This HydroShare resource accompanies the journal article, “A cloud-based JupyterHub platform for community research with the NextGen water resources modeling framework,” published in Environmental Modelling & Software. The resource provides the datasets, workflows, notebooks, and supporting materials used in the study to facilitate reproducibility, collaboration, and community-based research with the NextGen water resources modeling framework. The paper is available at: https://doi.org/10.1016/j.envsoft.2026.107031

This HydroShare resource delivers a complete, modular workflow for implementing the Next Generation Water Resources Modeling Framework (NextGen) using cloud-based or containerized computing environments. The workflow guides users through each key component of a research-scale hydrologic modeling application, including model input data preparation, model configuration and execution, calibration, and performance evaluation.

To run this workflow, users must launch the resource within an interactive computing environment. From the HydroShare "Open With" web app connector, select "CIROH-2i2c JupyterHub", then choose the pre-configured "CIROH Community NextGen Hub" image. This environment includes all required NextGen tools and dependencies to ensure consistent, reproducible execution.

The workflow is organized into five interoperable Jupyter Notebooks that can be executed independently or as a full end-to-end sequence:

1. NextGen Data Preparation – Subsets the hydrofabric for a user-defined Area of Interest (AOI), generates meteorological forcing data, and creates model configuration files and realizations for CFE and Noah-OWP model components.

2. NextGen Run – Executes the NextGen model using default configurations to establish baseline simulation performance.

3. NextGen TEEHR Evaluation – Compares simulated streamflow results with USGS observations and the National Water Model Retrospective Analysis v3.0 using TEEHR (Tools for Exploratory Evaluation in Hydrologic Research).

4. NextGen Output Analysis – Visualizes water balance components and other model outputs for interpretation and post-processing.

5. NextGen Calibration – Applies SPOTPY-based optimization to improve model performance through automated streamflow calibration.

A lightweight Python wrapper, pyngiab.py, streamlines interaction with the NextGen model engine by managing configuration loading, model execution, and output organization directly from the notebooks.

Supplementary Python utility scripts support data subsetting, visualization, calibration, programmatic execution, and reproducible model management. Together, these components establish a transparent, adaptable, and fully traceable workflow to support collaborative hydrologic research, model testing, and community-driven advancement of the NextGen framework.