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Data Assimilation for the Modeling Engines and Framework Prototypes that use BMI for connecting models

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NWC-CUAHSI-Summer-Institute/data_assimilation_with_bmi

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Data Assimilation for Nextgen with BMI

This repository contains two methods of data assimilation currently under development with potential applications for the Nextgen Water Modeling Framework Prototype (https://github.com/NOAA-OWP/ngen).

  • Data assimilation for the Conceptual Functional Equivalent model (CFE; https://github.com/NOAA-OWP/cfe). This method uses observed streamflow values to update the states of CFE, which improves the rainfall-runoff estimate from the hydrofabric catchments. This method has been developed by groups during the 2022 and 2023 Summer Institute.
  • Data assimilation for the routing network. This method updates the streamflow across the entire network of routing links. This method has been developed by the 2023 Summer Institue.

Installation

There are two main notebooks to run the DA methods.

  • DA-Routing/carmel_muskingum_cunge.ipynb
  • example_run_da_CFE/my_run.ipynb

Dependencies

There are quite a few libraries that you'll need to install, and you can do so with the command: pip install -r requirements.txt

Installation

Detailed instructions on how to install, configure, and get the project running. This should be frequently tested to ensure reliability. Alternatively, link to a separate INSTALL document.

Usage

There will be a notebook which demonstrates how to run the code outside of the Nextgen Framework.
There will be some code explaining how to run this within the Nextgen Framework

How to test the software

If the software will include automated tests.

Known issues

  • Not exactly sure where to host code for different models/modules that will be used in the examples.
  • CFE data assimilation is not quite stable, need to work out some sensitivity issues.

Getting help

If you have questions, concerns, bug reports, etc, please file an issue in this repository's Issue Tracker.

Getting involved

Please see our contribution instructions CONTRIBUTING.


Open source licensing info

  1. TERMS
  2. LICENSE

Credits and references

  • Timilsina et al. 2023. “Data Assimilation in the Nextgen Framework for Improved Streamflow Predictions”. Upcoming 2023 AGU Fall Meeting.
  • Foroumandi et al., 2023. “Development of an Ensemble Hydrologic Data Assimilation within NextGen Framework”. Upcoming 2023 AGU Fall Meeting.
  • Deardorff E., A. Modaresi Rad, et al. (2022). National Water Center Innovators Program - Summer Institute, CUAHSI Technical Report, HydroShare, http://www.hydroshare.org/resource/096e7badabb44c9f8c29751098f83afa
  • Wolkeba F. T., K. O. Ekpetere, M. S. Abualqumboz , and Z. J. Butler (2022). Data assimilation of USGS streamflow in the Nextgen Framework
  • Abualqumboz et al. 2022. “Data Assimilation of USGS Streamflow Data in the Nextgen Framework”. AGU Fall Meeting

Some old figures

This figure describes the difference between the naive NWM data assimilation method and this BMI-based general data assimilation framework.

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