Droughts and their hydrological consequences are a major threat to food security throughout the world. In arid and semiarid regions dependent on irrigated agriculture, prolonged droughts lead to significant and recurring economic and social losses. In this Feasibility Stage 1 project, the assembled research and end-user team presents a plan for integrating multi-resolution, remote sensing-based drought indices into an online, cloud computing-based visualization platform. We have selected to use a well-established water stress index to conduct drought monitoring and decision-maker engagement at multiple scales, with a focus on drought-prone areas in northwest Mexico and northeast Brazil. In the project, we will expand the capabilities of the secure, cloud-based geospatial platform to incorporate drought monitoring and change detection using frequent, high-resolution remote sensing data and hydrologic model outputs at the basin-level. In addition, we will populate the online visualization platform with a range of new geospatial data to improve drought-related information. We will carry out basin-level applications using two hydrologic models in study watersheds in Mexico and Brazil to demonstrate the feasibility of providing end-user specific drought products. Both models have track record of hydrologic applications in semiarid areas of Mexico and Brazil. The cloud-based visualization platform is designed to engage stakeholders and decision-makers in local to regional problems concerned with natural resources and risk management. As such, iterative feedback with end-users will allow the research team to fine-tune the drought products, their delivery and presentation, and the analytical tools available during the course of the project. We expect to innovate in both the cloud-based drought delivery mechanism and in the process by which we co-develop products and knowledge with end-users. As a result, the research and end-user team hypothesizes that the cloud-based platform will be a game-changing approach for drought monitoring, assessment and prediction at a range of scales.