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grazing for a southern caldenal soil in Argentina. However, we also found that soil physical functions had been improved after fenced for a longer period (e.g., 25 yr in UG 79), as mirrored by a decrease in bulk density accompanied by an increase of total pore volume. Processes contributing to the natural recovery of physically degraded soil in the ungrazed sites might include reduction of animal trampling, earthworm burrowing, root penetration and decay, wetting and drying cycles, and freezing and thawing cycles (Drewry et al., 2006). Our results therefore suggests that reduction of grazing intensity could improve soil functions again, which was in agreement with Proffitt et al. (1995), who found that natural recovery of soil physical properties under pasture happened relatively rapid. 106 Grazing influenced hydraulic parameters, i.e., decreasing θs, θr, α, and Ks due to compaction effects. These grazing-induced changes were parameterized by the coupled water and heat model HYDRUS-1D. To account for the special conditions in grazed semi-arid grassland systems we modified root growth dynamics and boundary conditions according to the different grazing intensities. Particularly, three main improvements were underlined. Firstly, we ran root growth model to reflect dynamics of plant water uptake, which was important because models designed to simulate agriculture management were normally limited to simulate crop growing. Secondly, estimate of the intercepted water provided an accurate boundary condition. Finally, the ET partitioning, based on the actual measurements, was essential for the prediction of plant transpiration since it was only determined by root water extraction function related with potential transpiration in HYDRUS code. After the model parameterization, there was a good matching between measured and simulated soil moisture and temperature at each site. This indicated that HYDRUS-1D model was suitable tool to reflect the grazing effects on water and heat fluxes. The LDP model was better than the NN model to predict the water fluxes as it reflected the soil structural changes affected by soil compaction. This result was consistent with Richard et al. (2001), who
Chapter 5 Modeling Grazing Effects on Coupled Water and Heat Fluxes in Inner Mongolia Grassland distinguished textural and structural fractions for the soil pore space and found that soil compaction mainly affected the structural pore space. This can explain why the NN model, that only accounted for soil textural fraction, can not make an accurately predictions of compaction effects. Therefore, we consider that in situ measurements of θ(h) and K(h) are necessary to reflect the soil structural changes induced by land management when process-oriented modeling techniques is used to evaluate the influences of land management. Moreover, we showed both water and heat transports as a function of grazing managements and therefore coupled water flow with heat transport. However, we emphasized particularly on aspects of water fluxes (detailed in the next section) because the heat stress was weaker for grass growth than the water stress in this grassland (Zhang et al., 2005). Grazing Effects on Water Budget in Semi-arid Grassland The components of ET, i.e., interception, transpiration and evaporation significantly varied with grazing intensity, although ET itself was only slightly influenced by grazing as shown by other studies (e.g., Bremer et al., 2001; Chen et al., 2007). Compared with the grazed sites, interception and transpiration increased and soil evaporation decreased in the ungrazed sites where soil was covered more completely by live or dead plant materials. In contrast to this, evaporation in the grazed sites simultaneously increased due to larger bare ground areas. Consequently, soil water storage decreased with increasing grazing intensity. Parameters that influence the simulation of water budgets were soil hydraulic properties, plant characteristics and weather conditions, of which the latest one was assumed identical for all sites, while the other parameters were grazing-dependent. Because of the grazing-induced changes, overall, water budget in Inner Mongolia grassland was significantly influenced by grazing. Firstly, grazing decreased hydraulic conductivity because of animals trampling, especially in the topsoil (Wang and Ripley, 1997; Krümmelbein et al., 2006). Combined with weakly intercepted water, the infiltration excess runoff was most 107
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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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Page 85 and 86: Chapter 4 Temporal stability of soi
Page 89 and 90: Y orientation Chapter 4 Temporal st
Page 93 and 94: MRD(%) MRD(%) 100 80 60 40 20 0 -20
Page 101 and 102: Soil water content (%) 40 30 20 10
Page 105 and 106: Chapter 5 Modeling Grazing Effects
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Page 135 and 136: Chapter 6 Modeling of Coupled Water
Page 159 and 160: Chapter 7 General discussion and co
Page 167 and 168: References Chapter 7 General discus
Page 171 and 172: 8. ACKNOWLEDGMENTS Firstly I would
Page 173 and 174: Curriculum Vitae M.Sc. Ying Zhao Of
Page 175: Schriftenreihe des Instituts Neuere
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