Groundwater level estimation model on peatlands using SAR Sentinel-1 Data in part of Riau, Indonesia

The character of peatlands has the ability to store large amounts of water, but the surface of the peatlands dries quickly and easy to burn during the dry season. Research aims to build a model to estimate groundwater level of peatland. Statistical analysis of Karl Pearson Product Moment correlation test was used to determine the relationship between the back scatter values and the Surface Soil Moisture (SSM) values from the Sentinel-1 SAR data processing with the groundwater level values measured using the Sipalaga instrument. Regression analysis was used to determine the model that could be used to estimate the groundwater level of peatlands in the study area based on the results of Sentinel-1 SAR data processing. The results showed that the Sentinel-1 SAR data with the Sigma_0 format in decibel (db) units with VV polarization had the highest correlation value with the groundwater level data of peatlands measured using the Sipalaga instrument, with a value of r -0.648 (moderate correlation). Model to estimate water level of peatlands was Y = -101.629 + (-7.414 x), where 'Y' was the groundwater level of peatlands in the study area and 'x' was the Sentinel-1 SAR data with Sigma_0 format in decibel (db) units with VV polarization. The spatial and temporal patterns of peatlands groundwater level in the study area from Sentinel-1 SAR data showed peatlands that to survive at a water level <40 cm was in the area around of the Rokan River and also in plantation areas, especially Acacia plantations, where canals were made to irrigate and land management.