Improvements in the Definition of Cryic and Pergelic Soil Temperature Regimes in Soil Taxonomy Using Daylength/Solar Radiation

Soil Horizons ◽  
1995 ◽  
Vol 36 (1) ◽  
pp. 20 ◽  
Author(s):  
S. E. Samson-Liebig ◽  
J. M. Kimble ◽  
C. L. Ping
Keyword(s):  
Solar Radiation ◽  
Soil Temperature ◽  
Soil Taxonomy ◽  
Temperature Regimes ◽  
Definition Of

Soil temperature regimes in Cameroon as defined in soil taxonomy

Geoderma ◽  
1986 ◽  
Vol 37 (2) ◽  
pp. 149-155 ◽  
Author(s):  
Jef Embrechts ◽  
René Tavernier
Keyword(s):  
Soil Temperature ◽  
Soil Taxonomy ◽  
Temperature Regimes

Controversies in the Definition of “Iso” Soil Temperature Regimes

2009 ◽  
Vol 73 (3) ◽  
pp. 983-988 ◽  
Author(s):  
M. Tejedor ◽  
C. Jiménez ◽  
M. Rodríguez ◽  
J. Neris
Keyword(s):  
Soil Temperature ◽  
Temperature Regimes ◽  
Definition Of

COMPARISON OF CANADIAN AND AMERICAN CLASSIFICATION SYSTEMS FOR SOME ARCTIC SOILS OF THE UNGAVA-LABRADOR PENINSULA

1985 ◽  
Vol 65 (2) ◽  
pp. 283-291 ◽  
Author(s):  
W. H. HENDERSHOT
Keyword(s):  
Soil Temperature ◽  
Key Words ◽  
Soil Classification ◽  
Fine Sand ◽  
Classification Systems ◽  
Shallow Depth ◽  
American System ◽  
Arctic Soils ◽  
Temperature Regimes ◽  
Definition Of

Thirteen pedons in an arctic environment were classified according to the Canadian and American systems of soil classification. Major differences in groupings result from the contrasting approaches. Although the definition used in Canada to define Cryosols is sometimes difficult to apply in the field, the underlying concept is valid, since soils with permafrost at a shallow depth should be separated at the highest level of classification. The American system virtually ignores the influence of permafrost on pedogenesis. Its reliance on soil temperature regimes at both the great group and subgroup levels is redundant. It is suggested that the definition of Cryosols, in the Canadian system, be changed to include strongly cryoturbated soils with very cold or colder soil temperature regimes. The American system should be altered to provide for pergelic great groups; in addition permafrost and strong cryoturbation should be used to create new subgroups. The requirement that a cambic horizon have a texture finer than loamy fine sand should be waived in soils having cryic or pergelic soil temperature regimes. Key words: Cryosols, cryoturbated soils, permafrost, pergelic soils

scholarly journals Soil temperature regimes in Finland

1998 ◽  
Vol 7 (4) ◽  
pp. 507-512 ◽  
Author(s):  
M. YLI-HALLA ◽  
D. MOKMA
Keyword(s):  
Soil Temperature ◽  
Temperature Regime ◽  
Soil Surface ◽  
Soil Classification ◽  
Soil Taxonomy ◽  
The North ◽  
Temperature Regimes ◽  
Soil Temperature Regime ◽  
The Mean ◽  
The Difference

Soil temperature regime substantially influences soil classification in Soil Taxonomy particularly in temperate areas. To facilitate correct classification of soils of Finland, the temperature regimes in soils of the country were determined. The mean annual soil temperature, measured at 50 cm below soil surface, ranged from 6.4°C at the warmest site (Anjala) to 1.9°C at the coldest one (Utsjoki, Kevo), and the mean summer soil temperature from 13.7°C to 6.2°C at the same stations, all being in the range of the cryic temperature regime. The mean annual soil temperature was 2 to 5°C higher than the mean annual air temperature, the difference (Y, °C) depending on the duration of snow coverage (X, days) according to the following equation: Y = 0.0305 X - 2.16, R2 = 0.91, n = 9. Even soils of the warmest areas in southern Finland and the mineral soils of the coldest areas in the north, at least for the most part, have cryic soil temperature regimes. Therefore, most soils of Finland, classified according to Soil Taxonomy, have names where the cryic temperature regime appears on the suborder or great group level.;

Seasonal soil temperature regimes in south-eastern Australia

Soil Research ◽  
1980 ◽  
Vol 18 (3) ◽  
pp. 325 ◽  
Author(s):  
CL Watson
Keyword(s):  
Soil Temperature ◽  
Soil Taxonomy ◽  
South Eastern ◽  
Air Temperatures ◽  
South Wales ◽  
Temperature Regimes ◽  
Eastern Australia ◽  
Soil Temperatures ◽  
Western Victoria ◽  
South Eastern Australia

The soil temperature regimes of 15 locations in south-eastern Australia were categorized by using criteria adopted by the US. Soil Taxonomy. On the basis of mean annual and seasonal soil temperatures from depths of 50-61 cm, all sites but one were classed as thermic, having mean annual soil temperatures between 15� and 22�C and seasonal differences of more than 5�C. Mean annual and seasonal soil temperatures were significantly correlated with the corresponding mean air temperatures. Estimates of soil temperature regimes at other similar locations in the region may therefore be made, provided the appropriate air temperature data are available. It appears that the thermic category will not apply to certain areas of southern Victoria or to the high altitude areas of the Great Dividing Range, that extend from western Victoria through to northern New South Wales.

