scholarly journals An assessment of the effect of horizontal soil moisture heterogeneity on the area-average measurement of cosmic-ray neutrons

2013 ◽  
Vol 49 (10) ◽  
pp. 6450-6458 ◽  
Author(s):  
Trenton E. Franz ◽  
M. Zreda ◽  
T. P. A. Ferre ◽  
R. Rosolem
2021 ◽  
Author(s):  
Markus Köhli ◽  
Jannis Weimar ◽  
Benjamin Fersch ◽  
Roland Baatz ◽  
Martin Schrön ◽  
...  

<p>The novel method of Cosmic-ray neutron sensing (CRNS) allows non-invasive soil moisture measurements at a hectometer scaled footprint. Up to now, the conversion of soil moisture to a detectable neutron count rate relies mainly on the equation presented by Desilets et al. (2010). While in general a hyperbolic expression can be derived from theoretical considerations, their empiric parameterisation needs to be revised for two reasons. Firstly, a rigorous mathematical treatment reveals that the values of the four parameters are ambiguous because their values are not independent. We find a 3-parameter equation with unambiguous values of the parameters which is equivalent in any other respect to the 4-parameter equation. Secondly, high-resolution Monte-Carlo simulations revealed a systematic deviation of the count rate to soil moisture relation especially for extremely dry conditions as well as very humid conditions. That is a hint, that a smaller contribution to the intensity was forgotten or not adequately treated by the conventional approach. Investigating the above-ground neutron flux by a broadly based Monte-Carlo simulation campaign revealed a more detailed understanding of different contributions to this signal, especially targeting air humidity corrections. The packages MCNP and URANOS were used to derive a function able to describe the respective dependencies including the effect of different hydrogen pools and the detector-specific response function. The new relationship has been tested at three exemplary measurement sites and its remarkable performance allows for a promising prospect of more comprehensive data quality in the future.</p>


Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1362 ◽  
Author(s):  
Mustafa Berk Duygu ◽  
Zuhal Akyürek

Soil moisture content is one of the most important parameters of hydrological studies. Cosmic-ray neutron sensing is a promising proximal soil moisture sensing technique at intermediate scale and high temporal resolution. In this study, we validate satellite soil moisture products for the period of March 2015 and December 2018 by using several existing Cosmic Ray Neutron Probe (CRNP) stations of the COSMOS database and a CRNP station that was installed in the south part of Turkey in October 2016. Soil moisture values, which were inferred from the CRNP station in Turkey, are also validated using a time domain reflectometer (TDR) installed at the same location and soil water content values obtained from a land surface model (Noah LSM) at various depths (0.1 m, 0.3 m, 0.6 m and 1.0 m). The CRNP has a very good correlation with TDR where both measurements show consistent changes in soil moisture due to storm events. Satellite soil moisture products obtained from the Soil Moisture and Ocean Salinity (SMOS), the METOP-A/B Advanced Scatterometer (ASCAT), Soil Moisture Active Passive (SMAP), Advanced Microwave Scanning Radiometer 2 (AMSR2), Climate Change Initiative (CCI) and a global land surface model Global Land Data Assimilation System (GLDAS) are compared with the soil moisture values obtained from CRNP stations. Coefficient of determination ( r 2 ) and unbiased root mean square error (ubRMSE) are used as the statistical measures. Triple Collocation (TC) was also performed by considering soil moisture values obtained from different soil moisture products and the CRNPs. The validation results are mainly influenced by the location of the sensor and the soil moisture retrieval algorithm of satellite products. The SMAP surface product produces the highest correlations and lowest errors especially in semi-arid areas whereas the ASCAT product provides better results in vegetated areas. Both global and local land surface models’ outputs are highly compatible with the CRNP soil moisture values.


