Peat soil is an important ecosystem (Adon et al. 2013) and plays as a natural fertilizer that can improve the quality of the soil. Hence, the information about the properties of peat soil needs to be fully understood. The complex behavior of the petrophysical properties of peat soil, especially in terms of the quality of the soil, necessitates extensive research for an understanding of the behavior of these properties. Water content is one of the properties that can influence soil quality. Kaiser et al. (2010) mentioned that water presence more in organic soils than mineral soils and clearly making it possible for SWC estimation. Indeed, water is the component that has the greatest influence on the apparent dielectric permittivity (81). This is because, since water contains ion and the electrical conductivity associated with ion mobility is the dominant factor in determining bulk material electrical conductivity. Besides, as water presents in pore space Abstract: Estimating Soil Water Content (SWC) for peat soil is fundamental parameters that are essential for quality of soil especially during drying periods. Transformations and subsequent losses to groundwater or atmosphere are mediated by moisture conditions in the soil. Success or failure of food, fiber, and energy production from agricultural crops depends on soil water storage between rainfall and/or irrigation events. Despite this importance, predicting soil water dynamics especially during dry and wet season remains a major challenge in hydrology, environmental science, agriculture, and engineering. Hence this study aims to determine the mathematical model for the site-specific of petrophysical relationship for wet and dry season between dielectric permittivity and water content of the peat soil. Field survey measurements and laboratory measurements were conducted at peat soil area. Soil samples were collected from 0 to 1.0m layer for 20 point. Dielectric permittivity values were determined using 2D adjusted of parallel plate capacitor. The oven-drying process was conducted for soil water content estimation. Linear and polynomial models were adjusted for the peat soil between dielectric permittivity and water content. From the results shows that the modeled of site-specific of petrophysical relationship gives better correlation for dry season (R 2 =0.9812) and wet season (R 2 =0.9441). The comparisons of GPR-derived estimates of water content to gravimetric measurements showed that GPR measurements using the modeled site-specific petrophysical relationships for both season had a root mean square error of 0.017 (wet season) and 0.25 (dry season). This indicates that the modeled equations can be used to estimate the water content of the peat soil when measured it by using GPR. Besides, through verifying the model of site-specific of petrophysical relationship using ground penetrating radar (GPR) along with three proposed model (Roth equation, Schaap equation and Idi equation) where the season was taken as consideration, the adjusted models provide sufficient...

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Accurate measurements of Soil Water Content (SWC) with applicable and relevant support are essential in many fields of earth and soil engineering research. Ground Penetrating Radar (GPR) is a geophysical tool that measures and provides accurate results for determination of the SWC. To prove the accuracy of SWC measurement using GPR, a field survey was performed in peat soil. This paper presents a fieldwork survey with the aim of assessing the SWC measurement using GPR. The survey work was conducted at Johor Bharu using different antenna frequencies (250 and 700 MHz). Five profiles, which is 5m by 5m in length, were scanned along an eastwest direction with a common offset at an equal spacing of 1m. To measure the SWC using GPR, the researchers used the velocity from the GPR's signal from the receiving antenna to the soil. Statistical analysis was carried out based on the dielectric permittivity and SWC. Schaap's equation and Roth's equation were used to distinguish the relative dielectric permittivity of the soil to SWC. The results of this study show the linear function, for the measured SWC. The validation graph shows that at a frequency of 250 MHz, the depth of penetration was greater compared to the frequency of 750 MHz. These results, suggest that a higher frequency will give higher resolution but lower depth penetration.