This article originates from the theoretical and empirical characterization of factors in the World Trade Model (WTM), see Duchin (2005). It first illustrates the usefulness of this type of model for water research to address policy questions related to virtual water trade, water constraints and water scarcity. It also illustrates the importance of certain key decisions regarding the heterogeneity of water and its relation to the technologies being employed and the prices obtained. With regard to WTM, the global economic input–output model in which multiple technologies can produce a “homogeneous output”, Steenge et al. (2018) showed that two different mechanisms should be distinguished by which multiple technologies can arise, i.e., from “technology-specific” or from “shared” factors, which implies a mechanism-specific set of prices, quantities and rents. We discuss and extend these characterizations, notably in relation to the real-world characterization of water as a factor (for which we use the terms technology specific, fully shared and “mixed”). We propose that the presence of these separate mechanisms results in the models being sensitive to relatively small variations in specific numerical values. To address this sensitivity, we suggest a specific role for specific (sub)models or key choices to counter unrealistic model outcomes. To support our proposal we present a selection of simulations for aggregated world regions, and show how key results concerning quantities, prices and rents can be subject to considerable change depending on the precise definitions of resource endowments and the technology-specificity of the factors. For instance, depending on the adopted water heterogeneity level, outcomes can vary from relatively low-cost solutions to higher cost ones and can even reach infeasibility. In the main model discussed here (WTM) factor prices are exogenous, which also contributes to the overall numerical sensitivity of the model. All this affects to a large extent our interpretation of the water challenges, which preferably need to be assessed in integrated frameworks, to account for the main socioeconomic variables, technologies and resources.