scholarly journals Towards disentangling heterogeneous soil moisture patterns in cosmic-ray neutron sensor footprints

2021 ◽  
Vol 25 (12) ◽  
pp. 6547-6566
Author(s):  
Daniel Rasche ◽  
Markus Köhli ◽  
Martin Schrön ◽  
Theresa Blume ◽  
Andreas Güntner
Keyword(s):  
Soil Moisture ◽  
Near Field ◽  
Cosmic Ray ◽  
Moisture Distribution ◽  
Organic Soils ◽  
Thermal Neutrons ◽  
Epithermal Neutrons ◽  
Combined Use ◽  
Mineral Soils ◽  
Northeastern Germany

Abstract. Cosmic-ray neutron sensing (CRNS) allows for non-invasive soil moisture estimations at the field scale. The derivation of soil moisture generally relies on secondary cosmic-ray neutrons in the epithermal to fast energy ranges. Most approaches and processing techniques for observed neutron intensities are based on the assumption of homogeneous site conditions or of soil moisture patterns with correlation lengths shorter than the measurement footprint of the neutron detector. However, in view of the non-linear relationship between neutron intensities and soil moisture, it is questionable whether these assumptions are applicable. In this study, we investigated how a non-uniform soil moisture distribution within the footprint impacts the CRNS soil moisture estimation and how the combined use of epithermal and thermal neutrons can be advantageous in this case. Thermal neutrons have lower energies and a substantially smaller measurement footprint around the sensor than epithermal neutrons. Analyses using the URANOS (Ultra RApid Neutron-Only Simulation) Monte Carlo simulations to investigate the measurement footprint dynamics at a study site in northeastern Germany revealed that the thermal footprint mainly covers mineral soils in the near-field to the sensor while the epithermal footprint also covers large areas with organic soils. We found that either combining the observed thermal and epithermal neutron intensities by a rescaling method developed in this study or adjusting all parameters of the transfer function leads to an improved calibration against the reference soil moisture measurements in the near-field compared to the standard approach and using epithermal neutrons alone. We also found that the relationship between thermal and epithermal neutrons provided an indicator for footprint heterogeneity. We, therefore, suggest that the combined use of thermal and epithermal neutrons offers the potential of a spatial disaggregation of the measurement footprint in terms of near- and far-field soil moisture dynamics.

scholarly journals Towards disentangling heterogeneous soil moisture patterns in Cosmic-Ray Neutron Sensor footprints

2021 ◽  
Author(s):  
Daniel Rasche ◽  
Markus Köhli ◽  
Martin Schrön ◽  
Theresa Blume ◽  
Andreas Güntner
Keyword(s):  
Soil Moisture ◽  
Near Field ◽  
Cosmic Ray ◽  
Moisture Distribution ◽  
Organic Soils ◽  
Thermal Neutrons ◽  
Epithermal Neutrons ◽  
Combined Use ◽  
Mineral Soils ◽  
Processing Techniques

Abstract. Cosmic-Ray Neutron Sensing (CRNS) allows for non-invasive soil moisture measurements at the field scale. The derivation of soil moisture generally relies on secondary cosmic-ray neutrons in the epithermal-to-fast energy range. Most approaches and processing techniques for observed neutron intensities are based on the assumption of homogeneous site conditions within the measurement footprint of the neutron detector. In this study we investigated how a non-uniform soil moisture distribution within the footprint impacts the CRNS soil moisture estimation and how the combined use of epithermal and thermal neutrons can be advantageous in this case. Thermal neutrons have lower energies and a substantially smaller measurement footprint around the sensor than epithermal neutrons. Analyses using URANOS neutron Monte-Carlo simulations to investigate measurement footprint dynamics at a study site in north-eastern Germany revealed that the thermal footprint mainly covers mineral soils in the near-field to the sensor while the epithermal footprint also covers large areas with organic soils. We found that either combining the observed thermal and epithermal neutron intensities by a rescaling method developed in this study, or adjusting all parameters of the transfer function leads to an improved calibration against reference soil moisture measurements in the near field compared to the standard approach and using epithermal neutrons alone. We also found that the relationship between thermal and epithermal neutrons provided an indicator for footprint heterogeneity. We therefore suggest that the combined use of thermal and epithermal neutrons offers the potential of a spatial discretization of the measurement footprint in terms of near and far field soil moisture dynamics.

scholarly journals Towards disentangling heterogeneous soil moisture patterns in Cosmic-Ray Neutron Sensor footprints

