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as snow. The snow routine predicts up to 15 mm snow depth (Fig. 6a), however, the simulated runoff after air temperature increasing above 0°C is negligible (Fig. 6c). This might relate with that the snow routine does not account for surface runoff from the frozen soil layer since the code cannot consider the subsurface soil freezing and thawing process. In fact, it is likely that surface runoff is generated during snowmelt while soil is fully or at least partially frozen (Fig. 6b). Unexpectedly, the freezing model, which can account for the subsurface freezing and thawing processes, also does not compute surface runoff during winter (Fig. 2c). Instead, we found that the simulated SWC by freezing model is higher than the measured values in the transition time when soil begins to thaw (Figs. 4a and 5a). This implies that the freezing model might overestimate water content and underestimate surface runoff after spring snowmelt. Therefore, the freezing model seems still not sensitive enough to estimate surface runoff accompanied with snowmelt from the soil frozen layer. This might relate to the fact that the freezing model we applied adopts soil surface temperature as the atmospheric boundary condition instead of air temperature, which neglects the lag-effects of energy transfer. Consequently, the freezing model may incorrectly partition all the snowmelt into infiltration as both soil thawing and snow melting happen simultaneously. Therefore, to solve this, a transferable and double-layered boundary condition (e.g., one accounting for air temperature and other accounting for considering soil temperature) should be introduced. Additionally, the gradual release of water from the frozen soil profile also might reduce the maximum rate of runoff. 130 In contrast to the freezing model, an ‘‘implicit’’ frozen soil module that used in other studies might totally stop water infiltration inside the soil (Mitchell and Warrilow, 1987) by specifying that the meltwater has to run off when snow melts while soil is still frozen. However, the soil ice is subsequently melting when the snow is melting (Luo et al., 2003). Thus the frozen soil layer moves downward and leaves the upper soil layer available for infiltration. In contrast to this, an ‘‘explicit’’ frozen soil module like the freezing model that we used is theoretically reasonable as it only reduces the infiltration rate based on soil temperature, soil
Chapter 6 Modeling of Coupled Water and Heat Transfer in Freezing and Thawing Soil ice content, and soil hydraulic properties (Luo et al., 2003). However, the reduction in infiltration capacity owing to the blocking effects of ice is possibly underestimated by the current freezing model. Snow depth (mm) Temperature ( o C) Runoff (mm) 16 14 4 2 0 30 20 10 0 -10 -20 -30 0.24 0.20 0.16 0.12 0.08 0.04 0.00 a b c 9-Feb 21-Mar 30-Apr 9-Jun 19-Jul 28-Aug 7-Oct 16-Nov 26-Dec Air Soil 9-Feb 21-Mar 30-Apr 9-Jun 19-Jul 28-Aug 7-Oct 16-Nov 26-Dec Snow routine Freezing model 9-Feb 21-Mar30-Apr 9-Jun 19-Jul28-Aug 7-Oct 16-Nov26-Dec Time (days) Rainfall Fig. 6.6. Rainfall, measured air and soil temperature, simulated snow depth and runoff during the whole year of 2006. 60 40 20 0 Rainfall (mm) Frozen soil was expected to have a great influence on the runoff simulation (Mitchell and Warrilow, 1987; Pitman et al., 1999). But in agreement with our study, Pitman et al. (1999) did not obtain the improvement of runoff simulation when soil ice was included in their model. Cherkauer and Lettenmaier (1999) also found that the frozen soil module had a relatively small effect on runoff. 131
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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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Page 173 and 174: Curriculum Vitae M.Sc. Ying Zhao Of
Page 175: Schriftenreihe des Instituts Neuere
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