Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

Franz, Trenton E.; Wahbi, Ammar; Vreugdenhil, Mariëtte; Weltin, Georg; Heng, Lee; Oismueller, Markus; Strauß, Peter; Dercon, Gerd; Desilets, Darin

doi:10.1155/2016/4323742

Cited by 49 publications

(52 citation statements)

References 49 publications

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“…The COSMIC operator [Shuttleworth et al, 2013] enables effective data assimilation for snow-free environments. As approaches to separate the signal of different hydrogen pools are emerging [Baatz et al, 2015;Baroni and Oswald, 2015;Franz et al, 2016;Heidb€ uchel et al, 2016;Tian et al, 2016], applications in other environments than open fields, including measurements of snow canopy interactions, are promising [Desilets, 2014].…”

Section: Introductionmentioning

confidence: 99%

Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing

Schattan

Baroni

Oswald

et al. 2017

Water Resources Research

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The characteristics of an aboveground cosmic‐ray neutron sensor (CRNS) are evaluated for monitoring a mountain snowpack in the Austrian Alps from March 2014 to June 2016. Neutron counts were compared to continuous point‐scale snow depth (SD) and snow‐water‐equivalent (SWE) measurements from an automatic weather station with a maximum SWE of 600 mm (April 2014). Several spatially distributed Terrestrial Laser Scanning (TLS)‐based SD and SWE maps were additionally used. A strong nonlinear correlation is found for both SD and SWE. The representative footprint of the CRNS is in the range of 230–270 m. In contrast to previous studies suggesting signal saturation at around 100 mm of SWE, no complete signal saturation was observed. These results imply that CRNS could be transferred into an unprecedented method for continuous detection of spatially averaged SD and SWE for alpine snowpacks, though with sensitivity decreasing with increasing SWE. While initially different functions were found for accumulation and melting season conditions, this could be resolved by accounting for a limited measurement depth. This depth limit is in the range of 200 mm of SWE for dense snowpacks with high liquid water contents and associated snow density values around 450 kg m−3 and above. In contrast to prior studies with shallow snowpacks, interannual transferability of the results is very high regardless of presnowfall soil moisture conditions. This underlines the unexpectedly high potential of CRNS to close the gap between point‐scale measurements, hydrological models, and remote sensing of the cryosphere in alpine terrain.

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Section: Introductionmentioning

confidence: 99%

Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing

Schattan

Baroni

Oswald

et al. 2017

Water Resources Research

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“…Compared with the equal weighting of independent soil moisture measurements suggested by Franz et al (2012b), improved soil moisture estimates were obtained by applying a weighting function (Schrön et al, 2017). In principle, a single calibration campaign is adequate; however, when additional pools of H are present, two or more campaigns at different soil water contents will produce better calibration (Franz et al, 2012b, 2013a, 2016; Lv et al, 2014; Iwema et al, 2015; Heidbüchel et al, 2016). Finally, an alternative calibration function for soil moisture estimation was developed by Franz et al (2013b).…”

Section: Status Of the Methodsmentioning

confidence: 99%

Status and Perspectives on the Cosmic‐Ray Neutron Method for Soil Moisture Estimation and Other Environmental Science Applications

Andreasen

Jensen

Desilets³

et al. 2017

Vadose Zone Journal

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117

109

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Core Ideas Numerous studies have been conducted to develop and examine the accuracy of the method. Cosmic‐ray neutron soil moisture estimates compare well with independent measurements. These estimates are useful for modeling, data assimilation, and calibration of satellite products. Many studies have used the neutron detector for other applications; results have been promising. Since the introduction of the cosmic‐ray neutron method for soil moisture estimation, numerous studies have been conducted to test and advance the accuracy of the method. Almost 200 stationary neutron detector systems have been installed worldwide, and roving systems have also started to gain ground. The intensity of low‐energy neutrons produced by cosmic rays, measured above the ground surface, is sensitive to soil moisture in the upper decimeters of the ground within a radius of hectometers. The method has been proven suitable for estimating soil moisture for a wide range of land covers and soil types and has been used for hydrological modeling, data assimilation, and calibration and validation of satellite products. The method is challenged by the effect on neutron intensity of other hydrogen pools such as vegetation, canopy interception, and snow. Identifying the signal of the different pools can be used to improve the cosmic‐ray neutron soil moisture method as well as extend the application to, e.g., biomass and canopy interception surveying. More fundamental research is required for advancement of the method to include more energy ranges and consider multiple height levels.

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“…Numerous validation studies across the globe (see e.g. Bogena et al 2013;Franz et al 2015Franz et al , 2016Iwema et al 2017, among others) have shown the CRNP to have area-average measurement accuracies of less than 0.03 cm 3 cm −3 against a variety of industry standard SWC point scale probes. The calculated SWC within the measurement volume in a non-linearly weighed average with increased sensitivity near the CRNP (Schrön et al 2017).…”

Section: Hydrogeophysical Datasetsmentioning

confidence: 99%

“…Binley et al 2015;Coopersmith et al 2014;Franz et al 2016;Villarreyes et al 2011) offer promising opportunities in precision agriculture. One such instrument to be explored in this work is the cosmicray neutron probe (CRNP), which has been used within agricultural systems to approximate SWC at the field-to small-watershed-scale (Franz et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

et al. 2018

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Precision agriculture offers the technologies to manage for infield variability and incorporate variability into irrigation management decisions. The major limitation of this technology often lies in the reconciliation of disparate data sources and the generation of irrigation prescription maps. Here the authors explore the utility of the cosmic-ray neutron probe (CRNP) which measures volumetric soil water content (SWC) in the top ~ 30 cm of the soil profile. The key advantages of CRNP is that the sensor is passive, non-invasive, mobile and soil temperature-invariant, making data collection more compatible with existing farm operations and extending the mapping period. The objectives of this study were to: (1) improve the delineation of irrigation management zones within a field and (2) estimate spatial soil hydraulic properties to make effective irrigation prescriptions. Ten CRNP SWC surveys were collected in a 53-ha field in Nebraska. The SWC surveys were analyzed using Empirical Orthogonal Functions (EOFs) to isolate the underlying spatial structure. A statistical bootstrapping analysis confirmed the CRNP + EOF provided superior soil hydraulic property estimates, compared to other hydrogeophysical datasets, when linearly correlated to laboratory measured soil hydraulic properties (field capacitydigitalcommons.unl.edu F i n k e n b i n e r e t a l . i n P r e c i s i o n A g r i c u lt u r e , 2 0 1 8 2estimates reduced 20-25% in root mean square error). The authors propose a soil sampling strategy for better quantifying soil hydraulic properties using CRNP + EOF methods. Here, five CRNP surveys and 6-8 sample locations for laboratory analysis were sufficient to describe the spatial distribution of soil hydraulic properties within this field. While the proposed strategy may increase overall effort, rising scrutiny for agricultural water-use could make this technology cost-effective.

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Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

Cited by 49 publications

References 49 publications

Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing

Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing

Status and Perspectives on the Cosmic‐Ray Neutron Method for Soil Moisture Estimation and Other Environmental Science Applications

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

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