Book/Dissertation / PhD Thesis

FZJ-2017-02363

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Process-based modelling of regional water and energy fluxes taking into account measured neutron intensities by cosmic-ray probes

Baatz, R. (Corresponding author)FZJ*

2017
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag Jülich
ISBN: 978-3-95806-211-5

Please use a persistent id in citations: http://hdl.handle.net/2128/14041  urn:nbn:de:0001-2017032820

Abstract: At the land surface, the hydrologic cycle is strongly linked to soil water content (SWC). Land surface models describe the mass and energy fluxes at the land surface and to the atmosphere with a spatial resolution of a few km$^{2}$ at the catchment scale. The calibration and evaluation of land surface models requests observation data, ideally at the same spatial resolution. SWC characterization by model prediction and observation remains a challenge in land surface hydrology. Recently, cosmic-ray probes (CRPs) were developed for continuous passive SWCe stimation from neutron flux measurements at a scale relevant for land surface models. One objective of this work was to set up a network of ten CRPs and to evaluate SWC estimates by CRPs. For evaluation, the footprint average SWC of the CRPs was compared to the horizontally and vertically weighted signal of two distributed networks of in-situ SWC sensors. Three different parameterization methods to estimate SWC from neutron flux were compared. Numerical complexity and potential applications distinguish the three parameterization methods. The three parameterization methods resulted in close SWC estimates at the ten study sites although the neutron flux – SWC relationships were slightly different amongst the parameterization methods. SWC estimated by the calibrated CRPs was very close to SWC measured by alternative SWC measurements. Root mean square errors (RMSEs) of the SWC were 0.031 cm$^{3}$/cm$^{3}$ at the distributed in-situ SWC sensor networks. [...]

Note: RWTH Aachen, Diss., 2016

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Contributing Institute(s):

1. Agrosphäre (IBG-3)

Research Program(s):

1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2017

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Database coverage:
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