Advancing the Representation of Human Actions in Macro-Scale Hydrologic Models

Characterizing the impact of human actions on terrestrial water fluxes and storages at multi-basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the inclusion of human-water interactions in macro-scale hydrologic models is still rather crude, fragmented across models, and often implemented at coarse resolutions that cannot accurately capture local water management decisions. In this work, we focus on the state-of-the-art and argue that the increasing interest in hyper-resolution models (~0.1-1 km) and the availability of new remotely-sensed observations can help change the status quo. This would require addressing three key challenges, namely creating datasets that describe human actions with an unprecedented level of detail, improving the accuracy with which anthropogenic impacts on water quality and quantity are represented in hydrologic models, and ensuring that models remain reliable and computationally efficient. These challenges and opportunities are exemplified using case studies from multiple river basins.