AWI GitHub
The AWI GitHub page hosts several open source projects and pages with more information about various models, data, and tools.
Data Access
The Cooperative Institute for Research to Operations in Hydrology (CIROH) has provideda guide on how to access various data sets and resources. The page linked below describes how to access several data sets, as well as provides links to other resources.
Tools
NextGen In A Box
NextGen In A Box (NGIAB) is a containerized version of the NextGen National Water Resources Modeling Framework. The goal is to make the NextGen National Water Resources Modeling Framework more accessible to researchers. NGIAB is a community version of the National Water Model.
NOAA Water Node
The Water Node website is a collaborative effort between CIROH, NOAA CoastWatch, and the National Water Center. The purpose of the website will be to intake and disseminate remote sensing data relevant to hydrological modeling, prediction, and analysis. The data will come from a variety of sources from within NOAA, CIROH, as well as potentially other agencies and companies. This data will be disseminated to CIROH researchers, NWC operations, and the general public.
Research-Oriented Streamflow Evaluation Tool
Research-Oriented Streamflow Evaluation Tool (ROSET) is a Python-based, user-friendly, fast, and model agnostic streamflow evaluator tool. This tool can be used to evaluate any hydrological model that uses NHDPlus dataset. It allows a user to evaluate the performance of a hydrological model at the collocated USGS gauges and NHDPlus stream reaches. This tool helps visualize the results and investigate the model performance interactively.
Tools for Exploratory Evaluation in Hydrologic Research
Tools for Exploratory Evaluation in Hydrologic Research (TEEHR) is a python tool set for loading, storing, processing and visualizing hydrologic data, particularly National Water Model data, for the purpose of exploring and evaluating the datasets to assess their skill and performance.
TETHYS – NWM Research Apps Portal
Comprised of a large technologically and topically diverse group of scientists, CIROH and NOAA NWM researchers require a means to organize, catalog, coordinate, and share research data products, tools, visualizations, and interactive software applications in an accessible, consistent, and intuitive manner. This project aims to address this need by building and seeding a web-based catalog of interactive web applications, notebooks, software tools, and learning modules that demonstrate and provide access to NWM modeling advances, datasets, visualizations, and information synthesis innovations.
HydroServer
HydroServer is an open-source software stack with functionality for collecting, managing, and sharing operational hydrologic data – e.g., time series of hydrologic observations from fixed monitoring sites like streamflow gages. HydroServer development for CIROH is focused on creating an enhanced, national-scale stream gage network to make more data available to operational modeling.
Scientific Models
National Snow Model
The National Snow Model incorporates ground-based snow measuring sites, remotely-sensed snow cover information, and an artificial neural network to provide point estimations of snow water equivalent. The network was trained on historical data from NASA’s ASO missions, divided into regions, and then a LightGBM gradient boosting framework was used to preform recursive feature elimination to produce an efficient feature selection and region-specific model. The class contains the required functions for downloading data, pre-processing, running inference, and producing visualizations.
Streamflow Evaluator
The streamflow evaluation tool (ROSET) compares modeled streamflow to in situ USGS monitoring sites, with interactive visualizations supporting an in-depth analysis.
Machine Learning Water Systems Model
This machine learning workflow demonstrates a framework to function as a digital twin of a systems dynamics model for urban water system seasonal water system reliability, resilience, and vulnerability analysis.