Land use allocation is determined by a variety of local and global drivers impacting agricultural markets. We developed a collaborative effort between two Multisector Dynamics teams to advance capabilities in projecting land use change across multiple spatial scales and also considering interactions between natural and human systems. We coupled a multi-sectoral and multi-regional socio-economic model of the world economy that included details on land use and multiple crops to an open-source downscaling model. The framework enables translation of regional projections of land use to a high-resolution representation of time-evolving land cover. The socio-economic model determines land use allocation at the regional level, given costs of transition, land availability and demand for agricultural goods. The downscaling model is rule-based, distributing the regional land use projection into the grid level, with a prescribed priority among uses as well the proportion of expansion that occurs within grids that already include that land use type. The framework presents great flexibility to add other rules for land cover spatial transition, such as crop suitability, conservation constraints, and climate risks. We applied the framework to 16 global land use scenarios that account for various global and regional drivers of land use, including economic growth, climate impacts on yields, dietary change, population growth, and trade in agricultural commodities, varying the strength of the force up or down from a Business as Usual (BAU) case. Forces were varied separately, and all together. The combination of all forces together when varied up required twice as much land use change in most river-basins around the world than in the BAU scenario. Pasture areas tend to expand more than other land uses under increasing pressures on agricultural expansion, but these changes are not evenly distributed across different river basins. The Amazon, Congo, Mekong and Orinoco basins experience more pasture expansion than others, while the Nile basin experiences strong land shifts toward croplands. These results can imply important changes in carbon storage, soil erosion, chemical use, hydrology, and water quality. The employed framework greatly facilitates interoperability among models and across various spatial scales.