Published July 1, 2022 | Version V2

RRR/RAPID input and output files corresponding to "Underlying Fundamentals of Kalman Filtering for River Network Modeling"

  • 1. Jet Propulsion Laboratory, California Institute of Technology
  • 2. University of Massachusetts Amherst
  • 3. Princeton University
  • 4. University of Saskatchewan
  • 5. Northeastern University
  • 6. NASA Goddard Space Flight Center

Description

Corresponding peer-reviewed publication

This dataset corresponds to all the RRR/RAPID input and output files that were used in the study reported in:

  • Emery, C. M., C. H. David, K. M. Andreadis, M. J. Turmon, J. T. Reager, and J. M. Hobbs (2020), Underlying Fundamentals of Kalman Filtering for River Network Modeling, Journal of Hydrometeorology, 21, 453-474, DOI: 10.1175/JHM-D-19-0084.1.

When making use of any of the files in this dataset, please cite both the aforementioned article and the dataset herein. 

Known bugs and limitations in this dataset or the associated manuscript.

In the final version of the published manuscript, Figure 5a, Figure 5b, Figure 5c, and Figure SF1 are inaccurate.  The issue in these figures is that they were all prepared with an incorrect indexing relating observed and simulated discharge, hence observations at any one location were consistently being compared to simulations at another different location.  As a result, all values of "measured" discharge errors (i.e. Bias, STDE, and RMSE) are incorrect.  This issue did not affect the values of "estimated" errors, nor did it affect all values of the Nash-Sutcliffe effeciency that are presented.  The figures published in the manuscript can all be recreated using the files in which "BUG_DO_NOT_USE" was appended to the name.  Correct figures can also be created using corresponding file names that were not so appended. 

Note that corrected versions of Figure 5a, Figure 5b, Figure 5c, and Figure SF1 all retain the same strong linear relationships that are discussed in the paper.  The slope of the daily discharge STDE trend initially reported as \(\alpha = 0.3876\) in Figure 5c changes to \(\alpha = 0.4507\) after correction.  The resulting value of the ideal inflation factor hence changes from \(I = {1 \over 0.3876} \approx 2.58\) to \(I = {1 \over 0.4507} \approx 2.22\). This updated ideal inflation factor has no impact on the conclusions reached in the manuscript because it remains closer to \(I = 2.58\) than to \(I = 1\) or \(I = 5\), i.e. the three values that were evaluated.

Additionally, a faulty version 1.3.1 of the Python toolbox netCDF4 led to incorrect interpretation of _FillValue in which every data point of value greater than _FillValue was interpreted as masked. This created discrepancies in the following three files, which were updated between V1 and V2 of this dataset: "timeseries_rap_exp01.csv", "timeseries_rap_exp18.csv", and "stats_rap_exp18.csv". Faulty versions of the same files have "BUG_NETCDF4" appended to their names. Correct files have been recreated with file names that were not so appended. 

Files

catchment_Reg12.zip

Files (10.4 GB)

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Additional details

Related works

Cites
Journal article: 10.1175/JHM-D-19-0084.1 (DOI)
Software: 10.5281/zenodo.3236649 (DOI)
Software: 10.5281/zenodo.593867 (DOI)