Selection and use of representative sites in a large neutron moisture meter network

Soil Research ◽  
1979 ◽  
Vol 17 (2) ◽  
pp. 249 ◽  
Author(s):  
GG Johns
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Root Mean Square ◽  
Mean Square ◽  
Short Term ◽  
Moisture Meter ◽  
Routine Basis ◽  
Neutron Moisture ◽  
Key Sites ◽  
The Relationship

The assessment of the representivity of individual sites in a large neutron moisture meter (NMM) network, and the errors incurred by selecting subsets of various sizes, and using different methods to estimate the full set value from the subsets, is described. Soil water data collected over 13 months from the NMM network (240 sites, divided into eight strata) were analysed to determine the relationship between individual sites and their stratum means. Relationships were assessed using the following four methods: (1) root mean square of the discrepancy; (2) linear regression; (3) quadratic regression; (4) power curve regression. Sites best related to their stratum means were then included in various size subsets, and estimates based on these subsets were compared with the respective full stratum means using 24 months' data. The best estimates of stratum means were obtained by using quadratic regressions and c. eight sites per subset. Using this method, the root mean square discrepancy between estimates of profile water content and observed full stratum means averaged 2.1 mm when the total profile was estimated directly and 2.5 mm when the profile water content was computed as the sum of individual estimates for four arbitrary horizons within the profile. Daily readings of one group of selected subsets indicated the potential of frequent NMM readings at key sites to indicate short-term changes in the soil water content of an area. The performance of the selected subsets has been monitored for a further 12 months as an independent check on their representivity. The root mean square discrepancy of estimates during that period was 2.7 mm. Subsequently only the selected eight sites in each stratum of the field study are being read on a routine basis.

Screening potato clones for resistance to common scab (Streptomyces scabies) in the field

1972 ◽  
Vol 79 (1) ◽  
pp. 75-81 ◽  
Author(s):  
F. A. Langton
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Common Scab ◽  
Severe Infection ◽  
Field Capacity ◽  
Streptomyces Scabies ◽  
Screening Tests ◽  
Moisture Meter ◽  
Neutron Moisture

SUMMARYPotato varieties were grown in the field in soil uniformly infected with Streptomyces scabies. In 1969 tubers were severely and evenly infected but in 1971 infection was slight and not uniform. Agreement of varietal ranking with agricultural experience was good in 1969 but poor in 1971.In 1971, plots protected from rainfall after planting were dry enough at the start of tubering for severe infection; covering the plots for a further 6 weeks followed by irrigation to field capacity resulted in good yields of evenly and severely scabbed tubers. Irrigation during this period suppressed scabbing. The results were easily interpreted in relation to fluctuations in soil-water content measured by a neutron moisture-meter.The efficiency of using only one site and the need to reduce variability in scab screening tests are discussed.

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

2014 ◽  
Vol 28 (2) ◽  
pp. 133-142 ◽  
Author(s):  
Eugene Balashov ◽  
Natalya Buchkina ◽  
Elena Rizhiya ◽  
Csilla Farkas
Keyword(s):  
Sensitivity Analysis ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Root Mean Square ◽  
Seasonal Dynamics ◽  
Mean Square ◽  
Plant Model ◽  
Decomposition Model ◽  
Soil Temperatures

Abstract The objectives of the research were to: fulfil the preliminary assessment of the sensitivity of the soil, water, atmosphere, and plant and denitrification and decomposition models to variations of climate variables based on the existing soil database; validate the soil, water, atmosphere, and plant and denitrification and decomposition modelled outcomes against measured records for soil temperature and water content. The statistical analyses were conducted by the sensitivity analysis, Nash-Sutcliffe efficiency coefficients and root mean square error using measured and modelled variables during three growing seasons. Results of sensitivity analysis demonstrated that: soil temperatures predicted by the soil, water, atmosphere, and plant model showed a more reliable sensitivity to the variations of input air temperatures; soil water content predicted by the denitrification and decomposition model had a better reliability in the sensitivity to daily precipitation changes. The root mean square errors and Nash-Sutcliffe efficiency coefficients demonstrated that: the soil, water, atmosphere, and plant model had a better efficiency in predicting seasonal dynamics of soil temperatures than the denitrification and decomposition model; and among two studied models, the denitrification and decomposition model showed a better capability in predicting the seasonal dynamics of soil water content.

