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temperature is a main factor in determining biological processes, e.g. annual carbon uptake in the grassland ecosystem (Liu et al., 2007). As land surface schemes begin to simulate carbon and nitrogen fluxes from biological processes, they need to get soil freezing and soil temperature correctly. Our results suggest that it is possible to do that since the freezing model can provide an accurate temperature simulation. 144 However, the freezing model seems to overestimate water content after spring snowmelt and thus underestimate runoff. We considered that it is reasoned that the freezing model adopted soil surface temperature instead of air temperature as the atmospheric boundary condition in the numerical algorithm of the freezing model. Consequently, the model incorrectly partitions all the snowmelt into infiltration as soil thawing and snow melting happen simultaneously. At this moment, the complicated interactions between the soil surface microclimate and physical processes is not solved. Obviously the surface runoff algorithm in the freezing model is not sensitive enough. In addition, the Theta-probe that we used cannot measure the ice content under frozen condition, which also limited the verification of modeled ice content in this study. Moreover, the rain gauge just can record the snow-water equivalent, which obviously omitted the time of snow falling and melting. We suggests that the seasonal water balance, especially considering rainfall water stored as snow, snow drift and the lateral flow on frozen soil layers need to be investigated further. Conclusions 1. Soil hydraulic, thermal and mechanical properties were interrelated and modified by grazing. Especially, multivariate geostatistical analysis revealed scale-dependent correlations among them at multiple spatial scales. 2. Soil compaction by sheep trampling resulted in a homogenous spatial distribution of soil properties, which increased soil vulnerability against water and wind erosion.
Chapter 7 General discussion and conclusions 3. After the long-term exclosure (~ 25 yr), grassland soils showed distinct signs of recovery from grazing-caused damages in hydraulic as well as mechanical aspects. 4. The temporal stability concept, linked with a hydraulic model, provided a useful tool for sampling strategies and verifications of hydraulic process. 5. The modified hydraulic model HYDRUS was successful in simulating the coupled transport of water and heat in the investigated rangeland ecosystems. The model results showed that intense grazing deteriorated soil functions, consequently reduced the plant available water and thus grassland productivity. 6. An extended freezing model is validated with measured data, which provide a basis for simulations of snow hydrology and soil freezing and thawing processes. Outlook It is still a challenge to estimate fluxes at different spatial scales. Especially, how hydraulic model, e.g. HYDRUS-1D/2D can be applied to a large area, e.g. Xinlin River catchment where the MAGIM project took place with the knowledge of scaling (regionalization, transferability and upscaling). The monitoring (e.g. soil hydraulic properties, water content) in the deep soil must be determined not only for water use efficiency considering water use by roots deep penetrating into deeper soil layers (e.g. hydraulic lift) but also for the verification of model. Improvement of boundary conditions, respectively, an assessment of regional heterogeneity of rainfall is vital for model validations. 145
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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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