Global land surface processes play an important role in the earth system through land-atmosphere exchanges of energy, water, and trace gases and by providing fresh water and nutrients to oceans. For this reason, global earth system models (ESMs) include sophisticated land models. However, the governing equations in the vertical one-dimensional (1-D) direction only are solved for these land processes along with a simple river routing. The increase in computational power enables us to more accurately represent important small-scale horizontal hydrological processes. A grand challenge in hydrological science is therefore the efficient high-resolution hydrological modeling. This challenge is further complicated by computational design limitations since current ESMs use vertical columns representative for a given coarse (~1 deg) grid box. Different from conceptual approaches currently used in ESMs, we have developed a preliminary framework to represent the horizontal hydrological response at the 1 km pixel level using a physically based approach, while taking sub-pixel information into account (e.g. hillslopes, riparian zones, wetlands, river network). For a given ESM grid-box the 1 km pixel information is then aggregated to enable interaction with the vertical soil column in the grid box and hence with the atmosphere in ESMs. However, to be able to run this model, high-resolution datasets are needed as input, which are not generally available at present. Therefore, we have also developed global 1-km datasets of depth to bedrock information, river network, riparian zone and hillslope width delineation, and vegetation variations using global high-resolution elevation (DEM) and satellite (MODIS) information. Once finalized, these datasets will also be available to the community. In this presentation, we will discuss our global 1 km hybrid 3-D hydrological model development, software engineering issues, and the associated global land dataset development.