TY  - GEN
A1  - Schrön, Martin
A1  - Köhli, Markus
A1  - Scheiffele, Lena
A1  - Iwema, Joost
A1  - Bogena, Heye R.
A1  - Lv, Ling
A1  - Martini, Edoardo
A1  - Baroni, Gabriele
A1  - Rosolem, Rafael
A1  - Weimar, Jannis
A1  - Mai, Juliane
A1  - Cuntz, Matthias
A1  - Rebmann, Corinna
A1  - Oswald, Sascha Eric
A1  - Dietrich, Peter
A1  - Schmidt, Ulrich
A1  - Zacharias, Steffen
T1  - Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity
T2  - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe
N2  - 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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 636 
KW  - forested headwater catchment
KW  - moisture observing system
KW  - soil-water content
KW  - parameterization methods
KW  - scale
KW  - field
KW  - dynamics
KW  - observatories
KW  - networks
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419134
IS  - 636
SP  - 5009
EP  - 5030
ER  -