Integrating of equations of the Lagrange for definition of disturbances from a solar radiation in orbits of geosynchronous satellites

2010 ◽  
Vol 27 (0) ◽  
pp. 118-125
Author(s):  
В. У. Клімик ◽  
В. П. Єпішев ◽  
І. І. Мотрунич ◽  
В. І. Кудак ◽  
Г. М. Мацо
Keyword(s):  
Solar Radiation ◽  
Definition Of ◽  
Geosynchronous Satellites

Estimation of development times for immature stages of the bush fly, Musca vetustissima Walker (Diptera: Muscidae), and their simulation from air temperature and solar radiation records

1990 ◽  
Vol 80 (1) ◽  
pp. 73-78 ◽  
Author(s):  
W. G. Vogt ◽  
J.M. Walker ◽  
S Runko
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Adult Development ◽  
Development Rate ◽  
Immature Stages ◽  
Rate Model ◽  
Development Times ◽  
Temperature Regimes ◽  
Non Linear ◽  
Constant And Fluctuating Temperature

AbstractImmature stages of bush fly, Musca vetustissima Walker, were reared at constant temperatures ranging from 18°C to 39°C. Mean egg to adult development times ranged from 7.0 to 25.8 days. Eggs, larval instars I, II and III, and pupae averaged, respectively, 3.1, 4.4, 5.5, 36.4 and 50.6% of the total development time. Mean development rate was a non-linear function of temperature. A non-linear development rate model accurately estimated mean development times of immature stages under both constant and fluctuating temperature regimes. Simulation of dung pad temperatures, from air temperature and solar radiation records, predicted development times of soil- and dunginhabiting stages of M. vetustissima to within 4% of those observed under field conditions.

A Modeling Approach to Simulate Effects of Intercropping and Interspecific Competition in Arable Crops

2012 ◽  
pp. 160-181
Author(s):  
Heike Knörzer ◽  
Simone Graeff-Hönninger ◽  
Bettina U. Müller ◽  
Hans-Peter Piepho ◽  
Wilhelm Claupein
Keyword(s):  
Solar Radiation ◽  
Soil Temperature ◽  
Interspecific Competition ◽  
Neighborhood Effects ◽  
Individual Growth ◽  
Beneficial Effects ◽  
Modeling Approaches ◽  
Use Efficiency ◽  
And Performance ◽  
Radiation Use

Interspecific competition between species influences their individual growth and performance. Neighborhood effects become especially important in intercropping systems, and modeling approaches could be a useful tool to simulate plant growth under different environmental conditions to help identify appropriate combinations of different crops while managing competition. This study gives an overview of different competition models and their underlying modeling approaches. To model intercropping in terms of neighbouring effects in the context of field boundary cultivation, a new model approach was developed and integrated into the DSSAT model. The results indicate the possibility of simulating general competition and beneficial effects due to different incoming solar radiation and soil temperature in a winter wheat/maize intercropping system. Considering more than the competition factors is important, that is, sunlight, due to changed solar radiation alone not explaining yield differences in all cases. For example, intercropped maize could compensate low radiation due to its high radiation use efficiency. Wheat benefited from the increased solar radiation, but even more from the increased soil temperature.

A Revised Force–Restore Model for Land Surface Modeling

2004 ◽  
Vol 43 (11) ◽  
pp. 1768-1782 ◽  
Author(s):  
Diandong Ren ◽  
Ming Xue
Keyword(s):  
Soil Temperature ◽  
Skin Temperature ◽  
Land Surface ◽  
Deep Layer ◽  
Additional Term ◽  
Prediction Equation ◽  
Lapse Rate ◽  
Temperature Prediction ◽  
Land Surface Modeling ◽  
Definition Of

Abstract To clarify the definition of the equation for the temperature toward which the soil skin temperature is restored, the prediction equations in the commonly used force–restore model for soil temperature are rederived from the heat conduction equation. The derivation led to a deep-layer temperature, commonly denoted T2, that is defined as the soil temperature at depth πd plus a transient term, where d is the e-folding damping depth of soil temperature diurnal oscillations. The corresponding prediction equation for T2 has the same form as the commonly used one except for an additional term involving the lapse rate of the “seasonal mean” soil temperature and the damping depth d. A term involving the same also appears in the skin temperature prediction equation, which also includes a transient term. In the literature, T2 was initially defined as the short-term (over several days) mean of the skin temperature, but in practice it is often used as the deep-layer temperature. Such inconsistent use can lead to drift in T2 prediction over a several-day period, as is documented in this paper. When T2 is properly defined and initialized, large drift in T2 prediction is avoided and the surface temperature prediction is usually improved. This is confirmed by four sets of experiments, each for a period during each season of 2000, that are initialized using and verified against measurements of the Oklahoma Atmospheric Surface-Layer Instrumentation System (OASIS) project.

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