was less harmful. Conversely, we also noticed that soil physical functions had recovered to some extent after being fenced for a long-term period (e.g. 25 yr in UG 79). Drewry et al. (2006) summarized that processes contributing to the natural recovery of physically degraded soil might include reduction of soil compaction (e.g. tillage, wheel-traffic compaction), earthworm burrowing, root penetration and decay, wetting and drying cycles, and freezing and thawing cycles (Drewry et al., 2006). Owing to exclusion of animal trampling, we mainly ascribed the soil recovery in the ungrazed sites to the regeneration of soil structure by root penetration and decay, wetting and drying cycles, and freezing and thawing cycles. In agreement with Proffitt et al. (1995), our results proofed that reduction 141
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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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Die Beweidung beieinflusst besonder
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II List of figures Fig. 2.1. Locati
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measured soil moisture in time stab
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III List of tables Table 2.1. Descr
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1.1 Background Chapter 1 Introducti
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Chapter 1 Introduction is also unce
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Chapter 1 Introduction water in spr
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Chapter 1 Introduction requires the
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Chapter 1 Introduction Krümmelbein
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Chapter 2 Spatial variability of so
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Chapter 3 Spatio-temporal variabili
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Chapter 3 Factors controlling spati
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Chapter 4 Temporal stability of soi
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Y orientation Chapter 4 Temporal st
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MRD(%) MRD(%) 100 80 60 40 20 0 -20
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Soil water content (%) 40 30 20 10
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Chapter 5 Modeling Grazing Effects
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Chapter 5 Modeling Grazing Effects
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