Investigation of Wetting Front Propagation Dynamics Using Soil Impedance Measurements: Implications for Modelling and Irrigation Scheduling

The authors propose a measurement method that divides the depth of the soil sample in discrete regions to investigate soil water propagation dynamics using soil impedance measurements. Experiments were conducted on a cylindrical phantom using a clay loam soil sample (60 % clay, 21 % loam and 19 % sa...

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Bibliographic Details
Published in:Water resources management 2015-01, Vol.29 (1), p.197-210
Main Authors: Gutierrez Gnecchi, Jose Antonio, Mendez Patiño, Arturo, Landeros Paramo, Fernando, Tellez Anguiano, Adriana del Carmen, Lorias Espinoza, Daniel
Format: Article
Language:English
Subjects:
Atmospheric Sciences
Automation
Civil Engineering
Clay loam
Data acquisition systems
Data compression
Dynamic tests
Earth and Environmental Science
Earth Sciences
Electrodes
Environment
Experiments
Geotechnical Engineering & Applied Earth Sciences
Hydraulics
Hydrogeology
Hydrology/Water Resources
Impedance
Irrigation
Irrigation scheduling
Keyboards
Laboratories
Loam soils
Mathematical models
Measurement techniques
Moisture content
Neural networks
Propagation
Sand
Scheduling
Sensors
Signal processing
Soil depth
Soil dynamics
Soil investigations
Soil mechanics
Soil water
Studies
Tomography
Water
Water content
Water depth
Water resources management
Wetting
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Description
Summary:The authors propose a measurement method that divides the depth of the soil sample in discrete regions to investigate soil water propagation dynamics using soil impedance measurements. Experiments were conducted on a cylindrical phantom using a clay loam soil sample (60 % clay, 21 % loam and 19 % sand). The resulting impedance changes represent the wetting front (WF) propagation process at the different measurement depths. The measured impedance data is used to A) show graphically the wetting front propagation process, obtain B) a 1st order model, C) an ARX1821 model of the impedance change as a function of the irrigation volume applied and D) estimating changes in water content using a neural network. The results indicate that the proposed measurement technique can be used to detect and predict the movement of liquid trough the soil sample. The neural network permits inferring the water content from impedance and soil-water mixture temperature values. Changes in soil impedance in each segment, due to the water propagating downwards through the soil sample, can be used to study the dynamics of the wetting front, irrigation scheduling and model improvement from physical data.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-014-0835-4