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@ARTICLE{Schrn:840429,
      author       = {Schrön, Martin and Köhli, Markus and Scheiffele, Lena and
                      Iwema, Joost and Bogena, Heye and Lv, Ling and Martini,
                      Edoardo and Baroni, Gabriele and Rosolem, Rafael and Weimar,
                      Jannis and Mai, Juliane and Cuntz, Matthias and Rebmann,
                      Corinna and Oswald, Sascha E. and Dietrich, Peter and
                      Schmidt, Ulrich and Zacharias, Steffen},
      title        = {{I}mproving calibration and validation of cosmic-ray
                      neutron sensors in the light of spatial sensitivity},
      journal      = {Hydrology and earth system sciences},
      volume       = {21},
      number       = {10},
      issn         = {1607-7938},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2017-07946},
      pages        = {5009 - 5030},
      year         = {2017},
      abstract     = {In the last few years the method of cosmic-ray neutron
                      sensing (CRNS) has gained popularity among hydrologists,
                      physicists, and land-surface modelers. The sensor provides
                      continuous soil moisture data, averaged over several
                      hectares and tens of decimeters in depth. However, the
                      signal still may contain unidentified features of
                      hydrological processes, and many calibration datasets are
                      often required in order to find reliable relations between
                      neutron intensity and water dynamics. Recent insights into
                      environmental neutrons accurately described the spatial
                      sensitivity of the sensor and thus allowed one to quantify
                      the contribution of individual sample locations to the CRNS
                      signal. Consequently, data points of calibration and
                      validation datasets are suggested to be averaged using a
                      more physically based weighting approach. In this work, a
                      revised sensitivity function is used to calculate weighted
                      averages of point data. The function is different from the
                      simple exponential convention by the extraordinary
                      sensitivity to the first few meters around the probe, and by
                      dependencies on air pressure, air humidity, soil moisture,
                      and vegetation. The approach is extensively tested at six
                      distinct monitoring sites: two sites with multiple
                      calibration datasets and four sites with continuous time
                      series datasets. In all cases, the revised averaging method
                      improved the performance of the CRNS products. The revised
                      approach further helped to reveal hidden hydrological
                      processes which otherwise remained unexplained in the data
                      or were lost in the process of overcalibration. The
                      presented weighting approach increases the overall accuracy
                      of CRNS products and will have an impact on all their
                      applications in agriculture, hydrology, and modeling.},
      cin          = {IBG-3},
      ddc          = {550},
      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:000412473100001},
      doi          = {10.5194/hess-21-5009-2017},
      url          = {https://juser.fz-juelich.de/record/840429},
}