2013 ◽  
Vol 10 (4) ◽  
pp. 4237-4274 ◽  
Author(s):  
C. A. Rivera Villarreyes ◽  
G. Baroni ◽  
S. E. Oswald

Abstract. Measurement of soil moisture at the plot or hill-slope scale is an important link between local vadose-zone hydrology and catchment hydrology. This study evaluates the applicability of the cosmic-ray neutron sensing for soil moisture in cropped fields. Measurements of cosmic-ray neutrons (fast neutrons) were performed at a lowland farmland in Bornim (Brandenburg, Germany) cropped with sunflower and winter rye. Three field calibration approaches and four different ways of integration the soil moisture profile to an integral value for cosmic-ray neutron sensing were evaluated in this study. The cosmic-ray sensing (CRS) probe was calibrated against a network of classical point-scale soil moisture measurements. A large CRS parameter variability was observed by choosing calibration periods within the different growing stages of sunflower and winter rye. Therefore, it was not possible to identify a single set of parameters perfectly estimating soil moisture for both sunflower and winter rye periods. On the other hand, CRS signal and its parameter variability could be understood by some crop characteristics and by predicting the attenuated neutrons by crop presence. This study proves the potentiality of the cosmic-ray neutron sensing at the field scale; however, its calibration needs to be adapted for seasonal vegetation in cropped fields.


2021 ◽  
Vol 3 ◽  
Author(s):  
Andres Patrignani ◽  
Tyson E. Ochsner ◽  
Benjamin Montag ◽  
Steven Bellinger

During the past decade, cosmic-ray neutron sensing technology has enabled researchers to reveal soil moisture spatial patterns and to estimate landscape-average soil moisture for hydrological and agricultural applications. However, reliance on rare materials such as helium-3 increases the cost of cosmic-ray neutron probes (CRNPs) and limits the adoption of this unique technology beyond the realm of academic research. In this study, we evaluated a novel lower cost CRNP based on moderated ultra-thin lithium-6 foil (Li foil system) technology against a commercially-available CRNP based on BF3 (boron trifluoride, BF-3 system). The study was conducted in a cropped field located in the Konza Prairie Biological Station near Manhattan, Kansas, USA (325 m a.s.l.) from 10 April 2020 to 18 June 2020. During this period the mean atmospheric pressure was 977 kPa, the mean air relative humidity was 70%, and the average volumetric soil water content was 0.277 m3 m−3. Raw fast neutron counts were corrected for atmospheric pressure, atmospheric water vapor, and incoming neutron flux. Calibration of the CRNPs was conducted using four intensive field surveys (n > 120), in combination with continuous observations from an existing array of in situ soil moisture sensors. The time series of uncorrected neutron counts of the Li foil system was highly correlated (r2 = 0.91) to that of the BF-3 system. The Li foil system had an average of 2,250 corrected neutron counts per hour with an uncertainty of 2.25%, values that are specific to the instrument size, detector configuration, and atmospheric conditions. The estimated volumetric water content from the Li foil system had a mean absolute difference of 0.022 m3 m−3 compared to the value from the array of in situ sensors. The new Li foil detector offers a promising lower cost alternative to existing cosmic-ray neutron detection devices used for hectometer-scale soil moisture monitoring.


Author(s):  
Carsten Montzka ◽  
Heye R. Bogena ◽  
Marek Zreda ◽  
Alessandra Monerris ◽  
Ross Morrison ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Martin Bouda ◽  
Jan Vanderborght ◽  
Mathieu Javaux

<p>Recent advances in scaling up water flows on root system networks hold promise for improving predictions of water uptake at large scales. These developments are particularly timely, as persistent difficulties in getting Earth system models to accurately represent soil-root water flows, especially under drying or heterogeneous soil moisture conditions, are now a major obstacle describing the water limitation of terrestrial fluxes.</p><p>One recently developed upscaling formalism has been shown to be both free of discretisation error in flow predictions regardless of scale and with computational cost linearly diminishing with the number of soil subdomains considered. What has been missing from this approach, however, is a proven method to apply it generally – i.e. to an arbitrary root system architecture discretised on an arbitrary grid.</p><p>The work presented here demonstrates a general algorithm that can be applied to a wide range of root system architectures (the only assumption being that only one lateral root originates at one point along a parent root) discretised on a grid consisting of a series of soil layers of variable thickness, as is common in Earth system models. It is further shown theoretically that both of these restrictions can in principle be relaxed and that this approach can in principle be extended to conditions of soil moisture heterogeneity – i.e. situations where each root segment in a soil grid cell faces a different water potential at the soil-root interface.</p><p>This work represents both a practical advance bringing broad applicability to this upscaling approach and a major theoretical advance as exact solutions for water uptake under conditions of soil moisture heterogeneity within grid cells were previously unknown. While obtaining exact solutions despite heterogeneity within the grid cell requires a way of finding the overall mean soil water potential faced by the plant, this advance nevertheless points to possible directions of future research for overcoming the major hurdle of soil moisture heterogeneity.</p>


