Traditional, mainstream definitions of drought describe it as deficit in water‐related variables or water‐dependent activities (e.g., precipitation, soil moisture, surface and groundwater storage, and irrigation) due to natural variabilities that are out of the control of local decision‐makers. Here, we argue that within coupled human‐water systems, drought must be defined and understood as a process as opposed to a product to help better frame and describe the complex and interrelated dynamics of both natural and human‐induced changes that define anthropogenic drought as a compound multidimensional and multiscale phenomenon, governed by the combination of natural water variability, climate change, human decisions and activities, and altered micro‐climate conditions due to changes in land and water management. This definition considers the full spectrum of dynamic feedbacks and processes (e.g., land‐atmosphere interactions and water and energy balance) within human‐nature systems that drive the development of anthropogenic drought. This process magnifies the water supply demand gap and can lead to water bankruptcy, which will become more rampant around the globe in the coming decades due to continuously growing water demands under compounding effects of climate change and global environmental degradation. This challenge has de facto implications for both short‐term and long‐term water resources planning and management, water governance, and policymaking. Herein, after a brief overview of the anthropogenic drought concept and its examples, we discuss existing research gaps and opportunities for better understanding, modeling, and management of this phenomenon.

The warming climate can considerably affect socioeconomic activities and environmental health conditions in Canada. Climate models play a key role in evaluating the impact of climate change and developing adaption and mitigation strategies corresponding to Canadian regions. This study compares the behavior of climate models participating in the Climate Model Intercomparison Project Phase 6 (CMIP6) with their CMIP5 predecessors in representing a set of climate indices relevant to Canada’s agricultural productivity, infrastructure resilience, and environmental health. Our results show that although CMIP5 and CMIP6 multi‐model ensemble mean values for the considered indices are almost similar, the behavior of individual CMIP5 and CMIP6 models or even the model pairs of the same modeling center can be different across Canada. Moreover, the CMIP6 models do not necessarily outperform CMIP5 in comparison to NOAA and NCEP reanalysis datasets in simulating the annual mean and coefficient of variation values for the indices during the historical period. The comparisons between models’ simulations also reveal that the envelope of estimated values based on individual CMIP6 models does not cover or overlap with their CMIP5 counterparts or even with other CMIP6 models. Therefore, the CMIP6 models with higher number of simulations do not necessarily provide a larger range of projections over Canadian regions. The divergence between CMIP5 and CMIP6 models’ behavior is more obvious under the 8.5 W/m² forcing in the long‐term horizon. Overall, the estimated sign, magnitude, and spatial pattern of changes in the climate indices depend on the considered climate model and forcing scenario.