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@ARTICLE{Bogena:877955,
      author       = {Bogena, Heye R. and Herrmann, Frank and Jakobi, Jannis and
                      Brogi, Cosimo and Ilias, Andreas and Huisman, Johan
                      Alexander and Panagopoulos, Andreas and Pisinaras,
                      Vassilios},
      title        = {{M}onitoring of {S}nowpack {D}ynamics {W}ith {C}osmic-{R}ay
                      {N}eutron {P}robes: {A} {C}omparison of {F}our {C}onversion
                      {M}ethods},
      journal      = {Frontiers in water},
      volume       = {2},
      issn         = {2624-9375},
      address      = {Lausanne},
      publisher    = {Frontiers Media},
      reportid     = {FZJ-2020-02534},
      pages        = {19},
      year         = {2020},
      abstract     = {Common snow monitoring instruments based on hydrostatic
                      pressure such as snow pillows are often influenced by
                      various disturbing effects, which result in a reduced
                      quality of the snow cover and snow water equivalent
                      estimates. Such disturbing effects include energy transport
                      into the snowpack, wind fields, and variations of snow
                      properties within the snowpack (e.g. ice layers). Recently,
                      it has been shown that Cosmic-Ray Neutron Probes (CRNP) are
                      a promising technique to monitor snow pack development. CRNP
                      can provide larger support and need lower maintenance
                      compared to conventional sensors. These instruments are
                      sensitive to the intensity of epithermal neutrons that are
                      produced in the soil by cosmic radiation and are widely used
                      to determine soil moisture in the upper decimetres of the
                      ground. The application of CRNP for snow monitoring is based
                      on the principle that snow water moderates the epithermal
                      neutron intensity, which can be directly related to the snow
                      water equivalent (SWE) of the snow pack. In this study,
                      long-term CRNP measurements in the Pinios Hydrologic
                      Observatory (PHO), Greece, were used to test different
                      methods for converting neutron count rates to snow pack
                      characteristics: i) linear regression, ii) standard
                      N0-calibration function, iii) a physically-based calibration
                      approach, and iv) thermal to epithermal neutron ratio. For
                      this, a sonic sensor located near the CRNP was used to
                      compare CRNP-derived snow pack dynamics with snow depth
                      measurements. We found that the above-ground CRNP is well
                      suited for measurement of field scale SWE, which is in
                      agreement with findings of other studies. The analysis of
                      the accuracy of the four conversion methods showed that all
                      methods were able to determine the mass of the snow pack
                      during the snow events reasonably well. The N0-calibration
                      function and the physically-based calibration function
                      performed best and the thermal to epithermal neutron ratio
                      performed worst. Furthermore, we found that SWE
                      determination with above-ground CRNP can be affected by
                      other influences (e.g. heavy rainfall). Nevertheless,
                      CRNP-based SWE determination is a potential alternative to
                      established method like snow depth-based SWE methods, as it
                      provides SWE estimate for a much larger scales (12-18 ha).},
      cin          = {IBG-3},
      ddc          = {333.7},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000659476100001},
      doi          = {10.3389/frwa.2020.00019},
      url          = {https://juser.fz-juelich.de/record/877955},
}