2020 ◽  
Vol 40 (6) ◽  
pp. 762-773 ◽  
Author(s):  
Jaime Puértolas ◽  
Marta Pardos ◽  
Carlos de Ollas ◽  
Alfonso Albacete ◽  
Ian C Dodd

Abstract Soil moisture heterogeneity in the root zone is common both during the establishment of tree seedlings and in experiments aiming to impose semi-constant soil moisture deficits, but its effects on regulating plant water use compared with homogenous soil drying are not well known in trees. Pronounced vertical soil moisture heterogeneity was imposed on black poplar (Populus nigra L.) grown in soil columns by altering irrigation frequency, to test whether plant water use, hydraulic responses, root phytohormone concentrations and root xylem sap chemical composition differed between wet (well-watered, WW), and homogeneously (infrequent deficit irrigation, IDI) and heterogeneously dry soil (frequent deficit irrigation, FDI). At the same bulk soil water content, FDI plants had greater water use than IDI plants, probably because root abscisic acid (ABA) concentration was low in the upper wetter layer of FDI plants, which maintained root xylem sap ABA concentration at basal levels in contrast with IDI. Soil drying did not increase root xylem concentration of any other hormone. Nevertheless, plant-to-plant variation in xylem jasmonic acid (JA) concentration was negatively related to leaf stomatal conductance within WW and FDI plants. However, feeding detached leaves with high (1200 nM) JA concentrations via the transpiration stream decreased transpiration only marginally. Xylem pH and sulphate concentration decreased in FDI plants compared with well-watered plants. Frequent deficit irrigation increased root accumulation of the cytokinin trans-zeatin (tZ), especially in the dry lower layer, and of the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC), in the wet upper soil layer. Root hormone accumulation might explain the maintenance of high root hydraulic conductance and water use in FDI plants (similar to well-watered plants) compared with IDI plants. In irrigated tree crops, growers could vary irrigation scheduling to control water use by altering the hormone balance.


2015 ◽  
Vol 19 (1) ◽  
pp. 615-629 ◽  
Author(s):  
X. Han ◽  
H.-J. H. Franssen ◽  
R. Rosolem ◽  
R. Jin ◽  
X. Li ◽  
...  

Abstract. The recent development of the non-invasive cosmic-ray soil moisture sensing technique fills the gap between point-scale soil moisture measurements and regional-scale soil moisture measurements by remote sensing. A cosmic-ray probe measures soil moisture for a footprint with a diameter of ~ 600 m (at sea level) and with an effective measurement depth between 12 and 76 cm, depending on the soil humidity. In this study, it was tested whether neutron counts also allow correcting for a systematic error in the model forcings. A lack of water management data often causes systematic input errors to land surface models. Here, the assimilation procedure was tested for an irrigated corn field (Heihe Watershed Allied Telemetry Experimental Research – HiWATER, 2012) where no irrigation data were available as model input although for the area a significant amount of water was irrigated. In the study, the measured cosmic-ray neutron counts and Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products were jointly assimilated into the Community Land Model (CLM) with the local ensemble transform Kalman filter. Different data assimilation scenarios were evaluated, with assimilation of LST and/or cosmic-ray neutron counts, and possibly parameter estimation of leaf area index (LAI). The results show that the direct assimilation of cosmic-ray neutron counts can improve the soil moisture and evapotranspiration (ET) estimation significantly, correcting for lack of information on irrigation amounts. The joint assimilation of neutron counts and LST could improve further the ET estimation, but the information content of neutron counts exceeded the one of LST. Additional improvement was achieved by calibrating LAI, which after calibration was also closer to independent field measurements. It was concluded that assimilation of neutron counts was useful for ET and soil moisture estimation even if the model has a systematic bias like neglecting irrigation. However, also the assimilation of LST helped to correct the systematic model bias introduced by neglecting irrigation and LST could be used to update soil moisture with state augmentation.


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