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Evaluation of Retrospective National Water Model Soil Moisture and Streamflow for Drought-Monitoring Applications

  • M. Hughes
  • , D. L. Jackson
  • , D. Unruh
  • , H. Wang
  • , M. Hobbins
  • , F. L. Ogden
  • , R. Cifelli
  • , B. Cosgrove
  • , D. DeWitt
  • , A. Dugger
  • , T. W. Ford
  • , B. Fuchs
  • , M. Glaudemans
  • , D. Gochis
  • , S. M. Quiring
  • , A. RafieeiNasab
  • , R. S. Webb
  • , Y. Xia
  • , L. Xu
    • National Oceanic and Atmospheric Administration
    • University of Colorado Boulder
    • University of Illinois at Urbana-Champaign
    • University of Nebraska-Lincoln
    • National Center for Atmospheric Research
    • Ohio State University
    • Inc.

    Research output: Contribution to journalArticlepeer-review

    17 Scopus citations

    Abstract

    The National Oceanic and Atmospheric Administration (NOAA)’s National Water Model (NWM) provides analyses and predictions of hydrologic variables relevant to drought monitoring and forecasts at fine time and space scales (hourly, 0.25–1 km). We present results exploring the potential for NWM soil moisture and streamflow analyses to inform operational drought monitoring. Both agricultural and hydrologic drought monitoring rely either explicitly or implicitly on an accurate representation of anomalous soil moisture values. Much of our analysis focuses on comparisons of soil moisture anomalies in the NWM to those from in-situ observations. To establish benchmarks for NWM soil moisture skill, we also include other gridded data sets currently used to inform the US Drought Monitor, specifically those from the North American Land Data Assimilation System phase 2 (NLDAS-2) land surface models. We then compare NWM streamflow low flows with ∼500 stream gauges from the United States Geological Survey (USGS) Hydro-Climatic Data Network of undisturbed basins. The NWM soil moisture simulation’s skill parallels that from NLDAS-2. The accuracy of drought condition identification from NWM streamflow exceeds that based on soil moisture as determined by Critical Success Index scores for extreme dry percentiles. Different meteorological forcings are used in the operational NWM cycles than those used in this retrospective analysis. This forcing disconnect, together with concerns about current-generation land surface model soil moisture-transport schemes, inhibit its current operational use for drought monitoring.

    Original languageEnglish
    Article numbere2023JD038522
    JournalJournal of Geophysical Research: Atmospheres
    Volume129
    Issue number6
    DOIs
    StatePublished - Mar 28 2024

    Keywords

    • National Water Model
    • drought monitoring
    • soil moisture

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