Investigation of soil moisture content over a cultivated farmland in Abeokuta Nigeria using electrical resistivity methods and soil analysis

Ganiyu, S. A.; Olurin, O. T.; Oladunjoye, Michael A.; Badmus, B. S.

doi:10.1016/j.jksus.2019.02.016

Cited by 17 publications

(13 citation statements)

References 30 publications

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“…The dataset in the appendix (Table A1) used in this model was collected from several scholars' papers published in journals such as IEEE, Applied physics letters, Research gates, Elsevier, among others. These scholars conducted laboratory and field experiments to investigate the resistivity of different types of soils and the impact of the moisture content on its resistivity [3], [8], [9], [31], [32]. which is a numerical computing software used to manipulate matrix, plotting data, implement models, create a user interface, etc.…”

Section: Knn Model Resultsmentioning

confidence: 99%

Estimation of Soil Moisture and Earth Resistivity Using Wenner’s Method and Machine Learning

Cussei

2021

Meet. Abstr.

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The present research consists of using Wenner's four electrodes method to measure the electrical resistivity of soil (e.g., clayey silt and clay), applying two machine-learning algorithms (k Nearest Neighbor (KNN) and Support Vector Machine (SVM)) to predict the type of soil. Such predictions may be leveraged, e.g., to extract parameters to help choose materials to withstand electrochemical corrosion in a hybrid environment (soil and moisture). A dataset of 162 sample points was obtained from the literature ( 151training, 11 testing points). From laboratory experiments, 26 sample points (corresponding to 130 measurements) were obtained; 6 points were added to the literature training dataset, and 20 were used as testing points for final validation. The results show that given the electrical resistivity of soil and its moisture, the KNN model is capable of predicting the type of soil with accuracy, error rate, sensitivity, specificity, and precision of 70%, 30%, 64%, 83%, and 90% respectively. In contrast, the SVM presented an error rate and accuracy of 44.1% and 55.9 % respectively.

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Section: Knn Model Resultsmentioning

confidence: 99%

Estimation of Soil Moisture and Earth Resistivity Using Wenner’s Method and Machine Learning

Cussei

2021

Meet. Abstr.

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“…One of the commonly used geophysical methods to delineate subsoil features, aquifer geometry, determine the depth to aquifer units, and characterise the hydrological properties in groundwater exploration is the geoelectrical resistivity method [ 2 ]. This method has been used extensively by researchers for various soil investigations, hydrological and agricultural purposes [ 3 , 8 , 11 , 14 , 17 , 18 , 29 , 34 , 36 , 39 ]. The heterogeneity of the area under investigation determines the type of survey to be performed (one-, two- or three-dimensional electrical resistivity survey) [ 36 ].…”

Section: Introductionmentioning

confidence: 99%

Geophysical and contamination assessment of soil spatial variability for sustainable precision agriculture in Omu-Aran farm, Northcentral Nigeria

Kayode

Aizebeokhai

Odukoya

2022

Heliyon

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“…Soil hydraulic capacitance can be measured with time and depth, β (z,t), using two types of probes. The first probe for detecting moisture with time and depth, ϴ (z,t), by the resistivity (Ganiyu et al, 2020). The second for detecting electrical conductivity with time and depth, EC (z,t).…”

Section: Introductionmentioning

confidence: 99%

The modified Richard’s equation for assessing the impact of drought and salinity in arid and semi-arid zones. part two: a soil hydraulic capacitance

Hegazy

2022

SVU-International Journal of Agricultural Sciences

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The soil hydraulic capacitance, a tank like the plant water reservoir, is being controlled by signals, valves like the switches. Three types of signaling devices, Geo, Bio, and weather controlled were discussed. The soil hydraulic capacitance property was first discovered by the author when modeling the wheat root water uptake under saline and drought conditions. Under the latter extreme conditions, treating plants with silica products was the common managerial practice used for enhancing uptake and plantation. A split-split plot experimental design with four replicates was used to conduct the research in Oraby Village, Maryout area, Alexandria, Egypt in the last year of the most water-scarce decade. The aim of the experiment was to put the sink/ source term of Richard's equation, S, into consideration under a macroscopic electrical modeling, AMUN_SHC. The S-shaped relative stress response function was used to describe the relation SSI= f (h, z, t). AMOUN_SHC showed that the sink term of Richard's equation is the product of multiplying the soil hydraulic capacitance and soil stress index. The soil stress index, plant stress index and strain of straw sap were calculated. The soil hydraulic capacitance was derived estimated and discussed. The effect of silicon as a beneficial element on the soil hydraulic capacitance and therefore the winter wheat water uptake was estimated and discussed. The brilliant result from the model is that the property soil hydraulic capacitance controls the compensated root water uptake under drought and saline conditions in accordance with stress, strain and weather controlled relationships. See the graphical abstract in Fig (1)

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Investigation of soil moisture content over a cultivated farmland in Abeokuta Nigeria using electrical resistivity methods and soil analysis

Cited by 17 publications

References 30 publications

Estimation of Soil Moisture and Earth Resistivity Using Wenner’s Method and Machine Learning

Estimation of Soil Moisture and Earth Resistivity Using Wenner’s Method and Machine Learning

Geophysical and contamination assessment of soil spatial variability for sustainable precision agriculture in Omu-Aran farm, Northcentral Nigeria

The modified Richard’s equation for assessing the impact of drought and salinity in arid and semi-arid zones. part two: a soil hydraulic capacitance

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