Using a data grid to automate data preparation pipelines required for regional-scale hydrologic modeling

Modeling a regional-scale hydrologic system introduces major data challenges related to the access and transformation of heterogeneous datasets into the information needed to execute a hydrologic model. These data preparation activities are difficult to automate, making the reproducibility and extensibility of model simulations conducted by others difficult or even impossible. This study addresses this challenge by demonstrating how the integrated Rule Oriented Data Management System (iRODS) can be used to support data processing pipelines needed when using data-intensive models to simulate regional-scale hydrologic systems. Focusing on the Variable Infiltration Capacity (VIC) model as a case study, data preparation steps are sequenced using rules within iRODS. VIC and iRODS are applied to study hydrologic conditions in the Carolinas, USA during the period 1998–2007 to better understand impacts of drought within the region. The application demonstrates how iRODS can support hydrologic modelers to create more reproducible and extensible model-based analyses. •An approach for data processing to support hydrologic modeling is presented.•The approach uses federated data grids and server-side data processing.•The approach is demonstrated using the Variable Infiltration Capacity (VIC) model.•The demonstration focuses on simulating drought in the Carolinas, USA.