Components of variance involved in estimating soil water content and water content change using a neutron moisture meter

Soil Research ◽  
1979 ◽  
Vol 17 (2) ◽  
pp. 237 ◽  
Author(s):  
DF Sinclair ◽  
J Williams
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Total Variance ◽  
Calibration Error ◽  
Location Error ◽  
Instrument Error ◽  
Moisture Meter ◽  
Site Heterogeneity ◽  
Neutron Moisture ◽  
The Mean

In order to rationalize the allocation of resources in the estimation of soil water content using the neutron moisture meter, it is essential to have a thorough understanding of the sources and magnitudes of the variance components. An error analysis, taking into consideration current technology and methodology, identifies three components of total variance, attributable to: location error due to site heterogeneity with respect to soil water and random error associated with positioning the probe; calibration error; and instrument error. Data from three locations illustrate that the location variance is the major source of random error in the total variance of an individual estimate. For the total variance of the mean over a site containing n sample estimates, the large location component is reduced by a factor of n such that in many circumstances it will reduce to the same order as the calibration component which is independent of n. This is particularly true for field calibration. The instrument error and that error introduced by the use of count rate ratio are small and contribute in a very minor way to the total variance of the mean. The analysis reveals that the nature of the relationship between the magnitude of the location error and the calibration error is dependent on site heterogeneity, the value of n and the precision of the calibration equation.

Neutron moisture meter : the dependence of their response on soil parameters

Soil Research ◽  
1986 ◽  
Vol 24 (1) ◽  
pp. 11 ◽  
Author(s):  
DJ Wilson ◽  
AIM Ritchie
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Nuclear Reactor ◽  
Diffusion Theory ◽  
Soil Parameters ◽  
Moisture Meter ◽  
Neutron Moisture ◽  
Theory Calculation ◽  
Neutron Absorption Cross Section

A multigroup diffusion theory calculation based on a nuclear reactor neutronics code is used to determine the response of a neutron moisture meter to changes in soil parameters such as dry soil density, soil water content, thermal neutron absorption cross-section and neutron scattering crosssection. Empirical equations which fit the results can be used to estimate the response at values of the soil parameters other than those used in the calculations. These equations can also be used to estimate the accuracy with which the parameters must be known to achieve a required accuracy in the derived soil water content.

The Relationship of Root Mean Square Value of Electromyography and Isometric Torque of Quadriceps in Normal Subjects

2016 ◽  
Vol 26 (1) ◽  
pp. 58
Author(s):  
Qiurong XIE ◽  
Zheng JIANG ◽  
Qinglu LUO ◽  
Jie LIANG ◽  
Xiaoling WANG ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Normal Subjects ◽  
Mean Square ◽  
Isometric Torque ◽  
Relationship Of ◽  
The Relationship

Soil Water Characteristic Curve and its Applications in Tunnel

2011 ◽  
Vol 261-263 ◽  
pp. 1039-1043
Author(s):  
Yu You Yang ◽  
Qin Xi Zhang ◽  
Gui He Wang ◽  
Jia Xing Yu
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Land Subsidence ◽  
Unsaturated Soil ◽  
Characteristic Curve ◽  
Tunnel Construction ◽  
Coupling Theory ◽  
Engineering Analysis ◽  
Soil Water Characteristic Curve ◽  
The Relationship

A soil water characteristic curve (SWCC) can describe the relationship between unsaturated soil matric suction and water content. By analyzing and researching the test data of the soil water characteristic curve researchers can initially establish the SWCC equation and apply this equation to the actual engineering analysis. In another words, this article is based on the fluid-solid coupling theory of unsaturated soil used to analyze and study the problem of land subsidence caused by tunnel construction. Numerical calculations show that the coupling results agree well with the measured curve works.

scholarly journals Relationship Between Millennials and Brand Loyalty: Mediating Brand Loyalty Factors

2017 ◽  
Vol 5 (3) ◽  
pp. 223
Author(s):  
Dhameeth, S. Gehan ◽  
Ochi, Yamamoto
Keyword(s):  
Root Mean Square ◽  
Brand Loyalty ◽  
Structural Equation ◽  
Brand Management ◽  
Management Strategies ◽  
Second Phase ◽  
Mean Square ◽  
Root Mean Square Residual ◽  
Mediating Factors ◽  
The Relationship

<p><em>The purpose of this study is to identify factors (brand elements) that mediate between Millennials and brand loyalty, and to test a theoretical model that includes these mediating factors in describing the relationship between millennials and brand loyalty. The study focused on the key factors that we identified and hypothesized to mediate the relationship between millennials and brand loyalty. The quantitative study surveyed two hundred and fifty-three (n=253) respondents randomly drawn. Structural Equation Modelling (SEM) was used to test a model of the relationship between the mediating factors, millennials and brand loyalty. All model fit parameters were well within acceptable bounds. The Comparative Fit Index (CFI) was 0.999, Root Mean Square Error of Approximation (RMSEA) was 0.018, and Standardized Root Mean Square Residual (SRMR) was 0.022. However, we believe that the model is over-fitting the data, and this is not surprising given that there are 22 variables and 253 data points. These results show promise, but require further investigation in a second phase of the inquiry. This study limited itself to surveying millennials, brand loyalty, and the seven mediating factors we identified and hypothesized to play a role in mediating between them. Based on this study, brand management strategies are proposed.</em><em></em></p>

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