Estimation and modelling of Olak Lempit peatlands based on ground penetrating radar and laboratory investigation
Peat soil is an important ecosystem which acts as natural fertilizer that can increase the quality of soil and is considered as gold mine for the agriculturists and farmers. Hence, the knowledge of peat soil properties which is high in water content must be well understood. During dry periods, if wa...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.utm.my/104544/1/NurulIzzatiAbdKarimPFTIR2019.pdf.pdf |
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| Summary: | Peat soil is an important ecosystem which acts as natural fertilizer that can increase the quality of soil and is considered as gold mine for the agriculturists and farmers. Hence, the knowledge of peat soil properties which is high in water content must be well understood. During dry periods, if water content is lower than the point of no return, the soil will shrink. Hence, by determining the accurate water content of peat soil during dry and wet seasons, the quality of peat soil can be enhanced. The aim of the thesis is to determine accurately the soil water content (SWC) estimation of peat soil using Ground Penetrating Radar (GPR) especially during wet and dry seasons. To achieve this aim, a site-specific petrophysical relationship model for SWC estimation was developed for wet and dry seasons. Samples of peat soils were collected during dry and wet seasons for laboratory measurements by utilising two processes namely dielectric permittivity determination and water content estimation. A 2-dimensional soil cylindrical capacitor was designed to measure the capacitance from the results of current and voltage produced by the samples. Then, dielectric permittivity of the soil was calculated using an equation. After the 24-hour oven-drying process at 105°C, the water content of the peat samples was measured. The results obtained from both measurements were used as a parameter for modelling the site-specific petrophysical relationship of wet and dry seasons. Third-order polynomial was found to be the best fitting model for dry season with the result of R2 = 0.944 and standard error = 0.146 and wet season with R2 = 0.981 and standard error = 0.063. Three existing models namely Roth model; Schaap model and Idi model were evaluated along with the third-order polynomial model and validated by gravimetric measurements for dry and wet seasons. Based on the result, the proposed model gives the most accurate measurement of water content with RMSE for dry and wet seasons at 0.15 and 0.17 respectively. The findings suggest the importance of site-specific petrophysical relationship to estimate water content using GPR and laboratory investigation for wet and dry seasons. |
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