7 posts tagged with "Cloud Services"

A screenshot of the HydroShare resource page for Jupyter Notebooks for the Retrieval of AORC Data for Hydrologic Analysis.

The Analysis of Record for Calibration (AORC) dataset is recognized as a high-value resource for the CUAHSI and CIROH community. This dataset is hosted by NOAA via Amazon Web Services (AWS) and is available in two primary formats: a latitude-longitude gridded dataset and the National Water Model (NWM) projected dataset, part of the NWM Retrospective archive. To enhance accessibility and illustrate analysis capabilities, we developed four user-friendly Jupyter Notebooks that enable data retrieval for both specific points of interest and spatial domains defined by shapefiles:

• AORC_LL_PointRetrieval.ipynb: For retrieving and aggregating data from the latitude-longitude gridded dataset for a specific point using geographic coordinates.
• AORC_LL_ZoneRetrieval.ipynb: For retrieving and aggregating data from the latitude-longitude gridded dataset for an area defined by a polygon shapefile.
• AORC_NWMProj_PointRetrieval.ipynb: For retrieving and aggregating data from the NWM projected dataset for a specific point using geographic coordinates.
• AORC_NWMProj_ZoneRetrieval.ipynb: For retrieving and aggregating data from the NWM projected dataset for an area defined by a polygon shapefile.

These Jupyter Notebooks, containing instructions and Python code to access the data, enable researchers to retrieve AORC data from AWS. From there, the notebooks offer options to subset and aggregate the data over user-defined time intervals (beyond the original hourly resolution) and spatial area. These serve as examples for how you could write or modify code to access AORC data in your work. The notebooks are publicly available on HydroShare and are compatible with JupyterHub computing platforms such as CIROH 2i2c JupyterHub linked to HydroShare.

To use these notebooks, go to the HydroShare resource, select "Open With" at the top right, and choose "CIROH 2i2c JupyterHub". This will copy the resource contents (notebooks and data) into the CIROH JupyterHub environment, where you can open and work through them to access the data. Note that you will need a CUAHSI HydroShare account to access "Open With" in HydroShare, and you will also need to request CIROH-2i2c JupyterHub access using a GitHub account.

Our work also includes a comparative analysis of the two AORC datasets with a summary of findings. While we mostly observed small differences, mainly due to projections, users should be aware of potential discrepancies between the datasets.

By providing these user-friendly tools and highlighting the characteristics of both AORC datasets, our work aims to support and facilitate more efficient hydrological and climate-related research within the CUAHSI and CIROH community.

References:​

• Salehabadi, H., D. Tarboton, A. Nassar, A. M. Castronova, P. Dash (2025). Jupyter Notebooks for the Retrieval of AORC Data for Hydrologic Analysis, HydroShare, http://www.hydroshare.org/resource/72ea9726187e43d7b50a624f2acf591f
• The development versions of these notebooks are available on GitHub: https://github.com/CUAHSI/notebooks in the Data Access Examples / AORC - Retrieval of AORC Data for Hydrologic Analysis folder.
• Patel, A., A. Castronova (2025). CIROH 2i2c JupyterHub, HydroShare, http://www.hydroshare.org/resource/2dd1ac86e8854d4fb9fe5fbafaec2b98

Predicting water flow with precision across the vast U.S. landscape is a complex challenge. That's why Song et al. 2024 developed δHBV2.0, a cutting-edge hydrologic model. It’s built with high-resolution modeling of physics to deliver seamless, highly accurate streamflow simulations, even down to individual sub-basins. It's already proven to be a major improvement, performing better than older tools at about 4,000 measurement sites. We also provide a comprehensive 40-year water dataset for ~180,000 river reaches to support this.

Penn State research group pushed δHBV2.0 further, training it with even more detailed river data and integrating other trusted models, aiming to make it a key part of the NextGen national water modeling system (as a potential NWM3.0 successor). But here’s a common hurdle: making powerful scientific tools like this easy and reliable for everyone to use within a larger framework can be tough. Setup issues, runtime errors, and inconsistent results can frustrate users.

NGIAB stepped in to solve exactly this problem. Team has taken the complexity out of using the operations-ready models within NextGen by creating one unified, reliable package. Thanks to NGIAB, users don't have to worry about tricky setups or whether the model will run correctly. NGIAB ensures that our models are compatible everywhere and, most importantly, that they run exactly as designed, consistently and faithfully, every single time, no babysitting required. This means users get the full power of our advanced modeling, without the headaches.

Pennsylvania State University (PSU) researchers have been leveraging CIROH Cyberinfrastructure to tackle complex hydrological modeling challenges. This post highlights their innovative approach using the Wukong computing platform in conjunction with Amazon S3 bucket storage to efficiently process and analyze large-scale environmental datasets. 🚀

Several important historical and ongoing National Water Model (NWM) datasets are now available on Google Cloud BigQuery, which makes them queryable through SQL using Google Cloud console. Some of these data sets are also accessible through an API (e.g. using Python). These datasets and their current status are as follows:

This month, we are excited to showcase two case studies that utilized our cyberinfrastructure tools and services. These case studies demonstrate how CIROH's cyberinfrastructure is being utilized to support hydrological research and operational advancements.

1. ngen-datastream and NGIAB​

Welcome to the January edition of the CIROH DocuHub blog, where we share the latest updates and news about the Community NextGen project monthly. NextGen is a cutting-edge hydrologic modeling framework that aims to advance the science and practice of hydrology and water resources management. In this month's blog, we will highlight some of the recent achievements and developments of the Community NextGen team.

We've released NGIAB v1.1.0! This release fixes issues:

• #21
• #67
• #44

More info: https://github.com/CIROH-UA/NGIAB-CloudInfra/releases/tag/v1.1.0

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