| Autor: |
Schrön, Martin, Köhli, Markus, Scheiffele, Lena, Iwema, Joost, Bogena, Heye R., Ling Lv, Martini, Eduardo, Baroni, Gabriele, Rosolem, Rafael, Weimar, Jannis, Mai, Juliane, Cuntz, Matthias, Rebmann, Corinna, Oswald, Sascha E., Dietrich, Peter, Schmidt, Ulrich, Zacharias, Steffen |
| Zdroj: |
Hydrology & Earth System Sciences Discussions; 2017, p1-30, 30p |
| Abstrakt: |
In the last years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among soil hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters 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 neutrons and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed 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 approach is extensively tested with two calibration and four time series datasets from a variety of sites and conditions. In all cases, the revised averaging method robustly improved the performance of the CRNS product and even helped to reveal otherwise hidden hydrological processes. The presented approach increases the overall accuracy of CRNS products and will have impact on all their applications in agriculture, hydrology, and modeling. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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