| dc.contributor.author |
Kargas, G |
en |
| dc.contributor.author |
Kerkides, P |
en |
| dc.date.accessioned |
2014-06-06T06:51:42Z |
|
| dc.date.available |
2014-06-06T06:51:42Z |
|
| dc.date.issued |
2012 |
en |
| dc.identifier.issn |
00167061 |
en |
| dc.identifier.uri |
http://dx.doi.org/10.1016/j.geoderma.2012.06.024 |
en |
| dc.identifier.uri |
http://62.217.125.90/xmlui/handle/123456789/5638 |
|
| dc.subject |
Dielectric device |
en |
| dc.subject |
Electrical conductivity |
en |
| dc.subject |
Pore water salinity |
en |
| dc.subject.other |
Bulk soils |
en |
| dc.subject.other |
Dielectric permittivities |
en |
| dc.subject.other |
Dielectric sensors |
en |
| dc.subject.other |
Electrical conductivity |
en |
| dc.subject.other |
Pore waters |
en |
| dc.subject.other |
Salinity levels |
en |
| dc.subject.other |
Sensor data |
en |
| dc.subject.other |
Soil pore waters |
en |
| dc.subject.other |
Dielectric devices |
en |
| dc.subject.other |
Electric conductivity |
en |
| dc.subject.other |
Forecasting |
en |
| dc.subject.other |
Mathematical models |
en |
| dc.subject.other |
Permittivity |
en |
| dc.subject.other |
Porous materials |
en |
| dc.subject.other |
Salinity measurement |
en |
| dc.subject.other |
Sensors |
en |
| dc.subject.other |
Soil moisture |
en |
| dc.subject.other |
Water |
en |
| dc.subject.other |
Geologic models |
en |
| dc.subject.other |
comparative study |
en |
| dc.subject.other |
electrical conductivity |
en |
| dc.subject.other |
error analysis |
en |
| dc.subject.other |
model test |
en |
| dc.subject.other |
numerical model |
en |
| dc.subject.other |
performance assessment |
en |
| dc.subject.other |
permittivity |
en |
| dc.subject.other |
porewater |
en |
| dc.subject.other |
porous medium |
en |
| dc.subject.other |
prediction |
en |
| dc.subject.other |
salinity |
en |
| dc.subject.other |
sensor |
en |
| dc.subject.other |
soil moisture |
en |
| dc.title |
Comparison of two models in predicting pore water electrical conductivity in different porous media |
en |
| heal.type |
journalArticle |
en |
| heal.identifier.primary |
10.1016/j.geoderma.2012.06.024 |
en |
| heal.publicationDate |
2012 |
en |
| heal.abstract |
In this paper a comparison of two models predicting electrical conductivity of the soil pore water (σ p) is attempted using data of soil dielectric permittivity ε and bulk soil electrical conductivity σ b, as these are obtained by two dielectric sensors the WET and the 5TE. These models are: The linear model by Hilhorst and the model of Rhoades. The evaluation of the models was performed in six different porous media and in different levels of salinity (0.28-6dS.m -1) and soil moisture content (θ). For the WET sensor the relationship ε-σ b is highly linear (0.960<R 2<0.999) for all porous media tested. The linear model overestimates σ p for salinity values up to 1.2dS.m -1 in all media except the sand, while for larger values it significantly underestimates σ p. For large values of θ (θ>0.2m 3/m 3) in the sandy media the σ p-predictions are relatively more accurate. The model of Rhoades gives better results than the linear model and closer to actual values of σ p. From the values of RMSE (%), the deviations are about 10% for the sands and 10-60% for the other soils. For the 5TE sensor the relationship ε-σ b is less linear than for the WET for all porous media with 0.893<R 2<0.996. There is a considerable scatter in σ p and in larger σ p values there is an overestimation, which is opposite than that for WET. The magnitude of the slopes of the lines (ε-σ b) depends mainly on the salinity level and as it increases the slope decreases. The magnitude of the slopes, for the same level of salinity, is much less than those of the WET for all porous media. The σ p values from the model of Rhoades using the data of 5TE are better than those obtained by the linear model. From the values of RMSE (%), the deviations in most of the cases are worse than those obtained with the WET data. In the sandy porous media another model, for the σ p prediction was used. The results were reasonable especially for the WET sensor data. © 2012 Elsevier B.V. |
en |
| heal.journalName |
Geoderma |
en |
| dc.identifier.volume |
189-190 |
en |
| dc.identifier.doi |
10.1016/j.geoderma.2012.06.024 |
en |
| dc.identifier.spage |
563 |
en |
| dc.identifier.epage |
573 |
en |