2021 ◽  
Author(s):  
Daniel Rasche ◽  
Markus Köhli ◽  
Martin Schrön ◽  
Theresa Blume ◽  
Andreas Güntner
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Neutron Transport ◽  
Common Knowledge ◽  
Near Field ◽  
Cosmic Ray ◽  
Average Moisture Content ◽  
Far Field ◽  
Thermal Neutrons ◽  
Moisture Conditions

<p>Cosmic-Ray Neutron Sensing (CRNS) has constantly advanced during the last decade as a modern technique for non-invasive soil moisture estimation at the field scale. Latest studies led to an improved understanding of the CRNS integration volume, weighting functions for reference soil moisture measurements and correction procedures of raw neutron counts.</p><p>It is common knowledge that soil moisture is highly variable in space. Nevertheless, the CRNS processing techniques currently assume that there is little structure to this variability within the 10 ha measurement footprint, i.e. no distinct difference in average moisture content between near and far field. In particular, with a single CRNS probe and the current knowledge it is not possible to separate different soil moisture conditions within the footprint.</p><p>Against this background, we investigated the effect of soil moisture patterns on the size of the measurement footprint and on the response of thermal and epithermal neutron intensities at a CRNS observation site in north-eastern Germany. The site exhibits pronounced differences in soil water content (and dynamics) in the near (0-60 m) and far field (> 60 m) of the neutron detector as the near field is dominated by mineral and the far field by organic peatland soils.</p><p>Neutron transport simulations with URANOS revealed that thermal neutrons have a smaller measurement footprint compared to epithermal neutrons. We show that thermal neutrons mainly originated from the mineral soils in the near field, while the larger epithermal footprint area also includes the peatland soils. However, the simulated thermal neutrons still seem to be influenced by peatland soil water variations.</p><p>With the support of the computer simulations, we were able to better interpret and identify patterns in the observed neutron count rates that represent different features of the heterogeneous field site. The study presents a new application for thermal detectors in concert with the standard epithermal detectors, and revealed opportunities for improving the calibration against soil moisture reference measurements in the near field. We illustrate the potential of CRNS for estimating soil moisture time series at heterogeneous study sites and for disentangling different soil moisture conditions within the measurement footprint.</p>

Field dissipation of S-metolachlor in organic and mineral soils used for sugarcane production in Florida

2019 ◽  
Vol 34 (3) ◽  
pp. 362-370
Author(s):  
Jose V. Fernandez ◽  
D. Calvin Odero ◽  
Gregory E. MacDonald ◽  
Jason A. Ferrell ◽  
Brent A. Sellers ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Linear Trend ◽  
Organic Matter Content ◽  
Field Studies ◽  
Matter Content ◽  
Organic Soils ◽  
Sugarcane Production ◽  
Mineral Soils ◽  
Moisture Conditions

AbstractDissipation of S-metolachlor, a soil-applied herbicide, on organic and mineral soils used for sugarcane production in Florida was evaluated using field studies in 2013 to 2016. S-metolachlor was applied PRE at 2,270 g ha−1 on organic and mineral soils with 75% and 1.6% organic matter, respectively. The rate of dissipation of S-metolachlor was rapid on mineral soils compared with organic soils. Dissipation of S-metolachlor on organic soils followed a negative linear trend resulting in half-lives (DT50) ranging from 50 to 126 d. S-metolachlor loss on organic soils was more rapid under high soil-moisture conditions than in corresponding low soil-moisture conditions. On mineral soils, dissipation of S-metolachlor followed an exponential decline. The DT50 of S-metolachlor on mineral soils ranged from 12 to 24 d. The short persistence of S-metolachlor on mineral soils was likely attributed to low organic matter content with limited adsorptive capability. The results indicate that organic matter content and soil moisture are important for persistence of S-metolachlor on organic and mineral soils used for sugarcane production in Florida.

Combining Cosmic-Ray Neutron and Capacitance Sensors and Fuzzy Inference to Spatially Quantify Soil Moisture Distribution

2014 ◽  
Vol 14 (10) ◽  
pp. 3465-3472 ◽  
Author(s):  
Auro C. Almeida ◽  
Ritaban Dutta ◽  
Trenton E. Franz ◽  
Andrew Terhorst ◽  
Philip J. Smethurst ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Fuzzy Inference ◽  
Cosmic Ray ◽  
Moisture Distribution ◽  
Soil Moisture Distribution

Catchment scale prediction of soil moisture trends from Cosmic Ray Neutron Rover Surveys using machine learning

2020 ◽  
Author(s):  
Erik Nixdorf ◽  
Marco Hannemann ◽  
Uta Ködel ◽  
Martin Schrön ◽  
Thomas Kalbacher
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Random Forest ◽  
River Basin ◽  
Hydrological Model ◽  
Cosmic Ray ◽  
Moisture Distribution ◽  
Catchment Scale ◽  
Forest Model ◽  
Soil Moisture Distribution

