Practical Data Products From Cosmic-Ray Neutron Sensing for Hydrological Applications Article Swipe
Trenton E. Franz
,
Ammar Wahbi
,
Jie Zhang
,
Mariëtte Vreugdenhil
,
Lee Heng
,
Gerd Dercon
,
Peter Strauß
,
Luca Brocca
,
Wolfgang Wagner
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3389/frwa.2020.00009
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3389/frwa.2020.00009
The Cosmic-Ray Neutron Sensor (CRNS) technique for estimating landscape average soil water content (SWC) is now a decade old and includes now many practical methods for implementing measurements, such as identification of detection area and depth, installation, calibration, and validation. However, in order to maximize the societal relevance of CRNS SWC data, practical value-added products need to be developed that can estimate both water flux (i.e. rainfall, deep percolation, evapotranspiration) and root zone storage changes. In particular, simple methods that can be used to estimate daily values at landscape average scales are needed by decision makers and stakeholders interested in utilizing this technique. Moreover, landscape average values are necessary for better comparisons with remote sensing products. In this work we utilize three well established algorithms to enhance the usability of the CRNS data. The algorithms aim to: 1) temporally smooth the neutron intensity and SWC time series, 2) estimate a daily rainfall product using the Soil Moisture 2 Rain (SM2RAIN) algorithm, and 3) estimate daily root zone SWC using an exponential filter algorithm. The algorithms are tested on the CRNS site at the Hydrological Open Air Laboratory experiment in Petzenkirchen, Austria. Independent observations of rainfall and point SWC data are used to calibrate and validate the algorithms. With respect to rainfall, the SM2RAIN algorithm resulted in a Kling-Gupta-Efficiency (KGE) criteria of 0.665 for daily and 0.819 for 5 day totals. With respect to SWC, the exponential filter algorithm resulted in a KGE of 0.909 for the 0-30cm depth and 0.912 for the 0-60 cm depth. A methodological framework is presented that summarizes the different processes, required data, algorithms, and products.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/frwa.2020.00009
- OA Status
- gold
- Cited By
- 49
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3017099161
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3017099161Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/frwa.2020.00009Digital Object Identifier
- Title
-
Practical Data Products From Cosmic-Ray Neutron Sensing for Hydrological ApplicationsWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
-
2020-04-16Full publication date if available
- Authors
-
Trenton E. Franz, Ammar Wahbi, Jie Zhang, Mariëtte Vreugdenhil, Lee Heng, Gerd Dercon, Peter Strauß, Luca Brocca, Wolfgang WagnerList of authors in order
- Landing page
-
https://doi.org/10.3389/frwa.2020.00009Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.3389/frwa.2020.00009Direct OA link when available
- Concepts
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Evapotranspiration, Environmental science, Calibration, Algorithm, Filter (signal processing), Water content, Computer science, Remote sensing, Meteorology, Mathematics, Statistics, Geography, Engineering, Computer vision, Geotechnical engineering, Biology, EcologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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49Total citation count in OpenAlex
- Citations by year (recent)
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2025: 6, 2024: 9, 2023: 4, 2022: 12, 2021: 16Per-year citation counts (last 5 years)
- References (count)
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44Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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