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Thus, for the ap- plication in climate models, both the spatial and temporal distributions of vegetation are required with a high level of detail (Lu and Shuttleworth, 2002).Ībstract.
![equivalent linear method elm flac3d equivalent linear method elm flac3d](http://docs.itascacg.com/flac3d700/_images/103f1059.png)
Vegetation devel- opment and land use/cover heterogeneity have a significant influence on climate model simulations such as predictions of surface temperature and precipitation. How- ever, feedback effects from the land surface to the atmo- sphere are not considered in this study. The importance of land use/cover information is increasing when investigating the interactions between the land surface and the atmosphere (Tian et al., 2004). The new land use approach could improve the model results signif- icantly. The modelled runoff was compared to measured data from the outlet gauge in Achleiten for a 30-year period from 1971 to 2000. The different spatial and tem- poral behaviour of modelled evapotranspiration again affects the water balance for the Upper Danube catchment in case of the three land use classifications. Due to those improve- ments, the simulated monthly evapotranspiration especially in May and August shows large differences in comparison with the simulations using the two possible homogeneous classifications, especially in regions dominated by spring or summer crops respectively. With the new heterogeneous land cover approach, the regional characteristics of arable crops can be addressed with a higher level of detail. There- fore, modelling the evapotranspiration for the Upper Danube catchment with the hydrological model PROMET, the new land use approach was compared to two possible extremes: In one case, the class arable land was interpreted as pure spring crop (winter wheat), whereas in a second case the complete arable land area was assumed to represent a sum- mer crop (maize). The land use/cover scheme strongly affects the sim- ulated evapotranspiration of a hydrological model. Subse- quently, the generated phenological classes were subdivided following statistical data from EUROSTAT for each NUTS region. Thus, phenological classes due to multiseasonal MERIS NDVI im- agery data were compiled in order to distinguish crop types following their different phenological behaviour. The simulation results are evaluated using observed latent heat flux (LE) and runoff data to assess the performance of the BC model in simulating land surface processes at the catchment scale.Ĭover map that uses the high resolution of the CLC classifi- cation but comprises the heterogeneity of arable land. Finally, the proposed model is applied to the Kennet catchment in south- ern England and the fluxes and states of the hydrological cy- cle are simulated for multiple years. This is achieved by randomly sampling the parameter space and extensively running the model in or- der to minimize the differences between observed and simu- lated soil moisture variability at different depths.
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At the point scale, the proposed parameterization is calibrated using observed soil moisture profile data. In this study, the BC model (included in JULES) is applied at two distinct spa- tial scales (i.e. uniform soil column representation using a general soil database as typically applied in land surface models), does not represent any chalk feature. In order to test the proposed parameterization, the BC model is included in JULES (version 4.2), which, by de- fault (i.e. In this context, we propose a new parameterization, namely the Bulk Conductivity (BC) model, as a first step to- wards a simple chalk representation suitable for land surface modelling. However, in- cluding chalk hydrology in large-scale land surface mod- elling using the contemporary dual-porosity concept can be complicated due to the large number of additional param- eters.
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The above-mentioned studies illustrate the importance of representing chalk in land surface modelling.