<p>Soil moisture is a critical hydrological component for determining hydrological state conditions and a crucial variable in controlling land-atmosphere interaction including evapotranspiration, infiltration and groundwater recharge.</p><p>At the catchment scale, spatial- temporal variations of soil moisture distribution are highly variable due to the influence of various factors such as soil heterogeneity, climate conditions, vegetation and geomorphology. Among the various existing soil moisture monitoring techniques, the application of vehicle-mounted Cosmic Ray Sensors (CRNS) allows monitoring soil moisture noninvasively by surveying larger regions within a reasonable time. However, measured data and their corresponding footprints are often allocated along the existing road network leaving inaccessible parts of a catchment unobserved and surveying larger areas in short intervals is often hindered by limited manpower.</p><p>In this study, data from more than 200 000 CRNS rover readings measured over different regions of Germany within the last 4 years have been employed to characterize the trends of soil moisture distribution in the 209 km<sup>2</sup> large Mueglitz River Basin in Eastern Germany. Subsets of the data have been used to train three different supervised machine learning algorithms (multiple linear regression, random forest and artificial neural network) based on 85 independent relevant dynamic and stationary features derived from public databases.  The Random Forest model outperforms the other models (R2= ~0.8), relying on day-of-year, altitude, air temperature, humidity, soil organic carbon content and soil temperature as the five most influencing predictors.</p><p>After test and training the models, CRNS records for each day of the last decade are predicted on a 250 × 250 m grid of Mueglitz River Basin using the same type of features. Derived CRNS record distributions are compared with both, spatial soil moisture estimates from a hydrological model and point estimates from a sensor network operated during spring 2019. After variable standardization, preliminary results show that the applied Random Forest model is able to resemble the spatio-temporal trends estimated by the hydrological model and the point measurements. These findings demonstrate that training machine learning models on domain-unspecific large datasets of CRNS records using spatial-temporally available predictors has the potential to fill measurement gaps and to improve soil moisture dynamics predictions on a catchment scale.</p>

scholarly journals Examining the relationship between intermediate-scale soil moisture and terrestrial evaporation within a semi-arid grassland

2016 ◽  
Vol 20 (10) ◽  
pp. 3987-4004 ◽  
Author(s):  
Raghavendra B. Jana ◽  
Ali Ershadi ◽  
Matthew F. McCabe
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
Water Cycle ◽  
Cosmic Ray ◽  
Moisture Distribution ◽  
Observation Data ◽  
Cold Temperatures ◽  
Intermediate Scale ◽  
Semi Arid

Abstract. Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Neutron Probe (CRNP) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here, we present a study to assess the utility of CRNP soil moisture observations in validating model evaporation estimates. The CRNP soil moisture product from a pasture in the semi-arid central west region of New South Wales, Australia, was compared to evaporation derived from three distinct approaches, including the Priestley–Taylor (PT-JPL), Penman–Monteith (PM-Mu), and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson's correlations, quantile–quantile (Q–Q) plots, and analysis of variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly 2 years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q–Q plots and ANOVA illustrate that the root-zone soil moisture represented by the CRNP measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were present, while SEBS model estimates displayed a disconnect from the soil moisture distribution in summers with long dry spells. Importantly, no single evaporation model matched the statistical distribution of the measured soil moisture for the entire period, highlighting the challenges in effectively capturing evaporative flux response within changing landscapes. One of the outcomes of this work is that the analysis points to the feasibility of using intermediate-scale soil moisture measurements to evaluate gridded estimates of evaporation, exploiting the independent, yet physically linked nature of these hydrological variables.

scholarly journals Floristic diversity of extensively used fresh meadows (6510) in the Wielki Łęg Obrzański complex

2015 ◽  
Vol 32 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Agnieszka Anna Klarzyńska ◽  
Anna Kryszak
Keyword(s):  
Soil Moisture ◽  
Poa Pratensis ◽  
Floristic Composition ◽  
Natura 2000 ◽  
Organic Soils ◽  
Habitat Conditions ◽  
Index Method ◽  
Laboratory Methods ◽  
Plant Associations ◽  
Mineral Soils

