@article{WeimarKoehliBudachetal.2020,
  author    = {Weimar, Jannis and K{\"o}hli, Markus and Budach, Christian and Schmidt, Ulrich},
  title     = {Large-scale boron-lined neutron detection systems as a 3He alternative for Cosmic Ray Neutron Sensing},
  series = {Frontiers in water},
  volume    = {2},
  journal   = {Frontiers in water},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {2624-9375},
  doi       = {10.3389/frwa.2020.00016},
  pages     = {17},
  year      = {2020},
  abstract  = {Cosmic-Ray neutron sensors are widely used to determine soil moisture on the hectare scale. Precise measurements, especially in the case of mobile application, demand for neutron detectors with high counting rates and high signal-to-noise ratios. For a long time Cosmic Ray Neutron Sensing (CRNS) instruments have relied on He-3 as an efficient neutron converter. Its ongoing scarcity demands for technological solutions using alternative converters, which are Li-6 and B-10. Recent developments lead to a modular neutron detector consisting of several B-10-lined proportional counter tubes, which feature high counting rates via its large surface area. The modularity allows for individual shieldings of different segments within the detector featuring the capability of gaining spectral information about the detected neutrons. This opens the possibility for active signal correction, especially useful when applied to mobile measurements, where the influence of constantly changing near-field to the overall signal should be corrected. Furthermore, the signal-to-noise ratio could be increased by combining pulse height and pulse length spectra to discriminate between neutrons and other environmental radiation. This novel detector therefore combines high-selective counting electronics with large-scale instrumentation technology.},
  language  = {en}
}
@misc{SchroenKoehliScheiffeleetal.2017,
  author    = {Schr{\"o}n, Martin and K{\"o}hli, Markus and Scheiffele, Lena and Iwema, Joost and Bogena, Heye R. 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 and Dietrich, Peter and Schmidt, Ulrich and Zacharias, Steffen},
  title     = {Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {636},
  doi       = {10.25932/publishup-41913},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419134},
  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.},
  language  = {en}
}
@article{SchroenKoehliScheiffeleetal.2017,
  author    = {Schr{\"o}n, Martin and K{\"o}hli, Markus and Scheiffele, Lena and Iwema, Joost and Bogena, Heye R. 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 and Dietrich, Peter and Schmidt, Ulrich and Zacharias, Steffen},
  title     = {Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity},
  series = {Hydrology and earth system sciences : HESS},
  volume    = {21},
  journal   = {Hydrology and earth system sciences : HESS},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1027-5606},
  doi       = {10.5194/hess-21-5009-2017},
  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.},
  language  = {en}
}