High-Resolution Data of Human-Water Systems to Advance Large-Scale Hydrologic Modeling

Human alterations to the hydrologic cycle, such as groundwater pumping, surface water diversions, and interbasin transfers, are often the dominant drivers of water availability and stress in the Anthropocene. However, large-scale hydrological models (LSHMs) have historically struggled to represent these anthropogenic fluxes with sufficient granularity, largely due to a scarcity of standardized, open-access data. Consequently, models often rely on coarse estimates or static coefficients that mask critical spatial and temporal heterogeneity.

In this presentation, I will provide an overview of a new suite of high-resolution, open-access datasets that describe water infrastructure and use across the United States at an unprecedented scale. I will highlight three foundational data products: (1) a comprehensive inventory of interbasin water transfers (IBTs) characterizing over 600 projects and their conveyance volumes; (2) the United States Groundwater Well Database (USGWD), which standardizes attributes for over 14.2 million wells to map subsurface infrastructure and aquifer access; and (3) the United States Water Withdrawals Database (USWWD), providing user-level historical time series for nearly 190,000 unique water users across all economic sectors. Collectively, these datasets offer a new empirical basis for parameterizing and validating the "human" components of LSHMs. I will discuss the implications of these data for reducing model uncertainty, specifically in closing local water budgets and characterizing the complex spatial connectivity introduced by infrastructure.

Finally, I will outline current initiatives to expand this data-intensive framework globally. As the field moves from data scarcity to data abundance, the modeling community plays a critical role in shaping how these data are structured and utilized. I will conclude by discussing how the large-scale hydrology community can contribute to and benefit from these emerging global data products to better predict the present and future state of water resources in a changing environment.