<p>One of the habitat types protected within the framework of the NATURA 2000 network due to the presence of species of European importance are fresh meadows from the <em>Arrhenatherion</em> alliance. The maintenance of their characteristic floristic composition depends on habitat conditions and extensive use, while any changes in this respect trigger succession transformations potentially threatening their nature value. </p><p>The aim of the study was to conduct nature and habitat valuation of one of the largest meadow complexes in the Wielkopolska region, i.e. Wielki Łęg Obrzański, which will make it possible to describe the preservation status of fresh meadows and their habitats. </p><p>Based on multifaceted analyses of 535 relevés made using the Braun-Blanquet method in the years 2006–2012 and representing the <em>Arrhenatherion</em> alliance, the phytosociological and botanical structure as well as constancy of species in individual variants (floristic types) were determined. Moreover, their habitat conditions were defined, i.e. soil moisture and nitrogen content using the index method according to Ellenberg, while laboratory methods were used to determine the content of organic matter, soil moisture as well as the contents of potassium, magnesium and phosphorus in soil. </p><p>Floristic composition of fresh meadows from the <em>Arrhenatherion</em> alliance differs due to high heterogeneity of habitat. The presence of fresh meadow phytocenoses both on dried organic soils (the driest forms of flood meadows) and on mineral soils (oak-hornbeam forests) contributes to differences in the floristic composition both in ryegrass meadows and grass–fescue meadows, mainly due to soil moisture and fertility as well as sward use type. This constituted the basis for the identification of lower syntaxonomic units in the internal structure of the plant associations. Five variants were distinguished in <em>Arrhenatheretum elatioris</em>, while the community of <em>Poa pratensis</em>–<em>Festuca rubra</em> was developed in as many as 8 variants.</p>

scholarly journals Examining the relationship between intermediate scale soil moisture and terrestrial evaporation within a semi-arid grassland

2016 ◽  
Author(s):  
Raghavendra B. Jana ◽  
Ali Ershadi ◽  
Matthew F. McCabe
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
Water Cycle ◽  
Cosmic Ray ◽  
Moisture Distribution ◽  
Observation Data ◽  
Cold Temperatures ◽  
High Soil Moisture ◽  
Semi Arid

Abstract. Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale-mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Soil Moisture Observing System (COSMOS) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here we present an examination of the links observed between COSMOS soil moisture retrievals and evaporation estimates over a pasture in the semi-arid central-west region of New South Wales, Australia. The COSMOS soil moisture product was compared to evaporation derived from three distinct approaches, including the Priestley-Taylor (PT-JPL), Penman-Monteith (PM-Mu) and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson’s Correlations, Quantile-Quantile (Q-Q) plots, and Analysis of Variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly two years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q-Q plots and ANOVA illustrate that the root-zone soil moisture represented by the COSMOS measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were present, while SEBS model estimates displayed a disconnect from the soil moisture distribution in summers with long dry spells. Importantly, no single evaporation model matched the statistical distribution of the measured soil moisture for the entire period, highlighting the challenges in effectively capturing evaporative flux response within changing landscapes.

scholarly journals Quantifying mesoscale soil moisture with the cosmic-ray rover

2013 ◽  
Vol 10 (6) ◽  
pp. 7127-7160 ◽  
Author(s):  
B. Chrisman ◽  
M. Zreda
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Cosmic Ray ◽  
Surface Fluxes ◽  
Moisture Distribution ◽  
Major Influence ◽  
Survey Area ◽  
Satellite Mission ◽  
Mass Balance Calculation ◽  
Moisture Profile

Abstract. Soil moisture governs the surface fluxes of mass and energy and is a major influence on floods and drought. Existing techniques measure soil moisture either at a point or over a large area many kilometers across. To bridge these two scales we used the cosmic-ray rover, an instrument similar to the recently developed COSMOS probe, but bigger and mobile. This paper explores the challenges and opportunities for mapping soil moisture over large areas using the cosmic-ray rover. In 2012, soil moisture was mapped 22 times in a 25 km × 40 km survey area of the Tucson Basin at 1 km2 resolution, i.e., a survey area extent comparable to that of a pixel for the Soil Moisture and Ocean Salinity (SMOS) satellite mission. The soil moisture distribution is dominated by climatic variations, notably by the North American monsoon, that results in a systematic increase in the standard deviation, observed up to 0.022 m3 m−3, as a function of the mean, between 0.06 and 0.14 m3 m−3. Two techniques are explored to use the cosmic-ray rover data for hydrologic applications: (1) interpolation of the 22 surveys into a daily soil moisture product by defining an approach to utilize and quantify the observed temporal stability producing an average correlation coefficient of 0.82 for the soil moisture distributions that were surveyed and (2) estimation of soil moisture profiles by combining surface moisture from satellite microwave sensors with deeper measurements from the cosmic-ray rover. The interpolated soil moisture and soil moisture profile estimates allow for basin-wide mass balance calculation of evapotranspiration, totaling 241 mm for the year 2012. Generating soil moisture maps with cosmic-ray rover at this intermediate scale may help in the calibration and validation of satellite campaigns and may also aid in various large scale hydrologic studies.

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