Articles | Volume 21, issue 10
https://doi.org/10.5194/hess-21-5009-2017
https://doi.org/10.5194/hess-21-5009-2017
Research article
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06 Oct 2017
Research article | Highlight paper |  | 06 Oct 2017

Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity

Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias

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Cited articles

Almeida, A. C., Dutta, R., Franz, T. E., Terhorst, A., Smethurst, P. J., Baillie, C., and Worledge, D.: Combining Cosmic-Ray Neutron and Capacitance Sensors and Fuzzy Inference to Spatially Quantify Soil Moisture Distribution, IEEE Sensors J., 14, 3465–3472, https://doi.org/10.1109/JSEN.2014.2345376, 2014.
Baatz, R., Bogena, H., Franssen, H.-J. H., Huisman, J., Qu, W., Montzka, C., and Vereecken, H.: Calibration of a catchment scale cosmic-ray probe network: A comparison of three parameterization methods, J. Hydrol., 516, 231–244, https://doi.org/10.1016/j.jhydrol.2014.02.026, 2014.
Baroni, G. and Oswald, S.: A scaling approach for the assessment of biomass changes and rainfall interception using cosmic-ray neutron sensing, J. Hydrol., 525, 264–276, https://doi.org/10.1016/j.jhydrol.2015.03.053, 2015.
Bogena, H. R., Herbst, M., Huisman, J., Rosenbaum, U., Weuthen, A., and Vereecken, H.: Potential of wireless sensor networks for measuring soil water content variability, Vadose Zone J., 9, 1002–1013, 2010.
Bogena, H. R., Huisman, J. A., Baatz, R., Hendricks Franssen, H.-J., and Vereecken, H.: Accuracy of the cosmic-ray soil water content probe in humid forest ecosystems: The worst case scenario, Water Resour. Res., 49, 5778–5791, https://doi.org/10.1002/wrcr.20463, 2013.
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Short summary
A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.