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SCHRIFTENREIHE Institut für Pflanzenernährung und Bodenkunde ...

SCHRIFTENREIHE Institut für Pflanzenernährung und Bodenkunde ...

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1.2 State of the art<br />

Given the vital importance for the production of live stock and the environmental<br />

changes, it is crucial to have a thorough <strong>und</strong>erstanding of the mechanisms that<br />

maintain or change the ecosystem in response to the changes of land<br />

management. In order to develop sustainable management strategies, it is<br />

essential to investigate the processes emerging from pasture practices. Since<br />

many of the rangelands are located in arid or semi-arid areas, water is one of the<br />

key variables determining the fate of ecosystem situated in such regions.<br />

Therefore, the <strong>und</strong>erstanding of the hydrologic processes is critically important<br />

(Sugita et al., 2007). Especially, the identification and prediction of soil moisture<br />

patterns (spatio-temporal organization) at different scales are necessary to<br />

<strong>und</strong>erstand <strong>und</strong>erlying processes controlling the hydrological response of a<br />

region or even catchment (Grayson et al., 2002; Lin et al., 2006).<br />

It has been accepted that environmental variables that are used to evaluate an<br />

ecosystem, e.g. soil properties, are spatial dependent (Goovaerts, 1998). The<br />

spatial dependency is commonly characterized and quantified by geostatistical<br />

methods such as autocorrelation and variogram analysis. Furthermore,<br />

multivariate geostatistics can deal with multivariate spatial data to classify the<br />

correlation of regionalization variables and to define scale-dependent<br />

relationships (Goovaerts, 1992). This is needed to extrapolate or interpolate<br />

variables from different spatial scales when employing either upscaling or<br />

downscaling procedures (Western et al., 1999). For instance, when matter fluxes<br />

on various scales are investigated, it could be very useful to upscale water flux<br />

with the aid of physically-based hydrological models from plot to catena and<br />

finally to a regional scale (Fig. 2).<br />

Furthermore, it is possible to select monitoring site(s) representing the true field<br />

mean conditions in terms of temporal stability concept. If this is assumed, it is<br />

suitable to turn to the detailed scenario analysis on the plot scale to evaluate<br />

effects of grazing on hydraulic process after investigating a general natural<br />

process in the regional or field scale. In addition, a hydrological model normally<br />

selected the modeled location without a prior analysis so that the modeled result<br />

2

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