Review comments to McJannet et al. (Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors)

2017 ◽  
Author(s):  
Anonymous
Keyword(s):  
Soil Moisture ◽  
Cosmic Ray ◽  
Soil Moisture Sensors

scholarly journals Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

2017 ◽  
Author(s):  
David McJannet ◽  
Aaron Hawdon ◽  
Brett Baker ◽  
Luigi Renzullo ◽  
Ross Searle
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Critical Role ◽  
Cosmic Ray ◽  
Process Models ◽  
Soil Moisture Sensors ◽  
Property Scale ◽  
Neutron Sensors ◽  
Local Farm ◽  
Soil Moisture Variability

Abstract. Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations at corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes a research project aimed at producing soil moisture estimates at a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property scale soil moisture which may also have application in calibration and validation studies or local farm management. Intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer scale soil moisture models.

scholarly journals Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

2017 ◽  
Vol 21 (12) ◽  
pp. 6049-6067 ◽  
Author(s):  
David McJannet ◽  
Aaron Hawdon ◽  
Brett Baker ◽  
Luigi Renzullo ◽  
Ross Searle
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Critical Role ◽  
Cosmic Ray ◽  
Process Models ◽  
Soil Moisture Sensors ◽  
Property Scale ◽  
Neutron Sensors ◽  
Local Farm ◽  
Soil Moisture Variability

Abstract. Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

Improving estimates of UK soil moisture using the JULES land surface model with COSMOS-UK measurements in the LaVEnDAR data assimilation framework

2020 ◽  
Author(s):  
Elizabeth Cooper ◽  
Ewan Pinnington ◽  
Richard Ellis ◽  
Eleanor Blyth ◽  
Simon Dadson ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Soil Texture ◽  
Land Surface ◽  
Land Surface Model ◽  
Cosmic Ray ◽  
Surface Model ◽  
Soil Physics ◽  
Soil Moisture Sensors ◽  
The Uk

<p>Soil moisture predictions are increasingly important in hydrological, ecological and agricultural applications. In recent years the availability of wide-area assessments of current and future soil-moisture states has grown, yet few studies have combined model-based assessments with observations beyond the point scale. Here we use the JULES land surface model together with COSMOS-UK data to evaluate the extent to which data assimilation can improve predictions of soil moisture across the United Kingdom.</p><p>COSMOS-UK is a network of soil moisture sensors run by UKCEH. The network provides soil moisture measurements at around 50 sites throughout the UK using innovative Cosmic Ray Neutron Sensors (CRNS). Half hourly measurements of the meteorological variables that the Joint UK Land Environment Simulator (JULES) requires as driving data are also recorded at COSMOS-UK sites, allowing us to run JULES at observation locations. This provides a unique opportunity to compare soil moisture outputs from JULES with CRNS observations; these measurements have a footprint of up to 12 ha (approx 30 acres) and are therefore better scale matched with JULES outputs than those from point sensors.</p><p>We have used the Land Variational Ensemble Data Assimilation Framework (LaVEnDAR) to combine soil moisture estimates from JULES with daily CRNS observations from one year at a number of COSMOS-UK sites. We show that this results in improved soil moisture predictions from JULES over several years. This has been achieved by optimising parameters in the pedo-transfer function used to derive JULES soil physics parameters from soil texture information. Using data assimilation with LaVEnDAR in this way allows us to explore the relationships between soil moisture estimates, soil physics parameters and soil texture, as well as improving the agreement between JULES model outputs and observations.</p>

Field scale root zone soil moisture estimation by coupling cosmic-ray neutron sensor with soil moisture sensors

2020 ◽  
Author(s):  
Hami Said ◽  
Georg Weltin ◽  
Lee Kheng Heng ◽  
Trenton Franz ◽  
Emil Fulajtar ◽  
...  
Keyword(s):  
Water Management ◽  
Soil Moisture ◽  
Root Zone ◽  
Cosmic Ray ◽  
Agricultural Water ◽  
Field Scale ◽  
Agricultural Water Management ◽  
Soil Moisture Sensors ◽  
Major Disadvantage ◽  
Filter Approach

