Spatially distributed physically based slope stability models are commonly used to assess landslide susceptibility of hillslope environments. Several of these models are able to account for vegetation related effects, such as evapotranspiration, interception and root cohesion, when assessing slope stability. However, particularly spatial information on the subsurface biomass or root systems is usually not represented as detailed as hydropedo- logical and geomechanical parameters. Since roots are known to influence slope stability due to hydrological and mechanical effects, we consider a detailed spatial representation as important to elaborate slope stability by means of physically based models. STARWARS/PROBSTAB, developed by Van Beek (2002), is a spatially distributed and dynamic slope stability model that couples a hydrological (STARWARS) with a geomechanical component (PROBSTAB). The infinite slope-based model is able to integrate a variety of vegetation related parameters, such as evaporation, interception capacity and root cohesion. In this study, we test two different approaches to integrate root cohesion forces into STARWARS/PROBSTAB. Within the first approach, the spatial distribution of root cohesion is directly related to the spatial distribution of land use areas classified as forest. Thus, each pixel within the forest class is defined by a distinct species related root cohesion value where the potential maximum rooting depth is only dependent on the respective species. The second method represents a novel approach that approximates the rooting area based on the location of single tree stems. Maximum rooting distance from the stem, maximum depth and shape of the root system relate to both tree species and external influences such as relief or soil properties. The geometrical cone-shaped approximation of the root system is expected to represent more accurately the area where root cohesion forces are apparent. Possibilities, challenges and limitations of approximating species-related root systems in infinite slope models are discussed.@en

The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. Consequently, the effect of the root zone parameterization on the runoff prediction of global hydrological or land surface models (hereafter, GHMs) can be quite large. Many studies have found that climate is the most important factor in explaining rooting depths of natural vegetation, and thus outweighs the importance of soil and vegetation type. Most GHMs, however, use only soil maps and look-up tables for root zone properties to parameterize the root zone. This is problematic, as the observations of the root zone may indirectly have some climate properties, but is still likely to contribute to errors as the data is scarce, often incomplete (i.e. not the entire vertical root profile), at the wrong scale (i.e. individual plant vs. ecosystem value vs. grid cell value), and it is uncertain which part of root zone is hydrologically active. Recent studies developed different optimization methods to a priori determine the root zone storage or rooting depth at the global scale. These studies also suggested that their values could potentially be directly exported to other GHMs. In this study we test which root zone storage and rooting depth would be optimal for the global hydrological model PCR-GLOBWB. We want to answer the following questions: • How much do the “best fit” root zone storages and rooting depths differ from each other with different model settings in PCR-GLOBWB? • Are calibrated root zone storage capacities and rooting depths for PCR-GLOBWB similar to root zone storage capacities and rooting depths obtained by other global studies? The optimal root zone parameters follow from taking the parameters that best reproduce the evaporative flux from a state-of-the-art ensemble of satellite remote sensing based gridded evaporation products. We find that the global spatial patterns of maximum root zone storage capacity are quite independent of other parameters in PCR-GLOBWB. These patterns are similar to the patterns found in recent global studies, but the absolute values are not. We believe that the future for GHMs lies in dynamically determining the root zone storage based on logical – climate based – optimization concepts that are tailor-made for each GHM independently. @en