• Bosart, L. F., , and Sanders F. , 1981: The Johnstown flood of July 1977: A long-lived convective system. J. Atmos. Sci., 38, 16161642.

  • Brock, F. V., , Crawford K. C. , , Elliott R. L. , , Cuperus G. W. , , Stadler S. J. , , Johnson H. L. , , and Eilts M. D. , 1995: The Oklahoma Mesonet: A technical overview. J. Atmos. Oceanic Technol., 12, 519.

    • Search Google Scholar
    • Export Citation
  • Burnash, R. J., 1995: The NWS River Forecast System—Catchment modeling. Computer Models of Watershed Hydrology, V. P. Sing, Ed., Water Resource Publications, 311–366.

    • Search Google Scholar
    • Export Citation
  • Campbell Scientific, cited 2010: CS616 and CS625 water content reflectometers. [Available online at http://www.campbellsci.com/documents/manuals/cs616.pdf.]

    • Search Google Scholar
    • Export Citation
  • Caracena, F., , Maddox R. A. , , Hoxit L. R. , , and Chappell C. F. , 1979: Mesoanalysis of the Big Thompson storm. Mon. Wea. Rev., 107, 117.

  • Chen, F., , and Dudhia J. , 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569585.

    • Search Google Scholar
    • Export Citation
  • Clark, M. P., , and Hay L. E. , 2004: Use of medium-range numerical weather prediction model output to produce forecasts of streamflow. J. Hydrometeor., 5, 1532.

    • Search Google Scholar
    • Export Citation
  • Flint, A. L., , Flint L. E. , , and Dettinger M. D. , 2008: Modeling soil moisture processes and recharge under a melting snowpack. Valdose Zone J., 7, 350357.

    • Search Google Scholar
    • Export Citation
  • Godfrey, C. M., , and Stensrud D. J. , 2008: Soil temperature and moisture errors in operational Eta model analyses. J. Appl. Meteor., 9, 367387.

    • Search Google Scholar
    • Export Citation
  • Hillel, D., 1998: Environmental Soil Physics. Academic Press, 771 pp.

  • Hogue, T. S., , Sorooshian S. , , Gupta H. , , Holz A. , , and Braatz D. , 2000: A multistep automatic calibration scheme for river forecasting models. J. Hydrometeor., 1, 524542.

    • Search Google Scholar
    • Export Citation
  • Illston, B. G., , Basara J. B. , , Fiebrich C. A. , , Crawford K. C. , , Hunt E. , , Fisher D. K. , , Elliott R. , , and Humes K. , 2008: Mesoscale monitoring of soil moisture across a statewide network. J. Atmos. Oceanic Technol., 25, 162182.

    • Search Google Scholar
    • Export Citation
  • Janjic, Z. I., 2003: A nonhydrostatic model based on a new approach. Meteor. Atmos. Phys., 82, 271285.

  • Kennedy, J. R., , Keefer T. O. , , Paige G. B. , , and Barnes E. , 2003: Evaluation of dielectric constant-based soil moisture sensors in a semiarid rangeland. Proc. First Interagency Conf. on Research in the Watersheds, Benson, AZ, USGS, 503–508. [Available online at http://www.tucson.ars.ag.gov/icrw/Proceedings/Kennedy.pdf.]

    • Search Google Scholar
    • Export Citation
  • Koren, V., , Schaake J. , , Mitchell K. , , Duan Q.-Y. , , Chen F. , , and Baker J. M. , 1999: A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. J. Geophys. Res., 104, 19 56919 585.

    • Search Google Scholar
    • Export Citation
  • Opitz, H. H., and Coauthors, 1995: The challenge of forecasting heavy rain and flooding throughout the eastern region of the National Weather Service. Part II: Forecast techniques and applications. Wea. Forecasting, 10, 91104.

    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., and Coauthors, 2005: Improving short-term (0–48 h) cool-season quantitative precipitation forecasting: Recommendations from a USWRP workshop. Bull. Amer. Meteor. Soc., 86, 16191632.

    • Search Google Scholar
    • Export Citation
  • Reed, S. M., , and Maidment D. R. , 1999: Coordinate transformations for using Nexrad data in GIS-based hydrologic modeling. J. Hydrol. Eng., 4, 174182.

    • Search Google Scholar
    • Export Citation
  • Renard, K. G., , Lane L. J. , , Simanton J. R. , , Emmerich W. E. , , Stone J. J. , , Weltz M. A. , , Goodrich D. C. , , and Yakowitz D. S. , 1993: Agricultural impacts in an arid environment: Walnut Gulch case study. J. Hydrol. Sci. Technol., 9, 145190.

