Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of largescale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human-water interface in hydrological models.

During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether thesemodels are suitable to capture hydrological drought, in terms of runoff, on a global scale. Amultimodel ensemble analysis was carried out to evaluate if 10 such large-scalemodels agree on major drought events during the second half of the twentieth century. Time series of monthly precipitation, monthly total runofffrom 10 global hydrologicalmodels, and their ensemblemedian have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoffand smallest in regions with high runoff. In vast regions, correlation between runoffdrought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoffdrought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoffresponse to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoffresponse was partly overcome and delay in drought propagating from meteorological drought to drought in runoffwas included. Finally, an ensemble of models also allows for consideration of uncertainty associated with individual model structures.