Landscape evolution modeling is the most common approach to predict the occurrence of bedrock erosion, sediment transport and depositional modeling at catchment scales. In the current study, Landlab (Landscape Evolution Model) is used in conjunction with components for evaluating fluvial erosion, hillslope evolution, weathering, and other surface processes over the entire catchment area. Landlab is a flexible, open source modeling framework written in Python allowing efficient model building and hypothesis testing across many sub-disciplines in earth science (Hobley, Adams et al. 2017). SPACE (stream power with alluvium conservation and entrainment) model is used for evaluating simultaneous bedrock erosion and sediment entrainment over two dimensional square grids in Landlab. SPACE is a component in Landlab modeling toolkit that allows free transition between detachment limited and transport limited behavior of bedrock erosion and sediment entrainment in fluvial environment (Shobe, Tucker et al. 2017).
Also the landscape evolution processes are strongly dependent on other parameters namely, vegetation, climate, and tectonic uplift. Hence, the effects of temporally variable climate (mainly rainfall) and vegetation cover will be studied over the model domain for a variety of tectonic uplift rates over smaller time periods (for seasonal variations) and Milankovitch cycles (for longer periods). The models will be then validated and applied to the field in Chilean Andes in South America and Ammer Catchment in South-West Germany.
The study finally aims to the reconstruction of the depositional sequences of sediment layers with respect to depositional age and grain size distribution as a tool to delineate possible aquifers.