<p>Since it has become clear that climate change is having a major impact on water availability for agriculture and crop productivity, an accurate estimation of field-scale root-zone soil moisture (RZSM) is essential for improved agricultural water management. The Cosmic Ray Neutron Sensor (CRNS) has recently been used for field-scale soil moisture (SM) monitoring in large areas and is a credible and robust technique. Like other remote or proximal sensing techniques, the CRNS provides only SM data in the near surface. One of the challenges and needs is to extend the vertical footprint of the CRNS to the root zone of major crops. This can be achieved by coupling the CRNS measurements with conventional methods for soil moisture measurements, which provide information on soil moisture for whole rooting depth.</p><p>The objective of this poster presentation is to estimate field-scale RZSM by correlating the CRNS information with that from soil moisture sensors that provide soil moisture data for the whole root depth. In this study, the Drill and Drop probes which provide continuous profile soil moisture were selected. The RZSM estimate was calculated using an exponential filter approach.</p><p>Winter Wheat cropped fields in Rutzendorf, Marchfeld region (Austria) were instrumented with a CRNS and Drill & Drop probes. An exponential filter approach was applied on the CRNS and Drill and drop sensor data to characterize the RZSM. The preliminary results indicate the ability of the merging framework procedure to improve field-scale RZSM in real-time. This study demonstrated how to combine the advantages of CRNS nuclear technique (especially the large footprint and good representativeness of obtained data) with the advantages of conventional methods (providing data for whole soil profile) and overcome the shortcoming of both methods (the lack of information in the deeper part of soil profile being the major disadvantage of CRNS and the spatial limitation and low representativeness of point data being the major disadvantage of conventional capacitance sensors). This approach can be very helpful for improving agricultural water management.</p>

Performance of soil moisture sensors in gypsiferous and salt-affected soils

2021 ◽  
Vol 209 ◽  
pp. 200-209
Author(s):  
Adil K. Salman ◽  
Saad E. Aldulaimy ◽  
Huthaifa J. Mohammed ◽  
Yaareb M. Abed
Keyword(s):  
Soil Moisture ◽  
Soil Moisture Sensors ◽  
Salt Affected Soils

Moisture and humidity dependence of the above-ground cosmic-ray neutron intensity revised

2021 ◽  
Author(s):  
Markus Köhli ◽  
Jannis Weimar ◽  
Benjamin Fersch ◽  
Roland Baatz ◽  
Martin Schrön ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Soil Moisture ◽  
Count Rate ◽  
Cosmic Ray ◽  
Mathematical Treatment ◽  
Specific Response ◽  
Parameter Equation ◽  
Neutron Count ◽  
Dry Conditions ◽  
Humidity Dependence

<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>

scholarly journals Using Cosmic-Ray Neutron Probes in Validating Satellite Soil Moisture Products and Land Surface Models

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1362 ◽  
Author(s):  
Mustafa Berk Duygu ◽  
Zuhal Akyürek
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Cosmic Ray ◽  
Surface Model ◽  
High Temporal Resolution ◽  
Land Surface Models ◽  
Statistical Measures ◽  
Surface Models ◽  
Global Land

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.

scholarly journals Calibration approaches of cosmic-ray neutron sensing for soil moisture measurement in cropped fields

2013 ◽  
Vol 10 (4) ◽  
pp. 4237-4274 ◽  
Author(s):  
C. A. Rivera Villarreyes ◽  
G. Baroni ◽  
S. E. Oswald
Keyword(s):  
Soil Moisture ◽  
Cosmic Ray ◽  
Fast Neutrons ◽  
Winter Rye ◽  
Moisture Profile ◽  
Hill Slope ◽  
Vadose Zone Hydrology ◽  
Classical Point ◽  
Soil Moisture Measurement ◽  
Single Set

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.

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