    • Search Google Scholar
    • Export Citation
  • Schaefer, G. L., , Cosh M. H. , , and Jackson T. J. , 2007: The USDA Natural Resources Conservation Service Soil Climate Analysis Network (SCAN). J. Atmos. Oceanic Technol., 24, 20732077.

    • Search Google Scholar
    • Export Citation
  • Veihmeyer, F. J., , and Hendrickson A. H. , 1931: The moisture equivalent as a measure of the field capacity of soils. Soil Sci. Soc. Amer. J., 32, 181193.

    • Search Google Scholar
    • Export Citation
  • Zreda, M., , Desilets D. , , Ferré T. P. A. , , and Scott R. L. , 2008: Measuring soil moisture content non-invasively at intermediate spatial scale using cosmic-ray neutrons. Geophys. Res. Lett., 35, L21402, doi:10.1029/2008GL035655.

    • Search Google Scholar
    • Export Citation
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The NOAA Hydrometeorology Testbed Soil Moisture Observing Networks: Design, Instrumentation, and Preliminary Results

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  • 1 NOAA/Earth System Research Laboratory, Boulder, Colorado
  • | 2 NOAA/National Weather Service Colorado River Basin Forecast Center, Salt Lake City, Utah
  • | 3 NOAA/Earth System Research Laboratory, Boulder, Colorado
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Abstract

The NOAA Hydrometeorology Testbed (HMT) program has deployed soil moisture observing networks in the watersheds of the Russian River and the North Fork (NF) of the American River in northern California, and the San Pedro River in southeastern Arizona. These networks were designed to serve the combined needs of the hydrological, meteorological, agricultural, and climatological communities for observations of soil moisture on time scales that range from minutes to decades.

The networks are a major component of the HMT program that has been developed to accelerate the development and infusion of new observing technologies, modeling methods, and recent scientific research into the National Weather Service (NWS) offices and to help focus research and development efforts on key hydrological and meteorological forecast problems. These forecast problems are not only of interest to the NWS, but they also play a crucial role in providing input to water managers who work at the national, state, and local government levels to provide water for human consumption, agriculture, and other needs.

The HMT soil moisture networks have been specifically designed to capture the changes in soil moisture that are associated with heavy precipitation events and runoff from snowpack during the melt season. This paper describes the strategies used to site the networks and sensors as well as the selection, testing, and calibration of the soil moisture probes. In addition, two illustrative examples of the data gathered by the networks are shown.

The first example shows changes in soil moisture observed before and during a flood event on the Babocomari River tributary of the San Pedro River near Sierra Vista, Arizona, on 23 July 2008. The second example examines a 5-yr continuous time series of soil moisture gathered at Healdsburg, California. The time series illustrates the transition from a multiyear wet period to exceptionally dry conditions from a soil moisture perspective.

Corresponding author address: Robert J. Zamora, NOAA/Earth System Research Laboratory, Physical Sciences Division, Water Cycle Branch, 325 Broadway, Boulder, CO 80303. E-mail: robert.j.zamora@noaa.gov

Abstract

The NOAA Hydrometeorology Testbed (HMT) program has deployed soil moisture observing networks in the watersheds of the Russian River and the North Fork (NF) of the American River in northern California, and the San Pedro River in southeastern Arizona. These networks were designed to serve the combined needs of the hydrological, meteorological, agricultural, and climatological communities for observations of soil moisture on time scales that range from minutes to decades.

The networks are a major component of the HMT program that has been developed to accelerate the development and infusion of new observing technologies, modeling methods, and recent scientific research into the National Weather Service (NWS) offices and to help focus research and development efforts on key hydrological and meteorological forecast problems. These forecast problems are not only of interest to the NWS, but they also play a crucial role in providing input to water managers who work at the national, state, and local government levels to provide water for human consumption, agriculture, and other needs.

The HMT soil moisture networks have been specifically designed to capture the changes in soil moisture that are associated with heavy precipitation events and runoff from snowpack during the melt season. This paper describes the strategies used to site the networks and sensors as well as the selection, testing, and calibration of the soil moisture probes. In addition, two illustrative examples of the data gathered by the networks are shown.

The first example shows changes in soil moisture observed before and during a flood event on the Babocomari River tributary of the San Pedro River near Sierra Vista, Arizona, on 23 July 2008. The second example examines a 5-yr continuous time series of soil moisture gathered at Healdsburg, California. The time series illustrates the transition from a multiyear wet period to exceptionally dry conditions from a soil moisture perspective.

Corresponding author address: Robert J. Zamora, NOAA/Earth System Research Laboratory, Physical Sciences Division, Water Cycle Branch, 325 Broadway, Boulder, CO 80303. E-mail: robert.j.zamora@noaa.gov
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